Medication Discrepancies and Medication-Related Problems in Psychiatric Patients: A Medication Reconciliation Study

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Medication reconciliation (MR) programs are implemented in many countries, including Iran, to identify, resolve, and prevent MDs and other medication-related problems (MRPs). In the psychiatric setting, the importance of identifying and addressing MRPs is even greater due to the high prevalence of polypharmacy, limited patient cooperation, and other factors. This study aimed to investigate the prevalence of MDs and MRPs in psychiatric patients. Methods: This study included 302 psychiatric patients receiving at least two systemic medications daily. Their medications were reviewed at discharge using the Pharmaceutical Society of Australia (PSA) guidelines to identify MRPs. The collected data were analyzed statistically. Results: In this study, patients were taking a total of 1421 medications (4.71 medications per patient). A total of 493 MDs and 392 MRPs were identified. The most common MRPs were, in decreasing order, medication underuse or non-adherence by the patient (175 cases, 44.64% of all MRPs) and drug interactions (168 cases, 42.85%). The number of drug interactions significantly increased with the increasing number of underlying diseases and the number of medications used (P < 0.001 in both cases). A total of 594 interventions were made by the pharmacist, of which the most common were referrals to the physician for medication adjustments (193 cases, 32.27% of all interventions) and increasing the medication dose or prescribing a missed medication (172 cases, 28.95%). Conclusion: This study showed that the prevalence of MRPs in psychiatric settings is considerable and that implementing an MR program and pharmacist intervention in MRPs can significantly improve the quality of care. Medication reconciliation Medication discrepancy Psychotropic medication Psychiatric disorder Figures Figure 1 Introduction Medication-related problems (MRPs) are common errors in hospital wards, occurring approximately 6.5 per 100 admissions, leading to adverse drug events (ADEs) and suboptimal treatment. Medication discrepancies (MDs) are a type of MRP that can occur during transitions in care, such as discharge from the hospital [ 1 ]. Medication reconciliation (MR) is a process aimed at identifying, resolving, and preventing MDs and other MRPs [ 2 , 3 , 4 ]. It has been implemented in many countries since 2005 to improve medication safety [ 4 ]. Psychiatric inpatients are at an increased risk of MRPs due to several factors, including polypharmacy, limited patient cooperation, and the complexity of psychotropic medications [ 5 , 6 , 7 ]. One study reveals that MR reduces the readmission of psychiatric patients to the hospital [ 8 ]. To date, no studies in Iran have investigated MRPs and MR in psychiatric patients. This study aimed to assess the prevalence of MRPs in psychotropic medications among patients discharged from the emergency department of Roozbeh Hospital, a leading psychiatric hospital in Iran. The findings of this study can be used by clinicians, policymakers, and researchers to improve medication safety in psychiatric settings. Methods Study Design and Setting This observational, cross-sectional study was conducted at the emergency department of Roozbeh Hospital, a leading psychiatric institution in Tehran, Iran, from October 2022 to August 2023. We aimed to assess the prevalence and characteristics of MSPs among hospitalized patients with psychiatric diagnoses. Participants and Sampling The target population included all adults admitted to the psychiatric wards during the study period. We employed a census approach, enrolling all eligible patients (n = 302) who met the following inclusion criteria: Confirmed psychiatric diagnosis by a qualified psychiatrist. Daily intake of at least two systemic medications. Patients were excluded if they presented with: No medication uses or consumption of less than two systemic medications daily. Impaired consciousness that could hinder accurate data collection. Inability to swallow medication safely. Unwillingness to participate in the study. Incomplete medical records that limited comprehensive data extraction. Data Collection We collected data through a multi-pronged approach to ensure reliability and completeness: Questionnaires: Two self-designed questionnaires were administered. The first focused on demographic information, medical history, and current medication details. The second, a MR form, served to identify potential discrepancies between the prescribed and actual medication regimens. Clinical Interviews: Trained interviewers conducted face-to-face interviews with participating patients and, when feasible, their caregivers, to gather additional clinical details and clarify any uncertainties in the questionnaire responses. Medical Record Review: Medical records of all participants were meticulously reviewed by trained personnel to extract relevant clinical data, medication history, and diagnoses. Ethical Considerations This study was approved by the Ethics Committee of Tehran University of Medical Sciences (IR.TUMS.MEDICINE.REC.1401.393). Informed consent was obtained from all participants after they received a thorough explanation of the study objectives, procedures, and potential risks and benefits. All collected data were anonymized before analysis to protect patient confidentiality. Data Analysis The statistical analysis was conducted at a significant level of less than 0.05 with a 95% Confidence Interval (CI). The analysis was performed using SPSS software version 27. The continuous variables’ normality was assessed using the Shapiro-Wilk test and Q-Q plot. For the description of continuous variables, mean and Standard Deviation (SD) and categorical variables were used from frequency and percentage (%). Results A total of 302 patients (139 women, and 163 men) were enrolled in the study. The mean age of the participants was 39.01 ± 13.07 years. The educational level of the participants is demonstrated in the table below. The majority of them had a high school diploma or higher (61.5%). Smoking with a prevalence of 46.6% is the most prevalent type of addictive behavior observed in the studied community (Table 1 ). There was no statistically significant difference regarding the Age and gender among the participants (p-value < 0.05). Table 1 General Information of participants Demographic Data Variable Age (Mean ± SD) 39.01 ± 13.07 Gender/F N (%) 139 (46%) Gender/M N (%) 163 (54%) Education Level N (%) No education 9 (2.9%) Primary 40 (13.2%) before high school 67 (22.2%) Diploma 118 (39%) Associate Degree 17 (5.6%) Bachelor Degree 31 (10.2%) Master degree 14 (4.6%) PHD Degree 6 (2%) Habitual History N (%) Smoking 144 (46.6%) Alcoholism 56 (18.1%) Substance Use 109 (35.3%) (F = Female, M = Male, SD = Standard Deviation) In this study, patients were using 1421 medications, out of which 1058 medications (74.45%) were psychotropic drugs. The mean number of medications prescribed per patient was 4.71, of which 3.51 were psychotropic medications. A total of 493 MDs and 392 MRPs were identified in this study. These MDs were classified into 3 categories: drug continuation, drug change, and drug discontinuation. Out of a total of 493 observed MDs, 419 were classified as unintentional, while 74 were intentional. The most prevalent type of unintentional discrepancy involved medication continuation, representing 211 out of the 419 reported unintentional discrepancies. Furthermore, in cases of intentional discrepancies, the type of medication discontinuation accounted for the highest number with 48 out of 74 cases (Table 2 ). Table 2 Types of medication discrepancies Discrepancies Continue Change Discontinue Total Percentage Intentional 11 15 48 74 15% Unintentional 211 28 180 419 85% In general, based on MRP, a total of 392 problems related to the use of pharmaceutical drugs were identified for the participants (an average of 0.27 interactions per prescription drug). The most observed MRP was the decrease in the amount of medication taken by the patient or not taking it (175 cases, equivalent to 44.64% of the cases) and then drug interactions (168 cases, equivalent to 42.85% of the cases) (Table 3 ). Table 3 Types of MRPs in the studied population MRP Classification Abbreviation No. Percent Duplication D1 8 2.04% Drug interaction D2 168 42.85% Wrong drug D3 0 0.0% Incorrect strength D4 1 0.2% Inappropriate dosage form D5 0 0.0% Contraindication apparent D6 1 0.2% No indication apparent D7 1 0.2% Other drug selection problem D0 0 0.0% Prescribed dose too high O1 0 0.0% Prescribed dose too low O2 1 0.2% Incorrect or unclear dosing instructions O3 1 0.2% Other dose problem O0 0 0.0% Under-use by patient C1 175 44.64% Over-use by patient C2 5 1.2% Erratic use of medication C3 0 0.0% Intentional drug misuse, including non-prescription medicines C4 0 0.0% Difficulty using dosage form C5 0 0.0% Other compliance problem C0 0 0.0% Condition undertreated U1 0 0.0% Condition untreated U2 0 0.0% Preventive therapy required U3 0 0.0% Other undertreated indication problem U0 0 0.0% Laboratory monitoring M1 30 7.65% Non-laboratory monitoring M2 1 0.02% Other monitoring problem M0 0 0.0% Patient requests drug information E1 0 0.0% Patient requests disease management advice E2 0 0.0% Other education or information problem - - - Clinical interventions that cannot be classified under another category N0 0 0.0% Toxicity, allergic reaction or adverse effect present T1 0 0.0% Total 392 100.0% The number of medications prescribed and the number of comorbid diseases were the most significant predictors of MRPs. A significant positive correlation was observed between the number of medications prescribed and the number of MRPs (r = 0.27, P < 0.001). Similarly, a significant positive correlation was observed between the number of comorbid diseases and the number of MRPs (r = 0.23, P < 0.001) (Tables 4 ). Table 4 Pearson correlation analysis of the number of prescribed medications & comorbid diseases and the number of MRPs Total consumed medications Psychiatric Medications Number of Concomitant diseases Medication Errors Pearson Correlation 0.383 0.285 0.235 Sig. (2-tailed) 0.000 0.000 0.000 N 302 301 300 The most common interventions performed for MRPs were referral to the prescriber for medication modification (32.3%), increase in medication dose or addition of a missed medication (28.9%), and patient education (27.8%) (Table 5 ). Table 5 Interventions performed for MRPs Recommendation Abbreviation No. Percent Dose increase R1 172 28.95% Dose decrease R2 21 3.53% Drug change R3 1 0.16% Drug formulation change R4 0 0.0% Drug brand change R5 0 0.0% Dose frequency/schedule change R6 1 0.16% Prescription not dispensed R7 0 0.0% Other changes to therapy R8 8 1.34% Refer to prescriber R9 193 32.27% Refer to hospital R10 0 0.0% Refer for medication review R11 0 0.0% Other referral required R12 0 0.0% Education or counselling session R13 1 0.16% Written summary of medicines R14 0 0.0% Recommend dose administration aid R15 0 0.0% Other written information R16 0 0.0% Monitoring: Laboratory R17 110 18.51% Monitoring: Non-laboratory R18 87 14.64% No recommendation necessary R19 0 0.0% Total 594 100.0% Receiver operating characteristic (ROC) analysis was performed to determine the optimal number of medications for identifying patients at risk of MRPs. The area under the curve (AUC) was 0.701 (95% CI: 0.653–0.749), and the optimal cutoff value was 0.701. This suggests that all patients taking more than one medication should be screened for MD and MRPs (Fig. 1 ). Discussion MR is a process of identifying and resolving MD in the hospital. It is also an important process in the field of psychiatry and can help to prevent medication errors and improve patient outcomes. However, various features in psychiatric hospitals, such as the difficulty of conducting clinical interviews with patients, polypharmacy, psychiatric medicine with different characteristics, the duration of hospitalization and its frequency, and the high number of transfers of care, make the MR challenging in this setting [ 9 ]. Studies have shown that the occurrence of errors related to neuropsychiatric medicines has a high prevalence in the mental health setting [10, 11]. For example, Brownlie Kay et al. investigated the prevalence of medication errors among prescriptions for psychiatric patients in England. In this study, of 377 hospitalized, 212 cases (56.2%) of medication errors were observed [11]. There are few studies that investigate the prevalence of MD and MRPs in psychiatric patients and no study in Iran has investigated this issue. The present study was conducted to investigate the prevalence of MD and MRPs in patients admitted to the psychiatric emergency department. The main finding of the study is that MD and MRPs with a prevalence of 27.8% and 35% respectively are considerable in hospitalized patients with psychiatric disorders. The most common types of MRPs were under-use by patients (44.64%) and drug interactions (42.85%). Our results are consistent with the findings of other studies that have evaluated the prevalence of MD and MRPs in patients discharged from the hospital [ 12 – 14 ]. According to earlier studies, the most common MD was medication omission [ 15 – 19 ], accounting for more than half of all MDs identified in one study [ 19 ]. This may be because most patients and their caregivers do not know about home medicine such as over-the-counter (OTC), herbal use, or another habit at home, or they consider them unimportant. Therefore, after being admitted to the hospital, they may stop their home medicine or take the wrong dose without awareness the attending physician. The number of medication errors increases with patient age, high number of prescription drugs, co-morbidities, multiple prescriptions for the same patient, and an overburdened healthcare system [ 20 – 22 ]. We have identified that the number of medications prescribed and the number of comorbid diseases were the most significant predictors of MRPs. These findings align with previous researches [ 19 , 20 ]. Our study also found that the pharmacist-led MR intervention was effective in identifying and resolving MRPs. The intervention resulted in the identification of 493 MD and 392 MRPs. Of these, 592 interventions were made by the pharmacist to resolve the discrepancies and problems. Several studies also verified the results, including the study by Kim Sook-Yoon et al., showing that patient education in relation to the medicine, its side effects, and the method of consumption and monitoring can significantly reduce errors in pharmacotherapy [23]. The results of a study by the American Society of Health-System Pharmacists found that pharmacist-led MR interventions can reduce the rate of medication errors by up to 50% [ 24 ]. Another study also showed that pharmacy-performed MR followed previous nursing-performed MR identifying an average of 2.9 differences per patient [25]. Therefore, it was concluded that medication reconciliation by pharmacists can be very effective in solving unintentional medication discrepancies, and improving the efficacy and safety of medications. This is the first study from Iran that investigates and reveals the high prevalence of major MD and MSPs in psychiatric patients discharged from hospital. Our findings suggest that MR is an important patient safety intervention that can help prevent medication errors and improve patient outcomes in this population. Further research is needed to evaluate the long-term impact of MR on the rate of hospital readmissions, the cost of care, and patient satisfaction and outcomes. Limitations This study has several limitations. First, it was conducted in a single psychiatric emergency department, and the findings may not be generalizable to other settings. Second, the study was observational, and the findings cannot be used to make causal inferences. Third, the study did not assess the long-term impact of MR on patient outcomes. Declarations Funding/Support This research did not receive any specific financial support from funding organizations in any department. Author Contribution MS and MP contributed to data curation, investigation, writing & editing the original manuscript . NM is responsible for the supervision and study design and writing the original manuscript , writing & editing the original manuscript .All authors reviewed the manuscript References RATRVASY. Medication Dispensing Errors and Prevention. 2023. Barnsteiner JH. Medication reconciliation. Patient safety and quality: an evidence-based handbook for nurses. 2008. Pronovost P, Weast B, Schwarz M, Wyskiel RM, Prow D, Milanovich SN, et al. Medication reconciliation: a practical tool to reduce the risk of medication errors. Journal of critical care. 2003;18(4):201-5. Using medication reconciliation to prevent errors. Sentinel event alert. 2006(35):1-4. Wolf C, Pauly A, Mayr A, Grömer T, Lenz B, Kornhuber J, et al. Pharmacist-Led Medication Reviews to Identify and Collaboratively Resolve Drug-Related Problems in Psychiatry - A Controlled, Clinical Trial. PloS one. 2015;10(11):e0142011. Soerensen AL, Lisby M, Nielsen LP, Poulsen BK, Mainz J. The medication process in a psychiatric hospital: are errors a potential threat to patient safety? Risk management and healthcare policy. 2013;6:23-31. Oliveira J, Silva TCE, Cabral AC, Lavrador M, Almeida FF, Macedo A, et al. Pharmacist-led medication reconciliation on admission to an acute psychiatric hospital unit. Pharmacy practice. 2022;20(2):2650. Vigod SN, Kurdyak PA, Dennis CL, Leszcz T, Taylor VH, Blumberger DM, et al . Transitional interventions to reduce early psychiatric readmissions in adults: systematic review. Br J Psychiatry 2013; 202: 187–94. Soerensen AL, Lisby M, Nielsen LP, Poulsen BK, Mainz J. The medication process in a psychiatric hospital: are errors a potential threat to patient safety? Risk management and healthcare policy.2013;6:23-3 Richard NK, Steven DW, Joe JV, Petra B, Joan M, Lorraine P, et al. Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicenter study. BMJ Open. 2014;4(9):e006084. Brownlie K, Schneider C, Culliford R, Fox C, Boukouvalas A, Willan C, et al. Medication reconciliation by a pharmacy technician in a mental health assessment unit. International journal of clinical pharmacy. 2014;36(2):303-9 Urban R, Armitage G, Morgan J, Marshall K, Blenkinsopp A, Scally A. Custom and practice: a multi-center study of medicines reconciliation following admission in four acute hospitals in the UK. Research in social & administrative pharmacy : RSAP. 2014;10(2):355-68. Bell CM, Bajcar J, Bierman AS, Li P, Mamdani MM, Urbach DR. Potentially unintended discontinuation of long-term medication use after elective surgical procedures. Arch Intern Med. 2006;166(22):2525-31. Bell CM, Rahimi-Darabad P, Orner AI. Discontinuity of chronic medications in patients discharged from the intensive care unit. Journal of general internal medicine. 2006;21(9):937-41. Rostami P, Heal C, Harrison A, Parry G, Ashcroft DM, Tully MP. Prevalence, nature and risk factors for medication administration omissions in English NHS hospital inpatients: a retrospective multicentre study using Medication Safety Thermometer data. BMJ Open. 2019;9(6):e028170 Nilsson N, Lea M, Lao Y, et al. Medication discrepancies revealed by medication reconciliation and their potential short-term and long-term effects: a Norwegian multicentre study carried out on internal medicine wards. Eur J Hosp Pharm . 2015;22:298-303. Tam VC, Knowles SR, Cornish PL, et al. Frequency, type and clinical importance of medication history errors at admission to hospital: a systematic review. CMAJ . 2005;173:510-515.D Modig S, Caleres G, Nymberg VM, et al. Assessment of medication discrepancies with point prevalence measurement: how accurate are the medication lists for Swedish patients? Drugs Ther Perspect . 2022;38:185-193. Mikaelsen HZ, Ulla IH, Karimi D, et al. Medication Discrepancies in Hospitalised Medical Patients – Status After a Decade With Targeted Medication Reconciliation Measures, a Cross-sectional Multicenter Study. Health Services Insights. 2024;17. doi:10.1177/11786329241254202D Giannini O, Rizza N, Pironi M, et al. Prevalence, clinical relevance and predictive factors of medication discrepancies revealed by medication reconciliation at hospital admission: prospective study in a Swiss internal medicine ward. BMJ Open . 2019;9:e026259. Damlien L, Davidsen N, Nilsen M, et al. Drug safety at admission to emergency department: an innovative model for PRIOritizing patients for MEdication Reconciliation (PRIOMER). Eur J Emerg Med . 2017;24:333-339. van der Nat DJ, Taks M, Huiskes VJB, van den Bemt BJF, van Onzenoort HAW. Risk factors for clinically relevant deviations in patients’ medication lists reported by patients in personal health records: a prospective cohort study in a hospital setting. Int J Clin Pharm . 2022;44:539-547. Kim YS, Kim HS, Kim HA, Chun J, Kwak MJ, Kim MS, et al. Can patient and family education prevent medical errors? A descriptive study. BMC health services research. 2020;20(1):269 Vigod SN, Kurdyak PA, Dennis CL, Leszcz T, Taylor VH, Blumberger DM, et al . Transitional interventions to reduce early psychiatric readmissions in adults: systematic review. Br J Psychiatry 2013; 202: 187–94. Accomando M, DeWitt K, Porter B. Pharmacist impact on medication reconciliation of behavioral health patients boarding in the emergency department. Ment Health Clin. 2022;12(3):187-92. DOI: 10.9740/mhc.2022.06.187 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-6371089","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":470165920,"identity":"18ba327c-0200-4912-a116-04e76d3fdd80","order_by":0,"name":"Mozhdeh Shahabi","email":"","orcid":"","institution":"School of Pharmacy, Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Mozhdeh","middleName":"","lastName":"Shahabi","suffix":""},{"id":470165921,"identity":"3c1968ea-d0bc-488a-a3ab-8bcfd277cf1f","order_by":1,"name":"Mahsa Panahishokouh","email":"","orcid":"","institution":"Department of Clinical Pharmacy, Isfahan University of Medical Sciences, Isfahan, Iran","correspondingAuthor":false,"prefix":"","firstName":"Mahsa","middleName":"","lastName":"Panahishokouh","suffix":""},{"id":470165922,"identity":"6cdb4474-0309-42f4-8781-798da1432535","order_by":2,"name":"Niayesh Mohebbi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7UlEQVRIiWNgGAWjYHACNgbGhgM8/EASWVSCsBbJBrAWA+K1MBgcAHMM8KmEAHOxw8cefNxxR8b4/OG2Bz8Y/iSu7T/A+OEHg0U+Li2Ws9PSDWeeecZjdiOx3bCHwSBx240EZskeBgnLBhxaDG7nmEnzth0GamFsk+ABa2FgkAb6BacTwVr+ArUY9x9sk/wD0nL+APNvgloYgVoMGBLbpMG2HEhgI2BLWppkL9AvEjeAWmQMjI23ARmWPQb4tCQfk/i54449f//xZ5JvKuRkt50/fPjGj4o6IoIbYgKIAMUpsRpGwSgYBaNgFGAFAKyIVcLUtxmjAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Clinical Pharmacy, Tehran University of Medical Sciences, Tehran, Iran","correspondingAuthor":true,"prefix":"","firstName":"Niayesh","middleName":"","lastName":"Mohebbi","suffix":""}],"badges":[],"createdAt":"2025-04-03 16:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6371089/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6371089/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":84817709,"identity":"9a9183db-6ed4-48ac-8b35-48f65ee6e14b","added_by":"auto","created_at":"2025-06-17 15:50:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":11932,"visible":true,"origin":"","legend":"\u003cp\u003eROC diagram of the incidence of the number of prescribed medications and the number of MRPs\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-6371089/v1/d8ba598a796fda8a25fb895e.png"},{"id":90941764,"identity":"f9280da0-2b35-45e6-b9af-2e12b632b6c2","added_by":"auto","created_at":"2025-09-09 18:31:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":719960,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6371089/v1/67e65095-afff-4d6c-b091-72a63cfa9324.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Medication Discrepancies and Medication-Related Problems in Psychiatric Patients: A Medication Reconciliation Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eMedication-related problems (MRPs) are common errors in hospital wards, occurring approximately 6.5 per 100 admissions, leading to adverse drug events (ADEs) and suboptimal treatment. Medication discrepancies (MDs) are a type of MRP that can occur during transitions in care, such as discharge from the hospital [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Medication reconciliation (MR) is a process aimed at identifying, resolving, and preventing MDs and other MRPs [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. It has been implemented in many countries since 2005 to improve medication safety [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Psychiatric inpatients are at an increased risk of MRPs due to several factors, including polypharmacy, limited patient cooperation, and the complexity of psychotropic medications [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. One study reveals that MR reduces the readmission of psychiatric patients to the hospital [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. To date, no studies in Iran have investigated MRPs and MR in psychiatric patients. This study aimed to assess the prevalence of MRPs in psychotropic medications among patients discharged from the emergency department of Roozbeh Hospital, a leading psychiatric hospital in Iran. The findings of this study can be used by clinicians, policymakers, and researchers to improve medication safety in psychiatric settings.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis observational, cross-sectional study was conducted at the emergency department of Roozbeh Hospital, a leading psychiatric institution in Tehran, Iran, from October 2022 to August 2023. We aimed to assess the prevalence and characteristics of MSPs among hospitalized patients with psychiatric diagnoses.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eParticipants and Sampling\u003c/h3\u003e\n\u003cp\u003eThe target population included all adults admitted to the psychiatric wards during the study period. We employed a census approach, enrolling all eligible patients (n\u0026thinsp;=\u0026thinsp;302) who met the following inclusion criteria:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eConfirmed psychiatric diagnosis by a qualified psychiatrist.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eDaily intake of at least two systemic medications.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003ePatients were excluded if they presented with:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eNo medication uses or consumption of less than two systemic medications daily.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eImpaired consciousness that could hinder accurate data collection.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eInability to swallow medication safely.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eUnwillingness to participate in the study.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eIncomplete medical records that limited comprehensive data extraction.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eWe collected data through a multi-pronged approach to ensure reliability and completeness:\u003c/p\u003e \u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003eQuestionnaires: Two self-designed questionnaires were administered. The first focused on demographic information, medical history, and current medication details. The second, a MR form, served to identify potential discrepancies between the prescribed and actual medication regimens.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e Clinical Interviews: Trained interviewers conducted face-to-face interviews with participating patients and, when feasible, their caregivers, to gather additional clinical details and clarify any uncertainties in the questionnaire responses.\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003eMedical Record Review: Medical records of all participants were meticulously reviewed by trained personnel to extract relevant clinical data, medication history, and diagnoses.\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003e This study was approved by the Ethics Committee of Tehran University of Medical Sciences (IR.TUMS.MEDICINE.REC.1401.393). Informed consent was obtained from all participants after they received a thorough explanation of the study objectives, procedures, and potential risks and benefits. All collected data were anonymized before analysis to protect patient confidentiality.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eThe statistical analysis was conducted at a significant level of less than 0.05 with a 95% Confidence Interval (CI). The analysis was performed using SPSS software version 27.\u003c/p\u003e \u003cp\u003eThe continuous variables\u0026rsquo; normality was assessed using the Shapiro-Wilk test and Q-Q plot. For the description of continuous variables, mean and Standard Deviation (SD) and categorical variables were used from frequency and percentage (%).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 302 patients (139 women, and 163 men) were enrolled in the study. The mean age of the participants was 39.01\u0026thinsp;\u0026plusmn;\u0026thinsp;13.07 years. The educational level of the participants is demonstrated in the table below. The majority of them had a high school diploma or higher (61.5%). Smoking with a prevalence of 46.6% is the most prevalent type of addictive behavior observed in the studied community (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). There was no statistically significant difference regarding the Age and gender among the participants (p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\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\u003eGeneral Information of participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographic Data\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\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\u003e39.01\u0026thinsp;\u0026plusmn;\u0026thinsp;13.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender/F\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (46%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender/M\u003c/p\u003e \u003cp\u003eN (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e163 (54%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducation Level N (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (2.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (13.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ebefore high school\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e67 (22.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiploma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118 (39%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssociate Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17 (5.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePHD Degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eHabitual History N (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e144 (46.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAlcoholism\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e56 (18.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSubstance Use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109 (35.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e(F\u0026thinsp;=\u0026thinsp;Female, M\u0026thinsp;=\u0026thinsp;Male, SD\u0026thinsp;=\u0026thinsp;Standard Deviation)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn this study, patients were using 1421 medications, out of which 1058 medications (74.45%) were psychotropic drugs. The mean number of medications prescribed per patient was 4.71, of which 3.51 were psychotropic medications.\u003c/p\u003e \u003cp\u003eA total of 493 MDs and 392 MRPs were identified in this study. These MDs were classified into 3 categories: drug continuation, drug change, and drug discontinuation.\u003c/p\u003e \u003cp\u003eOut of a total of 493 observed MDs, 419 were classified as unintentional, while 74 were intentional. The most prevalent type of unintentional discrepancy involved medication continuation, representing 211 out of the 419 reported unintentional discrepancies.\u003c/p\u003e \u003cp\u003eFurthermore, in cases of intentional discrepancies, the type of medication discontinuation accounted for the highest number with 48 out of 74 cases (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\u003eTypes of medication discrepancies\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eDiscrepancies\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eContinue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eChange\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eDiscontinue\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003ePercentage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntentional\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e15%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eUnintentional\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e419\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e85%\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn general, based on MRP, a total of 392 problems related to the use of pharmaceutical drugs were identified for the participants (an average of 0.27 interactions per prescription drug). The most observed MRP was the decrease in the amount of medication taken by the patient or not taking it (175 cases, equivalent to 44.64% of the cases) and then drug interactions (168 cases, equivalent to 42.85% of the cases) (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\u003eTypes of MRPs in the studied population\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\u003eMRP Classification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbbreviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003eDuplication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.04%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug interaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42.85%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWrong drug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncorrect strength\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInappropriate dosage form\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContraindication apparent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo indication apparent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther drug selection problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eD0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescribed dose too high\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescribed dose too low\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIncorrect or unclear dosing instructions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther dose problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eO0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnder-use by patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e175\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e44.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOver-use by patient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eErratic use of medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntentional drug misuse, including non-prescription medicines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifficulty using dosage form\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther compliance problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition undertreated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition untreated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreventive therapy required\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther undertreated indication problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eU0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLaboratory monitoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.65%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-laboratory monitoring\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther monitoring problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eM0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient requests drug information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePatient requests disease management advice\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther education or information problem\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=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical interventions that cannot be classified under another category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eToxicity, allergic reaction or adverse effect present\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e392\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe number of medications prescribed and the number of comorbid diseases were the most significant predictors of MRPs. A significant positive correlation was observed between the number of medications prescribed and the number of MRPs (r\u0026thinsp;=\u0026thinsp;0.27, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, a significant positive correlation was observed between the number of comorbid diseases and the number of MRPs (r\u0026thinsp;=\u0026thinsp;0.23, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Tables\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\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\u003ePearson correlation analysis of the number of prescribed medications \u0026amp; comorbid diseases and the number of MRPs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTotal consumed medications\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePsychiatric Medications\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNumber of Concomitant diseases\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003eMedication Errors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003ePearson Correlation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.383\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.285\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.235\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSig. (2-tailed)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e301\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe most common interventions performed for MRPs were referral to the prescriber for medication modification (32.3%), increase in medication dose or addition of a missed medication (28.9%), and patient education (27.8%) (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\u003eInterventions performed for MRPs\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecommendation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbbreviation\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\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\u003eDose increase\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e172\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e28.95%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDose decrease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3.53%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug formulation change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrug brand change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDose frequency/schedule change\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrescription not dispensed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther changes to therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.34%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRefer to prescriber\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e32.27%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRefer to hospital\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRefer for medication review\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther referral required\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation or counselling session\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWritten summary of medicines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecommend dose administration aid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther written information\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonitoring: Laboratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18.51%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMonitoring: Non-laboratory\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo recommendation necessary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eR19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e594\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e100.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eReceiver operating characteristic (ROC) analysis was performed to determine the optimal number of medications for identifying patients at risk of MRPs. The area under the curve (AUC) was 0.701 (95% CI: 0.653\u0026ndash;0.749), and the optimal cutoff value was 0.701. This suggests that all patients taking more than one medication should be screened for MD and MRPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eMR is a process of identifying and resolving MD in the hospital. It is also an important process in the field of psychiatry and can help to prevent medication errors and improve patient outcomes. However, various features in psychiatric hospitals, such as the difficulty of conducting clinical interviews with patients, polypharmacy, psychiatric medicine with different characteristics, the duration of hospitalization and its frequency, and the high number of transfers of care, make the MR challenging in this setting [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Studies have shown that the occurrence of errors related to neuropsychiatric medicines has a high prevalence in the mental health setting [10, 11]. For example, Brownlie Kay et al. investigated the prevalence of medication errors among prescriptions for psychiatric patients in England. In this study, of 377 hospitalized, 212 cases (56.2%) of medication errors were observed [11].\u003c/p\u003e \u003cp\u003eThere are few studies that investigate the prevalence of MD and MRPs in psychiatric patients and no study in Iran has investigated this issue. The present study was conducted to investigate the prevalence of MD and MRPs in patients admitted to the psychiatric emergency department.\u003c/p\u003e \u003cp\u003eThe main finding of the study is that MD and MRPs with a prevalence of 27.8% and 35% respectively are considerable in hospitalized patients with psychiatric disorders. The most common types of MRPs were under-use by patients (44.64%) and drug interactions (42.85%).\u003c/p\u003e \u003cp\u003eOur results are consistent with the findings of other studies that have evaluated the prevalence of MD and MRPs in patients discharged from the hospital [\u003cspan additionalcitationids=\"CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e12\u003c/span\u003e–\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to earlier studies, the most common MD was medication omission [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR14\" class=\"CitationRef\"\u003e15\u003c/span\u003e–\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e19\u003c/span\u003e], accounting for more than half of all MDs identified in one study [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This may be because most patients and their caregivers do not know about home medicine such as over-the-counter (OTC), herbal use, or another habit at home, or they consider them unimportant. Therefore, after being admitted to the hospital, they may stop their home medicine or take the wrong dose without awareness the attending physician.\u003c/p\u003e \u003cp\u003eThe number of medication errors increases with patient age, high number of prescription drugs, co-morbidities, multiple prescriptions for the same patient, and an overburdened healthcare system [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR19\" class=\"CitationRef\"\u003e20\u003c/span\u003e–\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. We have identified that the number of medications prescribed and the number of comorbid diseases were the most significant predictors of MRPs. These findings align with previous researches [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOur study also found that the pharmacist-led MR intervention was effective in identifying and resolving MRPs. The intervention resulted in the identification of 493 MD and 392 MRPs. Of these, 592 interventions were made by the pharmacist to resolve the discrepancies and problems.\u003c/p\u003e \u003cp\u003eSeveral studies also verified the results, including the study by Kim Sook-Yoon et al., showing that patient education in relation to the medicine, its side effects, and the method of consumption and monitoring can significantly reduce errors in pharmacotherapy [23].\u003c/p\u003e \u003cp\u003eThe results of a study by the American Society of Health-System Pharmacists found that pharmacist-led MR interventions can reduce the rate of medication errors by up to 50% [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAnother study also showed that pharmacy-performed MR followed previous nursing-performed MR identifying an average of 2.9 differences per patient [25].\u003c/p\u003e \u003cp\u003eTherefore, it was concluded that medication reconciliation by pharmacists can be very effective in solving unintentional medication discrepancies, and improving the efficacy and safety of medications.\u003c/p\u003e \u003cp\u003eThis is the first study from Iran that investigates and reveals the high prevalence of major MD and MSPs in psychiatric patients discharged from hospital. Our findings suggest that MR is an important patient safety intervention that can help prevent medication errors and improve patient outcomes in this population.\u003c/p\u003e \u003cp\u003eFurther research is needed to evaluate the long-term impact of MR on the rate of hospital readmissions, the cost of care, and patient satisfaction and outcomes.\u003c/p\u003e\n\n"},{"header":"Limitations","content":"\u003cp\u003eThis study has several limitations. First, it was conducted in a single psychiatric emergency department, and the findings may not be generalizable to other settings. Second, the study was observational, and the findings cannot be used to make causal inferences. Third, the study did not assess the long-term impact of MR on patient outcomes.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eFunding/Support\u003c/strong\u003e \u003cp\u003eThis research did not receive any specific financial support from funding organizations in any department.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eMS and MP contributed to data curation, investigation, writing \u0026amp; editing the original manuscript . NM is responsible for the supervision and study design and writing the original manuscript , writing \u0026amp; editing the original manuscript .All authors reviewed the manuscript\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eRATRVASY. Medication Dispensing Errors and Prevention. 2023.\u003c/li\u003e\n\u003cli\u003eBarnsteiner JH. Medication reconciliation. Patient safety and quality: an evidence-based handbook for nurses. 2008.\u003c/li\u003e\n\u003cli\u003ePronovost P, Weast B, Schwarz M, Wyskiel RM, Prow D, Milanovich SN, et al. Medication reconciliation: a practical tool to reduce the risk of medication errors. Journal of critical care. 2003;18(4):201-5.\u003c/li\u003e\n\u003cli\u003eUsing medication reconciliation to prevent errors. Sentinel event alert. 2006(35):1-4.\u003c/li\u003e\n\u003cli\u003eWolf C, Pauly A, Mayr A, Gr\u0026ouml;mer T, Lenz B, Kornhuber J, et al. Pharmacist-Led Medication Reviews to Identify and Collaboratively Resolve Drug-Related Problems in Psychiatry - A Controlled, Clinical Trial. PloS one. 2015;10(11):e0142011.\u003c/li\u003e\n\u003cli\u003eSoerensen AL, Lisby M, Nielsen LP, Poulsen BK, Mainz J. The medication process in a psychiatric hospital: are errors a potential threat to patient safety? Risk management and healthcare policy. 2013;6:23-31.\u003c/li\u003e\n\u003cli\u003eOliveira J, Silva TCE, Cabral AC, Lavrador M, Almeida FF, Macedo A, et al. Pharmacist-led medication reconciliation on admission to an acute psychiatric hospital unit. Pharmacy practice. 2022;20(2):2650.\u003c/li\u003e\n\u003cli\u003eVigod SN,\u0026nbsp;Kurdyak PA,\u0026nbsp;Dennis CL,\u0026nbsp;Leszcz T,\u0026nbsp;Taylor VH,\u0026nbsp;Blumberger DM,\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e.\u0026nbsp;Transitional interventions to reduce early psychiatric readmissions in adults: systematic review.\u0026nbsp;\u003cem\u003eBr J Psychiatry\u003c/em\u003e2013;\u0026nbsp;202:\u0026nbsp;187\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eSoerensen AL, Lisby M, Nielsen LP, Poulsen BK, Mainz J. The medication process in a psychiatric hospital: are errors a potential threat to patient safety? Risk management and healthcare policy.2013;6:23-3\u003c/li\u003e\n\u003cli\u003eRichard NK, Steven DW, Joe JV, Petra B, Joan M, Lorraine P, et al. Prevalence, nature and predictors of prescribing errors in mental health hospitals: a prospective multicenter study. BMJ Open. 2014;4(9):e006084.\u003c/li\u003e\n\u003cli\u003eBrownlie K, Schneider C, Culliford R, Fox C, Boukouvalas A, Willan C, et al.\u003cbr /\u003e Medication reconciliation by a pharmacy technician in a mental health assessment unit.\u003cbr /\u003e International journal of clinical pharmacy. 2014;36(2):303-9\u003c/li\u003e\n\u003cli\u003eUrban R, Armitage G, Morgan J, Marshall K, Blenkinsopp A, Scally A. Custom and practice: a multi-center study of medicines reconciliation following admission in four acute hospitals in the UK. Research in social \u0026amp; administrative pharmacy : RSAP. 2014;10(2):355-68.\u003c/li\u003e\n\u003cli\u003eBell CM, Bajcar J, Bierman AS, Li P, Mamdani MM, Urbach DR. Potentially unintended discontinuation of long-term medication use after elective surgical procedures. Arch Intern Med. 2006;166(22):2525-31.\u003c/li\u003e\n\u003cli\u003eBell CM, Rahimi-Darabad P, Orner AI. Discontinuity of chronic medications in patients discharged from the intensive care unit. Journal of general internal medicine. 2006;21(9):937-41.\u003c/li\u003e\n\u003cli\u003eRostami P, Heal C, Harrison A, Parry G, Ashcroft DM, Tully MP. Prevalence, nature and risk factors for medication administration omissions in English NHS hospital inpatients: a retrospective multicentre study using Medication Safety Thermometer data. BMJ Open. 2019;9(6):e028170\u003c/li\u003e\n\u003cli\u003eNilsson N, Lea M, Lao Y, et al. Medication discrepancies revealed by medication reconciliation and their potential short-term and long-term effects: a Norwegian multicentre study carried out on internal medicine wards.\u0026nbsp;\u003cem\u003eEur J Hosp Pharm\u003c/em\u003e. 2015;22:298-303.\u003c/li\u003e\n\u003cli\u003eTam VC, Knowles SR, Cornish PL, et al. Frequency, type and clinical importance of medication history errors at admission to hospital: a systematic review.\u0026nbsp;\u003cem\u003eCMAJ\u003c/em\u003e. 2005;173:510-515.D\u003c/li\u003e\n\u003cli\u003eModig S, Caleres G, Nymberg VM, et al. Assessment of medication discrepancies with point prevalence measurement: how accurate are the medication lists for Swedish patients?\u0026nbsp;\u003cem\u003eDrugs Ther Perspect\u003c/em\u003e. 2022;38:185-193.\u003c/li\u003e\n\u003cli\u003eMikaelsen HZ, Ulla IH, Karimi D, et al. Medication Discrepancies in Hospitalised Medical Patients \u0026ndash; Status After a Decade With Targeted Medication Reconciliation Measures, a Cross-sectional Multicenter Study. Health Services Insights. 2024;17. doi:10.1177/11786329241254202D\u003c/li\u003e\n\u003cli\u003eGiannini O, Rizza N, Pironi M, et al. Prevalence, clinical relevance and predictive factors of medication discrepancies revealed by medication reconciliation at hospital admission: prospective study in a Swiss internal medicine ward.\u0026nbsp;\u003cem\u003eBMJ Open\u003c/em\u003e. 2019;9:e026259.\u003c/li\u003e\n\u003cli\u003eDamlien L, Davidsen N, Nilsen M, et al. Drug safety at admission to emergency department: an innovative model for PRIOritizing patients for MEdication Reconciliation (PRIOMER).\u0026nbsp;\u003cem\u003eEur J Emerg Med\u003c/em\u003e. 2017;24:333-339.\u003c/li\u003e\n\u003cli\u003evan der Nat DJ, Taks M, Huiskes VJB, van den Bemt BJF, van Onzenoort HAW. Risk factors for clinically relevant deviations in patients\u0026rsquo; medication lists reported by patients in personal health records: a prospective cohort study in a hospital setting.\u0026nbsp;\u003cem\u003eInt J Clin Pharm\u003c/em\u003e. 2022;44:539-547.\u003c/li\u003e\n\u003cli\u003eKim YS, Kim HS, Kim HA, Chun J, Kwak MJ, Kim MS, et al. Can patient and\u003cbr /\u003e family education prevent medical errors? A descriptive study. BMC health services research.\u003cbr /\u003e 2020;20(1):269 Vigod SN,\u0026nbsp;Kurdyak PA,\u0026nbsp;Dennis CL,\u0026nbsp;Leszcz T,\u0026nbsp;Taylor VH,\u0026nbsp;Blumberger DM,\u0026nbsp;\u003cem\u003eet al\u003c/em\u003e.\u0026nbsp;Transitional interventions to reduce early psychiatric readmissions in adults: systematic review.\u0026nbsp;\u003cem\u003eBr J Psychiatry\u003c/em\u003e2013;\u0026nbsp;202:\u0026nbsp;187\u0026ndash;94.\u003c/li\u003e\n\u003cli\u003eAccomando M, DeWitt K, Porter B. Pharmacist impact on medication reconciliation of behavioral health patients boarding in the emergency department. Ment Health Clin. 2022;12(3):187-92. DOI: 10.9740/mhc.2022.06.187\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"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":"Medication reconciliation, Medication discrepancy, Psychotropic medication, Psychiatric disorder","lastPublishedDoi":"10.21203/rs.3.rs-6371089/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6371089/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Medication discrepancies (MDs) are common medication errors that can lead to adverse drug events (ADEs) and suboptimal treatment. Medication reconciliation (MR) programs are implemented in many countries, including Iran, to identify, resolve, and prevent MDs and other medication-related problems (MRPs). In the psychiatric setting, the importance of identifying and addressing MRPs is even greater due to the high prevalence of polypharmacy, limited patient cooperation, and other factors. This study aimed to investigate the prevalence of MDs and MRPs in psychiatric patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e This study included 302 psychiatric patients receiving at least two systemic medications daily. Their medications were reviewed at discharge using the Pharmaceutical Society of Australia (PSA) guidelines to identify MRPs. The collected data were analyzed statistically.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eIn this study, patients were taking a total of 1421 medications (4.71 medications per patient). A total of 493 MDs and 392 MRPs were identified. The most common MRPs were, in decreasing order, medication underuse or non-adherence by the patient (175 cases, 44.64% of all MRPs) and drug interactions (168 cases, 42.85%). The number of drug interactions significantly increased with the increasing number of underlying diseases and the number of medications used (P \u0026lt; 0.001 in both cases). A total of 594 interventions were made by the pharmacist, of which the most common were referrals to the physician for medication adjustments (193 cases, 32.27% of all interventions) and increasing the medication dose or prescribing a missed medication (172 cases, 28.95%).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e This study showed that the prevalence of MRPs in psychiatric settings is considerable and that implementing an MR program and pharmacist intervention in MRPs can significantly improve the quality of care.\u003c/p\u003e","manuscriptTitle":"Medication Discrepancies and Medication-Related Problems in Psychiatric Patients: A Medication Reconciliation Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-17 15:50:18","doi":"10.21203/rs.3.rs-6371089/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":"52c85a08-bf04-49d8-ba54-38e767d8d8e1","owner":[],"postedDate":"June 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-09T18:23:23+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-17 15:50:18","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6371089","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6371089","identity":"rs-6371089","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}