Cost-effectiveness analysis of the community pharmacist-based intervention in Type 2 diabetes mellitus a service trial

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Objective Since there are no well-designed randomized service trials to assess the impact of community pharmacist intervention on the improvement of T2DM management in Iran, we aimed to (a) determine the long-term effects, (b) evaluate the cost-effectiveness of care provided to T2DM patients, and (c) help policymakers to value these services. Methods In a 12-month trial at a community pharmacy, 55 patients received usual care, while another 55 received a diabetes management protocol from the pharmacist. The pharmacist focused on correcting medication use, lifestyle modification, and improving diet. The technical aspects of economic evaluation contained conducting the study from the healthcare system perspective, a 10-year time horizon was chosen to assess the long-term effects and cost savings. Direct medical costs included the costs of medications, lab tests, and physician visits. Intervention costs covered pharmacist time, patient education materials, and glucose monitoring supplies. The primary outcome was the change in HbA1c levels. Secondary outcomes included life years gained (LYG) and the reduction in the 10-year risk of cardiovascular events. Results Pharmacist's interventions significantly reduced average HbA1c levels and lowered risks for CVD and stroke in the intervention group compared to the control group (p value = 0.009). Cost-effectiveness analysis showed that this intervention resulted in a cost reduction and life years gained over a 10-year time horizon. The PSA analysis showed that pharmacist interventions led to more LYGs and lower costs for the intervention group compared to the control group. The cost-effectiveness plane for 1,000 individuals showed 95.2% of ICER points in the southeast quadrant, indicating the intervention's dominance. Conclusion Involving community pharmacists in diabetic programs can reduce short-term and long-term complications. It emphasizes that providing primary diabetes care by pharmacists benefits patients and brings significant cost savings to the healthcare system. diabetes care pharmaceutical care randomized service trial type 2 diabetes mellitus UKPDS risk score cost-effectiveness analysis community pharmacy Figures Figure 1 Figure 2 Figure 3 Background Diabetes mellitus (DM) is one of the most critical metabolic diseases with a rapid growth rate in developed and developing countries.( 1 ). DM is determined by unstable insulin secretion or insulin resistance, leading to impaired carbohydrates, protein, and fat.( 2 ). Diabetes is a grave public health problem with an astronomical impact on human life and health expenditures.( 3 ). In 2019, diabetes-related health expenditure in adults with a range of 20–79 years was estimated to be 760 billion dollars globally. It is estimated to grow to 825 billion dollars each year by 2030( 1 ). Type 2 diabetes mellitus (T2DM) is a growing epidemic worldwide, and according to the World Health Organization (WHO) statistics, In 2019, diabetes was the 9th leading cause of death with 1.5 million deaths globally. ( 4 ). As T2DM rapidly grows ( 5 ), its long-term uncontrolled conditions lead to severe micro and macrovascular complications( 6 ), significantly raising morbidity and mortality rates. The management of diabetes and its complications imposes substantial burdens on individuals, families, and society, making it a significant public health and economic concern( 3 ). Effective diabetes management through medications is crucial, with pharmacists playing a vital role in ensuring medication quality and safety( 7 ). Pharmacists, alongside physicians, provide essential healthcare services that improve HbA1c, fasting blood sugar, and medication adherence, and reduce medication errors and diabetes-related complications( 8 , 9 ). There is limited research on the effectiveness of community pharmacist interventions in diabetes management. Studies by Matthew Lee Smith et al.( 10 )have shown improvements in HbA1c through pharmacist-led interventions. However, further research is needed to assess the long-term efficacy and economic impact of these interventions, especially in different economic contexts.( 11 ) According to the WHO, Cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17.9 million lives each year.( 12 ), which more than 75% take place in nations with low and moderate incomes, and T2DM is a significant modifiable risk factor for cardiovascular diseases. CVD problems can account for as much as 20–49% of total direct treatment expenditures for type 2 diabetes( 13 ), we pay attention to patients’ CVD situation as well as diabetes. In the United States, each year $ 237 billion is spent on direct medical costs and another $ 90 billion on reduced productivity by CVD.( 14 ). In comparison to T2DM patients without CVD, the median yearly expenses for patients with CVD, coronary artery disease, heart failure, and stroke were, respectively, 112%, 107%, 59%, and 322% higher in comparison with those with T2DM.( 15 ). Therefore, effective CVD preventive interventions can lower a significant amount of the burden of T2DM that may be related to cardiovascular problems. Literature shows that based on global trends, patients with diabetes have a 10-year risk of CVD, which increases the disease burden on communities. Community pharmacist-based interventions are safe and essential for enhancing public health outcomes in Iran. These interventions can significantly improve medication adherence, manage chronic diseases, and provide accessible healthcare advice. However, several challenges need to be addressed: challenges such as regulatory hurdles, resource allocation, public awareness, collaboration with healthcare providers, and providing more research and evidence to demonstrate the effectiveness and cost-efficiency of pharmacist interventions, thereby supporting policy changes. Considering the significant absence of cost-effectiveness data for pharmacist-led interventions in Iran, this study seeks to address this critical gap by evaluating both clinical and economic outcomes. METHODS Study design This study was conducted over 12 months, as a randomized, controlled, parallel-group service trial at one community pharmacy in Tehran, the capital city of Iran. One trained pharmacist was selected to gather the participants and service providing. In the initial stages of the study, it was essential to establish and standardize the services provided by community pharmacists, as the current scope of practice is limited to dispensing prescriptions and over-the-counter medications. Standardization of the service had been conducted using the published guidelines by the International Diabetes Federation and the Gabric Diabetes Education Association in Iran. After extracting the exact type of service from the mentioned guidances, two key opinion leaders of endocrinologies validated the service and trained the community pharmacist informing her how to implement the service for patients. Ethical Code The study was carried out using the principles of good clinical practice and the Declaration of Helsinki. The Shahid Beheshti University of Medical Science's ethics committee approved this clinical study (IR.SMBU.PHARMACY.REC.1400.450). Written informed consent was obtained from each participant. Randomization Process The randomization process was applied at the pharmacy level. The participants were sequentially and randomly assigned to control and intervention groups by the pharmacist considering inclusion and exclusion criteria. Patients receiving oral hypoglycemic medication for at least 6 months, patients between 20 and 80 years old, old, and HbA1c ≥ 8% for more than 3 months and have at least one underlying disease than T2DM enrolled in this study. Being on insulin treatment, and under 20 years old, patients with cognitive disorders, patients with pregnancy diabetes, and patients with T1DM were the exclusionary factor. Sample Size Based on H. Okada's 2016 randomized controlled trial assessing community pharmacists' interventions, the effect size, standard deviation, and drop-out rate were extracted to calculate the number of patients needed. Studies emphasize a 0.5% reduction in HbA1c levels in T2D patients as the effect size.( 16 ). Consequently, a 0.5% reduction was considered for our intervention group. The required sample size was 55 per group, accounting for a 15% drop-out rate, with a type 1 error of 5% and 90% power at a two-tailed 5% significance level.( 17 ): n = 2 (Z[1-α/2] + Z [1-β])2 × SD2 /d2 Table 1 factors for calculating the sample size of the service trial Result Parameters No. of parameters 0.5 effect size (HbA1c%) 1 0.9 Standard Deviation 2 20.995 2*(zα + z[1-β]) 2 3 2.25 SD 2 /d 2 4 47 No. patients in each group 5 55 Dropout rate (15%) 6 Recruitment process This study was conducted by one trained community pharmacist in the pharmacy consultation room and a 6-month periodic monitoring phase. Potentially eligible patients, according to the inclusion and exclusion criteria, were recruited by the community pharmacy between October 2021 and October 2022. According to the reviewed literature evaluated the same goal as our study and reference to the necessary inputs for the UKPDS model, primary and secondary outcomes of this study were extracted as shown in Table 2 . Table 2 Primary and Secondary outcomes of the study No. Primary outcomes Interval of assessment 1 Hb A1c Every 3 months 2 FBS Every month 3 EQ-5D-5L Every month No. Secondary outcomes Interval of assessment 1 SBP & DBP Every month 2 Weight and BMI 3 Lipid Profile: LDL, HDL, Tg and Cholesterol 4 BUN & Cr The intervention design was based on the below components and provided to the intervention group: Patient education about T2DM and its complications. Patient education about the proper use of oral hypoglycemic medications (timing about food) and other medications. Facilitation of medication adherence (by counseling) Patient education about leading a healthy lifestyle (diet, exercise, and quitting smoking). Reminders about the timing of the pharmacist’s visit during the next intervals. All services provided by community pharmacists are conducted within safe and defined parameters, strictly adhering to the mentioned components. These services exclude any form of invasive intervention or alterations to prescribed medications, as suggested by the pharmacist The pharmacist, who graduated from one of the Pharmacy Schools in Iran, only received a free consultation from two endocrinologists to be sure about the lifestyle modifications in T2DM patients and the appropriate consultation for the patients, applied all protocol components to every patient in the intervention group and patients in the control group received standard pharmacy care as usual (only dispensing their medication prescription). At the beginning of the study and in every 3-month intervals, patients in both groups were measured for the parameters listed in Table 3 . All the patients in both the intervention and control groups were followed up by the pharmacist by telephone call to arrange the in-person visits. Initial Visit In the first phase, each patient had a 30-minute initial visit where the community pharmacist carefully reviewed their medical, and medication history and the necessary parameters for measurement listed in Table 3 . The community pharmacist also assessed the patient's knowledge and health behavior, focusing on adherence to current medication therapy, diet, smoking behavior alcohol consumption, and exercise regimen. Additionally, the community pharmacist answered any questions the patients may had about the study to set one long-term health goal and three short-term, measurable management goals by the community pharmacist. Patients were informed that their clinical values would be gathered in two different ways. The pharmacy collaborated with the nearest laboratory to provide support for patients to obtain monthly blood tests for FBS, 2-hpp, lipid profile, BUN, and Creatinine assessments. Every 3 months, patients undergo HbA1c testing, as well as SBP, DBP, weight measurements, BMI calculations, and completion of the EQ-5D-5L questionnaire by the community pharmacist during each visit. Table 3 List of demographic and clinical parameters of the patients No. Parameter measurement unit 1 Name of Pt ID cart 2 Sex M/ F 3 Race Iranian or non-Iranian 4 Date of birth DD/MM/YY 5 Age Year 6 Weight Kg 7 Height Cm 8 BMI index Kg/ cm2 9 List of current medicines in use Based on prescriptions 10 T2DM duration Months or years 11 Family history of T2DM Patient's statement 12 HbA1c level in the past 3 months Percentage 13 FBS and 2-hpp (entry phase) mg/ dl 14 Lipid profile mg/ dl 15 Creatinin level mg/ dl 16 BUN level mg/ dl 17 SBP & DBP mmHg 18 Cigarette & Alcohol consumption Patient's statement 19 Atrial fibrillation Patient's statement 20 Neuropathy complications of DM: numbness or wounds in feet Patient's statement 21 Nephropathy complications of DM 22 Retinopathy complications of DM: any changes in visual status 23 Quality of Life EQ-5D-5L questionnaire and VAS index Ongoing Visits During each follow-up visit, the community pharmacist collected and assessed the patient’s disease status, medications, and study outcomes. All the data gathered from the patients were documented individually in Excel sheets. Before each visit, the pharmacist called the patients. If there was no answer, she tried to reach them through messages to ensure their availability for the next in-person visit. Patients were incentivized with free e-prescriptions to do the laboratories, free consultation, and health assessment by community pharmacists, and also one thermometer from the pharmacy. Short-term data analysis: Short-term data, including HbA1c, LDL, HDL-C, and SBP, are necessary outcomes for the UKPDS risk score model, affecting cardiovascular disease risks (Table 4). The collected data were subsequently evaluated for normality using the One-sample Kolmogorov-Smirnov Test (SPSS Statistics 27.0.1). Additionally, an Independent T-Test was conducted to assess the differences between groups. Long-term data analysis using Markov modeling A Markov model with a one-year cycle length and a 10-year time horizon was developed to simulate long-term CVD events, death risk, and related expenditures for two groups of intervention and control group of Iranian patients with participation in this study. Patients in the intervention group were those who received standardized diabetes care services from a community pharmacist and patients in the control group received their routine pharmacy services. The study model illustrated in Fig. 1 . Based on the study conducted by Mousa et alin 2021 in Jordan. In this model the Individuals with T2DM were initially included in the model in the "well" state, meaning they had not previously experienced any cardiovascular events.( 18 ) Throughout the 10-year simulation, individuals might age without experiencing any CVD events, experience a first-ever CVD event (fatal or nonfatal), experience a subsequent CHD, or stroke, or pass away from CVD events or non-cardiovascular causes. Individuals who underwent a primary myocardial infarction (i.e., nonfatal) could continue to be in this condition of health until they died from a fatal myocardial infarction stroke, or any other reason. ( 18 ). The United Kingdom Prospective Diabetes Study (UKPDS) Risk Engine (version 2) was used to estimate the CVD risks as the Markov model inputs. In this study, all the necessary inputs for the calculation of the risks including the patient's age at diagnosis state, gender, ethnicity, smoking status, arrhythmia, length of diabetes, systolic blood pressure (SBP), total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) levels were gathered from the baseline and at the follow-ups visits. Transition probabilities. We estimated the transition probabilities of the Markov model (Fig. 1 ) based on several CVD events using the UKPDS Risk Engine Version 02: absolute risk of stroke and CHD, both fatal and nonfatal. The final calculated probabilities have been validated by R. Mousa, an expert in the cost-effectiveness of the pharmacist’s services. The observed impacts of A1c, SBP, TC, and HDL-C, together with other patient-specific factors, were translated into the estimated 10-year risks for CHD events and stroke using the prediction algorithm in this Risk Engine. Consequently, the calculated risks were converted to transition probabilities using the following equation: R= - [ln (1-p)]/t Utility Measures. Patients were enrolled in this study based on their utility score of each health state in the Markov model that was taken from extracted measures of the EQ-5D-5L questionnaire and using the interim national value set of them for the Iran population. ( 19 ). According to this value set, a score of 0 denotes death, and a value of 1 indicates complete health. Both branches were subject to a 5% discount rate for final health outcomes after the first year. ( 20 ). The utility of each state was taken from the conducted study by R. Mousa in 2020 for measuring the cost-effectiveness of pharmacist-led care in T2DM patients in Jordan.( 18 ). Then the final cost-effectiveness analysis was conducted by Excel 2021. Tornado Diagram. To identify the primary factors influencing cost-effectiveness outcomes, we will conduct a sensitivity analysis by systematically varying one parameter at a time while maintaining the others constant. Additionally, we will construct a diagram to visually depict the impact of each parameter's variation on the final result, thereby demonstrating the robustness of our findings. Probabilistic Sensitivity Analysis (PSA). To thoroughly assess uncertainty, we incorporated probability distributions for each variable, enabling us to provide confidence intervals for the ICER. This elucidates the range within which the true value of the ICER is likely to reside. Additionally, we generated a cost-effectiveness plane to visualize the distribution of the results across each quadrant. RESULTS One of the patients from the intervention group lost to follow-up, due to a major diabetic wound, and two patients due to unwillingness to study proceeding. One of the patients in the control group was dead due to major cardiovascular diabetic complications. In the end, the number of patients in the intervention group reached 52 participants, and for the control group 54. The main primary outcomes, HbA1c together with secondary outcomes including LDL, HDL, and SBP of the patients are shown in Table 4. Pharmacists’ intervention showed better improvement in the main primary outcomes, mainly, a decrease in average HbA1c level was higher in the intervention group (base: 8.47 vs. month-12: 8.45) compared to the control group (base: 8.64 vs. month-12: 8.88). Short-term data analysis: Short-term data, including HbA1c, LDL, HDL-C, and SBP, are necessary outcomes for the UKPDS risk score model, affecting cardiovascular disease risks (Table 4). Following a 12-month study, patients in the intervention group displayed a significant reduction in their HbA1c levels during each assessment (p-value = 0.009; from 8.47 at the baseline to 8.45 at the end). Conversely, patients in the control group saw an increase in their HbA1c levels (from 8.64 at the baseline to 8.88 at the end). Our study showed that the community pharmacist made a statistically significant improvement in improving the HDL-C profile of patients in the intervention group during each assessment (p-value = 0.016). The HDL-C levels decreased from 1.31 at the baseline to 1.13 at the end, while patients in the control group experienced a decrease from 1.17 at the baseline to 1.04 at the end. In terms of LDL, a major risk factor for cardiovascular disease, the community pharmacist intervention had a statistically significant reduction in its level (p-value = 0.05; from 4.25 at the baseline to 3.37 at the end). However, it had no significant impact on patients in the control group, as their LDL levels went from 3.97 at the baseline to 3.93 at the end. In the intervention group, the SBP of the patients showed a statistically significant improvement from the community pharmacist standard care, with a significant decrease from 134.55 at the beginning to 133.85 at the end (p-value = 0.003). Conversely, the control group experienced increased SBP levels, rising from 136.79 at the baseline to 140.46 at the end. Table 4-Clinical inputs of the study patients, at baseline, 6 months, and 12 months after study initiation The pharmacists’ intervention showed a slight improvement in the primary outcome of HbA1c levels, with a decrease from 8.47 to 8.45. Although this change is minor and may not appear clinically significant at first glance, it is important to consider the broader context. Even small reductions in HbA1c can lead to better long-term glycemic control and potentially reduce the risk of diabetes-related complications( 21 , 22 ). Moreover, the intervention's consistency and sustainability over 12 months indicate its potential effectiveness and utility in managing T2DM patients. Therefore, while the immediate change in HbA1c is modest, the intervention's overall impact on patient care and management strategies can be considered clinically meaningful. Clinical inputs for CVD risk prediction. Determining the clinical inputs for calculating and predicting risks of CVD events was conducted using the UKPDS guidance. By applying the UKPDS guidance, the clinical inputs for estimating the risks of CVD events were determined. The UKPDS risk score engine was used to estimate the CVD risks for the patients who were enrolled in the control and intervention groups for 10 years. The results are displayed in Table 5 . Following 12 months of observation, the intervention group's estimated risks for CHD and stroke—both nonfatal and fatal—were lower than those of received routine care. Throughout each group's ten-year course, the annual risk increased as predicted for the aging patients. Furthermore, over time, there was an increase in the absolute risk reduction (ARR) between the control and intervention groups. Cost inputs and utilization of medical resources. To demonstrate the cost-effectiveness of the implemented service to healthcare system policymakers, the study was conducted from the healthcare system's perspective, leading us to utilize direct medical costs. The cost inputs used in the model were the healthcare provider's direct medical costs obtained from the study conducted by Bayazidi et al. (19, 23, 24). Annual medication costs per patient were calculated based on the national guidelines published for CHD management and available works of literature. Based on the time preference measure of the social discount rate for Iran, a discount rate of 5.8% was applied for the costs based on national evidence. (20) and shown in Table 6. Table 6 Cost and Utility of each Markov states Health State Cost Lower limit Upper limit State Utility Well- Intervention $ 1,979 $ 395.80 $ 2,374.80 0.810 Well- Control $ 4,279 $ 855.80 $ 5,134.80 0.809 Primary Stroke $ 2,185 $ 437.00 $ 2,622.00 0.645 Secondary Stroke $ 4,936 $ 987.20 $ 5,923.20 0.556 Primary CHD $ 3,828 $ 765.60 $ 4,593.60 0.725 Secondary CHD $ 11,533 $ 2,306.60 $ 13,839.60 0.684 The model calculated the predicted survival for both the control and intervention groups of patients based on the total amount of time they spent in each health state. To calculate the costs and life years gained (LYGs) for each cycle, relevant costs were allocated to each health state in the Markov model, weighted by the transition probability, and then totaled over all the health states. The aggregated costs and LYGs were then determined by adding the mean costs and LYGs for each of the ten annual cycles. The main outcome of the model was determining the incremental cost-effectiveness ratio (ICER) by dividing the cost differences by the LYG differences of both groups. The cost-effectiveness (CE) threshold by the pharmacoeconomics committee of the Iranian Food and Drug Administration (IFDA) representing the willingness-to-pay (WTP) value of 700,000,000 Iranian Rials (IRR) (equal to 2,456 USD) was considered as the CE threshold of this study. The Exchange rate of IRR to USD (in the year of study, 2021) was 285,000 IRR. Base-case analysis According to calculations conducted using each patient's costs and outcomes, it is shown that pharmacists' interventions in T2DM patients resulted in a cost of -1469.02 USD with 0.045 LYGs compared to the control group (Table 7). Probabilistic sensitivity analysis (PSA) analysis The PSA analysis, like the base-case analysis, revealed that the interventions of the pharmacists resulted in additional LYGs and less cost for the intervention group in comparison with the control one. The cost-effectiveness plane (Fig. 2) which was run for 1,000 individuals showing the distribution of 95.2% of ICER points in the southeast quadrant indicated that the intervention is dominant. The southeast quadrant in the cost-effectiveness plane represents the most favorable outcome, as it signifies interventions that deliver superior effectiveness at a lower cost relative to the standard treatment. Within this quadrant, the intervention not only enhances health outcomes but also achieves cost savings, rendering it the optimal choice from both clinical and economic perspectives. Tornado diagram To show how sensitive different variables are to change the final result of our study, helping stakeholders prioritize their focus a tornado diagram of all the variables was drawn (Fig. 3) These findings suggest that the cost of renal failure has a significant impact on the calculated ICER, while the cost of services provided by community pharmacists does not affect ICER. Discussion In this study, we pursued a novel economic study to know if implementing services by community pharmacists for T2DM patients is cost-effective. Iran as a low-middle-income country located in the Middle East region lacked any specific services provided by community pharmacists. Several factors contribute to the lack of standard care services in community pharmacies in Iran. These include the lack of public awareness that such services may be available at community pharmacies, the lack of acceptance by physicians that trained community pharmacists are eligible to provide medication regimens, and the lack of government initiatives to include the services provided by community pharmacists in insurance coverage ( 25 ). Studies from countries like Australia and Canada have demonstrated the effectiveness of pharmacist-led diabetes management programs. For example, Hughes et al. showed how pharmacists in Australia significantly improved patients’ glycemic control and medication adherence, leading to reduced healthcare costs( 26 ). Garcia-Cardenas et al. conducted a study in Canada in 2016 and revealed that pharmacists’ involvement in diabetes care resulted in better blood sugar control and patient satisfaction, emphasizing their role as essential healthcare providers( 27 ). The effectiveness of a variety of services offered by community pharmacists has been extensively researched in numerous countries. However, in Iran, there is a significant gap in the evaluation of these studies. One key finding of this study was that we analyzed over 200 articles that focused on the services provided by community pharmacists, and we selected 183 of them. Among these, it was found that diabetes-related services were the most researched area in which community pharmacists could add value. The current cost-effectiveness studies have a significant gap when it comes to demonstrating the limits of cost-effectiveness. Most studies only focus on determining whether a specific service is cost-effective to implement. However, none of them have looked into providing a service package to healthcare providers to request insurance coverage. According to the result provided in our study, the modest change in HbA1c from 8.47 to 8.45 over 12 months may appear minimal, but even slight reductions can lead to significant clinical benefits, such as reduced risks for complications in T2DM patients. Factors like patient baseline levels, short duration of study, and real-world application complexities could contribute to the modest change. Despite this, the intervention's consistency over 12 months highlights its potential for sustainable glycemic control, underscoring the clinical meaningfulness of our findings. Our study in line with several global studies showed that adding pharmacists to diabetic care, mainly T2DM decreases the long-term risks of cardiovascular diseases.( 28 ). In addition, Similar to our results, the study conducted by Siaw MYL showed that by implementing community pharmacist care for T2DM patients the estimated discounted cost savings per patient over 10 years was 1709.95 USD ( 10 ). In a similar context, Rimal M. et al conducted a study that focused on demonstrating the cost-effectiveness of pharmacist-led care services in reducing the 10-year CVD risks in Jordanian patients with T2DM. They found that standard care services would generate 0.3 LYG with an additional cost of 1,747.24 USD( 18 ). To integrate pharmacists into healthcare systems, policy changes are necessary; findings of Leal et al. in 2013 suggest that revising insurance coverage to include pharmacist services not only encourages healthcare providers to collaborate but also makes these services accessible to patients, especially in low- and middle-income countries( 29 ). The main result of our study, which sets it apart from other studies in this era, is that it demonstrated the limit of cost-effectiveness of providing T2DM services by community pharmacists which is still novel among published studies worldwide. Moreover, our study found that the pharmacist program improved patients' knowledge of diabetes, self-care activities, and their awareness regarding the importance of lifestyle modifications. Intensive patient-pharmacist contact and regular glucose self-measurements contribute to the brilliant achievements in T2DM disease control. To our knowledge, this is the first service trial accompanied by the economic evolution of pharmacists’ T2DM services. However, more long-run multi-center studies are needed to determine how clinical improvements can be maintained over time. Even though all the patients included in the study were already on pharmacotherapy for one year or more, our program was still beneficial to them. We would expect it to have an even greater impact on patients with treatment-resistant diabetes, as they have a higher need for information and education. Another long-term sustainability of the community pharmacist-based intervention will be achieved by enhancing the training of pharmacists to ensure they are well-equipped with the latest knowledge and skills in diabetes management, Increase public awareness about the role of pharmacists in diabetes care through community outreach programs, social media campaigns, and collaboration with healthcare providers, Integrate pharmacist services into primary healthcare settings to ensure a holistic approach to diabetes management and conduct ongoing research and evaluation to assess the effectiveness and cost-effectiveness of pharmacist-led interventions. Study limitations: It is important to acknowledge that our investigation, like all experiments, has certain limitations. Firstly, the use of a single community pharmacist constrains our ability to generalize the findings to a broader population. Secondly, the observed effectiveness of the intervention group may have been influenced by the Hawthorne effect, whereby participants alter their behavior in response to being observed( 30 ). Furthermore, in a service trial such as an RCT, patients in the intervention group are often motivated to achieve better results, leading to improved adherence and behavior in following the guidelines provided by the community pharmacist. Consequently, the effect size may be underestimated, as the performance of the control group can also improve simply by participating in the study. Another limitation of our study is that the participants may not fully represent the general population of type 2 diabetic patients, as they were volunteers for the study. Although we measured all necessary indicators for calculating the UKPDS risk score, including systolic blood pressure, lipid profile, and other cardiovascular parameters, our study primarily focused on HbA1c as the main endpoint, rather than on secondary outcomes. Given the uncertainties surrounding the long-term sustainability of the observed improvements, future research should prioritize the development of effective strategies to ensure the durability of these positive effects. Conclusion This study presents new evidence gathered through a randomized service trial, which highlights the benefits of community pharmacist intervention in the clinical management of patients with type 2 diabetes in collaboration with physicians. One of the key findings of this study is the suggestion of a value for community pharmacists to healthcare payers based on the cost-effectiveness of implementing services for T2DM. Our research indicates that providing these services through community pharmacists remains cost-saving even when the incremental cost is zero. According to our study, for it to be cost-saving, the maximum payment for pharmacists’ services per patient per year would be 927.52 USD, and any lower fee for this service would still result in cost savings for the Iran healthcare system. Based on the published data, in 2023, the prevalence of diabetes in Iran was 13.4%and 85.5% of them are T2DM.( 31 ); This means that in 2024, there will be approximately 10,216,524 individuals with T2DM in the country. Scaling pharmacist-led diabetes care services could yield substantial cost savings for the Iranian healthcare system. Declarations Acknowledgment We express our sincere appreciation to the patients who participated in this study. Funding Statement All the authors declare that no funding has been received for this study. Conflict of Interest The authors have declared that they do not have any conflicts of interest to disclose. Ethical Approval The study was carried out using the principles of good clinical practice and the Declaration of Helsinki. The Shahid Beheshti University of Medical Science's ethics committee approved this service trial study (IR.SMBU.PHARMACY.REC.1400.450). Written informed consent was obtained from each participant. References Williams R, Karuranga S, Malanda B, Saeedi P, Basit A, Besançon S, et al. Global and regional estimates and projections of diabetes-related health expenditure: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2020;162. DeFronzo RA, Ferrannini E, Groop L, Henry RR, Herman WH, Holst JJ, et al. Type 2 diabetes mellitus. Nat Rev Dis Prim [Internet]. 2015;1(July):1–23. Available from: http://dx.doi.org/10.1038/nrdp.2015.19 Onyango EM, Onyango BM. 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The costs of interventions for type 2 diabetes mellitus, hypertension and cardiovascular disease in South Africa – a systematic literature review. BMC Public Health [Internet]. 2022;22(1):1–11. Available from: https://doi.org/10.1186/s12889-022-14730-4 Prevention C of DC and. National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). 2020. Cost of Diabetes in the United States. Available from: https://www.cdc.gov/chronicdisease/programs-impact/pop/diabetes.htm Einarson TR, Acs A, Ludwig C, Panton UH. Economic Burden of Cardiovascular Disease in Type 2 Diabetes: A Systematic Review. Value Heal [Internet]. 2018;21(7):881–90. Available from: http://dx.doi.org/10.1016/j.jval.2017.12.019 Okada H, Onda M, Shoji M, Kotani K, Nakayama T, Nakagawa Y, et al. Effects of Lifestyle Intervention Performed by Community Pharmacists on Glycemic Control in Patients with Type 2 Diabetes: The Community Pharmacists Assist (Compass) Project, a Pragmatic Cluster Randomized Trial. Pharmacol & Pharm. 2016;07(03):124–32. Nima Motamed, Zamani F. sample size in medical and clinical assessments. 1395. 284 p. Mousa R, Hammad E. Cost-effectiveness of pharmacist-led care versus usual care in type 2 diabetic Jordanians: a Markov modeling of cardiovascular diseases prevention. Expert Rev Pharmacoeconomics Outcomes Res [Internet]. 2021;21(5):1069–79. Available from: https://doi.org/10.1080/14737167.2021.1838900 Ameri H, Safari H, Yousefi M, faradonbeh SB, Goudarzi R, Soofi M. Interim value set for the EQ-5D-5L in Iran using the Crosswalk method. Med J Islam Repub Iran. 2020;34:1–5. Daneshmand A, Jahangard E, Abdollah-Milani M. A time preference measure of the social discount rate for Iran. J Econ Struct [Internet]. 2018;7(1). Available from: https://doi.org/10.1186/s40008-018-0127-x Khunti K, Aroda VR. Coming Full Circle: Prioritizing Early Glycemic Control to Reduce Microvascular and Macrovascular Complications in People With Type 2 Diabetes. Diabetes Care. 2022;45(4):766–8. Evans M, Welsh Z, Seibold A. Reductions in HbA1c with Flash Glucose Monitoring Are Sustained for up to 24 Months: A Meta-Analysis of 75 Real-World Observational Studies. Diabetes Ther. 2022;13(6):1175–85. Movahed MS, Barghazan SH, Adel A, Rezapour A. Economic Burden of Stroke in Iran: A Population-Based Study. Value Heal Reg Issues [Internet]. 2021;24:77–81. Available from: https://doi.org/10.1016/j.vhri.2020.04.004 Jalilian H, Heydari S, Imani A, Salimi M, Mir N, Najafipour F. Economic burden of type 2 diabetes in Iran: A cost-of-illness study. Heal Sci Reports. 2023;6(2). Loh P, Chua SS, Karuppannan M. The extent and barriers in providing pharmaceutical care services by community pharmacists in Malaysia: a cross-sectional study. BMC Health Serv Res. 2021;21(1):1–14. Krass I, Hebing R, Mitchell B, Hughes J, Peterson G, Song YJC, et al. Diabetes management in an Australian primary care population. J Clin Pharm Ther [Internet]. 2011 Dec;36(6):664–72. Available from: https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2710.2010.01221.x Garcia-Cardenas V, Armour C, Benrimoj SI, Martinez-Martinez F, Rotta I, Fernandez-Llimos F. Pharmacists’ interventions on clinical asthma outcomes: A systematic review. Eur Respir J [Internet]. 2016;47(4):1134–43. Available from: http://dx.doi.org/10.1183/13993003.01497-2015 Yu J, Shah BM, Ip EJ, Chan J. A markov model of the cost-effectiveness of pharmacist care for diabetes in prevention of cardiovascular diseases: Evidence from kaiser permanente northern california. J Manag Care Pharm. 2013;19(2):102–14. Hayes AJ, Leal J, Gray AM, Holman RR, Clarke PM. UKPDS Outcomes Model 2: A new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year united kingdom prospective diabetes Study: UKPDS 82. Diabetologia. 2013;56(9):1925–33. Breitscheidel L, Stamenitis S, Dippel FW, Schöffski O. Economic impact of compliance to treatment with antidiabetes medication in type 2 diabetes mellitus: A review paper. J Med Econ. 2010;13(1):8–15. Hazar N, Jokar M, Namavari N, Hosseini S, Rahmanian V. An updated systematic review and Meta-analysis of the prevalence of type 2 diabetes in Iran, 1996–2023. Front Public Heal. 2024;12(April):1–15. Table 4, 5, 7 Table 4, 5, 7 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table457.docx Cite Share Download PDF Status: Published Journal Publication published 29 Aug, 2025 Read the published version in Cost Effectiveness and Resource Allocation → Version 1 posted Editorial decision: Revision requested 23 Jun, 2025 Reviews received at journal 22 Jun, 2025 Reviewers agreed at journal 21 Jun, 2025 Reviews received at journal 01 May, 2025 Reviewers agreed at journal 01 May, 2025 Reviewers invited by journal 13 Apr, 2025 Submission checks completed at journal 18 Mar, 2025 First submitted to journal 18 Mar, 2025 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. 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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-5788534","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":442519368,"identity":"ab2d44bb-3fbd-4ed4-8143-ed1ae52d9254","order_by":0,"name":"Zahra Ghasemi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Zahra","middleName":"","lastName":"Ghasemi","suffix":""},{"id":442519369,"identity":"91466100-df50-4f29-aa1b-e46d9fc5cf14","order_by":1,"name":"Rimal Mousa","email":"","orcid":"","institution":"University of Jordan","correspondingAuthor":false,"prefix":"","firstName":"Rimal","middleName":"","lastName":"Mousa","suffix":""},{"id":442519370,"identity":"ba329d79-e8d1-437e-a8f8-f02271edb361","order_by":2,"name":"Farzad Peiravian","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Farzad","middleName":"","lastName":"Peiravian","suffix":""},{"id":442519371,"identity":"319e409e-c669-49b1-a1dd-6005693f10e2","order_by":3,"name":"Nazila Yousefi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYJCCAw/gTBsJOTQRHFoS4Mw0CWM0ERwASQtDYgOqCCYwZz/+8EBCjR2DwfEe4w8fEizS54cdBoow2MnpNmDXYtmTkHAg4Vgyg8GZM2aSMxIkcjfeTjMAakk2NjuAXQtQ9sCBBDZmBoMbOWbMvD+AWmYngLQcSNyGS8v5hw0HEv7Vg7QYf/6TIJFuODv9A34tN5KBsm2HQVoMpBkSJBLkpXMI2HLjGVC27ziP5JljZZI9CRKGG6RzCg4kGODxy/n0xx8+fKuW4zvevPnDj4Q6efnZ6Zs/fKiwk8OlBQZ4FGAKDMAMA/zKwUC+AZ0xCkbBKBgFowAKALC3aAyLdEceAAAAAElFTkSuQmCC","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Nazila","middleName":"","lastName":"Yousefi","suffix":""}],"badges":[],"createdAt":"2025-01-08 11:23:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5788534/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5788534/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12962-025-00651-7","type":"published","date":"2025-08-29T15:58:20+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80790907,"identity":"27a22183-0949-438c-8f76-c8c5cc280bcc","added_by":"auto","created_at":"2025-04-17 06:42:51","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":125991,"visible":true,"origin":"","legend":"\u003cp\u003eMarkov Model of CVD occurrences experienced in patients with T2DM showing the different status of a patient with T2DM.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-5788534/v1/68be4937f1e19d8d66b5d118.png"},{"id":80791529,"identity":"07251c12-a633-4606-a3c8-b40d3fb15aee","added_by":"auto","created_at":"2025-04-17 06:50:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":360616,"visible":true,"origin":"","legend":"\u003cp\u003eCost-effectiveness plan of pharmacist-led care compared to usual care. The calculated ICER revealed that 95.2% of the ICER points were situated in the southeast quadrant, indicating the intervention's dominance.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-5788534/v1/1470ede01e88acab2edfd33d.png"},{"id":80789369,"identity":"dbf4192a-4e40-415e-9263-2adbb49e1f36","added_by":"auto","created_at":"2025-04-17 06:34:51","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":42370,"visible":true,"origin":"","legend":"\u003cp\u003eTornado diagram illustrating the variables influencing cost-effectiveness status. It shows that the cost of community pharmacist services has no impact on the ICER.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5788534/v1/53dc0f77f6924b8f9be2812e.png"},{"id":90345555,"identity":"25bda559-9604-4c6c-925a-ef45d728caac","added_by":"auto","created_at":"2025-09-01 16:10:33","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1141997,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5788534/v1/979dce24-4e13-430d-a536-18e0ab9ce2c9.pdf"},{"id":80789367,"identity":"271df667-ac84-4939-a7f1-c6c181d33351","added_by":"auto","created_at":"2025-04-17 06:34:51","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":54791,"visible":true,"origin":"","legend":"","description":"","filename":"Table457.docx","url":"https://assets-eu.researchsquare.com/files/rs-5788534/v1/a9d914ca0330c8007e4686c4.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Cost-effectiveness analysis of the community pharmacist-based intervention in Type 2 diabetes mellitus a service trial","fulltext":[{"header":"Background","content":"\u003cp\u003eDiabetes mellitus (DM) is one of the most critical metabolic diseases with a rapid growth rate in developed and developing countries.(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). DM is determined by unstable insulin secretion or insulin resistance, leading to impaired carbohydrates, protein, and fat.(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Diabetes is a grave public health problem with an astronomical impact on human life and health expenditures.(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In 2019, diabetes-related health expenditure in adults with a range of 20\u0026ndash;79 years was estimated to be 760\u0026nbsp;billion dollars globally. It is estimated to grow to 825\u0026nbsp;billion dollars each year by 2030(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Type 2 diabetes mellitus (T2DM) is a growing epidemic worldwide, and according to the World Health Organization (WHO) statistics, In 2019, diabetes was the 9th leading cause of death with 1.5\u0026nbsp;million deaths globally. (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs T2DM rapidly grows (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e), its long-term uncontrolled conditions lead to severe micro and macrovascular complications(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), significantly raising morbidity and mortality rates. The management of diabetes and its complications imposes substantial burdens on individuals, families, and society, making it a significant public health and economic concern(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Effective diabetes management through medications is crucial, with pharmacists playing a vital role in ensuring medication quality and safety(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Pharmacists, alongside physicians, provide essential healthcare services that improve HbA1c, fasting blood sugar, and medication adherence, and reduce medication errors and diabetes-related complications(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is limited research on the effectiveness of community pharmacist interventions in diabetes management. Studies by Matthew Lee Smith et al.(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)have shown improvements in HbA1c through pharmacist-led interventions. However, further research is needed to assess the long-term efficacy and economic impact of these interventions, especially in different economic contexts.(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAccording to the WHO, Cardiovascular diseases (CVDs) are the leading cause of death globally, taking an estimated 17.9\u0026nbsp;million lives each year.(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e), which more than 75% take place in nations with low and moderate incomes, and T2DM is a significant modifiable risk factor for cardiovascular diseases. CVD problems can account for as much as 20\u0026ndash;49% of total direct treatment expenditures for type 2 diabetes(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), we pay attention to patients\u0026rsquo; CVD situation as well as diabetes. In the United States, each year \u003cspan\u003e$\u003c/span\u003e237\u0026nbsp;billion is spent on direct medical costs and another \u003cspan\u003e$\u003c/span\u003e90\u0026nbsp;billion on reduced productivity by CVD.(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). In comparison to T2DM patients without CVD, the median yearly expenses for patients with CVD, coronary artery disease, heart failure, and stroke were, respectively, 112%, 107%, 59%, and 322% higher in comparison with those with T2DM.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Therefore, effective CVD preventive interventions can lower a significant amount of the burden of T2DM that may be related to cardiovascular problems. Literature shows that based on global trends, patients with diabetes have a 10-year risk of CVD, which increases the disease burden on communities.\u003c/p\u003e \u003cp\u003eCommunity pharmacist-based interventions are safe and essential for enhancing public health outcomes in Iran. These interventions can significantly improve medication adherence, manage chronic diseases, and provide accessible healthcare advice. However, several challenges need to be addressed: challenges such as regulatory hurdles, resource allocation, public awareness, collaboration with healthcare providers, and providing more research and evidence to demonstrate the effectiveness and cost-efficiency of pharmacist interventions, thereby supporting policy changes.\u003c/p\u003e \u003cp\u003eConsidering the significant absence of cost-effectiveness data for pharmacist-led interventions in Iran, this study seeks to address this critical gap by evaluating both clinical and economic outcomes.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eStudy design\u003c/p\u003e \u003cp\u003eThis study was conducted over 12 months, as a randomized, controlled, parallel-group service trial at one community pharmacy in Tehran, the capital city of Iran. One trained pharmacist was selected to gather the participants and service providing. In the initial stages of the study, it was essential to establish and standardize the services provided by community pharmacists, as the current scope of practice is limited to dispensing prescriptions and over-the-counter medications. Standardization of the service had been conducted using the published guidelines by the International Diabetes Federation and the Gabric Diabetes Education Association in Iran. After extracting the exact type of service from the mentioned guidances, two key opinion leaders of endocrinologies validated the service and trained the community pharmacist informing her how to implement the service for patients.\u003c/p\u003e \u003cp\u003eEthical Code\u003c/p\u003e \u003cp\u003e The study was carried out using the principles of good clinical practice and the Declaration of Helsinki. The Shahid Beheshti University of Medical Science's ethics committee approved this clinical study (IR.SMBU.PHARMACY.REC.1400.450). Written informed consent was obtained from each participant.\u003c/p\u003e \u003cp\u003eRandomization Process\u003c/p\u003e \u003cp\u003eThe randomization process was applied at the pharmacy level. The participants were sequentially and randomly assigned to control and intervention groups by the pharmacist considering inclusion and exclusion criteria.\u003c/p\u003e \u003cp\u003ePatients receiving oral hypoglycemic medication for at least 6 months, patients between 20 and 80 years old, old, and HbA1c\u0026thinsp;\u0026ge;\u0026thinsp;8% for more than 3 months and have at least one underlying disease than T2DM enrolled in this study.\u003c/p\u003e \u003cp\u003eBeing on insulin treatment, and under 20 years old, patients with cognitive disorders, patients with pregnancy diabetes, and patients with T1DM were the exclusionary factor.\u003c/p\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003cp\u003eBased on H. Okada's 2016 randomized controlled trial assessing community pharmacists' interventions, the effect size, standard deviation, and drop-out rate were extracted to calculate the number of patients needed. Studies emphasize a 0.5% reduction in HbA1c levels in T2D patients as the effect size.(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Consequently, a 0.5% reduction was considered for our intervention group. The required sample size was 55 per group, accounting for a 15% drop-out rate, with a type 1 error of 5% and 90% power at a two-tailed 5% significance level.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e):\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;2 (Z[1-α/2]\u0026thinsp;+\u0026thinsp;Z [1-β])2 \u0026times; SD2 /d2\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\u003efactors for calculating the sample size of the service trial\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=\"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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResult\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo. of parameters\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eeffect size (HbA1c%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStandard Deviation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20.995\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2*(zα\u0026thinsp;+\u0026thinsp;z[1-β])\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSD\u003csup\u003e2\u003c/sup\u003e/d\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo. patients in each group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDropout rate (15%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\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\u003eRecruitment process\u003c/p\u003e \u003cp\u003eThis study was conducted by one trained community pharmacist in the pharmacy consultation room and a 6-month periodic monitoring phase. Potentially eligible patients, according to the inclusion and exclusion criteria, were recruited by the community pharmacy between October 2021 and October 2022. According to the reviewed literature evaluated the same goal as our study and reference to the necessary inputs for the UKPDS model, primary and secondary outcomes of this study were extracted as shown in 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\u003ePrimary and Secondary outcomes of the study\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary outcomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eInterval of assessment\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHb A1c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvery 3 months\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvery month\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEQ-5D-5L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEvery month\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNo.\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSecondary outcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eInterval of assessment\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSBP \u0026amp; DBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEvery month\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeight and BMI\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLipid Profile: LDL, HDL,\u0026nbsp;Tg and Cholesterol\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBUN \u0026amp; Cr\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 intervention design was based on the below components and provided to the intervention group:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePatient education about T2DM and its complications.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePatient education about the proper use of oral hypoglycemic medications (timing about food) and other medications.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eFacilitation of medication adherence (by counseling)\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003ePatient education about leading a healthy lifestyle (diet, exercise, and quitting smoking).\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eReminders about the timing of the pharmacist\u0026rsquo;s visit during the next intervals.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003cp\u003eAll services provided by community pharmacists are conducted within safe and defined parameters, strictly adhering to the mentioned components. These services exclude any form of invasive intervention or alterations to prescribed medications, as suggested by the pharmacist\u003c/p\u003e \u003cp\u003eThe pharmacist, who graduated from one of the Pharmacy Schools in Iran, only received a free consultation from two endocrinologists to be sure about the lifestyle modifications in T2DM patients and the appropriate consultation for the patients, applied all protocol components to every patient in the intervention group and patients in the control group received standard pharmacy care as usual (only dispensing their medication prescription). At the beginning of the study and in every 3-month intervals, patients in both groups were measured for the parameters listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. All the patients in both the intervention and control groups were followed up by the pharmacist by telephone call to arrange the in-person visits.\u003c/p\u003e \u003cp\u003eInitial Visit\u003c/p\u003e \u003cp\u003eIn the first phase, each patient had a 30-minute initial visit where the community pharmacist carefully reviewed their medical, and medication history and the necessary parameters for measurement listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The community pharmacist also assessed the patient's knowledge and health behavior, focusing on adherence to current medication therapy, diet, smoking behavior alcohol consumption, and exercise regimen. Additionally, the community pharmacist answered any questions the patients may had about the study to set one long-term health goal and three short-term, measurable management goals by the community pharmacist. Patients were informed that their clinical values would be gathered in two different ways.\u003c/p\u003e \u003cp\u003eThe pharmacy collaborated with the nearest laboratory to provide support for patients to obtain monthly blood tests for FBS, 2-hpp, lipid profile, BUN, and Creatinine assessments. Every 3 months, patients undergo HbA1c testing, as well as SBP, DBP, weight measurements, BMI calculations, and completion of the EQ-5D-5L questionnaire by the community pharmacist during each visit.\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\u003eList of demographic and clinical parameters of the patients\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParameter\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003emeasurement unit\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eName of Pt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eID cart\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSex\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM/ F\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRace\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIranian or non-Iranian\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDate of birth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eDD/MM/YY\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCm\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eKg/ cm2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eList of current medicines in use\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBased on prescriptions\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eT2DM duration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMonths or years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamily history of T2DM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient's statement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHbA1c level in the\u0026nbsp;past 3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercentage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFBS and 2-hpp (entry phase)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emg/ dl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLipid profile\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emg/ dl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCreatinin level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emg/ dl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBUN level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emg/ dl\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSBP \u0026amp; DBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emmHg\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCigarette \u0026amp; Alcohol consumption\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient's statement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAtrial fibrillation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePatient's statement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeuropathy complications of DM: numbness or wounds in feet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePatient's statement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNephropathy complications of DM\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRetinopathy complications of DM: any changes in visual status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQuality of Life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEQ-5D-5L questionnaire and VAS index\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\u003eOngoing Visits\u003c/p\u003e \u003cp\u003eDuring each follow-up visit, the community pharmacist collected and assessed the patient\u0026rsquo;s disease status, medications, and study outcomes. All the data gathered from the patients were documented individually in Excel sheets. Before each visit, the pharmacist called the patients. If there was no answer, she tried to reach them through messages to ensure their availability for the next in-person visit. Patients were incentivized with free e-prescriptions to do the laboratories, free consultation, and health assessment by community pharmacists, and also one thermometer from the pharmacy.\u003c/p\u003e \u003cp\u003eShort-term data analysis:\u003c/p\u003e \u003cp\u003eShort-term data, including HbA1c, LDL, HDL-C, and SBP, are necessary outcomes for the UKPDS risk score model, affecting cardiovascular disease risks (Table\u0026nbsp;4). The collected data were subsequently evaluated for normality using the One-sample Kolmogorov-Smirnov Test (SPSS Statistics 27.0.1). Additionally, an Independent T-Test was conducted to assess the differences between groups.\u003c/p\u003e \u003cp\u003eLong-term data analysis using Markov modeling\u003c/p\u003e \u003cp\u003eA Markov model with a one-year cycle length and a 10-year time horizon was developed to simulate long-term CVD events, death risk, and related expenditures for two groups of intervention and control group of Iranian patients with participation in this study. Patients in the intervention group were those who received standardized diabetes care services from a community pharmacist and patients in the control group received their routine pharmacy services. The study model illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Based on the study conducted by Mousa et alin 2021 in Jordan. In this model the Individuals with T2DM were initially included in the model in the \"well\" state, meaning they had not previously experienced any cardiovascular events.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThroughout the 10-year simulation, individuals might age without experiencing any CVD events, experience a first-ever CVD event (fatal or nonfatal), experience a subsequent CHD, or stroke, or pass away from CVD events or non-cardiovascular causes. Individuals who underwent a primary myocardial infarction (i.e., nonfatal) could continue to be in this condition of health until they died from a fatal myocardial infarction stroke, or any other reason. (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). The United Kingdom Prospective Diabetes Study (UKPDS) Risk Engine (version 2) was used to estimate the CVD risks as the Markov model inputs. In this study, all the necessary inputs for the calculation of the risks including the patient's age at diagnosis state, gender, ethnicity, smoking status, arrhythmia, length of diabetes, systolic blood pressure (SBP), total cholesterol (TC), and high-density lipoprotein cholesterol (HDL-C) levels were gathered from the baseline and at the follow-ups visits.\u003c/p\u003e \u003cp\u003eTransition probabilities. We estimated the transition probabilities of the Markov model (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) based on several CVD events using the UKPDS Risk Engine Version 02: absolute risk of stroke and CHD, both fatal and nonfatal. The final calculated probabilities have been validated by R. Mousa, an expert in the cost-effectiveness of the pharmacist\u0026rsquo;s services. The observed impacts of A1c, SBP, TC, and HDL-C, together with other patient-specific factors, were translated into the estimated 10-year risks for CHD events and stroke using the prediction algorithm in this Risk Engine.\u003c/p\u003e \u003cp\u003eConsequently, the calculated risks were converted to transition probabilities using the following equation:\u003c/p\u003e \u003cp\u003eR= - [ln (1-p)]/t\u003c/p\u003e \u003cp\u003eUtility Measures. Patients were enrolled in this study based on their utility score of each health state in the Markov model that was taken from extracted measures of the EQ-5D-5L questionnaire and using the interim national value set of them for the Iran population. (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). According to this value set, a score of 0 denotes death, and a value of 1 indicates complete health. Both branches were subject to a 5% discount rate for final health outcomes after the first year. (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe utility of each state was taken from the conducted study by R. Mousa in 2020 for measuring the cost-effectiveness of pharmacist-led care in T2DM patients in Jordan.(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Then the final cost-effectiveness analysis was conducted by Excel 2021.\u003c/p\u003e \u003cp\u003eTornado Diagram. To identify the primary factors influencing cost-effectiveness outcomes, we will conduct a sensitivity analysis by systematically varying one parameter at a time while maintaining the others constant. Additionally, we will construct a diagram to visually depict the impact of each parameter's variation on the final result, thereby demonstrating the robustness of our findings.\u003c/p\u003e \u003cp\u003eProbabilistic Sensitivity Analysis (PSA). To thoroughly assess uncertainty, we incorporated probability distributions for each variable, enabling us to provide confidence intervals for the ICER. This elucidates the range within which the true value of the ICER is likely to reside. Additionally, we generated a cost-effectiveness plane to visualize the distribution of the results across each quadrant.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eOne of the patients from the intervention group lost to follow-up, due to a major diabetic wound, and two patients due to unwillingness to study proceeding. One of the patients in the control group was dead due to major cardiovascular diabetic complications. In the end, the number of patients in the intervention group reached 52 participants, and for the control group 54.\u003c/p\u003e \u003cp\u003eThe main primary outcomes, HbA1c together with secondary outcomes including LDL, HDL, and SBP of the patients are shown in Table\u0026nbsp;4. Pharmacists\u0026rsquo; intervention showed better improvement in the main primary outcomes, mainly, a decrease in average HbA1c level was higher in the intervention group (base: 8.47 vs. month-12: 8.45) compared to the control group (base: 8.64 vs. month-12: 8.88).\u003c/p\u003e \u003cp\u003eShort-term data analysis:\u003c/p\u003e \u003cp\u003eShort-term data, including HbA1c, LDL, HDL-C, and SBP, are necessary outcomes for the UKPDS risk score model, affecting cardiovascular disease risks (Table\u0026nbsp;4).\u003c/p\u003e \u003cp\u003eFollowing a 12-month study, patients in the intervention group displayed a significant reduction in their HbA1c levels during each assessment (p-value\u0026thinsp;=\u0026thinsp;0.009; from 8.47 at the baseline to 8.45 at the end). Conversely, patients in the control group saw an increase in their HbA1c levels (from 8.64 at the baseline to 8.88 at the end).\u003c/p\u003e \u003cp\u003eOur study showed that the community pharmacist made a statistically significant improvement in improving the HDL-C profile of patients in the intervention group during each assessment (p-value\u0026thinsp;=\u0026thinsp;0.016). The HDL-C levels decreased from 1.31 at the baseline to 1.13 at the end, while patients in the control group experienced a decrease from 1.17 at the baseline to 1.04 at the end. In terms of LDL, a major risk factor for cardiovascular disease, the community pharmacist intervention had a statistically significant reduction in its level (p-value\u0026thinsp;=\u0026thinsp;0.05; from 4.25 at the baseline to 3.37 at the end). However, it had no significant impact on patients in the control group, as their LDL levels went from 3.97 at the baseline to 3.93 at the end.\u003c/p\u003e \u003cp\u003eIn the intervention group, the SBP of the patients showed a statistically significant improvement from the community pharmacist standard care, with a significant decrease from 134.55 at the beginning to 133.85 at the end (p-value\u0026thinsp;=\u0026thinsp;0.003). Conversely, the control group experienced increased SBP levels, rising from 136.79 at the baseline to 140.46 at the end.\u003c/p\u003e \u003cp\u003e Table 4-Clinical inputs of the study patients, at baseline, 6 months, and 12 months after study initiation\u003c/p\u003e \u003cp\u003eThe pharmacists\u0026rsquo; intervention showed a slight improvement in the primary outcome of HbA1c levels, with a decrease from 8.47 to 8.45. Although this change is minor and may not appear clinically significant at first glance, it is important to consider the broader context. Even small reductions in HbA1c can lead to better long-term glycemic control and potentially reduce the risk of diabetes-related complications(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Moreover, the intervention's consistency and sustainability over 12 months indicate its potential effectiveness and utility in managing T2DM patients. Therefore, while the immediate change in HbA1c is modest, the intervention's overall impact on patient care and management strategies can be considered clinically meaningful.\u003c/p\u003e \u003cp\u003eClinical inputs for CVD risk prediction. Determining the clinical inputs for calculating and predicting risks of CVD events was conducted using the UKPDS guidance. By applying the UKPDS guidance, the clinical inputs for estimating the risks of CVD events were determined. The UKPDS risk score engine was used to estimate the CVD risks for the patients who were enrolled in the control and intervention groups for 10 years. The results are displayed in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFollowing 12 months of observation, the intervention group's estimated risks for CHD and stroke\u0026mdash;both nonfatal and fatal\u0026mdash;were lower than those of received routine care. Throughout each group's ten-year course, the annual risk increased as predicted for the aging patients. Furthermore, over time, there was an increase in the absolute risk reduction (ARR) between the control and intervention groups.\u003c/p\u003e \u003cdiv\u003e\n \u003ctable id=\"Tab4\" border=\"1\"\u003e\u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eCost inputs and utilization of medical resources. To demonstrate the cost-effectiveness of the implemented service to healthcare system policymakers, the study was conducted from the healthcare system's perspective, leading us to utilize direct medical costs. The cost inputs used in the model were the healthcare provider's direct medical costs obtained from the study conducted by Bayazidi et al. (19, 23, 24). Annual medication costs per patient were calculated based on the national guidelines published for CHD management and available works of literature. Based on the time preference measure of the social discount rate for Iran, a discount rate of 5.8% was applied for the costs based on national evidence. (20) and shown in Table 6.\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab5\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eCost and Utility of each Markov states\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHealth State\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCost\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLower limit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eUpper limit\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eState Utility\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWell- Intervention\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$ 1,979\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 395.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 2,374.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.810\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWell- Control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$ 4,279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 855.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 5,134.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$ 2,185\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 437.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 2,622.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.645\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary Stroke\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$ 4,936\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 987.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 5,923.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.556\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary CHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$ 3,828\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 765.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 4,593.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.725\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSecondary CHD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e$ 11,533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 2,306.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e$ 13,839.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.684\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eThe model calculated the predicted survival for both the control and intervention groups of patients based on the total amount of time they spent in each health state. To calculate the costs and life years gained (LYGs) for each cycle, relevant costs were allocated to each health state in the Markov model, weighted by the transition probability, and then totaled over all the health states. The aggregated costs and LYGs were then determined by adding the mean costs and LYGs for each of the ten annual cycles. The main outcome of the model was determining the incremental cost-effectiveness ratio (ICER) by dividing the cost differences by the LYG differences of both groups.\u003c/p\u003e\n\u003cp\u003eThe cost-effectiveness (CE) threshold by the pharmacoeconomics committee of the Iranian Food and Drug Administration (IFDA) representing the willingness-to-pay (WTP) value of 700,000,000 Iranian Rials (IRR) (equal to 2,456 USD) was considered as the CE threshold of this study. The Exchange rate of IRR to USD (in the year of study, 2021) was 285,000 IRR.\u003c/p\u003e\n\u003cp\u003eBase-case analysis\u003c/p\u003e\n\u003cp\u003eAccording to calculations conducted using each patient's costs and outcomes, it is shown that pharmacists' interventions in T2DM patients resulted in a cost of -1469.02 USD with 0.045 LYGs compared to the control group (Table 7).\u003c/p\u003e\n\u003cp\u003eProbabilistic sensitivity analysis (PSA) analysis\u003c/p\u003e\n\u003cp\u003eThe PSA analysis, like the base-case analysis, revealed that the interventions of the pharmacists resulted in additional LYGs and less cost for the intervention group in comparison with the control one. The cost-effectiveness plane (Fig. 2) which was run for 1,000 individuals showing the distribution of 95.2% of ICER points in the southeast quadrant indicated that the intervention is dominant.\u003c/p\u003e\n\u003cp\u003eThe southeast quadrant in the cost-effectiveness plane represents the most favorable outcome, as it signifies interventions that deliver superior effectiveness at a lower cost relative to the standard treatment. Within this quadrant, the intervention not only enhances health outcomes but also achieves cost savings, rendering it the optimal choice from both clinical and economic perspectives.\u003c/p\u003e\n\u003cp\u003eTornado diagram\u003c/p\u003e\n\u003cp\u003eTo show how sensitive different variables are to change the final result of our study, helping stakeholders prioritize their focus a tornado diagram of all the variables was drawn (Fig. 3)\u003c/p\u003e\n\u003cp\u003eThese findings suggest that the cost of renal failure has a significant impact on the calculated ICER, while the cost of services provided by community pharmacists does not affect ICER.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, we pursued a novel economic study to know if implementing services by community pharmacists for T2DM patients is cost-effective. Iran as a low-middle-income country located in the Middle East region lacked any specific services provided by community pharmacists.\u003c/p\u003e \u003cp\u003eSeveral factors contribute to the lack of standard care services in community pharmacies in Iran. These include the lack of public awareness that such services may be available at community pharmacies, the lack of acceptance by physicians that trained community pharmacists are eligible to provide medication regimens, and the lack of government initiatives to include the services provided by community pharmacists in insurance coverage (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Studies from countries like Australia and Canada have demonstrated the effectiveness of pharmacist-led diabetes management programs. For example, Hughes et al. showed how pharmacists in Australia significantly improved patients\u0026rsquo; glycemic control and medication adherence, leading to reduced healthcare costs(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Garcia-Cardenas et al. conducted a study in Canada in 2016 and revealed that pharmacists\u0026rsquo; involvement in diabetes care resulted in better blood sugar control and patient satisfaction, emphasizing their role as essential healthcare providers(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe effectiveness of a variety of services offered by community pharmacists has been extensively researched in numerous countries. However, in Iran, there is a significant gap in the evaluation of these studies. One key finding of this study was that we analyzed over 200 articles that focused on the services provided by community pharmacists, and we selected 183 of them. Among these, it was found that diabetes-related services were the most researched area in which community pharmacists could add value.\u003c/p\u003e \u003cp\u003eThe current cost-effectiveness studies have a significant gap when it comes to demonstrating the limits of cost-effectiveness. Most studies only focus on determining whether a specific service is cost-effective to implement. However, none of them have looked into providing a service package to healthcare providers to request insurance coverage. According to the result provided in our study, the modest change in HbA1c from 8.47 to 8.45 over 12 months may appear minimal, but even slight reductions can lead to significant clinical benefits, such as reduced risks for complications in T2DM patients. Factors like patient baseline levels, short duration of study, and real-world application complexities could contribute to the modest change. Despite this, the intervention's consistency over 12 months highlights its potential for sustainable glycemic control, underscoring the clinical meaningfulness of our findings.\u003c/p\u003e \u003cp\u003eOur study in line with several global studies showed that adding pharmacists to diabetic care, mainly T2DM decreases the long-term risks of cardiovascular diseases.(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). In addition, Similar to our results, the study conducted by Siaw MYL showed that by implementing community pharmacist care for T2DM patients the estimated discounted cost savings per patient over 10 years was 1709.95 USD (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e In a similar context, Rimal M. et al conducted a study that focused on demonstrating the cost-effectiveness of pharmacist-led care services in reducing the 10-year CVD risks in Jordanian patients with T2DM. They found that standard care services would generate 0.3 LYG with an additional cost of 1,747.24 USD(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo integrate pharmacists into healthcare systems, policy changes are necessary; findings of Leal et al. in 2013 suggest that revising insurance coverage to include pharmacist services not only encourages healthcare providers to collaborate but also makes these services accessible to patients, especially in low- and middle-income countries(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main result of our study, which sets it apart from other studies in this era, is that it demonstrated the limit of cost-effectiveness of providing T2DM services by community pharmacists which is still novel among published studies worldwide. Moreover, our study found that the pharmacist program improved patients' knowledge of diabetes, self-care activities, and their awareness regarding the importance of lifestyle modifications. Intensive patient-pharmacist contact and regular glucose self-measurements contribute to the brilliant achievements in T2DM disease control. To our knowledge, this is the first service trial accompanied by the economic evolution of pharmacists\u0026rsquo; T2DM services. However, more long-run multi-center studies are needed to determine how clinical improvements can be maintained over time. Even though all the patients included in the study were already on pharmacotherapy for one year or more, our program was still beneficial to them. We would expect it to have an even greater impact on patients with treatment-resistant diabetes, as they have a higher need for information and education. Another long-term sustainability of the community pharmacist-based intervention will be achieved by enhancing the training of pharmacists to ensure they are well-equipped with the latest knowledge and skills in diabetes management, Increase public awareness about the role of pharmacists in diabetes care through community outreach programs, social media campaigns, and collaboration with healthcare providers, Integrate pharmacist services into primary healthcare settings to ensure a holistic approach to diabetes management and conduct ongoing research and evaluation to assess the effectiveness and cost-effectiveness of pharmacist-led interventions.\u003c/p\u003e \u003cp\u003eStudy limitations:\u003c/p\u003e \u003cp\u003eIt is important to acknowledge that our investigation, like all experiments, has certain limitations. Firstly, the use of a single community pharmacist constrains our ability to generalize the findings to a broader population. Secondly, the observed effectiveness of the intervention group may have been influenced by the Hawthorne effect, whereby participants alter their behavior in response to being observed(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e Furthermore, in a service trial such as an RCT, patients in the intervention group are often motivated to achieve better results, leading to improved adherence and behavior in following the guidelines provided by the community pharmacist. Consequently, the effect size may be underestimated, as the performance of the control group can also improve simply by participating in the study. Another limitation of our study is that the participants may not fully represent the general population of type 2 diabetic patients, as they were volunteers for the study.\u003c/p\u003e \u003cp\u003eAlthough we measured all necessary indicators for calculating the UKPDS risk score, including systolic blood pressure, lipid profile, and other cardiovascular parameters, our study primarily focused on HbA1c as the main endpoint, rather than on secondary outcomes.\u003c/p\u003e \u003cp\u003eGiven the uncertainties surrounding the long-term sustainability of the observed improvements, future research should prioritize the development of effective strategies to ensure the durability of these positive effects.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study presents new evidence gathered through a randomized service trial, which highlights the benefits of community pharmacist intervention in the clinical management of patients with type 2 diabetes in collaboration with physicians. One of the key findings of this study is the suggestion of a value for community pharmacists to healthcare payers based on the cost-effectiveness of implementing services for T2DM. Our research indicates that providing these services through community pharmacists remains cost-saving even when the incremental cost is zero. According to our study, for it to be cost-saving, the maximum payment for pharmacists\u0026rsquo; services per patient per year would be 927.52 USD, and any lower fee for this service would still result in cost savings for the Iran healthcare system. Based on the published data, in 2023, the prevalence of diabetes in Iran was 13.4%and 85.5% of them are T2DM.(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e); This means that in 2024, there will be approximately 10,216,524 individuals with T2DM in the country. Scaling pharmacist-led diabetes care services could yield substantial cost savings for the Iranian healthcare system.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe express our sincere appreciation to the patients who participated in this study.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFunding Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the authors declare that no funding has been received for this study. \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that they do not have any conflicts of interest to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was carried out using the principles of good clinical practice and the Declaration of Helsinki. The Shahid Beheshti University of Medical Science\u0026apos;s ethics committee approved this service trial study (IR.SMBU.PHARMACY.REC.1400.450). Written informed consent was obtained from each participant.\u0026nbsp;\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWilliams R, Karuranga S, Malanda B, Saeedi P, Basit A, Besan\u0026ccedil;on S, et al. Global and regional estimates and projections of diabetes-related health expenditure: Results from the International Diabetes Federation Diabetes Atlas, 9th edition. Diabetes Res Clin Pract. 2020;162. \u003c/li\u003e\n\u003cli\u003eDeFronzo RA, Ferrannini E, Groop L, Henry RR, Herman WH, Holst JJ, et al. Type 2 diabetes mellitus. Nat Rev Dis Prim [Internet]. 2015;1(July):1\u0026ndash;23. Available from: http://dx.doi.org/10.1038/nrdp.2015.19\u003c/li\u003e\n\u003cli\u003eOnyango EM, Onyango BM. The rise of noncommunicable diseases in Kenya: An examination of the time trends and contribution of the changes in diet and physical inactivity. J Epidemiol Glob Health. 2018;8(1\u0026ndash;2):1\u0026ndash;7. \u003c/li\u003e\n\u003cli\u003eReport W. Diabetes. 2021;(November):1\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eBeckman J. IDF Diabetes Atlas. Vol. 76, Offshore. 2016. 1 p. \u003c/li\u003e\n\u003cli\u003ePousinho S, Morgado M, Falc\u0026atilde;o A, Alves G. Pharmacist interventions in the management of type 2 diabetes mellitus: A systematic review of randomized controlled trials. J Manag Care Spec Pharm. 2016;22(5):493\u0026ndash;515. \u003c/li\u003e\n\u003cli\u003eBrewster S, Holt R, Portlock J, Price H. The role of community pharmacists and their position in the delivery of diabetes care: An update for medical professionals. Postgrad Med J. 2020;96(1138):473\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eClifford S, Garfield S, Eliasson L, Barber N. Medication adherence and community pharmacy: A review of education, policy and research in England. Pharm Pract (Granada). 2010;8(2):77\u0026ndash;88. \u003c/li\u003e\n\u003cli\u003eErku DA, Belachew SA, Mekuria AB, Taye Haile K, Gebresillassie BM, Tegegn HG, et al. The role of community pharmacists in patient counseling and health education: a survey of their knowledge and level of involvement in relation to type 2 diabetes mellitus. Integr Pharm Res Pract. 2017;Volume 6:137\u0026ndash;43. \u003c/li\u003e\n\u003cli\u003eSiaw MYL, Malone DC, Ko Y, Lee JYC. Cost-effectiveness of multidisciplinary collaborative care versus usual care in the management of high-risk patients with diabetes in Singapore: Short-term results from a randomized controlled trial. J Clin Pharm Ther. 2018;43(6):775\u0026ndash;83. \u003c/li\u003e\n\u003cli\u003eWu WC, Taveira TH, Jeffery S, Jiang L, Tokuda L, Musial J, et al. Costs and effectiveness of pharmacist-led group medical visits for type-2 diabetes: A multi-center randomized controlled trial. PLoS One. 2018;13(4):1\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eWorld Health Organization. WHO, Cardiovascular diseases [Internet]. 2022. Available from: https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1\u003c/li\u003e\n\u003cli\u003eMasuku SD, Lekodeba N, Meyer-Rath G. The costs of interventions for type 2 diabetes mellitus, hypertension and cardiovascular disease in South Africa \u0026ndash; a systematic literature review. BMC Public Health [Internet]. 2022;22(1):1\u0026ndash;11. Available from: https://doi.org/10.1186/s12889-022-14730-4\u003c/li\u003e\n\u003cli\u003ePrevention C of DC and. National Center for Chronic Disease Prevention and Health Promotion (NCCDPHP). 2020. Cost of Diabetes in the United States. Available from: https://www.cdc.gov/chronicdisease/programs-impact/pop/diabetes.htm\u003c/li\u003e\n\u003cli\u003eEinarson TR, Acs A, Ludwig C, Panton UH. Economic Burden of Cardiovascular Disease in Type 2 Diabetes: A Systematic Review. Value Heal [Internet]. 2018;21(7):881\u0026ndash;90. Available from: http://dx.doi.org/10.1016/j.jval.2017.12.019\u003c/li\u003e\n\u003cli\u003eOkada H, Onda M, Shoji M, Kotani K, Nakayama T, Nakagawa Y, et al. Effects of Lifestyle Intervention Performed by Community Pharmacists on Glycemic Control in Patients with Type 2 Diabetes: The Community Pharmacists Assist (Compass) Project, a Pragmatic Cluster Randomized Trial. Pharmacol \u0026amp;amp; Pharm. 2016;07(03):124\u0026ndash;32. \u003c/li\u003e\n\u003cli\u003eNima Motamed, Zamani F. sample size in medical and clinical assessments. 1395. 284 p. \u003c/li\u003e\n\u003cli\u003eMousa R, Hammad E. Cost-effectiveness of pharmacist-led care versus usual care in type 2 diabetic Jordanians: a Markov modeling of cardiovascular diseases prevention. Expert Rev Pharmacoeconomics Outcomes Res [Internet]. 2021;21(5):1069\u0026ndash;79. Available from: https://doi.org/10.1080/14737167.2021.1838900\u003c/li\u003e\n\u003cli\u003eAmeri H, Safari H, Yousefi M, faradonbeh SB, Goudarzi R, Soofi M. Interim value set for the EQ-5D-5L in Iran using the Crosswalk method. Med J Islam Repub Iran. 2020;34:1\u0026ndash;5. \u003c/li\u003e\n\u003cli\u003eDaneshmand A, Jahangard E, Abdollah-Milani M. A time preference measure of the social discount rate for Iran. J Econ Struct [Internet]. 2018;7(1). Available from: https://doi.org/10.1186/s40008-018-0127-x\u003c/li\u003e\n\u003cli\u003eKhunti K, Aroda VR. Coming Full Circle: Prioritizing Early Glycemic Control to Reduce Microvascular and Macrovascular Complications in People With Type 2 Diabetes. Diabetes Care. 2022;45(4):766\u0026ndash;8. \u003c/li\u003e\n\u003cli\u003eEvans M, Welsh Z, Seibold A. Reductions in HbA1c with Flash Glucose Monitoring Are Sustained for up to 24 Months: A Meta-Analysis of 75 Real-World Observational Studies. Diabetes Ther. 2022;13(6):1175\u0026ndash;85. \u003c/li\u003e\n\u003cli\u003eMovahed MS, Barghazan SH, Adel A, Rezapour A. Economic Burden of Stroke in Iran: A Population-Based Study. Value Heal Reg Issues [Internet]. 2021;24:77\u0026ndash;81. Available from: https://doi.org/10.1016/j.vhri.2020.04.004\u003c/li\u003e\n\u003cli\u003eJalilian H, Heydari S, Imani A, Salimi M, Mir N, Najafipour F. Economic burden of type 2 diabetes in Iran: A cost-of-illness study. Heal Sci Reports. 2023;6(2). \u003c/li\u003e\n\u003cli\u003eLoh P, Chua SS, Karuppannan M. The extent and barriers in providing pharmaceutical care services by community pharmacists in Malaysia: a cross-sectional study. BMC Health Serv Res. 2021;21(1):1\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eKrass I, Hebing R, Mitchell B, Hughes J, Peterson G, Song YJC, et al. Diabetes management in an Australian primary care population. J Clin Pharm Ther [Internet]. 2011 Dec;36(6):664\u0026ndash;72. Available from: https://onlinelibrary.wiley.com/doi/10.1111/j.1365-2710.2010.01221.x\u003c/li\u003e\n\u003cli\u003eGarcia-Cardenas V, Armour C, Benrimoj SI, Martinez-Martinez F, Rotta I, Fernandez-Llimos F. Pharmacists\u0026rsquo; interventions on clinical asthma outcomes: A systematic review. Eur Respir J [Internet]. 2016;47(4):1134\u0026ndash;43. Available from: http://dx.doi.org/10.1183/13993003.01497-2015\u003c/li\u003e\n\u003cli\u003eYu J, Shah BM, Ip EJ, Chan J. A markov model of the cost-effectiveness of pharmacist care for diabetes in prevention of cardiovascular diseases: Evidence from kaiser permanente northern california. J Manag Care Pharm. 2013;19(2):102\u0026ndash;14. \u003c/li\u003e\n\u003cli\u003eHayes AJ, Leal J, Gray AM, Holman RR, Clarke PM. UKPDS Outcomes Model 2: A new version of a model to simulate lifetime health outcomes of patients with type 2 diabetes mellitus using data from the 30 year united kingdom prospective diabetes Study: UKPDS 82. Diabetologia. 2013;56(9):1925\u0026ndash;33. \u003c/li\u003e\n\u003cli\u003eBreitscheidel L, Stamenitis S, Dippel FW, Sch\u0026ouml;ffski O. Economic impact of compliance to treatment with antidiabetes medication in type 2 diabetes mellitus: A review paper. J Med Econ. 2010;13(1):8\u0026ndash;15. \u003c/li\u003e\n\u003cli\u003eHazar N, Jokar M, Namavari N, Hosseini S, Rahmanian V. An updated systematic review and Meta-analysis of the prevalence of type 2 diabetes in Iran, 1996\u0026ndash;2023. Front Public Heal. 2024;12(April):1\u0026ndash;15. \u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table 4, 5, 7","content":"\u003cp\u003eTable 4, 5, 7 are available in the Supplementary Files section.\u003c/p\u003e\n"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"cost-effectiveness-and-resource-allocation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cera","sideBox":"Learn more about [Cost Effectiveness and Resource Allocation](http://resource-allocation.biomedcentral.com)","snPcode":"12962","submissionUrl":"https://submission.nature.com/new-submission/12962/3","title":"Cost Effectiveness and Resource Allocation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"diabetes care, pharmaceutical care, randomized service trial, type 2 diabetes mellitus, UKPDS risk score, cost-effectiveness analysis, community pharmacy","lastPublishedDoi":"10.21203/rs.3.rs-5788534/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5788534/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eStudies have shown that managing type 2 diabetes mellitus by community pharmacists improves clinical outcomes such as hemoglobin A1c, controls blood pressure and total cholesterol, and reduces the risk of cardiovascular disease.\u003c/p\u003e\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eSince there are no well-designed randomized service trials to assess the impact of community pharmacist intervention on the improvement of T2DM management in Iran, we aimed to (a) determine the long-term effects, (b) evaluate the cost-effectiveness of care provided to T2DM patients, and (c) help policymakers to value these services.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn a 12-month trial at a community pharmacy, 55 patients received usual care, while another 55 received a diabetes management protocol from the pharmacist. The pharmacist focused on correcting medication use, lifestyle modification, and improving diet. The technical aspects of economic evaluation contained conducting the study from the healthcare system perspective, a 10-year time horizon was chosen to assess the long-term effects and cost savings. Direct medical costs included the costs of medications, lab tests, and physician visits. Intervention costs covered pharmacist time, patient education materials, and glucose monitoring supplies. The primary outcome was the change in HbA1c levels. Secondary outcomes included life years gained (LYG) and the reduction in the 10-year risk of cardiovascular events.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003ePharmacist's interventions significantly reduced average HbA1c levels and lowered risks for CVD and stroke in the intervention group compared to the control group (p value\u0026thinsp;=\u0026thinsp;0.009). Cost-effectiveness analysis showed that this intervention resulted in a cost reduction and life years gained over a 10-year time horizon. The PSA analysis showed that pharmacist interventions led to more LYGs and lower costs for the intervention group compared to the control group. The cost-effectiveness plane for 1,000 individuals showed 95.2% of ICER points in the southeast quadrant, indicating the intervention's dominance.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eInvolving community pharmacists in diabetic programs can reduce short-term and long-term complications. It emphasizes that providing primary diabetes care by pharmacists benefits patients and brings significant cost savings to the healthcare system.\u003c/p\u003e","manuscriptTitle":"Cost-effectiveness analysis of the community pharmacist-based intervention in Type 2 diabetes mellitus a service trial","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-17 06:34:46","doi":"10.21203/rs.3.rs-5788534/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-06-23T10:00:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-23T00:09:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"134049736390005662229854108836888821911","date":"2025-06-21T07:10:40+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-01T10:24:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200208979086869261112549356175918794436","date":"2025-05-01T09:58:45+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-13T22:56:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-03-19T03:57:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Cost Effectiveness and Resource Allocation","date":"2025-03-18T07:07:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"cost-effectiveness-and-resource-allocation","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cera","sideBox":"Learn more about [Cost Effectiveness and Resource Allocation](http://resource-allocation.biomedcentral.com)","snPcode":"12962","submissionUrl":"https://submission.nature.com/new-submission/12962/3","title":"Cost Effectiveness and Resource Allocation","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"91f2879d-99e7-411c-9469-3fc178030be9","owner":[],"postedDate":"April 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-09-01T16:08:21+00:00","versionOfRecord":{"articleIdentity":"rs-5788534","link":"https://doi.org/10.1186/s12962-025-00651-7","journal":{"identity":"cost-effectiveness-and-resource-allocation","isVorOnly":false,"title":"Cost Effectiveness and Resource Allocation"},"publishedOn":"2025-08-29 15:58:20","publishedOnDateReadable":"August 29th, 2025"},"versionCreatedAt":"2025-04-17 06:34:46","video":"","vorDoi":"10.1186/s12962-025-00651-7","vorDoiUrl":"https://doi.org/10.1186/s12962-025-00651-7","workflowStages":[]},"version":"v1","identity":"rs-5788534","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5788534","identity":"rs-5788534","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}