Evaluation of Clinical Pharmacy Services in Patients Receiving Antithrombotic Treatment: A Randomized Controlled Trial

Evaluation of Clinical Pharmacy Services in Patients Receiving Antithrombotic Treatment: A Randomized Controlled Trial | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of Clinical Pharmacy Services in Patients Receiving Antithrombotic Treatment: A Randomized Controlled Trial Damla SOSYAL, Muhammed Yunus Bektay, Nusret Acikgoz, Fikret Vehbi Izzettin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4448386/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Antithrombotic drugs are frequently used in the Cardiology ward and patients receiving these drugs are thought to be vulnerable to drug-related problems (DRPs). The aim of this study was to evaluate clinical pharmacy services for the detection and prevention of DRPs in these patients. Methods: This prospective randomized controlled study included 400 patients receiving antithrombotic therapy in the Cardiology ward. The European Pharmaceutical Care Network Classification (PCNE v9.1) was used to assess DRPs. Patients were analyzed for readmission within 1 and 3 months after discharge. Results: The mean age of patients in the control and intervention groups was 67.2 ± 12.2 and 67.8 ± 12.3 years, respectively. Coronary artery disease (74.5%; 74.5%) and hypertension (70.5%; 70%) were the most common diseases. The number of DRPs detected was 561 in the control group and 497 in the intervention group. In both groups, the most frequently identified problem was related to treatment safety (73.62%; 74.25%). This was followed by treatment effectiveness (24.06%; 23.14%). The main causes of DRPs were drug selection (81.11%; 80.88%) and dose selection (19.08%; 16.10%). During the study, 248 (93.23%) recommendations were made for 266 clinically significant DRPs. Of these recommendations, 235 (94.76%) were accepted by physicians. The most common interventions at the drug level were changing the dose (29.65%) and starting a new drug (28.49%). There was no significant difference between the groups in terms of readmission within 1 and 3 months (p > 0.05), but a numerical decrease was observed in the intervention group. Conclusion: In our study, the number of clinically significant DRPs was statistically lower in the intervention group (p < 0.05). The high acceptance rates of the recommendations regarding the problems in the intervention group showed that the clinical pharmacist had a positive contribution to the reduction of DRPs. These results suggest that the inclusion of clinical pharmacists in the healthcare team and the expansion of their services will provide a better-quality healthcare service. Clinical pharmacist drug-related problem cardiology antithrombotic PCNE. Introduction According to the World Health Organization (WHO), the most common cause of adult death is cardiovascular disease (CVD). In 2030, it is estimated that there will be more than 22 million mortalities due to cardiovascular diseases 1 , 2 . Thrombosis is the most common cause of morbidity and mortality and causes a huge burden of disease worldwide 3 . In this case, antithrombotic therapy is important for the success of treatment. However, the widespread use of antithrombotic drugs suggests that patients receiving this treatment may be more vulnerable to DRPs 4 . The Pharmaceutical Care Network Europe (PCNE) defines an DRPs as an event involving drug treatment that actually or potentially interferes with desired health outcomes 5 . Adverse drug events (ADEs) constitute a small proportion of drug-related problems. Medication errors, overdose, drug dependence, adherence problems and therapeutic failure are among other important problems associated with drug use 6 . Patients with CVD are more likely to use high-risk medications such as antithrombotic drugs. These patients are also at significant risk of adverse drug events and medication errors 7 – 9 . By focusing on the prevention of medication-related adverse events and errors, patient outcomes related to these events can be improved 10 . The American Clinical Pharmacy Association (ACCP) defines clinical pharmacy services (CPS) as " A health sciences discipline in which pharmacists provide patient care that optimizes drug therapy and promotes health, wellness and disease prevention " 11 . Clinical pharmacist interventions are defined as "any action initiated by a pharmacist that results in a change in direct patient management or medication therapy" 12 . Clinical pharmacists have assumed important roles in ensuring the effective and correct use of medicines and in reducing and preventing DRPs. Interacting with a clinical pharmacist in the treatment of inpatients has helped to reduce adverse drug reactions, medication errors, improve post-discharge medication adherence and shorten the length of hospital stay. Overall, the provision of clinical pharmacy services in inpatients and outpatients has resulted in improved quality of care with no harm to patients 11 . This study aimed to identify and prevent drug-related problems (DRPs) in patients receiving antithrombotic therapy by clinical pharmacists. Additionally, clinical pharmacy services were also reviewed. Furthermore, the rehospitalizations of patients within the 1 to 3-month period were also assessed. Materials and methods Study design, participants and setting: A randomized controlled study was conducted on patients admitted to the Cardiology ward and receiving antithrombotic therapy for any reason at a tertiary-care university hospital in Istanbul, Türkiye, from November 2021 to November2022. Inclusion criteria for this study encompassed being 18 years of age or older and patients with a confirmed usage of any of the antithrombotic medications (ATC Group: B01). Participants were further required provide written informed consent for study participation. The patients with incomplete biochemistry-hemogram values taken twice and incomplete two-day medication list, patient follow-up and medication review lost were excluded. The study design and criteria aim to comprehensively assess the impact of CP interventions on the clinical outcomes of patients prescribes AT medications. The randomization process was performed as simple randomization using an algorithm generated by Research Randomizer® software that assigned patients to the control group (CG) or intervention group (IG) in a 1:1 ratio. In the study, a clinical pharmacist (CP) on the team developed a concealed allocation schedule. This schedule, stratified by groups, randomly assigned two sequences to a consecutive series of numbers. Upon enrollment, the CP assigned each participant the next consecutive number, determining the sequence of intervention. Participants were then randomly assigned to the CG and IG. The IG comprised patients for whom CP recommendations for DRPs were communicated to the healthcare team. Conversely, the CG consisted of patients for whom no such recommendations were made to the healthcare team by CP, concerning DRPs; only observations were conducted. Patients in CG who received their standard treatment were only monitored by the clinical pharmacist, while in the IG, in addition to this, recommendations were made to physicians regarding DRPs detected by the clinical pharmacist. Data collection: During the study, meticulous records were maintained with confidentiality, encompassing contact information, medical history, medication history, current medications, laboratory findings, and physical examination records. These details were carefully documented to ensure the highest level of privacy and compliance with ethical standards. The characteristics of the patients in the control and intervention groups were recorded through the hospital electronic record system. The evaluation and classification of DRPs were carried out by following five steps: (i) Recording the sociodemographic and hospitalization day information of the patients: Age, gender, disease, comorbid conditions, admission diagnoses, laboratory data during hospitalization (creatinine, blood glucose, AST, etc.). (ii) The medications (active substance, dose, route, time, frequency of drug administration, duration of treatment) previously used and prescribed during hospitalization were recorded. Local used drugs such as ointments, pomades and maintenance fluids were excluded. (iii) Assessment of patients' medications during hospitalization: The evaluation was based on current diagnostic and therapeutic guidelines (e.g. European Society of Cardiology, American Heart Association), health practice guidelines, clinical decision support systems and current literature (e.g. UpToDate®, RxMediaPharma® interactive drug information resource, IBM Micromedex drug reference®, Medscape®, Lexicomp®, Sanford Guide®). In the current study, these well-established guidelines collectively formed the basis for ensuring the appropriateness and adherence to best practices in antithrombotic therapy for patients prescribed with AT medication. (iv) Assessment of existing or potential drug-drug interactions: The Lexicomp® Drug Interactions application was used for this purpose. (v) Identification and classification of DRPs: The European Pharmaceutical Care Network's DRPs classification (v9.1) was used. The study also delved into DRPs, encompassing their causes, CP recommendations for resolution, and physicians' subsequent acceptance and implementation. The Turkish version of the Pharmaceutical Care Network Europe Association (PCNE) Classification scheme for Drug-Related Problems v9.1 was employed to identify DRPs. This version, validated by the PCNE working group, features a comprehensive classification system consisting of primary domains for problems, causes, planned interventions, level of acceptance (of interventions), and the status of the problem. On a more detailed level, the scheme comprises grouped sub-domains, providing explanatory granularity for the principal domains. The validated PCNE classification scheme offers a robust framework for systematically categorizing and addressing DRPs in the study context ( https://www.pcne.org/upload/files/417_PCNE_ classification _V9-1_ final.pdf). This study has been reported according to recommendation of Consolidated Standards of Reporting Trials (CONSORT) standards. Ethics approval: The studies involving human participants were reviewed and approved by the local Ethics Committee of Clinical Research with decision number 19/5. This study protocol has been registered at ClinicalTrials.gov (NCT06193473). Clinical interventions: The data of patients admitted to the cardiology ward with a prescription of antithrombotic (AT) medication were meticulously recorded during their hospitalization. During patients’ hospital stay, a multidisciplinary team evaluated the patients' treatment regimen and medications. The CP played an integral role in this process, closely monitoring the patient and treatment adjustments for patients and identifying DRPs through a comprehensive assessment of their medication information. The clinical pharmacist, together with the responsible physician and other health workers, attended daily ward visits on weekdays, conducted medication reviews and provided interventions for patients with DRPs in the intervention group. These interventions were face-to-face, verbal recommendations to the health workers in the team. Recommendations were made at the time of admission to the ward, during the hospital stay and at discharge. In the IG, the CP provided face-to-face recommendations for DRPs to the attending physician. An experienced multidisciplinary team containing CP jointly assessed the clinical significance of identified DRPs. The interventions were designed to detect and prevent DRPs, thereby addressing concerns in patients hospitalized with a AT medication. Recommendations included additions to the patient's treatment regimen, discontinuation of off-label or inappropriate medications, proposing alternative agents, altering the route of administration, suggesting therapeutic drug monitoring, advising dose adjustments, managing drug-drug interactions, and optimizing the duration of treatment. The clinical pharmacist provided advice on drug selection, addition, discontinuation, follow-up, dose adjustment, management of side effects, and potential drug-drug interactions. To analyze medications and evaluate potential drug-drug interactions (pDDIs), the Lexicomp® (Wolters Kluwer Health Inc.) database was utilized. The X (contraindicated) and D (drug change considered) levels, which are important levels for potential drug-drug interactions, were assessed. Among these, recommendations were made for those deemed clinically important. The drugs used by the patients from hospitalization to discharge and the agents responsible for DRPs were compared between the two groups. In addition, the groups were evaluated in terms of whether the patients were readmitted to hospital within 1 and 3 months after discharge. The LACE index score was used to predict readmission within 30 days after discharge 13 . Main outcome measure The primary outcomes of the study focused on the identification and classification of DRPs, the acceptance rate of CP recommendations, and rehospitalizations on both the 30th and 90th days among the groups. These outcomes were integral to assessing the impact of CP interventions on patient care and treatment outcomes. Additionally, secondary outcomes of the study included comparing patients in terms of disease course, rehospitalization rates. This secondary analysis aimed to comprehensively understand how CP involvement influenced key aspects of the disease trajectory and patient outcomes beyond the immediate post-discharge period. By systematically evaluating both primary and secondary outcomes, the study aimed to contribute valuable insights into the effectiveness of CP interventions in optimizing patient care, enhancing treatment outcomes, and potentially influencing the long-term prognosis of individuals prescribed with AT medications. Sample Size: The sample size calculation for the study was conducted based on data from the literature 14 , indicating that DRPs were reduced by an average of 1 per patient in groups where CP made recommendations. The standard deviation was assumed to be 1. According to our sample size calculations based on drug-related problems to determine the number of participants needed for the ethics committee application, the effect size (d) was calculated as 0.5540. Taking the alpha (α) error as 0.05 and beta (β) error as 0.95, at least 135 participants should be included for each group and the power of our study was calculated as 0.95. Statistical analysis: Analyses were performed using SPSS (Statistical Package for Social Sciences) Windows 11.0 program. The results were evaluated at 95% confidence interval and significance at p < 0.05 level. Demographic data were expressed as percentages, continuous and discrete variables were expressed as mean, standard deviation, median, interquartile distribution, and drug-related problems were expressed as percentages and numerical values. Whether the data were normally distributed or not was determined by Kolmogorov-Smirnov test; the differences between the two groups were evaluated using Student's t-test for those that met the normal distribution, Mann Whitney U test for parameters that did not meet the normal distribution condition, and Chi-square or Fisher exact tests for discrete variables. P < 0.05 was accepted as the level of statistical significance. Results Demographics, medications and hospital admission: Of the patients who met the inclusion criteria, 200 were included in the control group and 200 in the intervention group. The mean ages of these patients were 67.2 ± 12.2 and 67.8 ± 12.3, respectively. The mean number of diseases or comorbid conditions per patient in the control and intervention groups were 4.74 ± 1.88 and 4.77 ± 2.04, respectively. In both groups, a minimum of 1 and a maximum of 10 conditions were encountered in one patient. The most common disease was coronary artery disease, which was present in 149 patients (74.5%) in both groups. Subsequently, hypertension was seen in 141 (70.5%) and 140 (70%) patients in the control and intervention groups, respectively. Diabetes was the third most common disease in 99 (49.5%) of the control group and heart failure in 96 (48%) of the intervention group. It was also reported that more than 40% of patients developed acute coronary syndrome, 88 (44%) and 87 (43.5%) patients, respectively. AF and other rhythm disturbances were 68 (34%) and 76 (38%), respectively (Table 1 ). Table 1 Demographic Characteristics of Patients Baseline Characteristics of Patients Control Group (n = 200) Intervention Group (n = 200) p Sex (n, %) 0.26 # Female (n, %) 85 (42.5%) 74 (37%) Male (n, %) 115 (57.5%) 126 (63%) Age (mean ± SD) 67.2 ± 12.2 67.8 ± 12.3 0.93* Weight (kg) (mean ± SD) 79.8 ± 18.1 78.3 ± 12.5 0.79* BMI (mean ± SD) 28.9 ± 6.07 28.2 ± 4.61 0.17* No of Comorbidities (mean ± SD) 4.74 ± 1.88 4.77 ± 2.04 0.94* 1 (n) 2 3 2 (n) 19 20 3 (n) 36 34 4 (n) 47 45 5 (n) 29 38 6 (n) 27 25 7 (n) 24 9 8 (n) 9 11 Most common 10 diseases and comorbidities (n, %) Heart Valve Disease 55 (27.5%) 50 (25%) Arrhythmia 68 (34%) 76 (38%) Atrial fibrillation/ flutter (AF/AFL) Arrhythmia without AF/ AFL 58 (29%) 10 (5%) 60 (30%) 16 (8%) Cerebrovascular disease/ Transient ischemic attack 25 (12.5%) 16 (8%) Coronary artery disease 149 (74.5%) 149 (74.5%) Acute coronary syndrome Percutaneous coronary intervention Coronary artery bypass graft surgery 88 (44%) 70 (35%) 34 (17%) 87 (43.5%) 63 (31.5%) 29 (14.5%) Hypertension 141 (70.5%) 140 (70%) Heart failure 86 (43%) 97 (48.5%) Chronic kidney disease 28 (14%) 24 (12%) Diabetes mellitus 99 (49.5%) 96 (48%) Thyroid diseases 15 (7.5%) 25 (12.5%) Asthma/ Chronic obstructive pulmonary disease 29 (14.5%) 39 (19.5%) *Mann-Whitney U test, # Ki-Square test, SD: Standard derivation Patients in the control and intervention groups were most frequently referred to the cardiology service from the emergency department (52%; 51.5%). The second most frequent referral was from outpatient clinic to the ward (47.5%; 43.5%). The most common reasons for hospitalization and the corresponding diagnoses for each group are illustrated in Fig. 2 . The most frequently used 5 Anatomical Therapeutic Chemical (ATC) groups in both the CG and IG were cardiovascular system (C), digestive system and metabolism (A), blood and blood-forming organs (B), nervous system (N) and respiratory system (R) in the control and intervention groups (Fig. 3 ). In the control and intervention groups, the most commonly prescribed antiplatelet therapy was acetylsalicylic acid in 71% and 67.5% of patients, and anticoagulant therapy was enoxaparin in 44% and 53% of individuals, respectively. No significant difference was found between the groups in terms of LACE classification (p > 0.05). Similarly, there was no significant difference between the control and intervention groups in terms of emergency readmissions and unplanned hospitalizations within 1 and 3 months after discharge. Readmissions and rehospitalizations were numerically higher in the control group compared to the intervention group (Table 2 ). Table 2 Patient's hospitalization information and drug-related problems identified Data Control Group (n = 200) Intervention Group (n = 200) p Number of drugs (mean ± SD) 11.8 ± 5.52 12.6 ± 5.82 0.14* Length of stay (mean ± SD) 3.83 ± 3.41 4.04 ± 3.08 0.28* LACE Index for Readmission (mean ± SD) 7.25 ± 2.87 7.15 ± 2.70 0.95* Unplanned rehospitalization within 1 month (n) 12 6 0.16 # Unplanned rehospitalization within 3 month (n) 26 22 0.60 # The number of emergency and unplanned readmissions within 3 months (mean ± SD) 0.454 ± 0.955 0.38 ± 0.703 0.96* Total number of DRPs, n 561 497 0.15* Number of possible drug-drug interactions per patient (mean ± SD) 1.78 ± 1.95 1.58 ± 1.71 0.53* Number of clinically significant DRPs per patient (mean ± SD) 2.81 ± 2.87 1.33 ± 2.11 < 0.001* Accepted interventions, n (%) - 235 (94.76%) - Unaccepted interventions, n (%) - 13 (5.24%) - *Mann-Whitney U test, # Ki-Square test, SD: Standard derivation. Data presented as percentage. Drug-related problems and pharmacist interventions: According to the PCNE classification, the clinical pharmacist identified 561 possible DRPs in 166 (83%) patients in the control group and 497 possible DRPs in 153 (76.5%) patients in the intervention group. The most frequently identified DRPs were related to 'treatment safety'. Treatment safety-related DRPs accounted for 413 (73.62%) and 369 (74.25%) of the patient problems in the control and intervention groups, respectively. There were 135 (24.06%) problems related to 'treatment effectiveness' in the CG and 115 (23.14%) in the IG. It was observed that the most common cause of DRPs was 'drug selection' for both groups. 'Drug selection' accounted for 81.11% of the problems in the CG and 80.88% of the problems in the IG. The second most common reason was related to 'dose selection' in both groups. 107 (19.08%), 80 (16.10%) reasons were associated with 'dose selection', respectively. Among the reasons for most dose selection, 'low dose' and 'high dose' were 58 (10.34%) and 35 (6.24%) in the CG and 35 (7.04%) and 17 (3.42%) in the IG, respectively (Table 3 ). Table 3 Classification of drug-related problems according to PCNE v9.1 Problems (also potential) CG % IG % Causes CG % IG % P1. Treatment effectiveness 135 24.06% 115 23.14% C 3.1 Drug dose too low 58 10.34% 35 7.04% P1.1 No effect of drug treatment despite correct use - - 1 0.20% C3.2 Drug dose of a single active ingredient too high 35 6.24% 17 3.42% P1.2 Effect of drug treatment not optimal 99 17.64% 72 14.49% C3.3 Dosage regimen not frequent enough 13 2.32% 14 2.82% P1.3 Untreated symptoms or indication 36 6.42% 42 8.45% C3.4 Dosage regimen too frequent 1 0.18% 11 2.21% P2. Treatment safety 413 73.62% 369 74.25% C3.5 Dose timing instructions wrong, unclear or missing - - 3 0.60% P2.1 Adverse drug event (possibly) occurring 413 73.62% 369 74.25% C4. Treatment duration - - 2 0.40% P3. Other 13 2.32% 13 2.61% C4.2 Duration of treatment too long - 2 0.40% P3.1 Unnecessary drug-treatment 12 2.14% 7 1.41% C5. Dispensing - - 3 0.60% P3.2 Unclear problem/complaint. Further clarification necessary 1 0.18% 6 1.20% C5.1 Prescribed drug not available - 2 0.40% Causes C5.4 Wrong drug or strength dispensed - 1 0.20% C1. Drug selection 455 81.11% 402 80.88% C6. Drug use process - - 3 0.60% C1.1 Inappropriate drug according to guidelines/formulary 54 9.63% 30 6.04% C6.1 Inappropriate timing of administration or dosing intervals by a health professional - 3 0.60% C1.2 No indication for drug 1 0.18% 4 0.80% C7. Patient related - - 3 0.60% C1.3 Inappropriate combination of drugs, or drugs and herbal medications, or drugs and dietary supplements 359 64.00% 320 64.39% C7.2 Patient uses/takes more drug than prescribed - 1 0.20% C1.4 Inappropriate duplication of therapeutic group or active ingredient 2 0.36% 3 0.60% C7.4 Patient decides to use unnecessary drug - 2 0.40% C1.5 No or incomplete drug treatment in spite of existing indication 39 6.94% 44 8.85% C8. Patient transfer related 11 1.96% 22 4.43% C1.6 Too many different drugs/active ingredients prescribed for indication - - 1 0.20% C8.1 Medication reconciliation problem 11 1.96% 22 4.43% C2. Drug form - - 2 0.40% C9 Other 1 0.18% 11 2.21% C2.1 Inappropriate drug form/formulation (for this patient) - - 2 0.40% C9.1 No or inappropriate outcome monitoring (including TDM) - 1 0.20% C3. Dose selection 107 19.08% 80 16.10% C9.2 Other cause; specify 1 0.18% 10 2.01% CG: Control Group, IG: Intervention Group, %: Percentage The majority of the interventions performed by the clinical pharmacist were at the prescriber level (214, 86.29%) and at the drug level (172, 69.35%) (Table 4 ). The majority of the interventions in the other category were possible drug-drug interactions (pDDI) monitored by the clinical pharmacist during drug use. These interactions were potential problems such as QTc prolongation, the need for level monitoring of drugs such as warfarin, or potential major problems. Table 4 Level, acceptance and status of interventions Number of recommendations (n = 248) Percent Level of Interventions* I1. At prescriber level 214 86.29% I2. At patient level 3 1.21% I3. At drug level 172 69.35% I4. Other 81 32.66% Intervention Acceptance A1. Intervention accepted 235 94.76% A1.1 Intervention accepted and fully implemented 129 52.02% A1.2 Intervention accepted, partially implemented 47 18.95% A1.3 Intervention accepted but not implemented 57 22.98% A1.4 Intervention accepted, implementation unknown 2 0.81% A2. Intervention not accepted 13 5.24% A2.2 Intervention not accepted: no agreement 6 2.42% A2.3 Intervention not accepted: other reason (specify) 4 1.61% A2.4 Intervention not accepted: unknown reason 3 1.21% Status of Interventions O0. Problem status unknown 3 1.21% O1. Problem solved 140 56.45% O2. Problem partially solved 87 35.08% *Percentage over the total number of interventions (n = 248). Data presented as percentage. In the CG, 356 pDDI were identified in 130 individuals and 317 pDDI in 128 individuals in the IG. The majority of the potential problems identified in the intervention group that were not found to be clinically important. These drug-drug pairs consisted of medicines that were intentionally prescribed to patients for specific indications, were meant to be used together, and were the monitoring of clinical pharmacist. For this reason, there was no attempt to avoid using them. Taking this into consideration, the clinical pharmacist identified 86 pDDI that were considered important in the IG. In this case, the number of clinically significant DRPs expected to be the main problem in the IG with involvement of the clinical pharmacist was determined as 266. Additionally, there was a statistically significant reduction in the number of clinically significant DRPs in the IG compared to the CG (p < 0.01) (Table 2 ). In the IG, 248 recommendations (93.23%) for 126 patients (63%) regarding 266 clinically significant DRPs were made by the clinical pharmacist during hospitalization. Of the suggestions made, 235 (94.76%) were accepted. 91.53% of the intervened problems were resolved (Table 2 ). The correlation matrix of the patients was examined, revealing significant positive and negative correlations with respect to LACE score, length of stay and DRPs. The highest level of association between variables was found between pDDI and DRPs. Additionally, a significant correlation was observed between the day of hospitalization and readmissions within 1 month, and notably, within 3 months (Table 5 ). Table 5 Correlation matrix of some factors associated with hospitalizations and DRPs Variable LACE index score Length of stay (Day) Number of DRPs Number of comorbidities r:0.459*** r:0.317*** r:0.348*** Number of drugs r:0.478*** r:0.602*** r:0.621*** Number of possible drug-drug interactions r:0.378*** r:0.363*** r:0.882*** Age r:0.156** r:0.251*** r:0.177*** CRP mg/dl r:0.218*** r:0.322*** r:0.322*** Urea mg/dl r:0.271*** r:0.366*** r:0.272*** eGFR mL/min/1.73 m 2 r:-0.289*** r:-0.303*** r:-0.259*** Calcium mg/dL r:-0.184*** r:-0.342*** r:-0.153** Sodium mmol/L r:-0.143** r:-0.103* r:-0.154** Neutrophil/lymphocyte absolute count r:0.258*** r:0.307*** r:0.233*** HGB g/dl r:-0.246*** r:-0.365*** r:-0.245*** BNP ng/l r:0.228*** r:0.388*** r:0.127* Readmissions within 1 month r:0.155** r:0.111* - Readmissions within 3 month r:0.112* r:0.127*** - r: Correlation Coefficient; p: significance level, *p < 0.05; **p < 0.01; ***p < 0.001; eGFR: Estimated glomerular filtration rate; CRP: C-reactive protein; HGB: Hemoglobin; BNP: Brain natriuretic peptide. Data presented as percentage. In the groups in our study, it was observed that the most common agents causing DRPs in the ATC group were drugs used in the blood and blood-forming organs, digestive system and metabolism, cardiovascular system, anti-infective drugs and nervous system (Fig. 4 ). Similarly, the most common interventions were for these groups of drugs. Among these, systemic antibacterials, antithrombotics, drugs used in cardiac treatment, drugs used in diabetes treatment and psycholeptics were the drugs for which most interventions were performed (Fig. 5 ). The antithrombotic drugs most responsible for DRPs were similar in the control and intervention groups and the top 3 drugs were enoxaparin, acetylsalicylic acid and clopidogrel. Antithrombotic drugs for which most interventions were performed included enoxaparin, apixaban and warfarin (Fig. 6 ). Discussion In our study, 'coronary artery disease' (74.5%; 74.5%) was identified to be the most common disease in the control and intervention groups, which can be attributed to the inclusion criteria selecting patients receiving antithrombotic drugs. Hypertension was the second most common condition (70.5%; 70%), while diabetes was the third most common in the control group (49.5%) and heart failure (48%) in the intervention group. Our findings are consistent with the studies conducted by Patel et al. and Greeshma et al., both of which reported hypertension and diabetes as the most prevalent conditions in their studies 1516 . Clinical pharmacists have been demonstrated to improve the use of high-risk medicines through medication review and to ensure the accuracy of medication regimens in older patients 12 , 17 – 19 . In our study, the mean age of our patient population was 67 years in both groups and the medications used by the patients were carefully reviewed by the clinical pharmacist. One study reported a three-fold increased risk of developing DRPs in adults over 60 years of age 20 . This may be explained by factors such as increased incidence of renal and hepatic insufficiency, increased number of comorbidities and polypharmacy in elderly patients. Therefore, dosing errors, drug interactions, side effects and medication adherence problems may occur. Bektay et al. found a correlation between the number of DRPs and comorbidities and the number of drugs used (p < 0.05) 21 . Niriayo et al. reported that the likelihood of DRPs in patients with polypharmacy was approximately three times higher than in patients taking fewer medications. A possible explanation for this is that polypharmacy may lead to poor adherence, drug interactions and drug side effects. Similarly, an increased risk of drug interactions and side effects has been observed in patients with multiple comorbidities 22 . In our study, a positive correlation was observed between the number of DRPs detected and age (r: 0.177, p < 0.001), total number of comorbidities (r: 0.348; p < 0.001), and total number of drugs used during hospitalization (r: 0.621; p < 0.001). DRPs were detected in more than 75% of patients in both groups, with a contributing factor to this high rate identified as pDDI. Depending on the indications for antithrombotic drugs, patients were often required to use a combination of drugs, making them particularly susceptible to level D pDDI. Specific drugs or indications are thought to predispose to DRPs. According to a review, the ATC groups 'Cardiovascular system', 'Digestive system and metabolism', 'Blood and blood-forming organs' accounted for 32.1%, 29.4% and 11% of all DRPs, respectively. These findings suggest that patients taking these drug classes may be at increased risk of DRPs 23 . Furthermore, in both groups in our study, the causative agents of DRPs were most frequently found in these ATC groups. In this regard, our study aligns with and supports these previous findings. Additionally, as observed in the intervention group, the clinical pharmacist played a crucial role in managing drugs from different classes. Wang et al. found that the most frequently identified problems were related to 'treatment efficacy' (53.71%), followed by 'treatment safety' (33.90%) 24 . Conversely, Albayrak et al. reported that the most important problem in DRPs was 'treatment safety' 25 . In our study, the most common problem in the CG and IG was also found to be related to 'treatment safety' (73.62%; 74.25%). This was followed by problems linked to 'treatment efficacy' (24.06%; 23.14%). Given the prevalence of drug-related side effects in the cardiology ward, these problems are frequently encountered. Therefore, a thorough examination of treatment safety is important in this ward. In the literature, the main causes of DRPs were reported as 'drug selection' (51.41%), 'dose selection' (11.62%), 'patient-related' (10.70%) and 'other' (5.73%) 23 . In our study, the most common reasons for DRPs in the both groups were 'drug selection' (81.11%; 80.88%) and 'dose selection' (19.08%; 16.10%). Among dose selection reasons, 'low dose' (10.34%; 6.24%) and 'high dose' (7.04%; 3.42%) were the most common, respectively. In our study, a significant correlation was also found between elevated urea (r: 0.272, p < 0.001), blood urea nitrogen (r: 0.266, p < 0.001), creatinine (r: 0.186, p < 0.001) and DRPs. This suggests a potential association between DRPs and renal function levels, emphasizing the need for clinical pharmacists to exercise increased vigilance in cases of possible kidney disease. Of the medication-level interventions for DRPs deemed significant by the clinical pharmacist, 46.51% were dose changes and discontinuation/interruption. Most of these interventions were prompted by the presence of chronic, acute or acute-on-chronic renal dysfunction in patients with DRPs, necessitating dose adjustments based on declining or recovering renal function values. Additionally, DRPs were related to drugs such as enoxaparin and apixaban for which dose recommendations were also based on patient weight. All of these recommendations made by the clinical pharmacist were accepted, thus increasing the focus on these critical aspects. In the cardiology ward, patients need to be evaluated from a multidimensional perspective, taking into account their characteristics and clinical conditions. Our study pointed out that daily follow-up of patients and necessary dose adjustments are essential services that clinical pharmacists can provide to prevent unnecessary drug treatments, minimize side effects or ensure effective drug treatment. In the literature, 'Inappropriate drug selection' 26 – 32 ' no or incomplete drug treatment despite current indication' 26 – 28 , 30 , 33 , 34 and 'inappropriate drug combinations' 32 , 35 , 36 were observed as the most common causes of 'drug selection' problems. In our study, 'inappropriate drug selection or drug combination (N1.3)' was identified as the most common cause of 'drug selection'. The reason for this is that D and X level possible drug-drug interactions constitute the majority of DRPs in PCNE. Additionally, interventions related to drug interactions were found to be the less likely to be implemented in the literature 27 , 33 , 34 , 36 , 37 . In our study, since the clinical pharmacist intervened only for clinically significant interactions, these interventions were fewer than the number of pDDI identified. Possible drug-drug interactions for which no intervention was performed accounted for 92.77% of the problems without intervention. Furthermore, these interactions represented 46.48% of the potential or actual problems identified and 72.87% of the total pDDI identified. As observed in our study, most of these problems that were not intervened, which is approximately half of the total problems, were possible drug-drug interactions that were not considered clinically significant. The reason for not intervening was that these drugs are deliberately used together in the treatment of the patient and are drug combinations where drug-drug interaction is already an expected or desired outcome. For example, in cases such as acute coronary syndrome, the addition of anticoagulant drugs such as enoxaparin to antiplatelet therapy is one of the examples where drug combinations that act through different mechanisms are required to be used together in the guidelines. When such situations are taken into account, the total number of possible or actual DRPs which was 497 was replaced by 266 clinically significant DRPs, in the intervention group. In the total number of DRPs, there was a significant decrease (p < 0.001) in the intervention group where the clinical pharmacist was involved, compared to the control group. In addition, most of the interventions in the 'other' category, which accounted for 32.66% of the interventions in our study, consisted of possible drug-drug interactions that the clinical pharmacist considered to be clinically important, for which the clinical pharmacist recommended 'drug monitoring' to physicians. In particular, these were combinations of drugs that may prolong QTc or alter each other's levels. As was clearly seen during our study, the involvement of a clinical pharmacist in the health team can ensure the monitoring and appropriate use of medications. According to the PCNE classification, all significant level pDDI should be categorized as 'inappropriate drug combinations' in the 'drug selection' domain. Our study demonstrated the difficulty in the implementation of PCNE, as PCNE includes drug combinations given to patients for clinical indications as a problem under the heading of possible drug-drug interaction. In addition, it needs to revise itself under separate headings to elaborate at drug-level interventions such as 'drug preparation' and 'drug monitoring'. Such incomplete situations make it difficult to implement PCNE in the hospital setting. In addition, since the major conditions considered problematic in each ward may differ, we suggest developing special subsystem versions of PCNE and conducting reliability studies in this direction. It is stated that overcoming the limitations of PCNE is important for its implementation and dissemination in hospital settings. There are studies in the literature evaluating the impact of the clinical pharmacist on readmission. For instance, O'Dell et al. reported a significantly lower rate of readmission for cardiac reasons at 30 days in study patients compared to control patients 38 . On the other hand, Lowrie et al. found no significant difference between groups in outcomes, including death or hospitalization 39 . In our study, the total number of emergency and hospital readmissions within 3 months was numerically lower in the intervention group. However, no significant difference was observed in emergency admissions and unplanned hospitalizations in the follow-up periods. This may be associated with several reasons. It may be related to the fact that demographic, clinical, laboratory and other patient-related factors such as age, comorbidity, creatinine and number of medications used were similar between the two groups. In addition, adherence to treatment after discharge is also a parameter that should be evaluated in terms of rehospitalizations. A weak but significant positive correlation was found between LACE scores and readmissions within 1 and 3 months. Therefore, in addition to predicting readmissions within 1 month, it is envisaged that the LACE score can also be used for readmissions within 3 months with versions that can be developed. Harrison et al., identified antihypertensives, antibiotics, analgesics, antiplatelets and antidiabetics (5%-16%) as the primary drugs associated with DRPs 40 . Our study similarly found that the most common recommendations were related to antibacterials (15.45%), antithrombotics (15.45%), cardiac (12.73%) and diabetes medications (10.61%). Acheampong et al. reported anticoagulants as the leading cause of DRPs, consistent with our study where the majority of recommendations among antithrombotics were related to anticoagulants 41 . Enoxaparin (47.06%), apixaban (15.69%) and warfarin (15.69%) were the anticoagulants with the highest number of recommendations. Enoxaparin, in particular, was associated with increased DRPs and hence with a high number of recommendations, due to its frequent use as parenteral therapy without the need for follow-up. Our study demonstrated that the clinical pharmacist has an important role to play in the management of both long-established medicines and those recently included in guidelines. In one study, Stuhec et al. reported that more than one-third (32.7%) of interventions performed on patients were related to the treatment of cardiovascular disease 42 . Similarly, in our study, cardiovascular system medications (25.15%) were the most common medication group for which interventions were performed. This is attributed to the patients hospitalized in the ward having cardiovascular system-related issues that necessitate the use of these drugs. Additionally, effective adjustments related to the current medical condition can be made with physicians who share common information on this subject. In our study, anti-infective drugs were the second most common drug group (16.66%). Similar to Harrison et al., most of these were antibacterial drugs. Antimicrobials are frequently used drugs in hospitalized patients 40 . Infections such as pneumonia may accompany and exacerbate infections in patients with cardiovascular diseases such as heart failure. These reasons may explain the frequent occurrence of problems related to anti-infective treatments in our study. Our study demonstrated that anti-infective drug management in patients with cardiovascular disease is one of the important services that clinical pharmacists can provide. The third most common drug group for interventions was related to the digestive system and metabolism (15.16%). This is supported by the fact that DRPs was also found to be associated with the patients' diabetes in our study. In addition, the presence of interventions for antidiabetic drugs in the intervention group (10.61%) showed one of the service areas in which the clinical pharmacist can take part. The frequent observation of problems and interventions related to antithrombotic drugs draws attention to the necessity and importance of providing a clinical pharmacy service for patients using these drugs. In addition, the fact that recommendations were made for different drug groups showed that the clinical pharmacist increased the quality of health care with a multidisciplinary approach. Based on the study data, clinical pharmacists may be offered opportunities to specialize in areas such as cardiovascular system diseases, internal diseases and infectious diseases. Adjustments and diversifications can be made in the current training system that takes into account conditions such as antithrombotic management and electrolyte disturbances in relation to common problems specific to various clinics, thus increasing awareness of these issues. In the literature, acceptance rates of pharmacist interventions by physicians have been found to vary between 70–97% 38,43,44 . In our study, the acceptance rate of the interventions made by the clinical pharmacist was 94.76%. The high acceptance of clinical pharmacist recommendations in our study can be attributed to the pharmacist's active involvement in the patient-related process during prescribing, the recommendations being made in accordance with evidence-based literature, and face-to-face. The fact that the doctors in the team were already familiar with the clinical pharmacy system also contributed to the increased awareness of clinical pharmacy services. The value of our study is enhanced by the clinical pharmacist's active role in a multidisciplinary team, attending visits and closely monitoring the patient's condition to detect and prevent problems. Both the literature and our study demonstrate that the clinical pharmacist has a central role in the optimization of pharmacotherapeutic outcomes. Limitations of the study: The limitations of our study include the fact that randomization was performed at a single center was included and therefore the results could not be generalized. Other limitations include not knowing the drug regimens and patient factors during the three-month follow-up after discharge. When these factors are evaluated in terms of hospital admission and hospitalization, they are independent factors other than the clinical pharmacist. The fact that the change of physicians in the team is very low, the clinical pharmacist cannot be completely isolated from both groups and team collaborations come into play are among the limitations of our study, which may pose a risk of contamination. Conclusion It has been shown that clinical pharmacists can play an important role in the detection and prevention of DRPs by ensuring that appropriate, evidence-based pharmacotherapy regimens are prescribed during hospitalization and by detecting medication errors. Considering the data we evaluated with our high recommendation acceptance rates for DRPs and the studies in the literature, it was revealed that the introduction of clinical pharmacy services with a clinical pharmacist in a multidisciplinary healthcare team, the development and dissemination of these services and every step to be taken for these results will have positive effects on patient outcomes and improve the quality of healthcare. Declarations Author Contribution Conceptualization, DS, MYB; methodology, DS, MYB, FVI; software, DS, MYB; validation, DS, MYB; formal analysis, DS, MYB; investigation, DS, MYB; resources, DS, MYB, NA, and FVI; data curation, DS; writing—original draft preparation, DS, MYB; writing—review and editing, DS, MYB, NA, and FVI; visualization, DS, MYB; supervision, MYB and FVI; project administration, DS, MYB; All authors have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript. Acknowledgement The authors of this study are grateful to Bezmialem Vakif University for providing opportunities and support. This study was not funded by any organizations. The present study was conducted within the scope of a Clinical Pharmacy specialty thesis at the Bezmialem Vakif University, Faculty of Clinical Pharmacy. Data Availability The data will be madeavailable upon request from the corresponding author. References Dülek H, Tuzcular Vural Z, Gönenç I. Risk Factors in Cardiovascular Diseases. The Journal of Turkish Family Physician . 2018;9(2):53-58. doi:10.15511/tjtfp.18.00253 Abaci A. Kardiyovasküler risk faktörlerinin ülkemizdeki durumu. Turk Kardiyoloji Dernegi Arsivi . 2011;39(SUPP-4):1-5. doi:10.5543/tkda.2011.abaci Öngen Z. Anticoagulation therapy and the use of non-vitamin K antagonist oral anticoagulants in the elderly. Turk Kardiyoloji Dernegi Arsivi . 2017;45:86-88. doi:10.5543/tkda.2017.47034 Fauler J. Clinical pharmacology of antithrombotic drugs in coronary artery disease. Ther Adv Cardiovasc Dis . 2009;3(6):465-478. doi:10.1177/1753944709346517 Lim X, Yeo Q, Kng G, Chung W, Yap K. Validation of a Drug-Related Problem Classification System for the Intermediate and Long-Term Care Setting in Singapore. Pharmacy . 2018;6(4):109. doi:10.3390/pharmacy6040109 Van Den Bemt PMLA, Egberts TCG, De Jong-Van Den Berg LTW, Brouwers JRBJ. Drug-related problems in hospitalised patients. Drug Saf . 2000;22(4):321-333. doi:10.2165/00002018-200022040-00005 Rasool MF, Rehman A ur, Imran I, et al. Risk Factors Associated With Medication Errors Among Patients Suffering From Chronic Disorders. Front Public Health . 2020;8(November):1-7. doi:10.3389/fpubh.2020.531038 Paradissis C, Cottrell N, Coombes I, Scott I, Wang W, Barras M. Patient harm from cardiovascular medications. Ther Adv Drug Saf . 2021;12. doi:10.1177/20420986211027451 Allen LaPointe NM, Jollis JG. Medication errors in hospitalized cardiovascular patients. Arch Intern Med . 2003;163(12):1461-1466. doi:10.1001/archinte.163.12.1461 Lin G, Huang R, Zhang J, Li G, Chen L, Xi X. Clinical and economic outcomes of hospital pharmaceutical care: A systematic review and meta-analysis. BMC Health Serv Res . 2020;20(1):1-14. doi:10.1186/s12913-020-05346-8 Dunn SP, Birtcher KK, Beavers CJ, et al. The Role of the Clinical Pharmacist in the Care of Patients with Cardiovascular Disease. J Am Coll Cardiol . 2015;66(19):2129-2139. doi:10.1016/j.jacc.2015.09.025 Definition T part. The definition of clinical pharmacy. Pharmacotherapy . 2008;28(6):816-817. doi:10.1592/phco.28.6.816 van Walraven C, Wong J, Forster AJ. LACE+ index: extension of a validated index to predict early death or urgent readmission after hospital discharge using administrative data. Open Med . 2012;6(3):90-100. Bektay MY, Sancar M, Okyaltirik F, Durdu B, Izzettin FV. Investigation of drug-related problems in patients hospitalized in chest disease wards: A randomized controlled trial. Front Pharmacol . 2023;13:5078. doi:10.3389/FPHAR.2022.1049289 Greeshma M, Lincy S, Maheswari E, Tharanath S, Viswam S. Identification of drug related problems by clinical pharmacist in prescriptions with polypharmacy: A prospective interventional study. Journal of Young Pharmacists . 2018;10(4):460-465. doi:10.5530/jyp.2018.10.100 Patel V, Chatterji S, Chisholm D, et al. Chronic diseases and injuries in India. The Lancet . 2011;377(9763):413-428. doi:10.1016/S0140-6736(10)61188-9 Weddle SC, Shaun Rowe A, Jeter JW, Renwick RC, Chamberlin SM, Franks AS. Assessment of clinical pharmacy interventions to reduce outpatient use of high-risk medications in the elderly. J Manag Care Spec Pharm . 2017;23(5):520-524. doi:10.18553/jmcp.2017.23.5.520 Bektay MY, Sancar M, Okyaltirik F, Durdu B, Izzettin FV. Investigation of drug-related problems in patients hospitalized in chest disease wards: A randomized controlled trial. Front Pharmacol . 2023;13(January):1-13. doi:10.3389/fphar.2022.1049289 Ertuna E, Arun MZ, Ay S, Koçak FÖK, Gökdemir B, İspirli G. Evaluation of pharmacist interventions and commonly used medications in the geriatric ward of a teaching hospital in turkey: A retrospective study. Clin Interv Aging . 2019;14:587-600. doi:10.2147/CIA.S201039 Nukala A, Vanga H, Keerthi T, Kandukuri K. A Comprehensive Analysis of Impact of Past Medications on Current Admission in a Tertiary Care Hospital : A Prospective Observational Study. J Basic Clin Pharm . 2021;12(6):76-81. Gözlemsel İ, Çalışma B, Bektay MY, Sancar M, Okyaltirik FK, Durdu B. Identification of Drug-Related Problems and Investigation of Related Factors in Patients with COVID-19 : An Observational Study COVID-19 ’ lu Hastalarda İlaçla İlişkili Sorunların Belirlenmesi ve İlişkili Faktörlerin. 2022;10(6):777-785. doi:10.14235/bas.galenos.2022.63935 Niriayo YL, Kumela K, Kassa TD, Angamo MT. Drug therapy problems and contributing factors in the management of heart failure patients in Jimma University Specialized Hospital, Southwest Ethiopia. PLoS One . 2018;13(10):1-14. doi:10.1371/journal.pone.0206120 Plácido AI, Herdeiro MT, Morgado M, Figueiras A, Roque F. Drug-related Problems in Home-dwelling Older Adults: A Systematic Review. Clin Ther . 2020;42(4):559-572.e14. doi:10.1016/j.clinthera.2020.02.005 Wang X, Wang S, Yu X, et al. Impact of pharmacist-led medication therapy management in ambulatory elderly patients with chronic diseases. Br J Clin Pharmacol . 2021;87(7):2937-2944. doi:10.1111/bcp.14709 Albayrak A, Başgut B, Bıkmaz GA, Karahalil B. Clinical pharmacist assessment of drug-related problems among intensive care unit patients in a Turkish university hospital. BMC Health Serv Res . 2022;22(1):1-7. doi:10.1186/s12913-022-07494-5 Castelino RL, Bajorek B V., Chen TF. Are interventions recommended by pharmacists during Home Medicines Review evidence-based? J Eval Clin Pract . 2011;17(1):104-110. doi:10.1111/j.1365-2753.2010.01375.x Chau SH, Jansen APD, van de Ven PM, Hoogland P, Elders PJM, Hugtenburg JG. Clinical medication reviews in elderly patients with polypharmacy: a cross-sectional study on drug-related problems in the Netherlands. Int J Clin Pharm . 2016;38(1):46-53. doi:10.1007/s11096-015-0199-8 Kari H, Kortejärvi H, Airaksinen M, Laaksonen R. Patient involvement is essential in identifying drug-related problems. Br J Clin Pharmacol . 2018;84(9):2048-2058. doi:10.1111/bcp.13640 Leikola SNS, Virolainen J, Tuomainen L, Tuominen RK, Airaksinen MSA. Comprehensive medication reviews for elderly patients: Findings and recommendations to physicians. Journal of the American Pharmacists Association . 2012;52(5):630-633. doi:10.1331/JAPhA.2012.10163 Sellors J, Kaczorowski J, Sellors C, et al. A randomized controlled trial of a pharmacist consultation program for family physicians and their elderly patients. CMAJ Canadian Medical Association Journal . 2003;169(1):17-22. Touchette DR, Masica AL, Dolor RJ, et al. Safety-focused medication therapy management: A randomized controlled trial. Journal of the American Pharmacists Association . 2012;52(5):603-612. doi:10.1331/JAPhA.2012.12036 Vinks THAM, De Koning FHP, De Lange TM, Egberts TCG. Identification of potential drug-related problems in the elderly: The role of the community pharmacist. Pharmacy World and Science . 2006;28(1):33-38. doi:10.1007/s11096-005-4213-4 Kwint HF, Faber A, Gussekloo J, Bouvy ML. Effects of medication review on drug-related problems in patients using automated drug-dispensing systems: A pragmatic randomized controlled study. Drugs Aging . 2011;28(4):305-314. doi:10.2165/11586850-000000000-00000 Kwint HF, Faber A, Gussekloo J, Bouvy ML. The contribution of patient interviews to the identification of drug-related problems in home medication review. J Clin Pharm Ther . 2012;37(6):674-680. doi:10.1111/j.1365-2710.2012.01370.x Chan DC, Chen JH, Wen CJ, Chiu LS, Wu SC. Effectiveness of the medication safety review clinics for older adults prescribed multiple medications. Journal of the Formosan Medical Association . 2014;113(2):106-113. doi:10.1016/j.jfma.2012.04.013 Rhalimi M, Rauss A, Housieaux E. Drug-related problems identified during geriatric medication review in the community pharmacy. Int J Clin Pharm . 2018;40(1):109-118. doi:10.1007/s11096-017-0571-y Kovačević SV, Miljković B, Ćulafić M, et al. Evaluation of drug-related problems in older polypharmacy primary care patients. J Eval Clin Pract . 2017;23(4):860-865. doi:10.1111/jep.12737 O’Dell KM, Kucukarslan SN. Impact of the clinical pharmacist on readmission in patients with acute coronary syndrome. Annals of Pharmacotherapy . 2005;39(9):1423-1427. doi:10.1345/aph.1E640 Swieczkowski D, Merks P, Gruchala M, Jaguszewski MJ. The role of the pharmacist in the care of patients with cardiovascular diseases. Kardiol Pol . 2016;74(11):1319-1326. doi:10.5603/KP.a2016.0136 Amankwa Harrison M, Marfo AFA, Buabeng KO, Nkansah FA, Boateng DP, Ankrah DNA. Drug-related problems among hospitalized hypertensive and heart failure patients and physician acceptance of pharmacists’ interventions at a teaching hospital in Ghana. Health Sci Rep . 2022;5(5):1-10. doi:10.1002/hsr2.786 Acheampong F, Nkansah FA, Anto BP. Drug-related problems and their clinical interventions in a Ghanaian teaching hospital. Safety in Health . 2016;2(1):1-7. doi:10.1186/s40886-016-0050-5 Stuhec M, Flegar I, Zelko E, Kovačič A, Zabavnik V. Clinical pharmacist interventions in cardiovascular disease pharmacotherapy in elderly patients on excessive polypharmacy: A retrospective pre-post observational multicentric study. Wien Klin Wochenschr . 2021;133(15-16):770-779. doi:10.1007/s00508-020-01801-y Shareef J, Sandeep B, Shastry CS. Assessment of Drug Related Problems in Patients with Cardiovascular Diseases in a Tertiary Care Teaching Hospital. Journal of Pharmaceutical Care . 2014;2(2):70-76. Laranjeira T, Mirco A, Falcão F. 4CPS-027 Hospital pharmacist interventions in an accredited cardiology department. European Journal of Hospital Pharmacy . 2018;25(Suppl 1):A53 LP-A54. doi:10.1136/ejhpharm-2018-eahpconf.118 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4448386","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":308765033,"identity":"cc9504df-8c3d-438b-bae5-9fbcdf05e558","order_by":0,"name":"Damla SOSYAL","email":"","orcid":"","institution":"Department of Clinical Pharmacy, Basaksehir Cam and Sakura City Hospital","correspondingAuthor":false,"prefix":"","firstName":"Damla","middleName":"","lastName":"SOSYAL","suffix":""},{"id":308765034,"identity":"2a593ac1-540d-4982-a025-9a49b8bf63c9","order_by":1,"name":"Muhammed Yunus Bektay","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYLACxgYGAxD1AEjw8BGthYeBgRmkj4eNFC1sEiAOQS0GN3KPSf7cYWNsz37GrPJrjp0MGwPzw0c38GrJS5PmPZNmxsOTY3Zbdlsy0GFsxsY5eLXkmEkzth224WEAapHcxgzUwsMmTUiL5M+2/zY8/G/MiiW31ROnRYK37YAZj0SOGePHbYcJa5E888bYmvdMsjHPjWfF0ozbjvOwMRPwC9/xHMObP3fYGbb3J2/8+HNbtT0/e/PDx/i0KByAMzkMmHlANDMe5SAg3wBnsj9g/EFA9SgYBaNgFIxMAABaSUO1XoB+VAAAAABJRU5ErkJggg==","orcid":"","institution":"Department of Clinical Pharmacy, İstanbul University-Cerrahpaşa Faculty of Pharmacy.","correspondingAuthor":true,"prefix":"","firstName":"Muhammed","middleName":"Yunus","lastName":"Bektay","suffix":""},{"id":308765038,"identity":"40d7d85c-41c1-4f4d-b50e-1da2782d0dd1","order_by":2,"name":"Nusret Acikgoz","email":"","orcid":"","institution":"Department of Cardiology, Bezmialem Vakif University Faculty of Medicine.","correspondingAuthor":false,"prefix":"","firstName":"Nusret","middleName":"","lastName":"Acikgoz","suffix":""},{"id":308765039,"identity":"defd44b4-501b-4e79-bc3c-4176ef5743f2","order_by":3,"name":"Fikret Vehbi Izzettin","email":"","orcid":"","institution":"Department of Clinical Pharmacy, Bezmialem Vakif University Faculty of Pharmacy","correspondingAuthor":false,"prefix":"","firstName":"Fikret","middleName":"Vehbi","lastName":"Izzettin","suffix":""}],"badges":[],"createdAt":"2024-05-20 10:14:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4448386/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4448386/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":57519479,"identity":"f1893d02-38ba-432d-88be-9a6880614f61","added_by":"auto","created_at":"2024-05-31 20:44:12","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":892743,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4448386/v1/7173ee58-9de9-42e2-9f1b-56d34efe8d43.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of Clinical Pharmacy Services in Patients Receiving Antithrombotic Treatment: A Randomized Controlled Trial","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccording to the World Health Organization (WHO), the most common cause of adult death is cardiovascular disease (CVD). In 2030, it is estimated that there will be more than 22\u0026nbsp;million mortalities due to cardiovascular diseases \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Thrombosis is the most common cause of morbidity and mortality and causes a huge burden of disease worldwide \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. In this case, antithrombotic therapy is important for the success of treatment. However, the widespread use of antithrombotic drugs suggests that patients receiving this treatment may be more vulnerable to DRPs \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe Pharmaceutical Care Network Europe (PCNE) defines an DRPs as an event involving drug treatment that actually or potentially interferes with desired health outcomes \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Adverse drug events (ADEs) constitute a small proportion of drug-related problems. Medication errors, overdose, drug dependence, adherence problems and therapeutic failure are among other important problems associated with drug use \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. Patients with CVD are more likely to use high-risk medications such as antithrombotic drugs. These patients are also at significant risk of adverse drug events and medication errors \u003csup\u003e\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. By focusing on the prevention of medication-related adverse events and errors, patient outcomes related to these events can be improved \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe American Clinical Pharmacy Association (ACCP) defines clinical pharmacy services (CPS) as \"\u003cem\u003eA health sciences discipline in which pharmacists provide patient care that optimizes drug therapy and promotes health, wellness and disease prevention\u003c/em\u003e\" \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Clinical pharmacist interventions are defined as \"any action initiated by a pharmacist that results in a change in direct patient management or medication therapy\" \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Clinical pharmacists have assumed important roles in ensuring the effective and correct use of medicines and in reducing and preventing DRPs.\u003c/p\u003e \u003cp\u003eInteracting with a clinical pharmacist in the treatment of inpatients has helped to reduce adverse drug reactions, medication errors, improve post-discharge medication adherence and shorten the length of hospital stay. Overall, the provision of clinical pharmacy services in inpatients and outpatients has resulted in improved quality of care with no harm to patients \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. This study aimed to identify and prevent drug-related problems (DRPs) in patients receiving antithrombotic therapy by clinical pharmacists. Additionally, clinical pharmacy services were also reviewed. Furthermore, the rehospitalizations of patients within the 1 to 3-month period were also assessed.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design, participants and setting:\u003c/h2\u003e \u003cp\u003e A randomized controlled study was conducted on patients admitted to the Cardiology ward and receiving antithrombotic therapy for any reason at a tertiary-care university hospital in Istanbul, T\u0026uuml;rkiye, from November 2021 to November2022. Inclusion criteria for this study encompassed being 18 years of age or older and patients with a confirmed usage of any of the antithrombotic medications (ATC Group: B01). Participants were further required provide written informed consent for study participation. The patients with incomplete biochemistry-hemogram values taken twice and incomplete two-day medication list, patient follow-up and medication review lost were excluded. The study design and criteria aim to comprehensively assess the impact of CP interventions on the clinical outcomes of patients prescribes AT medications.\u003c/p\u003e \u003cp\u003eThe randomization process was performed as simple randomization using an algorithm generated by Research Randomizer\u0026reg; software that assigned patients to the control group (CG) or intervention group (IG) in a 1:1 ratio. In the study, a clinical pharmacist (CP) on the team developed a concealed allocation schedule. This schedule, stratified by groups, randomly assigned two sequences to a consecutive series of numbers. Upon enrollment, the CP assigned each participant the next consecutive number, determining the sequence of intervention. Participants were then randomly assigned to the CG and IG.\u003c/p\u003e \u003cp\u003eThe IG comprised patients for whom CP recommendations for DRPs were communicated to the healthcare team. Conversely, the CG consisted of patients for whom no such recommendations were made to the healthcare team by CP, concerning DRPs; only observations were conducted. Patients in CG who received their standard treatment were only monitored by the clinical pharmacist, while in the IG, in addition to this, recommendations were made to physicians regarding DRPs detected by the clinical pharmacist.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData collection:\u003c/h2\u003e \u003cp\u003eDuring the study, meticulous records were maintained with confidentiality, encompassing contact information, medical history, medication history, current medications, laboratory findings, and physical examination records. These details were carefully documented to ensure the highest level of privacy and compliance with ethical standards. The characteristics of the patients in the control and intervention groups were recorded through the hospital electronic record system. The evaluation and classification of DRPs were carried out by following five steps: \u003cem\u003e(i)\u003c/em\u003e Recording the sociodemographic and hospitalization day information of the patients: Age, gender, disease, comorbid conditions, admission diagnoses, laboratory data during hospitalization (creatinine, blood glucose, AST, etc.). \u003cem\u003e(ii)\u003c/em\u003e The medications (active substance, dose, route, time, frequency of drug administration, duration of treatment) previously used and prescribed during hospitalization were recorded. Local used drugs such as ointments, pomades and maintenance fluids were excluded. \u003cem\u003e(iii)\u003c/em\u003e Assessment of patients' medications during hospitalization: The evaluation was based on current diagnostic and therapeutic guidelines (e.g. European Society of Cardiology, American Heart Association), health practice guidelines, clinical decision support systems and current literature (e.g. UpToDate\u0026reg;, RxMediaPharma\u0026reg; interactive drug information resource, IBM Micromedex drug reference\u0026reg;, Medscape\u0026reg;, Lexicomp\u0026reg;, Sanford Guide\u0026reg;). In the current study, these well-established guidelines collectively formed the basis for ensuring the appropriateness and adherence to best practices in antithrombotic therapy for patients prescribed with AT medication. \u003cem\u003e(iv)\u003c/em\u003e Assessment of existing or potential drug-drug interactions: The Lexicomp\u0026reg; Drug Interactions application was used for this purpose. \u003cem\u003e(v)\u003c/em\u003e Identification and classification of DRPs: The European Pharmaceutical Care Network's DRPs classification (v9.1) was used.\u003c/p\u003e \u003cp\u003eThe study also delved into DRPs, encompassing their causes, CP recommendations for resolution, and physicians' subsequent acceptance and implementation. The Turkish version of the Pharmaceutical Care Network Europe Association (PCNE) Classification scheme for Drug-Related Problems v9.1 was employed to identify DRPs. This version, validated by the PCNE working group, features a comprehensive classification system consisting of primary domains for problems, causes, planned interventions, level of acceptance (of interventions), and the status of the problem. On a more detailed level, the scheme comprises grouped sub-domains, providing explanatory granularity for the principal domains. The validated PCNE classification scheme offers a robust framework for systematically categorizing and addressing DRPs in the study context (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.pcne.org/upload/files/417_PCNE_\u003c/span\u003e\u003cspan address=\"https://www.pcne.org/upload/files/417_PCNE_\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e classification _V9-1_ final.pdf).\u003c/p\u003e \u003cp\u003eThis study has been reported according to recommendation of Consolidated Standards of Reporting Trials (CONSORT) standards.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics approval:\u003c/strong\u003e \u003cp\u003e The studies involving human participants were reviewed and approved by the local Ethics Committee of Clinical Research with decision number 19/5. This study protocol has been registered at ClinicalTrials.gov (NCT06193473).\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eClinical interventions:\u003c/h2\u003e \u003cp\u003eThe data of patients admitted to the cardiology ward with a prescription of antithrombotic (AT) medication were meticulously recorded during their hospitalization. During patients\u0026rsquo; hospital stay, a multidisciplinary team evaluated the patients' treatment regimen and medications. The CP played an integral role in this process, closely monitoring the patient and treatment adjustments for patients and identifying DRPs through a comprehensive assessment of their medication information.\u003c/p\u003e \u003cp\u003eThe clinical pharmacist, together with the responsible physician and other health workers, attended daily ward visits on weekdays, conducted medication reviews and provided interventions for patients with DRPs in the intervention group. These interventions were face-to-face, verbal recommendations to the health workers in the team. Recommendations were made at the time of admission to the ward, during the hospital stay and at discharge.\u003c/p\u003e \u003cp\u003eIn the IG, the CP provided face-to-face recommendations for DRPs to the attending physician. An experienced multidisciplinary team containing CP jointly assessed the clinical significance of identified DRPs. The interventions were designed to detect and prevent DRPs, thereby addressing concerns in patients hospitalized with a AT medication. Recommendations included additions to the patient's treatment regimen, discontinuation of off-label or inappropriate medications, proposing alternative agents, altering the route of administration, suggesting therapeutic drug monitoring, advising dose adjustments, managing drug-drug interactions, and optimizing the duration of treatment. The clinical pharmacist provided advice on drug selection, addition, discontinuation, follow-up, dose adjustment, management of side effects, and potential drug-drug interactions. To analyze medications and evaluate potential drug-drug interactions (pDDIs), the Lexicomp\u0026reg; (Wolters Kluwer Health Inc.) database was utilized. The X (contraindicated) and D (drug change considered) levels, which are important levels for potential drug-drug interactions, were assessed. Among these, recommendations were made for those deemed clinically important. The drugs used by the patients from hospitalization to discharge and the agents responsible for DRPs were compared between the two groups. In addition, the groups were evaluated in terms of whether the patients were readmitted to hospital within 1 and 3 months after discharge. The LACE index score was used to predict readmission within 30 days after discharge \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMain outcome measure\u003c/h2\u003e \u003cp\u003eThe primary outcomes of the study focused on the identification and classification of DRPs, the acceptance rate of CP recommendations, and rehospitalizations on both the 30th and 90th days among the groups. These outcomes were integral to assessing the impact of CP interventions on patient care and treatment outcomes. Additionally, secondary outcomes of the study included comparing patients in terms of disease course, rehospitalization rates. This secondary analysis aimed to comprehensively understand how CP involvement influenced key aspects of the disease trajectory and patient outcomes beyond the immediate post-discharge period. By systematically evaluating both primary and secondary outcomes, the study aimed to contribute valuable insights into the effectiveness of CP interventions in optimizing patient care, enhancing treatment outcomes, and potentially influencing the long-term prognosis of individuals prescribed with AT medications.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSample Size:\u003c/h2\u003e \u003cp\u003eThe sample size calculation for the study was conducted based on data from the literature \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, indicating that DRPs were reduced by an average of 1 per patient in groups where CP made recommendations. The standard deviation was assumed to be 1. According to our sample size calculations based on drug-related problems to determine the number of participants needed for the ethics committee application, the effect size (d) was calculated as 0.5540. Taking the alpha (α) error as 0.05 and beta (β) error as 0.95, at least 135 participants should be included for each group and the power of our study was calculated as 0.95.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis:\u003c/h2\u003e \u003cp\u003eAnalyses were performed using SPSS (Statistical Package for Social Sciences) Windows 11.0 program. The results were evaluated at 95% confidence interval and significance at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 level. Demographic data were expressed as percentages, continuous and discrete variables were expressed as mean, standard deviation, median, interquartile distribution, and drug-related problems were expressed as percentages and numerical values. Whether the data were normally distributed or not was determined by Kolmogorov-Smirnov test; the differences between the two groups were evaluated using Student's t-test for those that met the normal distribution, Mann Whitney U test for parameters that did not meet the normal distribution condition, and Chi-square or Fisher exact tests for discrete variables. P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was accepted as the level of statistical significance.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eDemographics, medications and hospital admission:\u003c/h2\u003e \u003cp\u003eOf the patients who met the inclusion criteria, 200 were included in the control group and 200 in the intervention group. The mean ages of these patients were 67.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2 and 67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3, respectively. The mean number of diseases or comorbid conditions per patient in the control and intervention groups were 4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88 and 4.77\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04, respectively. In both groups, a minimum of 1 and a maximum of 10 conditions were encountered in one patient. The most common disease was coronary artery disease, which was present in 149 patients (74.5%) in both groups. Subsequently, hypertension was seen in 141 (70.5%) and 140 (70%) patients in the control and intervention groups, respectively. Diabetes was the third most common disease in 99 (49.5%) of the control group and heart failure in 96 (48%) of the intervention group. It was also reported that more than 40% of patients developed acute coronary syndrome, 88 (44%) and 87 (43.5%) patients, respectively. AF and other rhythm disturbances were 68 (34%) and 76 (38%), respectively (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of Patients\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBaseline Characteristics of Patients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl Group (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntervention Group (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eSex \u003cem\u003e(n, %)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale \u003cem\u003e(n, %)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85 (42.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e74 (37%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale \u003cem\u003e(n, %)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (57.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126 (63%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg) (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79.8\u0026thinsp;\u0026plusmn;\u0026thinsp;18.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.79*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28.9\u0026thinsp;\u0026plusmn;\u0026thinsp;6.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28.2\u0026thinsp;\u0026plusmn;\u0026thinsp;4.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.17*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo of Comorbidities (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.74\u0026thinsp;\u0026plusmn;\u0026thinsp;1.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.77\u0026thinsp;\u0026plusmn;\u0026thinsp;2.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e1 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e2 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e3 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e4 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e5 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e6 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e7 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003e8 (n)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eMost common 10 diseases and comorbidities (n, %)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart Valve Disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (27.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (25%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArrhythmia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e68 (34%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (38%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAtrial fibrillation/ flutter (AF/AFL)\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eArrhythmia without AF/ AFL\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (29%)\u003c/p\u003e \u003cp\u003e10 (5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (30%)\u003c/p\u003e \u003cp\u003e16 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCerebrovascular disease/ Transient ischemic attack\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCoronary artery disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e149 (74.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e149 (74.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAcute coronary syndrome\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003ePercutaneous coronary intervention\u003c/em\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eCoronary artery bypass graft surgery\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (44%)\u003c/p\u003e \u003cp\u003e70 (35%)\u003c/p\u003e \u003cp\u003e34 (17%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (43.5%)\u003c/p\u003e \u003cp\u003e63 (31.5%)\u003c/p\u003e \u003cp\u003e29 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e141 (70.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140 (70%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e86 (43%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic kidney disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (14%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (12%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99 (49.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (48%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThyroid diseases\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsthma/ Chronic obstructive pulmonary disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Mann-Whitney U test, \u003csup\u003e#\u003c/sup\u003eKi-Square test, SD: Standard derivation\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003ePatients in the control and intervention groups were most frequently referred to the cardiology service from the emergency department (52%; 51.5%). The second most frequent referral was from outpatient clinic to the ward (47.5%; 43.5%). The most common reasons for hospitalization and the corresponding diagnoses for each group are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eThe most frequently used 5 Anatomical Therapeutic Chemical (ATC) groups in both the CG and IG were cardiovascular system (C), digestive system and metabolism (A), blood and blood-forming organs (B), nervous system (N) and respiratory system (R) in the control and intervention groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the control and intervention groups, the most commonly prescribed antiplatelet therapy was acetylsalicylic acid in 71% and 67.5% of patients, and anticoagulant therapy was enoxaparin in 44% and 53% of individuals, respectively.\u003c/p\u003e \u003cp\u003eNo significant difference was found between the groups in terms of LACE classification (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Similarly, there was no significant difference between the control and intervention groups in terms of emergency readmissions and unplanned hospitalizations within 1 and 3 months after discharge. Readmissions and rehospitalizations were numerically higher in the control group compared to the intervention group (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient's hospitalization information and drug-related problems identified\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eData\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl Group (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntervention Group (n\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of drugs (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.8\u0026thinsp;\u0026plusmn;\u0026thinsp;5.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.6\u0026thinsp;\u0026plusmn;\u0026thinsp;5.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.14*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLength of stay (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.83\u0026thinsp;\u0026plusmn;\u0026thinsp;3.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.04\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.28*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLACE Index for Readmission (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7.25\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnplanned rehospitalization within 1 month (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.16\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnplanned rehospitalization within 3 month (n)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60\u003csup\u003e#\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe number of emergency and unplanned readmissions within 3 months (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.454\u0026thinsp;\u0026plusmn;\u0026thinsp;0.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.703\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.96*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of DRPs, n\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e561\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e497\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.15*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of possible drug-drug interactions per patient (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.78\u0026thinsp;\u0026plusmn;\u0026thinsp;1.95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.58\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.53*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of clinically significant DRPs per patient (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.81\u0026thinsp;\u0026plusmn;\u0026thinsp;2.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.33\u0026thinsp;\u0026plusmn;\u0026thinsp;2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccepted interventions, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e235 (94.76%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnaccepted interventions, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (5.24%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003e-\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e*Mann-Whitney U test, \u003csup\u003e#\u003c/sup\u003eKi-Square test, SD: Standard derivation. Data presented as percentage.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eDrug-related problems and pharmacist interventions:\u003c/h2\u003e \u003cp\u003eAccording to the PCNE classification, the clinical pharmacist identified 561 possible DRPs in 166 (83%) patients in the control group and 497 possible DRPs in 153 (76.5%) patients in the intervention group. The most frequently identified DRPs were related to 'treatment safety'. Treatment safety-related DRPs accounted for 413 (73.62%) and 369 (74.25%) of the patient problems in the control and intervention groups, respectively. There were 135 (24.06%) problems related to 'treatment effectiveness' in the CG and 115 (23.14%) in the IG. It was observed that the most common cause of DRPs was 'drug selection' for both groups. 'Drug selection' accounted for 81.11% of the problems in the CG and 80.88% of the problems in the IG. The second most common reason was related to 'dose selection' in both groups. 107 (19.08%), 80 (16.10%) reasons were associated with 'dose selection', respectively. Among the reasons for most dose selection, 'low dose' and 'high dose' were 58 (10.34%) and 35 (6.24%) in the CG and 35 (7.04%) and 17 (3.42%) in the IG, respectively (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eClassification of drug-related problems according to PCNE v9.1\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProblems (also potential)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCG\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCauses\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eIG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cem\u003e%\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP1. Treatment effectiveness\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.06%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC\u003c/b\u003e\u003cem\u003e3.1 Drug dose too low\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10.34%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e7.04%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP1.1 No effect of drug treatment despite correct use\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC3.2 Drug dose of a single active ingredient too high\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6.24%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e3.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP1.2 Effect of drug treatment not optimal\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.64%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14.49%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC3.3 Dosage regimen not frequent enough\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.82%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP1.3 Untreated symptoms or indication\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.42%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.45%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC3.4 Dosage regimen too frequent\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP2. Treatment safety\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC3.5 Dose timing instructions wrong, unclear or missing\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP2.1 Adverse drug event (possibly) occurring\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.62%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e74.25%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC4. Treatment duration\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP3. Other\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.32%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.61%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC4.2 Duration of treatment too long\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP3.1 Unnecessary drug-treatment\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.14%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.41%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC5. Dispensing\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP3.2 Unclear problem/complaint. Further clarification necessary\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC5.1 Prescribed drug not available\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCauses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC5.4 Wrong drug or strength dispensed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC1. Drug selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e455\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81.11%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e402\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e80.88%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC6. Drug use process\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC1.1 Inappropriate drug according to guidelines/formulary\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.63%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6.04%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC6.1 Inappropriate timing of administration or dosing intervals by a health professional\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC1.2 No indication for drug\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.80%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC7. Patient related\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC1.3 Inappropriate combination of drugs, or drugs and herbal medications, or drugs and dietary supplements\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e359\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e64.39%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC7.2 Patient uses/takes more drug than prescribed\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC1.4 Inappropriate duplication of therapeutic group or active ingredient\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.36%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.60%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC7.4 Patient decides to use unnecessary drug\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC1.5 No or incomplete drug treatment in spite of existing indication\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.94%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e8.85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eC8. Patient transfer related\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC1.6 Too many different drugs/active ingredients prescribed for indication\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC8.1 Medication reconciliation problem\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.96%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e4.43%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC2. Drug form\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e-\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eC9 Other\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eC2.1 Inappropriate drug form/formulation (for this patient)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.40%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC9.1 No or inappropriate outcome monitoring (including TDM)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e0.20%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC3. Dose selection\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e107\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.08%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e80\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e16.10%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eC9.2 Other cause; specify\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e2.01%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003eCG: Control Group, IG: Intervention Group, %: Percentage\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe majority of the interventions performed by the clinical pharmacist were at the prescriber level (214, 86.29%) and at the drug level (172, 69.35%) (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The majority of the interventions in the other category were possible drug-drug interactions (pDDI) monitored by the clinical pharmacist during drug use. These interactions were potential problems such as QTc prolongation, the need for level monitoring of drugs such as warfarin, or potential major problems.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLevel, acceptance and status of interventions\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of recommendations (n\u0026thinsp;=\u0026thinsp;248)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLevel of Interventions*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI1. At prescriber level\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e86.29%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI2. At patient level\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI3. At drug level\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e69.35%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eI4. Other\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32.66%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eIntervention Acceptance\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA1. Intervention accepted\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e94.76%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA1.1 Intervention accepted and fully implemented\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.02%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA1.2 Intervention accepted, partially implemented\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA1.3 Intervention accepted but not implemented\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.98%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA1.4 Intervention accepted, implementation unknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.81%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA2. Intervention not accepted\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.24%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA2.2 Intervention not accepted: no agreement\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.42%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA2.3 Intervention not accepted: other reason (specify)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.61%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eA2.4 Intervention not accepted: unknown reason\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eStatus of Interventions\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eO0. Problem status unknown\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.21%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eO1. Problem solved\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e140\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56.45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eO2. Problem partially solved\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.08%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e*Percentage over the total number of interventions (n\u0026thinsp;=\u0026thinsp;248). Data presented as percentage.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the CG, 356 pDDI were identified in 130 individuals and 317 pDDI in 128 individuals in the IG. The majority of the potential problems identified in the intervention group that were not found to be clinically important. These drug-drug pairs consisted of medicines that were intentionally prescribed to patients for specific indications, were meant to be used together, and were the monitoring of clinical pharmacist. For this reason, there was no attempt to avoid using them. Taking this into consideration, the clinical pharmacist identified 86 pDDI that were considered important in the IG. In this case, the number of clinically significant DRPs expected to be the main problem in the IG with involvement of the clinical pharmacist was determined as 266. Additionally, there was a statistically significant reduction in the number of clinically significant DRPs in the IG compared to the CG (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the IG, 248 recommendations (93.23%) for 126 patients (63%) regarding 266 clinically significant DRPs were made by the clinical pharmacist during hospitalization. Of the suggestions made, 235 (94.76%) were accepted. 91.53% of the intervened problems were resolved (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe correlation matrix of the patients was examined, revealing significant positive and negative correlations with respect to LACE score, length of stay and DRPs. The highest level of association between variables was found between pDDI and DRPs. Additionally, a significant correlation was observed between the day of hospitalization and readmissions within 1 month, and notably, within 3 months (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCorrelation matrix of some factors associated with hospitalizations and DRPs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLACE index score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLength of stay (Day)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNumber of DRPs\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of comorbidities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.459***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.317***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.348***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.478***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.602***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.621***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of possible drug-drug interactions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.378***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.363***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.882***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.156**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.251***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.177***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCRP \u003cem\u003emg/dl\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.218***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.322***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.322***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrea \u003cem\u003emg/dl\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.271***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.366***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.272***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR \u003cem\u003emL/min/1.73 m\u003c/em\u003e\u003csup\u003e\u003cem\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/em\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:-0.289***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:-0.303***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:-0.259***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCalcium \u003cem\u003emg/dL\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:-0.184***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:-0.342***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:-0.153**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium \u003cem\u003emmol/L\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:-0.143**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:-0.103*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:-0.154**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNeutrophil/lymphocyte absolute count\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.258***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.307***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.233***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHGB \u003cem\u003eg/dl\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:-0.246***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:-0.365***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:-0.245***\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBNP \u003cem\u003eng/l\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.228***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.388***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003er:0.127*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReadmissions within 1 month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.155**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.111*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReadmissions within 3 month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003er:0.112*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003er:0.127***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003er: Correlation Coefficient; p: significance level, *p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; **p\u0026thinsp;\u0026lt;\u0026thinsp;0.01; ***p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; eGFR: Estimated glomerular filtration rate; CRP: C-reactive protein; HGB: Hemoglobin; BNP: Brain natriuretic peptide. Data presented as percentage.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the groups in our study, it was observed that the most common agents causing DRPs in the ATC group were drugs used in the blood and blood-forming organs, digestive system and metabolism, cardiovascular system, anti-infective drugs and nervous system (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Similarly, the most common interventions were for these groups of drugs. Among these, systemic antibacterials, antithrombotics, drugs used in cardiac treatment, drugs used in diabetes treatment and psycholeptics were the drugs for which most interventions were performed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe antithrombotic drugs most responsible for DRPs were similar in the control and intervention groups and the top 3 drugs were enoxaparin, acetylsalicylic acid and clopidogrel. Antithrombotic drugs for which most interventions were performed included enoxaparin, apixaban and warfarin (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn our study, 'coronary artery disease' (74.5%; 74.5%) was identified to be the most common disease in the control and intervention groups, which can be attributed to the inclusion criteria selecting patients receiving antithrombotic drugs. Hypertension was the second most common condition (70.5%; 70%), while diabetes was the third most common in the control group (49.5%) and heart failure (48%) in the intervention group. Our findings are consistent with the studies conducted by Patel et al. and Greeshma et al., both of which reported hypertension and diabetes as the most prevalent conditions in their studies \u003csup\u003e1516\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eClinical pharmacists have been demonstrated to improve the use of high-risk medicines through medication review and to ensure the accuracy of medication regimens in older patients \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In our study, the mean age of our patient population was 67 years in both groups and the medications used by the patients were carefully reviewed by the clinical pharmacist. One study reported a three-fold increased risk of developing DRPs in adults over 60 years of age \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. This may be explained by factors such as increased incidence of renal and hepatic insufficiency, increased number of comorbidities and polypharmacy in elderly patients. Therefore, dosing errors, drug interactions, side effects and medication adherence problems may occur. Bektay et al. found a correlation between the number of DRPs and comorbidities and the number of drugs used (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Niriayo et al. reported that the likelihood of DRPs in patients with polypharmacy was approximately three times higher than in patients taking fewer medications. A possible explanation for this is that polypharmacy may lead to poor adherence, drug interactions and drug side effects. Similarly, an increased risk of drug interactions and side effects has been observed in patients with multiple comorbidities \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e. In our study, a positive correlation was observed between the number of DRPs detected and age (r: 0.177, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), total number of comorbidities (r: 0.348; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and total number of drugs used during hospitalization (r: 0.621; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). DRPs were detected in more than 75% of patients in both groups, with a contributing factor to this high rate identified as pDDI. Depending on the indications for antithrombotic drugs, patients were often required to use a combination of drugs, making them particularly susceptible to level D pDDI.\u003c/p\u003e \u003cp\u003eSpecific drugs or indications are thought to predispose to DRPs. According to a review, the ATC groups 'Cardiovascular system', 'Digestive system and metabolism', 'Blood and blood-forming organs' accounted for 32.1%, 29.4% and 11% of all DRPs, respectively. These findings suggest that patients taking these drug classes may be at increased risk of DRPs \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Furthermore, in both groups in our study, the causative agents of DRPs were most frequently found in these ATC groups. In this regard, our study aligns with and supports these previous findings. Additionally, as observed in the intervention group, the clinical pharmacist played a crucial role in managing drugs from different classes.\u003c/p\u003e \u003cp\u003eWang et al. found that the most frequently identified problems were related to 'treatment efficacy' (53.71%), followed by 'treatment safety' (33.90%) \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. Conversely, Albayrak et al. reported that the most important problem in DRPs was 'treatment safety' \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. In our study, the most common problem in the CG and IG was also found to be related to 'treatment safety' (73.62%; 74.25%). This was followed by problems linked to 'treatment efficacy' (24.06%; 23.14%). Given the prevalence of drug-related side effects in the cardiology ward, these problems are frequently encountered. Therefore, a thorough examination of treatment safety is important in this ward.\u003c/p\u003e \u003cp\u003eIn the literature, the main causes of DRPs were reported as 'drug selection' (51.41%), 'dose selection' (11.62%), 'patient-related' (10.70%) and 'other' (5.73%) \u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. In our study, the most common reasons for DRPs in the both groups were 'drug selection' (81.11%; 80.88%) and 'dose selection' (19.08%; 16.10%). Among dose selection reasons, 'low dose' (10.34%; 6.24%) and 'high dose' (7.04%; 3.42%) were the most common, respectively. In our study, a significant correlation was also found between elevated urea (r: 0.272, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), blood urea nitrogen (r: 0.266, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), creatinine (r: 0.186, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and DRPs. This suggests a potential association between DRPs and renal function levels, emphasizing the need for clinical pharmacists to exercise increased vigilance in cases of possible kidney disease. Of the medication-level interventions for DRPs deemed significant by the clinical pharmacist, 46.51% were dose changes and discontinuation/interruption. Most of these interventions were prompted by the presence of chronic, acute or acute-on-chronic renal dysfunction in patients with DRPs, necessitating dose adjustments based on declining or recovering renal function values. Additionally, DRPs were related to drugs such as enoxaparin and apixaban for which dose recommendations were also based on patient weight. All of these recommendations made by the clinical pharmacist were accepted, thus increasing the focus on these critical aspects. In the cardiology ward, patients need to be evaluated from a multidimensional perspective, taking into account their characteristics and clinical conditions. Our study pointed out that daily follow-up of patients and necessary dose adjustments are essential services that clinical pharmacists can provide to prevent unnecessary drug treatments, minimize side effects or ensure effective drug treatment.\u003c/p\u003e \u003cp\u003eIn the literature, 'Inappropriate drug selection'\u003csup\u003e\u003cspan additionalcitationids=\"CR27 CR28 CR29 CR30 CR31\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e ' no or incomplete drug treatment despite current indication' \u003csup\u003e\u003cspan additionalcitationids=\"CR27\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e and 'inappropriate drug combinations' \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e were observed as the most common causes of 'drug selection' problems. In our study, 'inappropriate drug selection or drug combination (N1.3)' was identified as the most common cause of 'drug selection'. The reason for this is that D and X level possible drug-drug interactions constitute the majority of DRPs in PCNE. Additionally, interventions related to drug interactions were found to be the less likely to be implemented in the literature \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. In our study, since the clinical pharmacist intervened only for clinically significant interactions, these interventions were fewer than the number of pDDI identified. Possible drug-drug interactions for which no intervention was performed accounted for 92.77% of the problems without intervention. Furthermore, these interactions represented 46.48% of the potential or actual problems identified and 72.87% of the total pDDI identified. As observed in our study, most of these problems that were not intervened, which is approximately half of the total problems, were possible drug-drug interactions that were not considered clinically significant. The reason for not intervening was that these drugs are deliberately used together in the treatment of the patient and are drug combinations where drug-drug interaction is already an expected or desired outcome. For example, in cases such as acute coronary syndrome, the addition of anticoagulant drugs such as enoxaparin to antiplatelet therapy is one of the examples where drug combinations that act through different mechanisms are required to be used together in the guidelines. When such situations are taken into account, the total number of possible or actual DRPs which was 497 was replaced by 266 clinically significant DRPs, in the intervention group. In the total number of DRPs, there was a significant decrease (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) in the intervention group where the clinical pharmacist was involved, compared to the control group. In addition, most of the interventions in the 'other' category, which accounted for 32.66% of the interventions in our study, consisted of possible drug-drug interactions that the clinical pharmacist considered to be clinically important, for which the clinical pharmacist recommended 'drug monitoring' to physicians. In particular, these were combinations of drugs that may prolong QTc or alter each other's levels. As was clearly seen during our study, the involvement of a clinical pharmacist in the health team can ensure the monitoring and appropriate use of medications.\u003c/p\u003e \u003cp\u003eAccording to the PCNE classification, all significant level pDDI should be categorized as 'inappropriate drug combinations' in the 'drug selection' domain. Our study demonstrated the difficulty in the implementation of PCNE, as PCNE includes drug combinations given to patients for clinical indications as a problem under the heading of possible drug-drug interaction. In addition, it needs to revise itself under separate headings to elaborate at drug-level interventions such as 'drug preparation' and 'drug monitoring'. Such incomplete situations make it difficult to implement PCNE in the hospital setting. In addition, since the major conditions considered problematic in each ward may differ, we suggest developing special subsystem versions of PCNE and conducting reliability studies in this direction. It is stated that overcoming the limitations of PCNE is important for its implementation and dissemination in hospital settings.\u003c/p\u003e \u003cp\u003eThere are studies in the literature evaluating the impact of the clinical pharmacist on readmission. For instance, O'Dell et al. reported a significantly lower rate of readmission for cardiac reasons at 30 days in study patients compared to control patients \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. On the other hand, Lowrie et al. found no significant difference between groups in outcomes, including death or hospitalization \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. In our study, the total number of emergency and hospital readmissions within 3 months was numerically lower in the intervention group. However, no significant difference was observed in emergency admissions and unplanned hospitalizations in the follow-up periods. This may be associated with several reasons. It may be related to the fact that demographic, clinical, laboratory and other patient-related factors such as age, comorbidity, creatinine and number of medications used were similar between the two groups. In addition, adherence to treatment after discharge is also a parameter that should be evaluated in terms of rehospitalizations. A weak but significant positive correlation was found between LACE scores and readmissions within 1 and 3 months. Therefore, in addition to predicting readmissions within 1 month, it is envisaged that the LACE score can also be used for readmissions within 3 months with versions that can be developed.\u003c/p\u003e \u003cp\u003eHarrison et al., identified antihypertensives, antibiotics, analgesics, antiplatelets and antidiabetics (5%-16%) as the primary drugs associated with DRPs \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Our study similarly found that the most common recommendations were related to antibacterials (15.45%), antithrombotics (15.45%), cardiac (12.73%) and diabetes medications (10.61%). Acheampong et al. reported anticoagulants as the leading cause of DRPs, consistent with our study where the majority of recommendations among antithrombotics were related to anticoagulants \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e. Enoxaparin (47.06%), apixaban (15.69%) and warfarin (15.69%) were the anticoagulants with the highest number of recommendations. Enoxaparin, in particular, was associated with increased DRPs and hence with a high number of recommendations, due to its frequent use as parenteral therapy without the need for follow-up. Our study demonstrated that the clinical pharmacist has an important role to play in the management of both long-established medicines and those recently included in guidelines.\u003c/p\u003e \u003cp\u003eIn one study, Stuhec et al. reported that more than one-third (32.7%) of interventions performed on patients were related to the treatment of cardiovascular disease \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. Similarly, in our study, cardiovascular system medications (25.15%) were the most common medication group for which interventions were performed. This is attributed to the patients hospitalized in the ward having cardiovascular system-related issues that necessitate the use of these drugs. Additionally, effective adjustments related to the current medical condition can be made with physicians who share common information on this subject. In our study, anti-infective drugs were the second most common drug group (16.66%). Similar to Harrison et al., most of these were antibacterial drugs. Antimicrobials are frequently used drugs in hospitalized patients \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Infections such as pneumonia may accompany and exacerbate infections in patients with cardiovascular diseases such as heart failure. These reasons may explain the frequent occurrence of problems related to anti-infective treatments in our study. Our study demonstrated that anti-infective drug management in patients with cardiovascular disease is one of the important services that clinical pharmacists can provide. The third most common drug group for interventions was related to the digestive system and metabolism (15.16%). This is supported by the fact that DRPs was also found to be associated with the patients' diabetes in our study. In addition, the presence of interventions for antidiabetic drugs in the intervention group (10.61%) showed one of the service areas in which the clinical pharmacist can take part.\u003c/p\u003e \u003cp\u003eThe frequent observation of problems and interventions related to antithrombotic drugs draws attention to the necessity and importance of providing a clinical pharmacy service for patients using these drugs. In addition, the fact that recommendations were made for different drug groups showed that the clinical pharmacist increased the quality of health care with a multidisciplinary approach. Based on the study data, clinical pharmacists may be offered opportunities to specialize in areas such as cardiovascular system diseases, internal diseases and infectious diseases. Adjustments and diversifications can be made in the current training system that takes into account conditions such as antithrombotic management and electrolyte disturbances in relation to common problems specific to various clinics, thus increasing awareness of these issues.\u003c/p\u003e \u003cp\u003eIn the literature, acceptance rates of pharmacist interventions by physicians have been found to vary between 70\u0026ndash;97% \u003csup\u003e38,43,44\u003c/sup\u003e. In our study, the acceptance rate of the interventions made by the clinical pharmacist was 94.76%. The high acceptance of clinical pharmacist recommendations in our study can be attributed to the pharmacist's active involvement in the patient-related process during prescribing, the recommendations being made in accordance with evidence-based literature, and face-to-face. The fact that the doctors in the team were already familiar with the clinical pharmacy system also contributed to the increased awareness of clinical pharmacy services. The value of our study is enhanced by the clinical pharmacist's active role in a multidisciplinary team, attending visits and closely monitoring the patient's condition to detect and prevent problems. Both the literature and our study demonstrate that the clinical pharmacist has a central role in the optimization of pharmacotherapeutic outcomes.\u003c/p\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eLimitations of the study:\u003c/h2\u003e \u003cp\u003eThe limitations of our study include the fact that randomization was performed at a single center was included and therefore the results could not be generalized. Other limitations include not knowing the drug regimens and patient factors during the three-month follow-up after discharge. When these factors are evaluated in terms of hospital admission and hospitalization, they are independent factors other than the clinical pharmacist. The fact that the change of physicians in the team is very low, the clinical pharmacist cannot be completely isolated from both groups and team collaborations come into play are among the limitations of our study, which may pose a risk of contamination.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIt has been shown that clinical pharmacists can play an important role in the detection and prevention of DRPs by ensuring that appropriate, evidence-based pharmacotherapy regimens are prescribed during hospitalization and by detecting medication errors. Considering the data we evaluated with our high recommendation acceptance rates for DRPs and the studies in the literature, it was revealed that the introduction of clinical pharmacy services with a clinical pharmacist in a multidisciplinary healthcare team, the development and dissemination of these services and every step to be taken for these results will have positive effects on patient outcomes and improve the quality of healthcare.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eConceptualization, DS, MYB; methodology, DS, MYB, FVI; software, DS, MYB; validation, DS, MYB; formal analysis, DS, MYB; investigation, DS, MYB; resources, DS, MYB, NA, and FVI; data curation, DS; writing\u0026mdash;original draft preparation, DS, MYB; writing\u0026mdash;review and editing, DS, MYB, NA, and FVI; visualization, DS, MYB; supervision, MYB and FVI; project administration, DS, MYB; All authors have read and agreed to the published version of the manuscript. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors of this study are grateful to Bezmialem Vakif University for providing opportunities and support. This study was not funded by any organizations. The present study was conducted within the scope of a Clinical Pharmacy specialty thesis at the Bezmialem Vakif University, Faculty of Clinical Pharmacy.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data will be madeavailable upon request from the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eD\u0026uuml;lek H, Tuzcular Vural Z, G\u0026ouml;nen\u0026ccedil; I. Risk Factors in Cardiovascular Diseases. \u003cem\u003eThe Journal of Turkish Family Physician\u003c/em\u003e. 2018;9(2):53-58. doi:10.15511/tjtfp.18.00253\u003c/li\u003e\n \u003cli\u003eAbaci A. Kardiyovask\u0026uuml;ler risk fakt\u0026ouml;rlerinin \u0026uuml;lkemizdeki durumu. \u003cem\u003eTurk Kardiyoloji Dernegi Arsivi\u003c/em\u003e. 2011;39(SUPP-4):1-5. doi:10.5543/tkda.2011.abaci\u003c/li\u003e\n \u003cli\u003e\u0026Ouml;ngen Z. Anticoagulation therapy and the use of non-vitamin K antagonist oral anticoagulants in the elderly. \u003cem\u003eTurk Kardiyoloji Dernegi Arsivi\u003c/em\u003e. 2017;45:86-88. doi:10.5543/tkda.2017.47034\u003c/li\u003e\n \u003cli\u003eFauler J. Clinical pharmacology of antithrombotic drugs in coronary artery disease. \u003cem\u003eTher Adv Cardiovasc Dis\u003c/em\u003e. 2009;3(6):465-478. doi:10.1177/1753944709346517\u003c/li\u003e\n \u003cli\u003eLim X, Yeo Q, Kng G, Chung W, Yap K. Validation of a Drug-Related Problem Classification System for the Intermediate and Long-Term Care Setting in Singapore. \u003cem\u003ePharmacy\u003c/em\u003e. 2018;6(4):109. doi:10.3390/pharmacy6040109\u003c/li\u003e\n \u003cli\u003eVan Den Bemt PMLA, Egberts TCG, De Jong-Van Den Berg LTW, Brouwers JRBJ. Drug-related problems in hospitalised patients. \u003cem\u003eDrug Saf\u003c/em\u003e. 2000;22(4):321-333. doi:10.2165/00002018-200022040-00005\u003c/li\u003e\n \u003cli\u003eRasool MF, Rehman A ur, Imran I, et al. Risk Factors Associated With Medication Errors Among Patients Suffering From Chronic Disorders. \u003cem\u003eFront Public Health\u003c/em\u003e. 2020;8(November):1-7. doi:10.3389/fpubh.2020.531038\u003c/li\u003e\n \u003cli\u003eParadissis C, Cottrell N, Coombes I, Scott I, Wang W, Barras M. Patient harm from cardiovascular medications. \u003cem\u003eTher Adv Drug Saf\u003c/em\u003e. 2021;12. doi:10.1177/20420986211027451\u003c/li\u003e\n \u003cli\u003eAllen LaPointe NM, Jollis JG. Medication errors in hospitalized cardiovascular patients. \u003cem\u003eArch Intern Med\u003c/em\u003e. 2003;163(12):1461-1466. doi:10.1001/archinte.163.12.1461\u003c/li\u003e\n \u003cli\u003eLin G, Huang R, Zhang J, Li G, Chen L, Xi X. Clinical and economic outcomes of hospital pharmaceutical care: A systematic review and meta-analysis. \u003cem\u003eBMC Health Serv Res\u003c/em\u003e. 2020;20(1):1-14. doi:10.1186/s12913-020-05346-8\u003c/li\u003e\n \u003cli\u003eDunn SP, Birtcher KK, Beavers CJ, et al. The Role of the Clinical Pharmacist in the Care of Patients with Cardiovascular Disease. \u003cem\u003eJ Am Coll Cardiol\u003c/em\u003e. 2015;66(19):2129-2139. doi:10.1016/j.jacc.2015.09.025\u003c/li\u003e\n \u003cli\u003eDefinition T part. The definition of clinical pharmacy. \u003cem\u003ePharmacotherapy\u003c/em\u003e. 2008;28(6):816-817. doi:10.1592/phco.28.6.816\u003c/li\u003e\n \u003cli\u003evan Walraven C, Wong J, Forster AJ. LACE+ index: extension of a validated index to predict early death or urgent readmission after hospital discharge using administrative data. \u003cem\u003eOpen Med\u003c/em\u003e. 2012;6(3):90-100.\u003c/li\u003e\n \u003cli\u003eBektay MY, Sancar M, Okyaltirik F, Durdu B, Izzettin FV. Investigation of drug-related problems in patients hospitalized in chest disease wards: A randomized controlled trial. \u003cem\u003eFront Pharmacol\u003c/em\u003e. 2023;13:5078. doi:10.3389/FPHAR.2022.1049289\u003c/li\u003e\n \u003cli\u003eGreeshma M, Lincy S, Maheswari E, Tharanath S, Viswam S. Identification of drug related problems by clinical pharmacist in prescriptions with polypharmacy: A prospective interventional study. \u003cem\u003eJournal of Young Pharmacists\u003c/em\u003e. 2018;10(4):460-465. doi:10.5530/jyp.2018.10.100\u003c/li\u003e\n \u003cli\u003ePatel V, Chatterji S, Chisholm D, et al. Chronic diseases and injuries in India. \u003cem\u003eThe Lancet\u003c/em\u003e. 2011;377(9763):413-428. doi:10.1016/S0140-6736(10)61188-9\u003c/li\u003e\n \u003cli\u003eWeddle SC, Shaun Rowe A, Jeter JW, Renwick RC, Chamberlin SM, Franks AS. Assessment of clinical pharmacy interventions to reduce outpatient use of high-risk medications in the elderly. \u003cem\u003eJ Manag Care Spec Pharm\u003c/em\u003e. 2017;23(5):520-524. doi:10.18553/jmcp.2017.23.5.520\u003c/li\u003e\n \u003cli\u003eBektay MY, Sancar M, Okyaltirik F, Durdu B, Izzettin FV. Investigation of drug-related problems in patients hospitalized in chest disease wards: A randomized controlled trial. \u003cem\u003eFront Pharmacol\u003c/em\u003e. 2023;13(January):1-13. doi:10.3389/fphar.2022.1049289\u003c/li\u003e\n \u003cli\u003eErtuna E, Arun MZ, Ay S, Ko\u0026ccedil;ak F\u0026Ouml;K, G\u0026ouml;kdemir B, İspirli G. Evaluation of pharmacist interventions and commonly used medications in the geriatric ward of a teaching hospital in turkey: A retrospective study. \u003cem\u003eClin Interv Aging\u003c/em\u003e. 2019;14:587-600. doi:10.2147/CIA.S201039\u003c/li\u003e\n \u003cli\u003eNukala A, Vanga H, Keerthi T, Kandukuri K. A Comprehensive Analysis of Impact of Past Medications on Current Admission in a Tertiary Care Hospital : A Prospective Observational Study. \u003cem\u003eJ Basic Clin Pharm\u003c/em\u003e. 2021;12(6):76-81.\u003c/li\u003e\n \u003cli\u003eG\u0026ouml;zlemsel İ, \u0026Ccedil;alışma B, Bektay MY, Sancar M, Okyaltirik FK, Durdu B. Identification of Drug-Related Problems and Investigation of Related Factors in Patients with COVID-19 : An Observational Study COVID-19 \u0026rsquo; lu Hastalarda İla\u0026ccedil;la İlişkili Sorunların Belirlenmesi ve İlişkili Fakt\u0026ouml;rlerin. 2022;10(6):777-785. doi:10.14235/bas.galenos.2022.63935\u003c/li\u003e\n \u003cli\u003eNiriayo YL, Kumela K, Kassa TD, Angamo MT. Drug therapy problems and contributing factors in the management of heart failure patients in Jimma University Specialized Hospital, Southwest Ethiopia. \u003cem\u003ePLoS One\u003c/em\u003e. 2018;13(10):1-14. doi:10.1371/journal.pone.0206120\u003c/li\u003e\n \u003cli\u003ePl\u0026aacute;cido AI, Herdeiro MT, Morgado M, Figueiras A, Roque F. Drug-related Problems in Home-dwelling Older Adults: A Systematic Review. \u003cem\u003eClin Ther\u003c/em\u003e. 2020;42(4):559-572.e14. doi:10.1016/j.clinthera.2020.02.005\u003c/li\u003e\n \u003cli\u003eWang X, Wang S, Yu X, et al. Impact of pharmacist-led medication therapy management in ambulatory elderly patients with chronic diseases. \u003cem\u003eBr J Clin Pharmacol\u003c/em\u003e. 2021;87(7):2937-2944. doi:10.1111/bcp.14709\u003c/li\u003e\n \u003cli\u003eAlbayrak A, Başgut B, Bıkmaz GA, Karahalil B. Clinical pharmacist assessment of drug-related problems among intensive care unit patients in a Turkish university hospital. \u003cem\u003eBMC Health Serv Res\u003c/em\u003e. 2022;22(1):1-7. doi:10.1186/s12913-022-07494-5\u003c/li\u003e\n \u003cli\u003eCastelino RL, Bajorek B V., Chen TF. Are interventions recommended by pharmacists during Home Medicines Review evidence-based? \u003cem\u003eJ Eval Clin Pract\u003c/em\u003e. 2011;17(1):104-110. doi:10.1111/j.1365-2753.2010.01375.x\u003c/li\u003e\n \u003cli\u003eChau SH, Jansen APD, van de Ven PM, Hoogland P, Elders PJM, Hugtenburg JG. Clinical medication reviews in elderly patients with polypharmacy: a cross-sectional study on drug-related problems in the Netherlands. \u003cem\u003eInt J Clin Pharm\u003c/em\u003e. 2016;38(1):46-53. doi:10.1007/s11096-015-0199-8\u003c/li\u003e\n \u003cli\u003eKari H, Kortej\u0026auml;rvi H, Airaksinen M, Laaksonen R. Patient involvement is essential in identifying drug-related problems. \u003cem\u003eBr J Clin Pharmacol\u003c/em\u003e. 2018;84(9):2048-2058. doi:10.1111/bcp.13640\u003c/li\u003e\n \u003cli\u003eLeikola SNS, Virolainen J, Tuomainen L, Tuominen RK, Airaksinen MSA. Comprehensive medication reviews for elderly patients: Findings and recommendations to physicians. \u003cem\u003eJournal of the American Pharmacists Association\u003c/em\u003e. 2012;52(5):630-633. doi:10.1331/JAPhA.2012.10163\u003c/li\u003e\n \u003cli\u003eSellors J, Kaczorowski J, Sellors C, et al. A randomized controlled trial of a pharmacist consultation program for family physicians and their elderly patients. \u003cem\u003eCMAJ Canadian Medical Association Journal\u003c/em\u003e. 2003;169(1):17-22.\u003c/li\u003e\n \u003cli\u003eTouchette DR, Masica AL, Dolor RJ, et al. Safety-focused medication therapy management: A randomized controlled trial. \u003cem\u003eJournal of the American Pharmacists Association\u003c/em\u003e. 2012;52(5):603-612. doi:10.1331/JAPhA.2012.12036\u003c/li\u003e\n \u003cli\u003eVinks THAM, De Koning FHP, De Lange TM, Egberts TCG. Identification of potential drug-related problems in the elderly: The role of the community pharmacist. \u003cem\u003ePharmacy World and Science\u003c/em\u003e. 2006;28(1):33-38. doi:10.1007/s11096-005-4213-4\u003c/li\u003e\n \u003cli\u003eKwint HF, Faber A, Gussekloo J, Bouvy ML. Effects of medication review on drug-related problems in patients using automated drug-dispensing systems: A pragmatic randomized controlled study. \u003cem\u003eDrugs Aging\u003c/em\u003e. 2011;28(4):305-314. doi:10.2165/11586850-000000000-00000\u003c/li\u003e\n \u003cli\u003eKwint HF, Faber A, Gussekloo J, Bouvy ML. The contribution of patient interviews to the identification of drug-related problems in home medication review. \u003cem\u003eJ Clin Pharm Ther\u003c/em\u003e. 2012;37(6):674-680. doi:10.1111/j.1365-2710.2012.01370.x\u003c/li\u003e\n \u003cli\u003eChan DC, Chen JH, Wen CJ, Chiu LS, Wu SC. Effectiveness of the medication safety review clinics for older adults prescribed multiple medications. \u003cem\u003eJournal of the Formosan Medical Association\u003c/em\u003e. 2014;113(2):106-113. doi:10.1016/j.jfma.2012.04.013\u003c/li\u003e\n \u003cli\u003eRhalimi M, Rauss A, Housieaux E. Drug-related problems identified during geriatric medication review in the community pharmacy. \u003cem\u003eInt J Clin Pharm\u003c/em\u003e. 2018;40(1):109-118. doi:10.1007/s11096-017-0571-y\u003c/li\u003e\n \u003cli\u003eKovačević SV, Miljković B, Ćulafić M, et al. Evaluation of drug-related problems in older polypharmacy primary care patients. \u003cem\u003eJ Eval Clin Pract\u003c/em\u003e. 2017;23(4):860-865. doi:10.1111/jep.12737\u003c/li\u003e\n \u003cli\u003eO\u0026rsquo;Dell KM, Kucukarslan SN. Impact of the clinical pharmacist on readmission in patients with acute coronary syndrome. \u003cem\u003eAnnals of Pharmacotherapy\u003c/em\u003e. 2005;39(9):1423-1427. doi:10.1345/aph.1E640\u003c/li\u003e\n \u003cli\u003eSwieczkowski D, Merks P, Gruchala M, Jaguszewski MJ. The role of the pharmacist in the care of patients with cardiovascular diseases. \u003cem\u003eKardiol Pol\u003c/em\u003e. 2016;74(11):1319-1326. doi:10.5603/KP.a2016.0136\u003c/li\u003e\n \u003cli\u003eAmankwa Harrison M, Marfo AFA, Buabeng KO, Nkansah FA, Boateng DP, Ankrah DNA. Drug-related problems among hospitalized hypertensive and heart failure patients and physician acceptance of pharmacists\u0026rsquo; interventions at a teaching hospital in Ghana. \u003cem\u003eHealth Sci Rep\u003c/em\u003e. 2022;5(5):1-10. doi:10.1002/hsr2.786\u003c/li\u003e\n \u003cli\u003eAcheampong F, Nkansah FA, Anto BP. Drug-related problems and their clinical interventions in a Ghanaian teaching hospital. \u003cem\u003eSafety in Health\u003c/em\u003e. 2016;2(1):1-7. doi:10.1186/s40886-016-0050-5\u003c/li\u003e\n \u003cli\u003eStuhec M, Flegar I, Zelko E, Kovačič A, Zabavnik V. Clinical pharmacist interventions in cardiovascular disease pharmacotherapy in elderly patients on excessive polypharmacy: A retrospective pre-post observational multicentric study. \u003cem\u003eWien Klin Wochenschr\u003c/em\u003e. 2021;133(15-16):770-779. doi:10.1007/s00508-020-01801-y\u003c/li\u003e\n \u003cli\u003eShareef J, Sandeep B, Shastry CS. Assessment of Drug Related Problems in Patients with Cardiovascular Diseases in a Tertiary Care Teaching Hospital. \u003cem\u003eJournal of Pharmaceutical Care\u003c/em\u003e. 2014;2(2):70-76.\u003c/li\u003e\n \u003cli\u003eLaranjeira T, Mirco A, Falc\u0026atilde;o F. 4CPS-027 Hospital pharmacist interventions in an accredited cardiology department. \u003cem\u003eEuropean Journal of Hospital Pharmacy\u003c/em\u003e. 2018;25(Suppl 1):A53 LP-A54. doi:10.1136/ejhpharm-2018-eahpconf.118\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Clinical pharmacist, drug-related problem, cardiology, antithrombotic, PCNE.","lastPublishedDoi":"10.21203/rs.3.rs-4448386/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4448386/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAntithrombotic drugs are frequently used in the Cardiology ward and patients receiving these drugs are thought to be vulnerable to drug-related problems (DRPs). The aim of this study was to evaluate clinical pharmacy services for the detection and prevention of DRPs in these patients.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis prospective randomized controlled study included 400 patients receiving antithrombotic therapy in the Cardiology ward. The European Pharmaceutical Care Network Classification (PCNE v9.1) was used to assess DRPs. Patients were analyzed for readmission within 1 and 3 months after discharge.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe mean age of patients in the control and intervention groups was 67.2\u0026thinsp;\u0026plusmn;\u0026thinsp;12.2 and 67.8\u0026thinsp;\u0026plusmn;\u0026thinsp;12.3 years, respectively. Coronary artery disease (74.5%; 74.5%) and hypertension (70.5%; 70%) were the most common diseases. The number of DRPs detected was 561 in the control group and 497 in the intervention group. In both groups, the most frequently identified problem was related to treatment safety (73.62%; 74.25%). This was followed by treatment effectiveness (24.06%; 23.14%). The main causes of DRPs were drug selection (81.11%; 80.88%) and dose selection (19.08%; 16.10%). During the study, 248 (93.23%) recommendations were made for 266 clinically significant DRPs. Of these recommendations, 235 (94.76%) were accepted by physicians. The most common interventions at the drug level were changing the dose (29.65%) and starting a new drug (28.49%). There was no significant difference between the groups in terms of readmission within 1 and 3 months (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), but a numerical decrease was observed in the intervention group.\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion:\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn our study, the number of clinically significant DRPs was statistically lower in the intervention group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The high acceptance rates of the recommendations regarding the problems in the intervention group showed that the clinical pharmacist had a positive contribution to the reduction of DRPs. These results suggest that the inclusion of clinical pharmacists in the healthcare team and the expansion of their services will provide a better-quality healthcare service.\u003c/p\u003e","manuscriptTitle":"Evaluation of Clinical Pharmacy Services in Patients Receiving Antithrombotic Treatment: A Randomized Controlled Trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-31 20:28:07","doi":"10.21203/rs.3.rs-4448386/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ecf0292a-a0d2-4a27-af03-2115a5fac6f0","owner":[],"postedDate":"May 31st, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-05-31T20:28:09+00:00","versionOfRecord":[],"versionCreatedAt":"2024-05-31 20:28:07","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4448386","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4448386","identity":"rs-4448386","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}