Using A RE-AIM Framework to Evaluate the Impact of Shared Medical Appointments for Diabetes Mellitus: A Systematic Review and Meta-analysis

Using A RE-AIM Framework to Evaluate the Impact of Shared Medical Appointments for Diabetes Mellitus: A Systematic Review and Meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Using A RE-AIM Framework to Evaluate the Impact of Shared Medical Appointments for Diabetes Mellitus: A Systematic Review and Meta-analysis Wei Yang, Run Mao, Ziyun Liang, Zihui Liang, Ruixin Wang, Jiamin Wang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4858860/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Jun, 2025 Read the published version in BMC Primary Care → Version 1 posted 12 You are reading this latest preprint version Abstract Background Diabetes is a major global health concern and a leading cause of morbidity and mortality. Shared medical appointment (SMA), an integrated treatment and health management service, is effective in improving the clinical and behavioral outcomes of people with diabetes (PWD). Using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, this review aimed to evaluate the impact of SMA on PWD treatment and management to inform the feasibility, scalability, and equity of future SMA implementation. Methods Eight electronic databases were searched for randomized controlled trials, non-randomized grouped controlled trials, pre/post studies, and interrupted time series model studies published in English and Chinese up to February 2024. We performed meta-analyses for all RCTs using a random-effects model and presented Forrest plots and test statistics (Cochran's Q and I 2 ) for heterogeneity analysis. Other results that did not lend themselves to quantitative analysis were summarized qualitatively. Results Forty-seven studies were included in the review. The SAM was a highly resource-demanded and complex intervention package. The studies were evaluated according to the RE-AIM framework, and most studies reported effectiveness well, while all other dimensions were poorly reported. Most studies demonstrated that SMA effectively improved patients’ HbA1c and SBP levels and reduced healthcare costs. Discussion The available evidence suggests that the SMA was beneficial in improving PWD management and health outcomes among PWD. However, its complexity would constrain its feasibility and scalability. Future research should assess the effect size of each intervention component and evaluate the implementation process, costs, and sustainability of SMA intervention, especially in resource-limited settings, to improve its scalability and equity. Trial registration PROSPERO CRD42019134273 people with diabetes shared medical appointments reach effectiveness adoption implementation and maintenance (RE-AIM) feasibility equity scalability systematic review meta-analysis Figures Figure 1 Figure 2 Highlights What is already known on this topic - Current studies demonstrated that the SMA effectively improved clinical and behavioral outcomes for people with diabetes (PWD) in experimental settings, which contained adequate resources. However, there was a notable gap in the research regarding the comprehensive evaluation of the implementation outcome using the RE-AIM framework, which would constrain the scale-up of the SMA and affect equity in resource-limited communities. What this study adds - This systematic review innovatively evaluates the impact of Shared Medical Appointments (SMA) on diabetic management by using the Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. It highlights the gap in effectiveness and implementation research, including the combination of the SMA intervention components' main and interactive effects, long-term sustainability, and equity, particularly in resource-limited settings. How this study might affect research, practice or policy - This study demonstrated the specific impact of SMA on biochemical markers and healthcare costs, supporting the effectiveness of SMA in primary healthcare (PHC) settings, mainly reflected in improved HbA1c and SBP levels. However, the resource-intensive characteristic of the SMA would affect its scale-up and equity in various PHC settings. Background People with diabetes (PWD) is a major global health concern and a leading cause of morbidity and mortality, with a rapid increase worldwide [1] . In 2021, there were 537 million PWD, accounting for 6.1% of the world population, which was expected to rise to 9.8% (1.31 billion) by 2050 [2] . PWD can lead to serious complications in multiple organs, such as blindness, heart attacks, and lower limb amputation [3] . According to the World Health Organization, PWD caused 1.5 million direct deaths worldwide in 2019, a 3% increase from 2010 [4] . The increasing prevalence, high avoidable morbidity and mortality, and huge economic burden make diabetes a significant global health challenge [5, 6] . Addressing the increasing global disease burden of PWD requires an affordable, feasible, and cost-effective comprehensive approach at the system level instead of the individual level, and one such approach is shared medical appointment (SMA) [7] . In SMA services, multidisciplinary medical treatment and health management providers successively provide medication consultation, physical examination, treatment, and health management services for a group of PWD with similar conditions in a consulting room [8] . The medical team typically includes at least one physician with prescribing rights and several trained or qualified staff, such as nurses, nutritionists, and psychologists [9, 10] . PWD can receive interactive education about their treatment options and share their personal experiences related to PWD management in a group consultation [11] . Several literature reviews have demonstrated that SMA is effective in improving PWD's clinical and behavioral outcomes, reflected as improved biochemical indicators, such as Hemoglobin A1c (HbA1c) and Systolic Blood Pressure (SBP), and healthier lifestyles such as diet control and exercise [7, 12, 13] . Thus, SMA represents a promising evidence-based practice (EBP) for addressing the challenges of diabetes control in other settings. However, in the existing study, the SMA services were a resource-intensive complex intervention conducted in well-resourced settings [9, 11] . While most previous SMA evaluations focused only on the effectiveness of the interventions, leaving researchers and practitioners with little information about the generalizability of the intervention context, practitioners, conditions, and findings [14] . There was insufficient evidence of system and process evaluation on SMA's context, mechanisms, complexity of the SMA intervention package (i.e., various components combinations), and outcomes (e.g., SMA effectiveness, management efficiency, costs, and fidelity of research), which was essential to translate the knowledge from interventions to policy and practice [15] , particularly for improving healthcare quality in primary healthcare (PHC) settings in low- and middle- income countries (LMICs) [16] . These limitations will constrain further implementation to improve the feasibility, scalability, and equity of SMA implementation in PWD and people with other chronic conditions in varied PHC settings. If an effective intervention is too complex and demands too many resources for a real-world frontline setting, it cannot be scaled up [17] . Furthermore, this may limit the equitable access to high-quality EBP for individuals, especially in resource-limited communities [18, 19] . The RE-AIM framework is one of the most frequently used frameworks to guide the design, implementation, and assessment of research programs to make the findings more generable and practical in real-world community settings [20] . RE-AIM is an acronym for the following five evaluation dimensions under two categories [21, 22] : Reach (R) and Effectiveness (E) at the individual level, and Adoption (A), Implementation (I), and Maintenance (M) at both the individual and setting level. The RE-AIM framework can improve transparency in reporting the critical components of an intervention and is particularly useful in the adoption, scaling, and maintenance of an effective intervention [23, 24] . Applying the RE-AIM framework, this systematic review and meta-analysis aimed to comprehensively summarize the effects of SMA on PWD by providing updated quantitative and qualitative evidence, which will inform the feasibility, scalability, and equity of future SMA implementation [25] . Methods The systematic review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 checklist [26] . A protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 28 November 2019 (registration number CRD42019134273). Eligibility criteria The inclusion/exclusion criteria were based on Populations, Intervention, Comparison, Outcome, and Study (PICO) design principles and research questions. Eligible study designs included randomized controlled trials (RCTs), non-randomized cluster-controlled trials, pre/post-design studies, and interrupted time-series designs. Other observational and qualitative studies on the economic costs and doctor-patient experiences were discussed in the results but not included in the statistical analysis. We included studies on SMA interventions that satisfy the following conditions: (1) in an outpatient setting; (2) with at least two medical visits over time; (3) intervention duration of more than three weeks; (4) including at least two patients in the same clinical setting; (5) involving at least one prescribing clinician; (6) addressing each patient's unique medical needs individually. The detailed characteristics of the criteria are shown in Appendix 1. Data sources and search strategy We searched the following databases for literature comparing the effectiveness of SMA and usual care in PWD from January 2012 to February 2024: PubMed, EMBASE, EBSCO, CINAHL, PsycINFO, Web of Science, CNKI, and Wan Fang. This review followed the same search strategy as Edelman et al.’s previous study [27] , including four search terms: group appointments, shared visits, interventions, and observational studies, and included papers in English and Chinese. In addition, our study population was limited to adults aged 18 years or older. See Appendix 2 for an overview of the search strategy. We looked for non-published studies in clinical trials to mitigate the risk of publication bias (available at https://www.clinicaltrials.gov/ ), manually searched reference lists, and tracked citations to identify additional literature. Study quality assessment Two reviewers assessed the methodological quality of the included studies according to the Agency for Healthcare Research and Quality's Methodological Guidelines for Review of Validity and Comparative Effectiveness [28] . Ratings were based on information richness reported in the literature regarding SMA for PWD. Any disagreement between the two reviewers was resolved by a third expert who was familiar with the study. This quality assessment method can help assess the risk of bias, the strength of the evidence, and the applicability of the included studies. Data collection and extraction After removing the duplicates, four researchers used the eligibility criteria to screen the title and abstract. The full text was reviewed in more detail based on a preliminary review. Concerning differences in full-text screening, researchers met to discuss and reach a consensus. Four researchers conducted data extraction independently using a predesigned Excel sheet. They compared their data extraction results and discussed any disagreements or revisions until a consensus was reached. Standardized tables were used to extract data and collect documentation. The data mainly consisted of six aspects: (1) Study characteristics: author, year, research design, and research setting; (2) SMA intervention characteristics: period, number of visits, composition of SMA service team, intervention patterns, and procedures; (3) RE-AIM framework contents: reach, effectiveness, adoption, implementation, and maintenance; (4) Outcome components: biochemical indicators, adherence, symptom severity and patient quality of life at effectiveness and maintenance dimensions, patient and staff experiences of participating SMA, staff-related indicators, and economic-related indicators at adoption, implementation and maintenance dimensions ; (5) Discussion: limitations, and future directions. Data Synthesis and Analysis We conducted a meta-analysis on RCTs to evaluate the combined effect of intervention by comparing the means and changes in the biometrics between the intervention and control groups after the intervention. Heterogeneity between studies was assessed using Foster's plots and test statistics (Cochran's Q and I 2 ), with a P 50 indicating significant heterogeneity. In addition, we performed subgroup analyses of categorical variables using a random effects model When I 2 > 50 or a fixed-effects model otherwise. All statistical analyses were conducted through Review Manager 5.4. When meta-analysis was not appropriate, qualitative summaries were performed. Results Search results Among the 885 citations initially identified through a complete database search, 217 were retrieved after the title and abstract screening. After screening for full text, 31 studies met inclusion criteria and were included in our final analysis. In addition, we added three studies through a manual search of the reference lists and another 13 RCT studies in the previous systemic review. Therefore, 47 studies contributed findings to the review, including 24 RCT studies for meta-analysis [29–52] and 23 observational studies for qualitative analysis [53–75] (Fig. 1). Figure 1 Literature flow diagram Study characteristics All 47 studies have compared the differences in treatment outcomes between SMA and usual one-on-one care. Most studies used Hemoglobin A1c (HbA1c) as the primary outcome, and some studies also included SBP, total cholesterol (TC), and low-density lipoprotein (LDL-c). The intervention duration was ≥ 1 year in 26 studies, between six months to 1 year in 13 studies, and < six months in 8 studies. Regarding quality, 18 were good, 20 were fair, and nine were poor (Appendix 3). SMA intervention characteristics Table 1 shows the characteristics of SMA intervention. Most interventions were implemented through specialty clinics in hospitals and primary healthcare centers. Thirty interventions were conducted in multiple centers. The median duration of the total intervention and each session were 12 months and 120 minutes, respectively. The median number of scheduled visits and patients per group were 7 (range: 6 to 12) and 10 (range: 8 to 13), respectively. The intervention team included a median of 4 (range: 3 to 7) members, mainly composed of clinicians (internists or endocrinologists or general practitioners) (74.5%), nurses (70.2%), and pharmacists (40.4%). Most studies' intervention frequency was once a month (40.4%). This review also assessed the provision of health education, psychological interventions, daily management, and dietary adjustments for patients, as well as the interaction with family and friends during their treatment process. The findings indicate that a vast majority of studies (89.4%) reported the implementation of health education. Beyond health education, 70.2% of studies implemented additional services such as psychological interventions, daily management, and dietary adjustments. Furthermore, in 83.0% of the studies, patients had the opportunity to share experiences and interact with others during the intervention process. However, only 25.5% of the studies reported that patients’ family and friends were involved in the treatment process. Table 1 SMA intervention characteristics Characteristics n (%) or M(IQR) Settings Community-based healthcare settings (i.e., PHC settings) 27(57.45) Specialized Clinic in Government (VA, FQC) or University-affiliated clinic or Private clinic 20(42.55) Duration of intervention (months) [ M (Q L , Q U ) ] 12 (6 to 17) Average visit duration (mins) [ M (Q L , Q U ) ] 120 (90 to 120) Times of planned visits [ M (Q L , Q U ) ] 7 (6 to 12) Number of patients per group [ M (Q L , Q U ) ] 10 (8 to 13) Intervention team size [ M (Q L , Q U ) ] 4 (3 to 7) Intervention team disciplines [n (%)] Clinicians(endocrinologists)/General Practitioners 35 (74.5) Nurses 33 (70.2) Pharmacists 19 (40.4) Psychologists (Counselors)/Behaviorists 10 (21.3) Nutritionists 10 (21.3) Public health physicians/diabetes educators 8(17.0) Physiotherapists/exercise specialists 7 (14.9) Social workers 5 (10.6) Medical assistant 4 (8.5) Researchers 3 (6.4) Others A 4 (8.5) Intervention team combinations [n (%)] B Clinician , nurse 5 (10.6) Clinician , nurse, public health doctor, others C 24 (51.1) Clinician , public health doctor, others D 4 (8.5) Clinician , others E 4 (8.5) Other F 3 (6.4) Not reported 7 (14.9) Frequency of intervention [n (%)] once /week 2 (4.3) once/2 weeks 2 (4.3) once/3 weeks 1 (2.1) once/month 19 (40.4) once/2 months 2 (4.3) once/3 months 4 (8.5) 6 times/month 1 (2.1) once/6 month 1(2.1) The research interventions with uneven frequency 8 (17.0) Not reported 7 (14.9) Availability of health education [n (%)] Yes 42 (89.4) Not reported 5 (10.6) Whether there is psychological intervention, daily management, or diet adjustment outside of education [n (%)] Yes 33 (70.2) Not reported 14 (29.8) Availability of experience sharing/interaction [n (%)] Yes 39 (83.0) Not reported 8 (17.0) Whether there are family/friends involved [n (%)] Yes 12 (25.5) Not reported 35 (74.5) Note : PHC setting: Primary healthcare setting, including the adult primary care center [31, 32] , community health centers [30, 36, 37, 44, 47] , non-profit community clinic [29, 59] . M : Median; IQR : Inter-Quartile Range; VA: department of veterans affairs; FQC: federally qualified center. A: Community health center director, clerical staff, front office administrator. B: All clinicians had rights to prescribe. C: Other providers were pharmacists, nutritionists, social workers, secretary, behaviorists, psychologists, medical assistants, researchers, exercise specialists, physiotherapists, counselors, and/or research assistants. D: Other providers were receptionist, psychologists, nutritionists, and/or medical assistants. E: psychologist, pharmacist, and/or researchers. F: Other providers were pharmacists, nurses, nutritionists, and/or physiotherapists. SMA intervention tasks The review summarized the implementation process of the SMA intervention, which included ① Self-introduction among patient participants and a description of their medical history, current glucose-lowering regimen, and effect of glycemic control. ② Individual counseling involves patients asking questions and getting physical examinations in turn, with medication adjustments made when necessary. ③ Collective discussion: the intervention team discusses and exchanges information with patients and their families on the key concerns individually and encourages patients to share their experience in self-glycemic control. The SMA services team will provide guidance and summarize this intervention’s unique and joint problems. ④Health education: the SMA services team will use different health education methods to explain various aspects of PWD management, including medication, diet, and exercise. Individuals providing SMA interventions are categorized into two major groups: clinical medicine and public health. Table 2 lists the specific tasks of SMA interventions provided by different personnel. Table 2 Providers Roles of different types of health service providers in SMA Providers Responsibilities Medical service providers Clinicians(endocrinologists) / General Practitioners 1. Conduct individual/group-based consultations with patients. 2. Review patients’ biochemical testing results. 3. Provide medication and behavioral interventions and modifications if necessary. Nurses 1. Conduct initial assessment of patient status and complete health education courses. 2. Physical examination: testing weight, height, blood pressure, and waist circumference, blood sampling for blood glucose, HbA1c, and urinalysis test, as well as other tests as applicable. 3. Medication adjustments (registered nurse only) Pharmacists 1. Conduct comprehensive medication management for patients, including clinical assessment and development of treatment plans. 2. Medication guidance. Public health service providers Psychologists (Counselors)/Behaviorists Psycho-education: providing behavior education, stress coping and motivational skills training to improve self-management and self-efficacy. Nutritionists Healthy diet education: nutritional knowledge and skills, including carbohydrate counting and the plate methods. Public health physicians/diabetes educators Health education: providing healthy eating, physical activity, etc. Physiotherapists/exercise specialists Health education: providing exercise instruction, behavioral interventions, etc. RE-AIM-based SMA outcomes We used the RE-AIM framework to summarize the study results by each element (Table 3 ). To increase transparency in reporting, we divided the reporting into 5 phases: enrollment, baseline of trial, mid-term of trial, endline of trial, and follow-up. The results from the follow-up phase were regarded as the maintenance results of the RE-AIM framework. Table 3 RE-AIM indicators with the number and percent of studies reporting each indicator (N = 47) RE-AIM dimensions and components The proportion of reports per study period (%) Enrolment Baseline Mid-term Endline Follow-up ( Maintenance: The extent to which SMA was consistently implemented after the study ended ) Reach: Number, proportion, and representativeness of diabetic patients participating in SMA who met inclusion The number of patients recruited 100.0 N/A N/A N/A N/A The number of patients recruited as a percentage of the target population 38.3 N/A N/A N/A N/A The number of patients who joined halfway through the project N/A N/A 0 N/A 0 The proportion of patients joining midway N/A N/A 0 N/A 0 The number of patients who dropped out in the middle of the project N/A N/A 44.7 N/A 0 The proportion of patients who withdrew midway N/A N/A 36.2 N/A 0 Effectiveness: Effectiveness of SMA interventions at the patient level Patient biochemical indicators A HbA1c N/A 85.1 27.7 83.0 0 FG N/A 17.0 4.3 17.0 2.1 Blood lipids (TC, LDL-c, HDL-c, TG) N/A 61.7 17.0 55.3 0 BP N/A 53.2 14.9 55.3 4.3 BMI N/A 6.4 6.4 38.3 4.3 Patient physical and behavioral indicators Patient quality of life 48.9 N/A 2.1 6.4 2.1 Medication compliance 19.1 N/A 6.4 29.8 0 diet 34.0 N/A 0 21.3 0 Diabetic self-efficacy 19.1 N/A 4.3 29.8 0 Diabetes management behavior 22.4 N/A 4.3 34.0 0 The cost of patient access to care Cumulative number of hospitalizations, days, and costs due to diabetes exacerbations or complications during the trial period N/A 2.1 8.5 12.8 4.3 Patients' treatment effect (cured, improved, ineffective) after each hospitalization N/A 0 0 0 0 Adoption: Number, proportion, and representation of institutions and physicians participating in SMA Indicators at the level of medical institutions The number and reasons for participating institutions and their representation in the study 68.1 0 0 0 0 The number and reasons for the withdrawal or addition of institutions N/A 0 2.1 0 0 Physician-level indicators The number of doctors involved in the study and why, and their representation in the program 63.8 0 0 0 0 The number of doctors who dropped out or joined in the midway N/A N/A 2.1 N/A N/A Implementation: The extent to which the implementation was completed according to the researcher's requirements (i.e., "fidelity"), the localization of SMA implementation process, and the cost of SMA implementation Fidelity of implementation The proportion of physicians performing and completing SMA intervention packages and reasons N/A 0 0 0 0 The extent to which the project is being implemented as originally planned 0 4.3 2.1 2.1 0 Duration and frequency of intervention 100.0 N/A N/A N/A N/A Cost of implementation The cost of money and staff time spent during SMA implementation N/A 0 0 0 0 Note : HbA1c: HemoglobinA1c; BP: Blood pressure; FG: Fasting plasma glucose; TC: total cholesterol; LDL-c: low-density lipoprotein cholesterol; HDL-c: high-density lipoprotein cholesterol; TG: triglyceride; BMI: Body mass index Reach Reach refers to the number, proportion, and representativeness of diabetic patients participating in SMA who met the inclusion criteria. During the enrolment phase, all studies reported the number of patients recruited. The proportion of patients recruited at the enrollment stage was 38.3%. The number and proportion of patients who dropped out at mid-term trials were 44.7% and 36.2%, respectively. Effectiveness Effectiveness refers to the effectiveness of the SMA intervention at the patient level. It includes three secondary indicators: patient biochemical indicators, physical and behavioral indicators, and the cost of patient access to care. Patient biochemical indicators Of the 24 RCT studies, 18 focused on type 2 diabetes [29–32, 34, 36–38, 40, 43, 44, 46–50] , five investigated mixed populations [33, 35, 39, 41, 45] , and only one investigated type 1 diabetes [42] . All diabetic patients had been diagnosed with HbA1c or poor glycemic control. 24 RCT studies compared the SMA intervention with usual care or other strategies. Some studies also used diabetes-related risk factors (e.g., SBP, TC, and LDL-c) as secondary outcome indicators. Among the various biochemical indicators, HbA1c was the most frequently reported at each stage: 85.1% at the trial's baseline,27.7% at the mid-term, and 83.0% at the endline. FG was less frequently reported, with a maximum reporting rate of 17.0%. Blood lipids (TC, LDL-c, HDL-c, TG) were reported by 61.7% of studies at the trial's baseline, 17.0% at mid-term, and 55.3% at the endline. BP was reported by 53.2% of studies at the baseline, 14.9% at the mid-term, and 55.3% at the endline. BMI was reported by 6.4% of studies at the baseline, 6.4% at the mid-term, and 38.3% at the endline. The review results of the leading biochemical indicators involved in the studies are reported below (Fig. 2). First, 22 RCT studies reported HbA1c levels or changes after SMA intervention [30–35, 37–46, 50, 52] . Compared with the conventional treatment group, the SMA intervention group had reduced HbA1c levels by 0.38% (95% CI : -0.55, -0.21), a statistically significant difference. In 15 observational studies, the effects of SMA interventions were consistent with proximate RCT investigations except for two studies [53–58, 60–62, 70, 71] . Second, 16 RCT studies included SBP levels or changes after SMA treatment as a secondary outcome [29, 30, 33, 35–37, 40, 41, 44, 46–49] . SBP levels were reduced by 3.24% (95% CI : -4.71, -1.77) in the SMA intervention group compared to the conventional treatment group. Eight observational studies reported SBP outcomes, yet with inconsistent results. In six of the eight studies [53, 55, 56, 60, 65, 75] , the pre-and post-SBP changes between the SMA intervention and conventional treatment groups were not significant ( P > 0.05). The results of the other two studies were consistent with the meta-analysis and supported using SMA intervention to improve SBP [61, 62] . Third, seven RCTs reported TC as a predictor of glycemic control after SMA treatment [31, 37, 42–45, 49] . The results showed a non-significant association between SMA and TC decline at the 95% confidence level (mean difference: -0.08 mg/dl [95% CI : -0.20, 0.03]). Four observational studies reported the results of SMA intervention on TC control, with two showing no significant effect [55, 60] and two showing a significant therapeutic effect of SMA in improving TC [62, 75] . Finally, nine RCTs showed that SMA did not significantly improve LDL-c (95% CI : -3.99, 4.66) compared with conventional treatment modalities at the 95% confidence level [53, 55, 56, 65, 75] . Seven observational studies reported biochemical findings related to LDL-C, with five studies showing no significant effect and two studies showing a significant therapeutic effect of SMA in improving TC [57, 62] . Figure 2 Biochemical Indicators Forest Plots: SMA Group vs. Usual Care Heterogeneity Analysis Heterogeneity analysis was conducted by calculating the percentage heterogeneity between studies included in the meta-analysis that was not due to chance (see Appendix 4 for the sensitivity analysis results). First, we performed sensitivity analyses for HbA1c and SBP. For HbA1c, although there were significant differences in treatment effects between studies, heterogeneity improved after excluding three studies [32, 39, 47] , with a mean difference of -0.29% ( Q : 51.83; DF : 18; P < 0.1; I 2 : 65); [95% CI : -0.42, -0.15]) (Appendix 4a). For SBP, sensitivity analysis showed significantly lower heterogeneity after excluding 1 [47] biased study, with a mean difference of -2.75% ( Q : 14.16; DF : 11; P < 0.1; I 2 : 22); [95% CI : -3.37, -2.14]) (Appendix 4b). The results of the subgroup analysis confirmed that the SMA intervention contributed to the improvement of HbA1c and SBP in diabetic patients. Second, we performed a subgroup analysis by dividing the study settings into PHC and non-PHC. For HbA1c, 15 studies were conducted in PHC and reported HbA1c as an outcome [29–34, 37–39, 41, 44, 45, 47, 49, 50, 52] . The mean reduction in HbA1c was 0.50% (95% CI : -0.79, -0.21) in the PHC setting and 0.20% (95% CI : -0.37, -0.04) in the non-PHC setting (Appendix 4c). Regarding SBP, nine studies were conducted in PHC and reported SBP as having an outcome of [29, 30, 33, 36, 37, 41, 44, 47, 49] . SBP decreased more in PHC subjects than non-PHC, with a mean reduction of -4.38 percentage points (95% CI : -6.17, -2.60) in the PHC setting (Appendix 4d). Psych behavioral indicators Thirty-nine studies reported five psych behavioral indicators by stage; each described as below: (1) Quality of life: enrolment (48.9%), mid-term of trial (2.1%), endline of trial (6.4%);(2) Medication compliance: enrolment (19.1%), mid-term of trial (6.4%), endline of trial (29.8%); (3) Diet: enrolment (34.0%), mid-term of trial (0), endline of trial (21.3%); (4) Diabetes self-efficacy: enrolment (19.1%), mid-term of trial (4.3%), endline of trial (29.8%); (5) Diabetes management behaviors: enrolment (22.4%), mid-term of trial (4.3%), endline of trial (34.0%). One pre-post controlled study and two RCTs found that the SMA intervention improved patients' perceptions of PWD [32, 44, 57] , which may indirectly improve medication adherence. Five studies of patients' diets reported that the SMA intervention led to healthier eating habits [36, 47, 51, 66, 75] . Studies also showed that SMA significantly improved PWD’ diabetes self-efficacy and self-management behaviors, such as blood glucose self-monitoring [36, 38, 51, 58, 66, 67, 69, 70, 73, 75] . One study showed no effect of SMA on PWD’ exercise levels [47] . An RCT and an observational study showed that patients in the SMA group underwent physical examinations (e.g., foot exams, eye exams, and lipid screenings) more frequently. This can allow patients to meet other patients with the same health problems, exchange their experiences, and receive peer support, which can motivate them to adopt healthier behaviors and feel more accomplished [47, 56] . Healthcare cost Eight studies reported data on healthcare costs (Appendix 5), including the accumulative number of hospitalizations, days, and expenses due to diabetes exacerbations or complications during the trial period. This information was reported as baseline (2.1%), mid-term (8.5%), and endline (12.8%). However, no studies reported patients’ therapeutic outcomes after each hospitalization (cured, improved, failure). Two studies showed no statistical difference in outpatient costs between the SMA and usual care groups ( P = 0.19) [45, 76] . Another study reported higher total expenditure in the SMA group than in the usual care group ( P = 0.0003) [31, 35] . However, the opposite results were reported by three other studies [31, 32, 46] . They showed that the total costs were lower in the SMA intervention than in the control group. Two studies reported the cost of participating in SMA but did not report statistical differences [33, 42] . Six studies reported the impact of SMA on hospital visits, such as admissions, emergency room visits, and primary care visits (Appendix 6). Two studies reported that PHC ensured at least one patient visit and intervention during the SMA intervention [33, 45] . Another four studies did not find differences in patient emergency room visits, hospitalization rates, or primary care visits between the SMA intervention and usual care groups [35, 39, 40, 47] . Adoption The adoption domain includes two indicators: medical institutions and physician-level. During the enrolment phase, the majority of studies reported: "the number and reasons for participating institutions and their representation in the study" (68.1%) and “the number of doctors involved in the study and their representation in the program” (63.8%). Only 2.1% of studies reported "the number and reasons for the withdrawal or addition of institutions" at the mid-term of the trial. Implementation The implementation domain includes two indicators: fidelity and cost of implementation. In terms of the fidelity to trial implementation, all studies reported the duration and frequency of the intervention during the recruitment phase. A lower proportion (0 to 4.3%) reported other dimensions and grade indicators. None of the studies reported implementation costs for institutional-level stakeholders. Maintenance The maintenance domain refers to how SMA was consistently implemented and patients’ health outcomes after the study ended. However, studies reporting maintenance levels of institutional indicators were minimal (0 to 4.3%) and mainly focused on patient biochemical indicators. Of the 47 included studies, the core indicators with reported maintenance levels were FG (2.1%), BP (4.3%), and BMI (4.3%). In addition, a few studies reported the cumulative number of hospitalizations, days, and costs due to worsening diabetes or complications during the project period (4.3%). Discussion This review summarized 24 RCTs and 23 observational studies. It systematically assessed the effectiveness of SMA interventions in diabetes management according to the guidelines of the five dimensions of the RE-AIM framework: reach, effectiveness, adoption, implementation, and maintenance. However, the report of each dimension was unbalanced, each discussed below: Effectiveness In line with the results of previous systematic reviews [77, 78] , we found type 2 PWD who benefited more from the SMA intervention than type 1 PWD. Although a few studies have reached opposite conclusions [32, 45, 46, 55] , most studies have demonstrated that SMA improved HbA1c and SBP and reduced hospitalizations due to hyperglycemia or complications among PWD. In addition, SMA interventions can potentially improve self-management behaviors and health outcomes in PWD. However, the risk of macrovascular and microvascular complications usually increases with the duration of PWD [79] . Therefore, the impact of SMA on preventing complications may be underestimated in interventions targeting early patients. Qualitative interviews revealed that most patients felt that SMA was time-efficient without incurring extra costs [56] . As the number of PWD continues to increase, there is a growing tension between the increased need for PWD care and the limited healthcare workforce. Wu suggested promoting SMA in PHCs to avoid competition with hospital referrals and specialty providers [46] . Lou and Liu noted that SMA interventions in PHCs positively impacted patient attendance due to high efficiency and low cost [36, 37] . Implementing SMA in non-PHC settings may reduce patient compliance and attendance [59] . In contrast, PHCs are located in the local communities, which may minimize attendance time and financial costs. One study pointed out a gap between PHCs and specialty hospitals in managing PWD and that PHCs lacked sufficient medical equipment and a workforce to meet the needs of patients [80] . However, another study showed that PHC providers had better connections with local patients regarding daily visits and communication, thus bridging the care gap with PWD specialty hospitals [44, 54] . Furthermore, similar to other evidence-based practices implemented in PHC settings [16, 81] , SMA would be a possible way to address the equity of access to practical, evidence-based innovations for patients with PWD in communities. Therefore, it is essential to strengthen the collaboration between PWD specialty hospitals and local PHCs to provide more training to PHCs to ensure adequate disease management [50] and improve healthcare equity [16] . Although the study showed the positive effectiveness of PHCs, which are mainly responsible for patients' daily treatment and health management in LMICs, we find that most studies contained more than two service providers. Besides, the SMA services were abundant, varied, and complex. The SMA was still a highly resource-demanded intervention. However, in resource-limited settings, its feasibility and scalability would face a lot of challenges, especially in lacking of human resources. Furthermore, its complex services would require more investigation, including the cost of staff and working hours. This would raise the medical services fee and exceed the patients’ affordability, especially in rural communities in LMICs [82] . Furthermore, this would increase the health inequity in different resource-distribution areas, especially in vulnerable populations in LMICs [83] . Reach, Adoption, Implementation, and Maintenance The included studies reported poor results on the reach, adoption, implementation, and maintenance dimensions. When researchers scale up an EBP from a highly restrictive experimental setting to real-world community settings, the implementability of the EBP will face challenges from the patient's reach and the providers' adoption [84, 85] . This study found that the included studies were conducted in resource-adequate settings. If future studies were conducted in other diverse and resource-limited settings, the external representation of the reach of patients and the adoption and complete implementation of providers would be an issue. None of the studies reported on physicians performing and completing SMA intervention packages or the costs of institutional-level stakeholder implementation. Previous studies have evaluated the duration of SMA visits and found that SMA was malleable in terms of time costs, clinical workload, and other measurable outcomes. SMA has been shown to be a feasible and cost-effective approach compared to conventional models [33] . Meanwhile, if all cost information on the institutional side is explored in depth in future studies to confirm that the benefits of SMA were maximized for both patients and institutions, it would be helpful to other researchers to transfer the SMA model to other settings. Maintenance refers to the long-term effect of EBP and the sustained implementation of SMA. A few studies have reported the long-term effects of some of the indicators of SMA [29, 33, 40, 46–48, 75] . However, there were no studies on the sustained implementation of SMA. A lack of focus on sustainability will result in a waste of investigation from research and human resources [86] . Future studies should focus on the sustainability of EBP, including both the long-term effect of EBP and its implementation. The assessment of EBP’s sustainability and its influencing factors are also important to improve the sustainability [87] . In our meta-analysis, we observed considerable heterogeneity among the studies included. While we were able to attribute this heterogeneity partly to certain biased studies, the SMA, which was a complex intervention package, would be the main source of heterogeneity. Although the SMA has been shown to improve patient health outcomes overall, it remains challenging to determine which specific component(s) or combination (i.e., configurations) thereof are mainly responsible for these improvements. Given the complexity of SMAs, their implementation in resource-limited settings raises concerns. Such environments often suffer from shortages in human resources, financial constraints, and a lack of diverse healthcare specialists, which may hinder the adoption of effective SMA configurations. Consequently, future research should employ the multiphase optimization strategy (MOST)-guided optimization trial [87, 88] to dissect the component's main effects and interactive effects among the SMA components. This approach will not only enhance our understanding of each component's impact but also improve the scalability and implementability of SMAs, thereby ensuring broader applicability and effectiveness in diverse clinical settings. Conclusion Based on the RE-AIM framework, our review showed that SMA intervention effectively reduced PWD' HbA1C, SBP, and healthcare costs. The findings suggest the superiority of SMA in primary care for effectively controlling PWD' biochemical indices. However, we should notice that the SMA was a highly resource-intensive complex intervention. Its reach, adoption, implementation, and maintenance would face challenges, such as investigation constraints and human resources limitations in LMICs. The next step in SMA research for PWD should be an optimization phase that focuses on confirming its main effect and interaction effect on its different components. Empirical evidence for SMA interventions conducted in resource-limited areas would be demanded. In addition, future studies should address the shortcomings identified in the review by accurately assessing the implementation process, cost, sustainability, and equity of SMA implementation. Abbreviations BP Blood Pressure BMI Body Mass Index EBP Evidence-Based Practices FG Fasting Glucose FQC Federally Qualified Center HbA1c Hemoglobin A1c HDL-c High-Density Lipoprotein cholesterol IQR Inter-Quartile Range LDL-c Low-Density Lipoprotein cholesterol LMICs Low- and Middle- Income Countries M Median MOST Multi-stage Optimization Strategy PHC Primary Healthcare PICOS Populations, Intervention, Comparison, Outcome, and Study PRISMA Preferred Reporting Items for Systematic Reviews and Meta-Analysis PROSPERO Prospective Register of Systematic Reviews PWD People With Diabetes RCT Randomized Controlled Trial RE-AIM Reach, Effectiveness, Adoption, Implementation, and Maintenance SBP Systolic Blood Pressure SMA Shared Medical Appointment TC Total Cholesterol TG Triglyceride VA Department of Veterans Affairs Declarations Ethics approval and consent to participate Not applicable. Consent for publication Not applicable. Availability of data and materials No additional data are available. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the National Natural Science Foundation of China (NNSFC) [grant 72164005], and China Medical Board Open Competition Grant, grant number CMB16-260. Authors' contributions WY: Data extraction, verification, and manuscript writing. RM: Data extraction and verification. ZhL, ZyL, JW, RW, XL, and ML: Formulating search strategies and extracting data. YC and DRX: Guiding the writing and revision of the manuscript as mentors. All co-authors participated in the revision and approved this manuscript. Acknowledgments Not applicable. Trial registration PROSPERO CRD42019134273 Declaration of generative AI and AI-assisted technologies in the writing process During the preparation of this work, we used [Grammarly] in order to [check the grammar of the manuscript]. 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University","correspondingAuthor":false,"prefix":"","firstName":"Meng","middleName":"","lastName":"Lyu","suffix":""},{"id":345054363,"identity":"655a2373-5816-4fdb-af96-834d35a1d114","order_by":8,"name":"Dong (Roman) Xu","email":"","orcid":"","institution":"Acacia Lab for Implementation Science, Department of Health Management, School of Health Management, Southern Medical University","correspondingAuthor":false,"prefix":"","firstName":"Dong","middleName":"(Roman)","lastName":"Xu","suffix":""},{"id":345054364,"identity":"02e0121b-6712-4dff-89e3-621612e6b59b","order_by":9,"name":"Yiyuan Cai","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA40lEQVRIiWNgGAWjYFACxgaGBBDN3gDjEq2F5wDRWmBAIoFILfzth9skHrYdljeXfH51ww8GG9kNB5ifPcBr9pnENonEtsOGO2fnlN3sYUgz3nCAzdwAnxYDBogWxg23c9JuMzAcTtxwgIdNAq8W/odgLfYbbp4BaflPhBYJiC2JG26wHwNqOUBYi8SNh80WCefSkzecyWG72WOQbDzzMJsZXi38/ekPb/4os7bdcPz4sxs/Kuxk+443P8OrBQhYJBjZQDSPASg0GBiYCagHKfnA8AdEsz8grHYUjIJRMApGJAAA3GlRoa9615sAAAAASUVORK5CYII=","orcid":"","institution":"Department of epidemiology and health statistics, School of Public Health, Guizhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yiyuan","middleName":"","lastName":"Cai","suffix":""}],"badges":[],"createdAt":"2024-08-05 03:06:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4858860/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4858860/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12875-025-02875-1","type":"published","date":"2025-06-05T15:57:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":64570163,"identity":"9a05ede2-d0cd-49d4-9076-740557d282a9","added_by":"auto","created_at":"2024-09-16 01:00:23","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":100212,"visible":true,"origin":"","legend":"\u003cp\u003eLiterature flow diagram\u003c/p\u003e","description":"","filename":"Figure1Literatureflowdiagram.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4858860/v1/591a4ba132e92cf896d506c4.jpg"},{"id":64570165,"identity":"b9f947a1-4120-4a43-9ca7-aa9d99cab059","added_by":"auto","created_at":"2024-09-16 01:00:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":563616,"visible":true,"origin":"","legend":"\u003cp\u003eBiochemical Indicators Forest Plots: SMA Group vs. Usual Care\u003c/p\u003e","description":"","filename":"Figure2BiochemicalIndicatorsForestPlotsSMAGroupvs.UsualCare.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4858860/v1/844e5dd1aa71f716ce1b2fcd.jpg"},{"id":84242525,"identity":"70ed5423-aabe-4259-8e01-51be78d85582","added_by":"auto","created_at":"2025-06-09 16:09:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2555925,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4858860/v1/4fb3f5da-f35a-47f8-8094-2dec6529d98e.pdf"},{"id":64570166,"identity":"5ae9535b-c71f-49ef-bdbd-10b47a794c90","added_by":"auto","created_at":"2024-09-16 01:00:26","extension":"docx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":199284,"visible":true,"origin":"","legend":"","description":"","filename":"3additionalfiles240522yw1909v240710.docx","url":"https://assets-eu.researchsquare.com/files/rs-4858860/v1/769792c2ff2b461c33adbd88.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Using A RE-AIM Framework to Evaluate the Impact of Shared Medical Appointments for Diabetes Mellitus: A Systematic Review and Meta-analysis","fulltext":[{"header":"Highlights","content":"\u003cul\u003e\n \u003cli\u003e\u003cstrong\u003eWhat is already known on this topic -\u0026nbsp;\u003c/strong\u003eCurrent studies demonstrated that the SMA effectively improved clinical and behavioral outcomes for\u0026nbsp;people with\u0026nbsp;diabetes\u0026nbsp;(PWD) in experimental settings, which contained adequate resources. However, there was a notable gap in the research regarding the comprehensive evaluation of the implementation outcome using the RE-AIM framework, which would constrain the scale-up of the SMA and affect equity in resource-limited communities.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eWhat this study adds\u003c/strong\u003e - This systematic review innovatively evaluates the impact of Shared Medical Appointments (SMA) on diabetic management by using the Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework. It highlights the gap in effectiveness and implementation research, including the combination of the SMA intervention components\u0026apos; main and interactive effects, long-term sustainability,\u0026nbsp;and equity, particularly in resource-limited settings.\u003c/li\u003e\n \u003cli\u003e\u003cstrong\u003eHow this study might affect research, practice or policy\u003c/strong\u003e - This study demonstrated the specific impact of SMA on biochemical markers and healthcare costs, supporting the effectiveness of SMA in primary healthcare (PHC) settings, mainly reflected in improved HbA1c and SBP levels. However, the resource-intensive characteristic of the SMA would affect its scale-up and equity in various PHC settings.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Background","content":"\u003cp\u003ePeople with diabetes (PWD) is a major global health concern and a leading cause of morbidity and mortality, with a rapid increase worldwide \u003csup\u003e[1]\u003c/sup\u003e. In 2021, there were 537\u0026nbsp;million PWD, accounting for 6.1% of the world population, which was expected to rise to 9.8% (1.31\u0026nbsp;billion) by 2050 \u003csup\u003e[2]\u003c/sup\u003e. PWD can lead to serious complications in multiple organs, such as blindness, heart attacks, and lower limb amputation \u003csup\u003e[3]\u003c/sup\u003e. According to the World Health Organization, PWD caused 1.5\u0026nbsp;million direct deaths worldwide in 2019, a 3% increase from 2010 \u003csup\u003e[4]\u003c/sup\u003e. The increasing prevalence, high avoidable morbidity and mortality, and huge economic burden make diabetes a significant global health challenge \u003csup\u003e[5, 6]\u003c/sup\u003e. Addressing the increasing global disease burden of PWD requires an affordable, feasible, and cost-effective comprehensive approach at the system level instead of the individual level, and one such approach is shared medical appointment (SMA) \u003csup\u003e[7]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn SMA services, multidisciplinary medical treatment and health management providers successively provide medication consultation, physical examination, treatment, and health management services for a group of PWD with similar conditions in a consulting room \u003csup\u003e[8]\u003c/sup\u003e. The medical team typically includes at least one physician with prescribing rights and several trained or qualified staff, such as nurses, nutritionists, and psychologists \u003csup\u003e[9, 10]\u003c/sup\u003e. PWD can receive interactive education about their treatment options and share their personal experiences related to PWD management in a group consultation \u003csup\u003e[11]\u003c/sup\u003e. Several literature reviews have demonstrated that SMA is effective in improving PWD's clinical and behavioral outcomes, reflected as improved biochemical indicators, such as Hemoglobin A1c (HbA1c) and Systolic Blood Pressure (SBP), and healthier lifestyles such as diet control and exercise \u003csup\u003e[7, 12, 13]\u003c/sup\u003e. Thus, SMA represents a promising evidence-based practice (EBP) for addressing the challenges of diabetes control in other settings.\u003c/p\u003e \u003cp\u003eHowever, in the existing study, the SMA services were a resource-intensive complex intervention conducted in well-resourced settings \u003csup\u003e[9, 11]\u003c/sup\u003e. While most previous SMA evaluations focused only on the effectiveness of the interventions, leaving researchers and practitioners with little information about the generalizability of the intervention context, practitioners, conditions, and findings \u003csup\u003e[14]\u003c/sup\u003e. There was insufficient evidence of system and process evaluation on SMA's context, mechanisms, complexity of the SMA intervention package (i.e., various components combinations), and outcomes (e.g., SMA effectiveness, management efficiency, costs, and fidelity of research), which was essential to translate the knowledge from interventions to policy and practice \u003csup\u003e[15]\u003c/sup\u003e, particularly for improving healthcare quality in primary healthcare (PHC) settings in low- and middle- income countries (LMICs)\u003csup\u003e[16]\u003c/sup\u003e. These limitations will constrain further implementation to improve the feasibility, scalability, and equity of SMA implementation in PWD and people with other chronic conditions in varied PHC settings. If an effective intervention is too complex and demands too many resources for a real-world frontline setting, it cannot be scaled up \u003csup\u003e[17]\u003c/sup\u003e. Furthermore, this may limit the equitable access to high-quality EBP for individuals, especially in resource-limited communities \u003csup\u003e[18, 19]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe RE-AIM framework is one of the most frequently used frameworks to guide the design, implementation, and assessment of research programs to make the findings more generable and practical in real-world community settings \u003csup\u003e[20]\u003c/sup\u003e. RE-AIM is an acronym for the following five evaluation dimensions under two categories \u003csup\u003e[21, 22]\u003c/sup\u003e: Reach (R) and Effectiveness (E) at the individual level, and Adoption (A), Implementation (I), and Maintenance (M) at both the individual and setting level. The RE-AIM framework can improve transparency in reporting the critical components of an intervention and is particularly useful in the adoption, scaling, and maintenance of an effective intervention \u003csup\u003e[23, 24]\u003c/sup\u003e. Applying the RE-AIM framework, this systematic review and meta-analysis aimed to comprehensively summarize the effects of SMA on PWD by providing updated quantitative and qualitative evidence, which will inform the feasibility, scalability, and equity of future SMA implementation \u003csup\u003e[25]\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThe systematic review is reported in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 checklist \u003csup\u003e[26]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eA protocol was registered with the International Prospective Register of Systematic Reviews (PROSPERO) on 28 November 2019 (registration number CRD42019134273).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEligibility criteria\u003c/h2\u003e \u003cp\u003eThe inclusion/exclusion criteria were based on Populations, Intervention, Comparison, Outcome, and Study (PICO) design principles and research questions. Eligible study designs included randomized controlled trials (RCTs), non-randomized cluster-controlled trials, pre/post-design studies, and interrupted time-series designs. Other observational and qualitative studies on the economic costs and doctor-patient experiences were discussed in the results but not included in the statistical analysis.\u003c/p\u003e \u003cp\u003eWe included studies on SMA interventions that satisfy the following conditions: (1) in an outpatient setting; (2) with at least two medical visits over time; (3) intervention duration of more than three weeks; (4) including at least two patients in the same clinical setting; (5) involving at least one prescribing clinician; (6) addressing each patient's unique medical needs individually. The detailed characteristics of the criteria are shown in Appendix 1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData sources and search strategy\u003c/h2\u003e \u003cp\u003eWe searched the following databases for literature comparing the effectiveness of SMA and usual care in PWD from January 2012 to February 2024: PubMed, EMBASE, EBSCO, CINAHL, PsycINFO, Web of Science, CNKI, and Wan Fang. This review followed the same search strategy as Edelman et al.\u0026rsquo;s previous study \u003csup\u003e[27]\u003c/sup\u003e, including four search terms: group appointments, shared visits, interventions, and observational studies, and included papers in English and Chinese. In addition, our study population was limited to adults aged 18 years or older. See Appendix 2 for an overview of the search strategy. We looked for non-published studies in clinical trials to mitigate the risk of publication bias (available at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.clinicaltrials.gov/\u003c/span\u003e\u003cspan address=\"https://www.clinicaltrials.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), manually searched reference lists, and tracked citations to identify additional literature.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eStudy quality assessment\u003c/h2\u003e \u003cp\u003eTwo reviewers assessed the methodological quality of the included studies according to the Agency for Healthcare Research and Quality's Methodological Guidelines for Review of Validity and Comparative Effectiveness \u003csup\u003e[28]\u003c/sup\u003e. Ratings were based on information richness reported in the literature regarding SMA for PWD. Any disagreement between the two reviewers was resolved by a third expert who was familiar with the study. This quality assessment method can help assess the risk of bias, the strength of the evidence, and the applicability of the included studies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData collection and extraction\u003c/h2\u003e \u003cp\u003eAfter removing the duplicates, four researchers used the eligibility criteria to screen the title and abstract. The full text was reviewed in more detail based on a preliminary review. Concerning differences in full-text screening, researchers met to discuss and reach a consensus.\u003c/p\u003e \u003cp\u003eFour researchers conducted data extraction independently using a predesigned Excel sheet. They compared their data extraction results and discussed any disagreements or revisions until a consensus was reached. Standardized tables were used to extract data and collect documentation. The data mainly consisted of six aspects: (1) Study characteristics: author, year, research design, and research setting; (2) SMA intervention characteristics: period, number of visits, composition of SMA service team, intervention patterns, and procedures; (3) RE-AIM framework contents: reach, effectiveness, adoption, implementation, and maintenance; (4) Outcome components: biochemical indicators, adherence, symptom severity and patient quality of life at effectiveness and maintenance dimensions, patient and staff experiences of participating SMA, staff-related indicators, and economic-related indicators at adoption, implementation and maintenance dimensions ; (5) Discussion: limitations, and future directions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eData Synthesis and Analysis\u003c/h2\u003e \u003cp\u003eWe conducted a meta-analysis on RCTs to evaluate the combined effect of intervention by comparing the means and changes in the biometrics between the intervention and control groups after the intervention. Heterogeneity between studies was assessed using Foster's plots and test statistics (Cochran's \u003cem\u003eQ\u003c/em\u003e and \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e), with a \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.10 or an \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;50 indicating significant heterogeneity. In addition, we performed subgroup analyses of categorical variables using a random effects model When \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026gt;\u0026thinsp;50 or a fixed-effects model otherwise. All statistical analyses were conducted through Review Manager 5.4. When meta-analysis was not appropriate, qualitative summaries were performed.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eSearch results\u003c/h2\u003e \u003cp\u003eAmong the 885 citations initially identified through a complete database search, 217 were retrieved after the title and abstract screening. After screening for full text, 31 studies met inclusion criteria and were included in our final analysis. In addition, we added three studies through a manual search of the reference lists and another 13 RCT studies in the previous systemic review. Therefore, 47 studies contributed findings to the review, including 24 RCT studies for meta-analysis \u003csup\u003e[29\u0026ndash;52]\u003c/sup\u003e and 23 observational studies for qualitative analysis \u003csup\u003e[53\u0026ndash;75]\u003c/sup\u003e (Fig.\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 1 Literature flow diagram\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eStudy characteristics\u003c/h2\u003e \u003cp\u003eAll 47 studies have compared the differences in treatment outcomes between SMA and usual one-on-one care. Most studies used Hemoglobin A1c (HbA1c) as the primary outcome, and some studies also included SBP, total cholesterol (TC), and low-density lipoprotein (LDL-c). The intervention duration was \u0026ge;\u0026thinsp;1 year in 26 studies, between six months to 1 year in 13 studies, and \u0026lt;\u0026thinsp;six months in 8 studies. Regarding quality, 18 were good, 20 were fair, and nine were poor (Appendix 3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eSMA intervention characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the characteristics of SMA intervention. Most interventions were implemented through specialty clinics in hospitals and primary healthcare centers. Thirty interventions were conducted in multiple centers. The median duration of the total intervention and each session were 12 months and 120 minutes, respectively. The median number of scheduled visits and patients per group were 7 (range: 6 to 12) and 10 (range: 8 to 13), respectively. The intervention team included a median of 4 (range: 3 to 7) members, mainly composed of clinicians (internists or endocrinologists or general practitioners) (74.5%), nurses (70.2%), and pharmacists (40.4%). Most studies' intervention frequency was once a month (40.4%).\u003c/p\u003e \u003cp\u003eThis review also assessed the provision of health education, psychological interventions, daily management, and dietary adjustments for patients, as well as the interaction with family and friends during their treatment process. The findings indicate that a vast majority of studies (89.4%) reported the implementation of health education. Beyond health education, 70.2% of studies implemented additional services such as psychological interventions, daily management, and dietary adjustments. Furthermore, in 83.0% of the studies, patients had the opportunity to share experiences and interact with others during the intervention process. However, only 25.5% of the studies reported that patients\u0026rsquo; family and friends were involved in the treatment process.\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\u003eSMA intervention characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en (%) or \u003cem\u003eM(IQR)\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSettings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity-based healthcare settings (i.e., PHC settings)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27(57.45)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpecialized Clinic in Government (VA, FQC) or University-affiliated clinic or Private clinic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20(42.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDuration of intervention (months) [\u003cem\u003eM (Q\u003c/em\u003e\u003csub\u003eL\u003c/sub\u003e, \u003cem\u003eQ\u003c/em\u003e\u003csub\u003eU\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (6 to 17)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAverage visit duration (mins) [\u003cem\u003eM (Q\u003c/em\u003e\u003csub\u003eL\u003c/sub\u003e, \u003cem\u003eQ\u003c/em\u003e\u003csub\u003eU\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e120 (90 to 120)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTimes of planned visits [\u003cem\u003eM (Q\u003c/em\u003e\u003csub\u003eL\u003c/sub\u003e, \u003cem\u003eQ\u003c/em\u003e\u003csub\u003eU\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6 to 12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of patients per group [\u003cem\u003eM (Q\u003c/em\u003e\u003csub\u003eL\u003c/sub\u003e, \u003cem\u003eQ\u003c/em\u003e\u003csub\u003eU\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (8 to 13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention team size [\u003cem\u003eM (Q\u003c/em\u003e\u003csub\u003eL\u003c/sub\u003e, \u003cem\u003eQ\u003c/em\u003e\u003csub\u003eU\u003c/sub\u003e\u003cem\u003e)\u003c/em\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (3 to 7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention team disciplines [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinicians(endocrinologists)/General Practitioners\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (74.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNurses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (70.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePharmacists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (40.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychologists (Counselors)/Behaviorists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutritionists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (21.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic health physicians/diabetes educators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(17.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysiotherapists/exercise specialists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSocial workers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical assistant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResearchers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervention team combinations [n (%)] \u003csup\u003eB\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinician\u003c/b\u003e, nurse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinician\u003c/b\u003e, nurse, public health doctor, others \u003csup\u003eC\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (51.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinician\u003c/b\u003e, public health doctor, others \u003csup\u003eD\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinician\u003c/b\u003e, others \u003csup\u003eE\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther \u003csup\u003eF\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (6.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of intervention [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce /week\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce/2 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce/3 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19 (40.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce/2 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (4.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce/3 months\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (8.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6 times/month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eonce/6 month\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(2.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe research interventions with uneven frequency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (17.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (14.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailability of health education [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (89.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (10.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhether there is psychological intervention, daily management, or diet adjustment outside of education [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (70.2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (29.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAvailability of experience sharing/interaction [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (83.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (17.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhether there are family/friends involved [n (%)]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (25.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot reported\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (74.5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003cem\u003eNote\u003c/em\u003e: PHC setting: Primary healthcare setting, including the adult primary care center\u003csup\u003e[31, 32]\u003c/sup\u003e, community health centers\u003csup\u003e[30, 36, 37, 44, 47]\u003c/sup\u003e, non-profit community clinic\u003csup\u003e[29, 59]\u003c/sup\u003e. \u003cem\u003eM\u003c/em\u003e: Median; \u003cem\u003eIQR\u003c/em\u003e: Inter-Quartile Range; VA: department of veterans affairs; FQC: federally qualified center.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eA: Community health center director, clerical staff, front office administrator.\u003c/p\u003e \u003cp\u003eB: All clinicians had rights to prescribe.\u003c/p\u003e \u003cp\u003eC: Other providers were pharmacists, nutritionists, social workers, secretary, behaviorists, psychologists, medical assistants, researchers, exercise specialists, physiotherapists, counselors, and/or research assistants.\u003c/p\u003e \u003cp\u003eD: Other providers were receptionist, psychologists, nutritionists, and/or medical assistants.\u003c/p\u003e \u003cp\u003eE: psychologist, pharmacist, and/or researchers.\u003c/p\u003e \u003cp\u003eF: Other providers were pharmacists, nurses, nutritionists, and/or physiotherapists.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eSMA intervention tasks\u003c/h2\u003e \u003cp\u003e The review summarized the implementation process of the SMA intervention, which included ① Self-introduction among patient participants and a description of their medical history, current glucose-lowering regimen, and effect of glycemic control. ② Individual counseling involves patients asking questions and getting physical examinations in turn, with medication adjustments made when necessary. ③ Collective discussion: the intervention team discusses and exchanges information with patients and their families on the key concerns individually and encourages patients to share their experience in self-glycemic control. The SMA services team will provide guidance and summarize this intervention\u0026rsquo;s unique and joint problems. ④Health education: the SMA services team will use different health education methods to explain various aspects of PWD management, including medication, diet, and exercise. Individuals providing SMA interventions are categorized into two major groups: clinical medicine and public health. Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e lists the specific tasks of SMA interventions provided by different personnel.\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\u003eProviders Roles of different types of health service providers in SMA\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProviders\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eResponsibilities\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedical service providers\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eClinicians(endocrinologists) / General Practitioners\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Conduct individual/group-based consultations with patients.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2. Review patients\u0026rsquo; biochemical testing results.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3. Provide medication and behavioral interventions and modifications if necessary.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNurses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Conduct initial assessment of patient status and complete health education courses.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2. Physical examination: testing weight, height, blood pressure, and waist circumference, blood sampling for blood glucose, HbA1c, and urinalysis test, as well as other tests as applicable.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3. Medication adjustments (registered nurse only)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePharmacists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1. Conduct comprehensive medication management for patients, including clinical assessment and development of treatment plans.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2. Medication guidance.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePublic health service providers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePsychologists (Counselors)/Behaviorists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePsycho-education: providing behavior education, stress coping and motivational skills training to improve self-management and self-efficacy.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNutritionists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealthy diet education: nutritional knowledge and skills, including carbohydrate counting and the plate methods.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePublic health physicians/diabetes educators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth education: providing healthy eating, physical activity, etc.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysiotherapists/exercise specialists\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth education: providing exercise instruction, behavioral interventions, etc.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eRE-AIM-based SMA outcomes\u003c/h2\u003e \u003cp\u003eWe used the RE-AIM framework to summarize the study results by each element (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). To increase transparency in reporting, we divided the reporting into 5 phases: enrollment, baseline of trial, mid-term of trial, endline of trial, and follow-up. The results from the follow-up phase were regarded as the maintenance results of the RE-AIM framework.\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\u003eRE-AIM indicators with the number and percent of studies reporting each indicator (N\u0026thinsp;=\u0026thinsp;47)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eRE-AIM dimensions and components\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e \u003cp\u003eThe proportion of reports per study period (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eEnrolment\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBaseline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMid-term\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eEndline\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eFollow-up (\u003cb\u003eMaintenance: The extent to which SMA was consistently implemented after the study ended\u003c/b\u003e)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReach: Number, proportion, and representativeness of diabetic patients participating in SMA who met inclusion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe number of patients recruited\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe number of patients recruited as a percentage of the target population\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe number of patients who joined halfway through the project\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe proportion of patients joining midway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe number of patients who dropped out in the middle of the project\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e44.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eThe proportion of patients who withdrew midway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEffectiveness: Effectiveness of SMA interventions at the patient level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePatient biochemical indicators \u003csup\u003eA\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHbA1c\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e85.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e83.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBlood lipids (TC, LDL-c, HDL-c, TG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePatient physical and behavioral indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatient quality of life\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedication compliance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ediet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e21.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetic self-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e29.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDiabetes management behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e34.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eThe cost of patient access to care\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCumulative number of hospitalizations, days, and costs due to diabetes exacerbations or complications during the trial period\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePatients' treatment effect (cured, improved, ineffective) after each hospitalization\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdoption: Number, proportion, and representation of institutions and physicians participating in SMA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIndicators at the level of medical institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number and reasons for participating institutions and their representation in the study\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e68.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number and reasons for the withdrawal or addition of institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePhysician-level indicators\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of doctors involved in the study and why, and their representation in the program\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe number of doctors who dropped out or joined in the midway\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eImplementation: The extent to which the implementation was completed according to the researcher's requirements (i.e., \"fidelity\"), the localization of SMA implementation process, and the cost of SMA implementation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFidelity of implementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe proportion of physicians performing and completing SMA intervention packages and reasons\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe extent to which the project is being implemented as originally planned\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDuration and frequency of intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCost of implementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eThe cost of money and staff time spent during SMA implementation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003e\u003cem\u003eNote\u003c/em\u003e: HbA1c: HemoglobinA1c; BP: Blood pressure; FG: Fasting plasma glucose; TC: total cholesterol; LDL-c: low-density lipoprotein cholesterol; HDL-c: high-density lipoprotein cholesterol; TG: triglyceride; BMI: Body mass index\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eReach\u003c/h2\u003e \u003cp\u003e \u003cem\u003eReach\u003c/em\u003e refers to the number, proportion, and representativeness of diabetic patients participating in SMA who met the inclusion criteria. During the enrolment phase, all studies reported the number of patients recruited. The proportion of patients recruited at the enrollment stage was 38.3%. The number and proportion of patients who dropped out at mid-term trials were 44.7% and 36.2%, respectively.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eEffectiveness\u003c/h2\u003e \u003cp\u003e \u003cem\u003eEffectiveness\u003c/em\u003e refers to the effectiveness of the SMA intervention at the patient level. It includes three secondary indicators: patient biochemical indicators, physical and behavioral indicators, and the cost of patient access to care.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003ePatient biochemical indicators\u003c/h2\u003e \u003cp\u003eOf the 24 RCT studies, 18 focused on type 2 diabetes \u003csup\u003e[29\u0026ndash;32, 34, 36\u0026ndash;38, 40, 43, 44, 46\u0026ndash;50]\u003c/sup\u003e, five investigated mixed populations \u003csup\u003e[33, 35, 39, 41, 45]\u003c/sup\u003e, and only one investigated type 1 diabetes \u003csup\u003e[42]\u003c/sup\u003e. All diabetic patients had been diagnosed with HbA1c or poor glycemic control. 24 RCT studies compared the SMA intervention with usual care or other strategies. Some studies also used diabetes-related risk factors (e.g., SBP, TC, and LDL-c) as secondary outcome indicators.\u003c/p\u003e \u003cp\u003eAmong the various biochemical indicators, HbA1c was the most frequently reported at each stage: 85.1% at the trial's baseline,27.7% at the mid-term, and 83.0% at the endline. FG was less frequently reported, with a maximum reporting rate of 17.0%. Blood lipids (TC, LDL-c, HDL-c, TG) were reported by 61.7% of studies at the trial's baseline, 17.0% at mid-term, and 55.3% at the endline. BP was reported by 53.2% of studies at the baseline, 14.9% at the mid-term, and 55.3% at the endline. BMI was reported by 6.4% of studies at the baseline, 6.4% at the mid-term, and 38.3% at the endline.\u003c/p\u003e \u003cp\u003eThe review results of the leading biochemical indicators involved in the studies are reported below (Fig.\u0026nbsp;2). First, 22 RCT studies reported HbA1c levels or changes after SMA intervention \u003csup\u003e[30\u0026ndash;35, 37\u0026ndash;46, 50, 52]\u003c/sup\u003e. Compared with the conventional treatment group, the SMA intervention group had reduced HbA1c levels by 0.38% (95% \u003cem\u003eCI\u003c/em\u003e: -0.55, -0.21), a statistically significant difference. In 15 observational studies, the effects of SMA interventions were consistent with proximate RCT investigations except for two studies \u003csup\u003e[53\u0026ndash;58, 60\u0026ndash;62, 70, 71]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSecond, 16 RCT studies included SBP levels or changes after SMA treatment as a secondary outcome \u003csup\u003e[29, 30, 33, 35\u0026ndash;37, 40, 41, 44, 46\u0026ndash;49]\u003c/sup\u003e. SBP levels were reduced by 3.24% (95% \u003cem\u003eCI\u003c/em\u003e: -4.71, -1.77) in the SMA intervention group compared to the conventional treatment group. Eight observational studies reported SBP outcomes, yet with inconsistent results. In six of the eight studies \u003csup\u003e[53, 55, 56, 60, 65, 75]\u003c/sup\u003e, the pre-and post-SBP changes between the SMA intervention and conventional treatment groups were not significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The results of the other two studies were consistent with the meta-analysis and supported using SMA intervention to improve SBP \u003csup\u003e[61, 62]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThird, seven RCTs reported TC as a predictor of glycemic control after SMA treatment \u003csup\u003e[31, 37, 42\u0026ndash;45, 49]\u003c/sup\u003e. The results showed a non-significant association between SMA and TC decline at the 95% confidence level (mean difference: -0.08 mg/dl [95% \u003cem\u003eCI\u003c/em\u003e: -0.20, 0.03]). Four observational studies reported the results of SMA intervention on TC control, with two showing no significant effect \u003csup\u003e[55, 60]\u003c/sup\u003e and two showing a significant therapeutic effect of SMA in improving TC \u003csup\u003e[62, 75]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eFinally, nine RCTs showed that SMA did not significantly improve LDL-c (95% \u003cem\u003eCI\u003c/em\u003e: -3.99, 4.66) compared with conventional treatment modalities at the 95% confidence level \u003csup\u003e[53, 55, 56, 65, 75]\u003c/sup\u003e. Seven observational studies reported biochemical findings related to LDL-C, with five studies showing no significant effect and two studies showing a significant therapeutic effect of SMA in improving TC \u003csup\u003e[57, 62]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2 Biochemical Indicators Forest Plots: SMA Group vs. Usual Care\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eHeterogeneity Analysis\u003c/h2\u003e \u003cp\u003eHeterogeneity analysis was conducted by calculating the percentage heterogeneity between studies included in the meta-analysis that was not due to chance (see Appendix 4 for the sensitivity analysis results).\u003c/p\u003e \u003cp\u003eFirst, we performed sensitivity analyses for HbA1c and SBP. For HbA1c, although there were significant differences in treatment effects between studies, heterogeneity improved after excluding three studies \u003csup\u003e[32, 39, 47]\u003c/sup\u003e, with a mean difference of -0.29% (\u003cem\u003eQ\u003c/em\u003e: 51.83; \u003cem\u003eDF\u003c/em\u003e: 18; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1; \u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e: 65); [95% \u003cem\u003eCI\u003c/em\u003e: -0.42, -0.15]) (Appendix 4a). For SBP, sensitivity analysis showed significantly lower heterogeneity after excluding 1\u003csup\u003e[47]\u003c/sup\u003e biased study, with a mean difference of -2.75% (\u003cem\u003eQ\u003c/em\u003e: 14.16; \u003cem\u003eDF\u003c/em\u003e: 11; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.1; \u003cem\u003eI\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e: 22); [95% \u003cem\u003eCI\u003c/em\u003e: -3.37, -2.14]) (Appendix 4b). The results of the subgroup analysis confirmed that the SMA intervention contributed to the improvement of HbA1c and SBP in diabetic patients.\u003c/p\u003e \u003cp\u003eSecond, we performed a subgroup analysis by dividing the study settings into PHC and non-PHC. For HbA1c, 15 studies were conducted in PHC and reported HbA1c as an outcome \u003csup\u003e[29\u0026ndash;34, 37\u0026ndash;39, 41, 44, 45, 47, 49, 50, 52]\u003c/sup\u003e. The mean reduction in HbA1c was 0.50% (95% \u003cem\u003eCI\u003c/em\u003e: -0.79, -0.21) in the PHC setting and 0.20% (95% \u003cem\u003eCI\u003c/em\u003e: -0.37, -0.04) in the non-PHC setting (Appendix 4c). Regarding SBP, nine studies were conducted in PHC and reported SBP as having an outcome of \u003csup\u003e[29, 30, 33, 36, 37, 41, 44, 47, 49]\u003c/sup\u003e. SBP decreased more in PHC subjects than non-PHC, with a mean reduction of -4.38 percentage points (95% \u003cem\u003eCI\u003c/em\u003e: -6.17, -2.60) in the PHC setting (Appendix 4d).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec18\" class=\"Section2\"\u003e \u003ch2\u003ePsych behavioral indicators\u003c/h2\u003e \u003cp\u003eThirty-nine studies reported five psych behavioral indicators by stage; each described as below: (1) Quality of life: enrolment (48.9%), mid-term of trial (2.1%), endline of trial (6.4%);(2) Medication compliance: enrolment (19.1%), mid-term of trial (6.4%), endline of trial (29.8%); (3) Diet: enrolment (34.0%), mid-term of trial (0), endline of trial (21.3%); (4) Diabetes self-efficacy: enrolment (19.1%), mid-term of trial (4.3%), endline of trial (29.8%); (5) Diabetes management behaviors: enrolment (22.4%), mid-term of trial (4.3%), endline of trial (34.0%).\u003c/p\u003e \u003cp\u003eOne pre-post controlled study and two RCTs found that the SMA intervention improved patients' perceptions of PWD \u003csup\u003e[32, 44, 57]\u003c/sup\u003e, which may indirectly improve medication adherence. Five studies of patients' diets reported that the SMA intervention led to healthier eating habits \u003csup\u003e[36, 47, 51, 66, 75]\u003c/sup\u003e. Studies also showed that SMA significantly improved PWD\u0026rsquo; diabetes self-efficacy and self-management behaviors, such as blood glucose self-monitoring \u003csup\u003e[36, 38, 51, 58, 66, 67, 69, 70, 73, 75]\u003c/sup\u003e. One study showed no effect of SMA on PWD\u0026rsquo; exercise levels \u003csup\u003e[47]\u003c/sup\u003e. An RCT and an observational study showed that patients in the SMA group underwent physical examinations (e.g., foot exams, eye exams, and lipid screenings) more frequently. This can allow patients to meet other patients with the same health problems, exchange their experiences, and receive peer support, which can motivate them to adopt healthier behaviors and feel more accomplished \u003csup\u003e[47, 56]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eHealthcare cost\u003c/h2\u003e \u003cp\u003eEight studies reported data on healthcare costs (Appendix 5), including the accumulative number of hospitalizations, days, and expenses due to diabetes exacerbations or complications during the trial period. This information was reported as baseline (2.1%), mid-term (8.5%), and endline (12.8%). However, no studies reported patients\u0026rsquo; therapeutic outcomes after each hospitalization (cured, improved, failure).\u003c/p\u003e \u003cp\u003eTwo studies showed no statistical difference in outpatient costs between the SMA and usual care groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.19) \u003csup\u003e[45, 76]\u003c/sup\u003e. Another study reported higher total expenditure in the SMA group than in the usual care group (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0003) \u003csup\u003e[31, 35]\u003c/sup\u003e. However, the opposite results were reported by three other studies\u003csup\u003e[31, 32, 46]\u003c/sup\u003e. They showed that the total costs were lower in the SMA intervention than in the control group. Two studies reported the cost of participating in SMA but did not report statistical differences \u003csup\u003e[33, 42]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSix studies reported the impact of SMA on hospital visits, such as admissions, emergency room visits, and primary care visits (Appendix 6). Two studies reported that PHC ensured at least one patient visit and intervention during the SMA intervention \u003csup\u003e[33, 45]\u003c/sup\u003e. Another four studies did not find differences in patient emergency room visits, hospitalization rates, or primary care visits between the SMA intervention and usual care groups \u003csup\u003e[35, 39, 40, 47]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eAdoption\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eadoption\u003c/em\u003e domain includes two indicators: medical institutions and physician-level. During the enrolment phase, the majority of studies reported: \"the number and reasons for participating institutions and their representation in the study\" (68.1%) and \u0026ldquo;the number of doctors involved in the study and their representation in the program\u0026rdquo; (63.8%). Only 2.1% of studies reported \"the number and reasons for the withdrawal or addition of institutions\" at the mid-term of the trial.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eImplementation\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eimplementation\u003c/em\u003e domain includes two indicators: fidelity and cost of implementation. In terms of the fidelity to trial implementation, all studies reported the duration and frequency of the intervention during the recruitment phase. A lower proportion (0 to 4.3%) reported other dimensions and grade indicators. None of the studies reported implementation costs for institutional-level stakeholders.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eMaintenance\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003emaintenance\u003c/em\u003e domain refers to how SMA was consistently implemented and patients\u0026rsquo; health outcomes after the study ended. However, studies reporting maintenance levels of institutional indicators were minimal (0 to 4.3%) and mainly focused on patient biochemical indicators. Of the 47 included studies, the core indicators with reported maintenance levels were FG (2.1%), BP (4.3%), and BMI (4.3%). In addition, a few studies reported the cumulative number of hospitalizations, days, and costs due to worsening diabetes or complications during the project period (4.3%).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis review summarized 24 RCTs and 23 observational studies. It systematically assessed the effectiveness of SMA interventions in diabetes management according to the guidelines of the five dimensions of the RE-AIM framework: reach, effectiveness, adoption, implementation, and maintenance. However, the report of each dimension was unbalanced, each discussed below:\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eEffectiveness\u003c/h2\u003e \u003cp\u003eIn line with the results of previous systematic reviews \u003csup\u003e[77, 78]\u003c/sup\u003e, we found type 2 PWD who benefited more from the SMA intervention than type 1 PWD. Although a few studies have reached opposite conclusions \u003csup\u003e[32, 45, 46, 55]\u003c/sup\u003e, most studies have demonstrated that SMA improved HbA1c and SBP and reduced hospitalizations due to hyperglycemia or complications among PWD. In addition, SMA interventions can potentially improve self-management behaviors and health outcomes in PWD. However, the risk of macrovascular and microvascular complications usually increases with the duration of PWD \u003csup\u003e[79]\u003c/sup\u003e. Therefore, the impact of SMA on preventing complications may be underestimated in interventions targeting early patients. Qualitative interviews revealed that most patients felt that SMA was time-efficient without incurring extra costs \u003csup\u003e[56]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs the number of PWD continues to increase, there is a growing tension between the increased need for PWD care and the limited healthcare workforce. Wu suggested promoting SMA in PHCs to avoid competition with hospital referrals and specialty providers \u003csup\u003e[46]\u003c/sup\u003e. Lou and Liu noted that SMA interventions in PHCs positively impacted patient attendance due to high efficiency and low cost \u003csup\u003e[36, 37]\u003c/sup\u003e. Implementing SMA in non-PHC settings may reduce patient compliance and attendance \u003csup\u003e[59]\u003c/sup\u003e. In contrast, PHCs are located in the local communities, which may minimize attendance time and financial costs. One study pointed out a gap between PHCs and specialty hospitals in managing PWD and that PHCs lacked sufficient medical equipment and a workforce to meet the needs of patients \u003csup\u003e[80]\u003c/sup\u003e. However, another study showed that PHC providers had better connections with local patients regarding daily visits and communication, thus bridging the care gap with PWD specialty hospitals \u003csup\u003e[44, 54]\u003c/sup\u003e. Furthermore, similar to other evidence-based practices implemented in PHC settings \u003csup\u003e[16, 81]\u003c/sup\u003e, SMA would be a possible way to address the equity of access to practical, evidence-based innovations for patients with PWD in communities. Therefore, it is essential to strengthen the collaboration between PWD specialty hospitals and local PHCs to provide more training to PHCs to ensure adequate disease management \u003csup\u003e[50]\u003c/sup\u003e and improve healthcare equity \u003csup\u003e[16]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAlthough the study showed the positive effectiveness of PHCs, which are mainly responsible for patients' daily treatment and health management in LMICs, we find that most studies contained more than two service providers. Besides, the SMA services were abundant, varied, and complex. The SMA was still a highly resource-demanded intervention. However, in resource-limited settings, its feasibility and scalability would face a lot of challenges, especially in lacking of human resources. Furthermore, its complex services would require more investigation, including the cost of staff and working hours. This would raise the medical services fee and exceed the patients\u0026rsquo; affordability, especially in rural communities in LMICs \u003csup\u003e[82]\u003c/sup\u003e. Furthermore, this would increase the health inequity in different resource-distribution areas, especially in vulnerable populations in LMICs \u003csup\u003e[83]\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eReach, Adoption, Implementation, and Maintenance\u003c/h2\u003e \u003cp\u003eThe included studies reported poor results on the reach, adoption, implementation, and maintenance dimensions. When researchers scale up an EBP from a highly restrictive experimental setting to real-world community settings, the implementability of the EBP will face challenges from the patient's reach and the providers' adoption \u003csup\u003e[84, 85]\u003c/sup\u003e. This study found that the included studies were conducted in resource-adequate settings. If future studies were conducted in other diverse and resource-limited settings, the external representation of the reach of patients and the adoption and complete implementation of providers would be an issue.\u003c/p\u003e \u003cp\u003eNone of the studies reported on physicians performing and completing SMA intervention packages or the costs of institutional-level stakeholder implementation. Previous studies have evaluated the duration of SMA visits and found that SMA was malleable in terms of time costs, clinical workload, and other measurable outcomes. SMA has been shown to be a feasible and cost-effective approach compared to conventional models \u003csup\u003e[33]\u003c/sup\u003e. Meanwhile, if all cost information on the institutional side is explored in depth in future studies to confirm that the benefits of SMA were maximized for both patients and institutions, it would be helpful to other researchers to transfer the SMA model to other settings.\u003c/p\u003e \u003cp\u003eMaintenance refers to the long-term effect of EBP and the sustained implementation of SMA. A few studies have reported the long-term effects of some of the indicators of SMA \u003csup\u003e[29, 33, 40, 46\u0026ndash;48, 75]\u003c/sup\u003e. However, there were no studies on the sustained implementation of SMA. A lack of focus on sustainability will result in a waste of investigation from research and human resources \u003csup\u003e[86]\u003c/sup\u003e. Future studies should focus on the sustainability of EBP, including both the long-term effect of EBP and its implementation. The assessment of EBP\u0026rsquo;s sustainability and its influencing factors are also important to improve the sustainability\u003csup\u003e[87]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn our meta-analysis, we observed considerable heterogeneity among the studies included. While we were able to attribute this heterogeneity partly to certain biased studies, the SMA, which was a complex intervention package, would be the main source of heterogeneity. Although the SMA has been shown to improve patient health outcomes overall, it remains challenging to determine which specific component(s) or combination (i.e., configurations) thereof are mainly responsible for these improvements. Given the complexity of SMAs, their implementation in resource-limited settings raises concerns. Such environments often suffer from shortages in human resources, financial constraints, and a lack of diverse healthcare specialists, which may hinder the adoption of effective SMA configurations. Consequently, future research should employ the multiphase optimization strategy (MOST)-guided optimization trial \u003csup\u003e[87, 88]\u003c/sup\u003e to dissect the component's main effects and interactive effects among the SMA components. This approach will not only enhance our understanding of each component's impact but also improve the scalability and implementability of SMAs, thereby ensuring broader applicability and effectiveness in diverse clinical settings.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eBased on the RE-AIM framework, our review showed that SMA intervention effectively reduced PWD' HbA1C, SBP, and healthcare costs. The findings suggest the superiority of SMA in primary care for effectively controlling PWD' biochemical indices. However, we should notice that the SMA was a highly resource-intensive complex intervention. Its reach, adoption, implementation, and maintenance would face challenges, such as investigation constraints and human resources limitations in LMICs. The next step in SMA research for PWD should be an optimization phase that focuses on confirming its main effect and interaction effect on its different components. Empirical evidence for SMA interventions conducted in resource-limited areas would be demanded. In addition, future studies should address the shortcomings identified in the review by accurately assessing the implementation process, cost, sustainability, and equity of SMA implementation.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"590\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eBP \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eBlood Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eBody Mass Index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eEBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eEvidence-Based Practices\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eFG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eFasting Glucose\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eFQC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eFederally Qualified Center\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eHbA1c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin A1c\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eHDL-c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eHigh-Density Lipoprotein cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eInter-Quartile Range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eLDL-c\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eLow-Density Lipoprotein cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eLMICs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eLow- and Middle- Income Countries\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eMOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eMulti-stage Optimization\u0026nbsp;Strategy\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003ePHC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary Healthcare\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003ePICOS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003ePopulations, Intervention, Comparison, Outcome, and Study\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003ePRISMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003ePreferred Reporting Items for Systematic Reviews and Meta-Analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003ePROSPERO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eProspective Register of Systematic Reviews\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003ePWD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003ePeople With Diabetes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eRCT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eRandomized Controlled Trial\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eRE-AIM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eReach, Effectiveness, Adoption, Implementation, and Maintenance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eSBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eSystolic Blood Pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eSMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eShared Medical Appointment\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eTC\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eTotal Cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eTG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eTriglyceride\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.185059422750424%\" valign=\"top\"\u003e\n \u003cp\u003eVA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"80.81494057724957%\" valign=\"top\"\u003e\n \u003cp\u003eDepartment of Veterans Affairs\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eNo additional data are available.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eThis work was supported by the National Natural Science Foundation of China (NNSFC) [grant 72164005], and China Medical Board Open Competition Grant, grant number CMB16-260.\u003c/p\u003e\n\u003ch2\u003eAuthors\u0026apos; contributions\u003c/h2\u003e\n\u003cp\u003eWY: Data extraction, verification, and manuscript writing. RM: Data extraction and verification. ZhL, ZyL, JW, RW, XL, and ML: Formulating search strategies and extracting data. YC and DRX: Guiding the writing and revision of the manuscript as mentors. All co-authors participated in the revision and approved this manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eTrial registration\u003c/h2\u003e\n\u003cp\u003ePROSPERO CRD42019134273\u003c/p\u003e\n\u003ch2\u003eDeclaration of generative AI and AI-assisted technologies in the writing process\u003c/h2\u003e\n\u003cp\u003eDuring the preparation of this work, we used [Grammarly] in order to [check the grammar of the manuscript]. After using this tool, we reviewed and edited the content as needed and took full responsibility for the content of the publication.\u003cbr\u003e\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003ePatil SR, Chavan AB, Patel AM, Chavan PD, Bhopale JV. 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The Effect of Diabetes Management Shared Care Clinic on Glycated Hemoglobin A1c Compliance and Self-Management Abilities in Patients with Type 2 Diabetes Mellitus. \u003cem\u003eINTERNATIONAL JOURNAL OF CLINICAL PRACTICE\u003c/em\u003e 2023; \u003cstrong\u003e2023\u003c/strong\u003e .\u003c/li\u003e\n\u003cli\u003eDrake C, Rader A, Clipper C, et al. Adaptation to Telehealth of Personalized Group Visits for Late-Stage Diabetic Kidney Disease. \u003cem\u003eKidney360\u003c/em\u003e 2023 : 10.34067.\u003c/li\u003e\n\u003cli\u003eNederveld A, Phimphasone-Brady P, Gurfinkel D, Waxmonsky JA, Kwan BM, Holtrop JS. Delivering diabetes shared medical appointments in primary care: early and mid-program adaptations and implications for successful implementation. \u003cem\u003eBMC Primary Care\u003c/em\u003e 2023; \u003cstrong\u003e24\u003c/strong\u003e: 1-12.\u003c/li\u003e\n\u003cli\u003ede Lourdes Arrieta-Canales M, Mukherjee J, Gilbert H, et al. 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Chinese Journal of Nursing, 2022,57(01):17-22 .\u003c/li\u003e\n\u003cli\u003eVaughan EM, Hyman DJ, Naik AD, Samson SL, Razjouyan J, Foreyt JP. A Telehealth-supported, Integrated care with CHWs, and MEdication-access (TIME) Program for Diabetes Improves HbA1c: a Randomized Clinical Trial. \u003cem\u003eJ Gen Intern Med\u003c/em\u003e 2021; \u003cstrong\u003e36\u003c/strong\u003e: 455-63.\u003c/li\u003e\n\u003cli\u003eHousden L, Wong ST, Dawes M. Effectiveness of group medical visits for improving diabetes care: a systematic review and meta-analysis. \u003cem\u003eCANADIAN MEDICAL ASSOCIATION JOURNAL\u003c/em\u003e 2013; \u003cstrong\u003e185\u003c/strong\u003e: E635-635E644.\u003c/li\u003e\n\u003cli\u003eSteinsbekk A, Rygg L, Lisulo M, Rise MB, Fretheim A. Group based diabetes self-management education compared to routine treatment for people with type 2 diabetes mellitus. 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Past and Present of Implementation Science (Part I)--Origin and Development[J]\u003cem\u003e[In Chinese]\u003c/em\u003e. \u003cem\u003eMedical Journal of Peking Union Medical College Hospital\u003c/em\u003e 2024 : 0-0.\u003c/li\u003e\n\u003cli\u003eManasse SM, Clark KE, Juarascio AS, Forman EM. Developing more efficient, effective, and disseminable treatments for eating disorders: An overview of the multiphase optimization strategy. \u003cem\u003eEating and Weight Disorders-Studies on Anorexia, Bulimia and Obesity\u003c/em\u003e 2019; \u003cstrong\u003e24\u003c/strong\u003e: 983-95.\u003c/li\u003e\n\u003c/ol\u003e"}],"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":"bmc-primary-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"famp","sideBox":"Learn more about [BMC Primary Care](https://bmcprimcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12875","title":"BMC Primary Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"people with diabetes, shared medical appointments, reach, effectiveness, adoption, implementation, and maintenance (RE-AIM), feasibility, equity, scalability, systematic review, meta-analysis","lastPublishedDoi":"10.21203/rs.3.rs-4858860/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4858860/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDiabetes is a major global health concern and a leading cause of morbidity and mortality. Shared medical appointment (SMA), an integrated treatment and health management service, is effective in improving the clinical and behavioral outcomes of people with diabetes (PWD). Using the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework, this review aimed to evaluate the impact of SMA on PWD treatment and management to inform the feasibility, scalability, and equity of future SMA implementation.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eEight electronic databases were searched for randomized controlled trials, non-randomized grouped controlled trials, pre/post studies, and interrupted time series model studies published in English and Chinese up to February 2024. We performed meta-analyses for all RCTs using a random-effects model and presented Forrest plots and test statistics (Cochran's \u003cem\u003eQ\u003c/em\u003e and \u003cem\u003eI\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e) for heterogeneity analysis. Other results that did not lend themselves to quantitative analysis were summarized qualitatively.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eForty-seven studies were included in the review. The SAM was a highly resource-demanded and complex intervention package. The studies were evaluated according to the RE-AIM framework, and most studies reported effectiveness well, while all other dimensions were poorly reported. Most studies demonstrated that SMA effectively improved patients\u0026rsquo; HbA1c and SBP levels and reduced healthcare costs.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eThe available evidence suggests that the SMA was beneficial in improving PWD management and health outcomes among PWD. However, its complexity would constrain its feasibility and scalability. Future research should assess the effect size of each intervention component and evaluate the implementation process, costs, and sustainability of SMA intervention, especially in resource-limited settings, to improve its scalability and equity.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003ePROSPERO CRD42019134273\u003c/p\u003e","manuscriptTitle":"Using A RE-AIM Framework to Evaluate the Impact of Shared Medical Appointments for Diabetes Mellitus: A Systematic Review and Meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-16 01:00:19","doi":"10.21203/rs.3.rs-4858860/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-12-11T12:05:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-07T05:33:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"227811059002701538254181539445970965002","date":"2024-12-06T22:05:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"39623654923889838161182798912188846983","date":"2024-11-22T03:59:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"160805170158418003984376588538007710942","date":"2024-10-18T14:43:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"190579945373544828472334514340198002967","date":"2024-10-17T21:25:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-19T06:30:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"224879284338284254919135335633047285063","date":"2024-08-16T01:43:17+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-08-09T09:18:15+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-07T06:14:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-06T23:18:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Primary Care","date":"2024-08-05T03:03:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-primary-care","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"famp","sideBox":"Learn more about [BMC Primary Care](https://bmcprimcare.biomedcentral.com/)","snPcode":"","submissionUrl":"https://author-welcome.nature.com/12875","title":"BMC Primary Care","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2559c166-f72c-4477-8332-c82db5b109cf","owner":[],"postedDate":"September 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-06-09T16:00:40+00:00","versionOfRecord":{"articleIdentity":"rs-4858860","link":"https://doi.org/10.1186/s12875-025-02875-1","journal":{"identity":"bmc-primary-care","isVorOnly":false,"title":"BMC Primary Care"},"publishedOn":"2025-06-05 15:57:15","publishedOnDateReadable":"June 5th, 2025"},"versionCreatedAt":"2024-09-16 01:00:19","video":"","vorDoi":"10.1186/s12875-025-02875-1","vorDoiUrl":"https://doi.org/10.1186/s12875-025-02875-1","workflowStages":[]},"version":"v1","identity":"rs-4858860","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4858860","identity":"rs-4858860","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}