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The Effectiveness of Patient-Centred Medical Home-Based Models of Care versus Standard Primary Care in Chronic Disease Management: A Systematic Review and Meta-Analysis of Randomised and Non-Randomised Controlled Trials

Patient-centred care by a coordinated primary care team may be more effective than standard care in chronic disease management. We synthesised evidence to determine whether patient-centred medical home (PCMH)-based care models are more effective than standard general practitioner (GP) care in improving biomedical, hospital, and economic outcomes. MEDLINE, CINAHL, Embase, Cochrane Library, and Scopus were searched to identify randomised (RCTs) and non-randomised controlled trials that evaluated two or more principles of PCMH among primary care patients with chronic diseases. Study selection, data extraction, quality assessment using Joanna Briggs Institute (JBI) appraisal tools, and grading of evidence using Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) approach were conducted independently. A quantitative synthesis, where possible, was pooled using random effects models and the effect size estimates of standardised mean differences (SMDs) and odds ratios (ORs) with 95% confidence intervals were reported. Of the 13,820 citations, we identified 78 eligible RCTs and 7 quasi trials which included 60,617 patients. The findings suggested that PCMH-based care was associated with significant improvements in depression episodes (SMD −0.24; 95% CI −0.35, −0.14; I2 = 76%) and increased odds of remission (OR 1.79; 95% CI 1.46, 2.21; I2 = 0%). There were significant improvements in the health-related quality of life (SMD 0.10; 95% CI 0.04, 0.15; I2 = 51%), self-management outcomes (SMD 0.24; 95% CI 0.03, 0.44; I2 = 83%), and hospital admissions (OR 0.83; 95% CI 0.70, 0.98; I2 = 0%). In terms of biomedical outcomes, with exception to total cholesterol, PCMH-based care led to significant improvements in blood pressure, glycated haemoglobin, and low-density lipoprotein cholesterol outcomes. The incremental cost of PCMH care was identified to be small and significantly higher than standard care (SMD 0.17; 95% CI 0.08, 0.26; I2 = 82%). The quality of individual studies ranged from “fair” to “good” by meeting at least 60% of items on the quality appraisal checklist. Additionally, moderate to high heterogeneity across studies in outcomes resulted in downgrading the included studies as moderate or low grade of evidence. PCMH-based care has been found to be superior to standard GP care in chronic disease management. Results of the review have important implications that may inform patient, practice, and policy-level changes.


Introduction
Chronic diseases have contributed to increased mortality and morbidity worldwide with the disease burden accelerating across both developed and developing nations [1,2]. The Global Burden of Diseases (GBD) Study in 2017 reported that chronic diseases accounted for 41% of increased disability and 73% of all deaths [1,2]. Moreover, with increasing life expectancy and ageing population, the global prevalence of multiple chronic conditions or multimorbidity is also on the rise, further exacerbating complications in quality and delivery of care [3,4]. As a result, patients with one or more chronic diseases often experience poor mental and physical functioning with increased psychological distress affecting their overall health-related quality of life (HRQoL) [5,6]. In addition to negative health outcomes, chronic diseases also contribute to significant economic ramifications to both patients and health care system in the form of increased health care utilisation and costs of care [7,8].
The long-term nature of chronic diseases and complexities of care require health care systems, worldwide, to revisit guidelines on effective chronic disease management [7]. The health and economic repercussions of chronic diseases are partly connected to the fragmented design and delivery of health care systems to focus on "single disease framework" as opposed to a "whole-person approach" [9]. However, there has been an increasing advocacy towards shift from a reactive health care system to one that is proactive, enabling an integrated systems approach towards chronic disease management [10]. In view of this, the World Health Organisation (WHO) and other leading organisations have acknowledged the importance of primary care as an ideal setting to facilitate patient-centred care, which could result in better patient outcomes [11,12]. There is a large body of evidence suggesting that coordinated team-based approaches in primary care are effective in chronic disease management [13,14].
The patient-centred medical home (PCMH) model is one of the chronic care models (CCM) that has reportedly shown to provide a multidimensional solution to effectively managing chronic illness and multimorbidity in primary care [15]. This enhanced primary care model typically consists of a general practitioner (GP)-led care, as part of a multidisciplinary team (MDT) that aims to provide patient-centred care that is also comprehensive and coordinated, with emphasis on self-management and patient education [12]. There is a growing body of literature, particularly in United States and several parts of United Kingdom and other European countries, reporting the effectiveness of PCMH care models in improving biomedical [16,17], HRQoL [18,19], hospital [20,21], and economic outcomes [22] compared to standard GP care.
A comprehensive systematic review and meta-analysis of PCMH care published in 2013 [23] reported improvements in patient experiences and some reduction in health utilisation among patients with multimorbidity. However, the effect of PCMH models on patients with single-disease care management was not reviewed. Whilst the review focuses on clinical quality and processes of care, there was insufficient evidence to estimate biomedical outcomes and quality of life. In addition, the review also included patients from non-primary care settings such as tertiary care hospitals, thereby limiting understanding of the true effectiveness of PCMH model in primary care settings. The current review was warranted as there has been increased advocacy for PCMH-based care models resulting in a number of new studies evaluating PCMH models being published since 2013 [18][19][20][21].
A systematic review and meta-analysis was conducted to assess the effectiveness of PCMH-based models of care when compared to standard GP care in improving biomedical, hospital, and economic outcomes of primary care patients with one or more chronic diseases. The findings of this review may help inform guidelines and practices.

Data Extraction
Data extraction of included articles was carried out independently by two reviewers (JRJ and HJ) using Excel spreadsheet (Microsoft Excel, Microsoft Corporation). Data extracted from included articles included key characteristics: first author and publication year; country of origin; sample size, age, and gender distribution; chronic disease profile; baseline characteristics reported as mean (SD) or proportions; PCMH components implemented; duration of follow-up; and outcomes. Whilst data extraction was performed using a customised spreadsheet, the Centre for Reviews and

Participants
Primary care patients aged at least 18 years with one or more chronic disease/s Intervention AMA recognised PCMH principles (must meet 1 and 2 criteria) 1) Integrated or MDT care AND 2) One or more of the following principles: i. Coordination of care ii. Data driven quality of care iii. Long-term patient-provider relationship iv. Patient empowerment and patient engagement

Standard GP care
Outcomes Patient outcomes (clinical and self-reported surveys) Hospital outcomes (hospital or emergency department visits) Economic outcomes (direct healthcare costs, incremental costs)

Study design
Randomised and non-randomised controlled trials

Data Extraction
Data extraction of included articles was carried out independently by two reviewers (JRJ and HJ) using Excel spreadsheet (Microsoft Excel, Microsoft Corporation). Data extracted from included articles included key characteristics: first author and publication year; country of origin; sample size, age, and gender distribution; chronic disease profile; baseline characteristics reported as mean (SD) or proportions; PCMH components implemented; duration of follow-up; and outcomes. Whilst data extraction was performed using a customised spreadsheet, the Centre for Reviews and Dissemination's (CRD) guidance for undertaking reviews in health care was followed [29]. Authors of studies with missing data were contacted by email up to two times; however, no response was received.

Quality Assessment and Risk of Bias
Two reviewers (JRJ and HJ) independently evaluated the methodological validity of included articles using relevant Joanna Briggs Institute (JBI) critical appraisal checklists (RCTs, quasi trials, and economic evaluations) [30,31]. Quality of studies were rated as good (≥8), fair (6)(7), or poor (≤5) based on the summary scores. We also used risk of bias in non-randomised studies of interventions (ROBINS-I) tool to supplement JBI appraisal for non-randomised trials [32]. Additionally, the quality of evidence across included studies reporting similar outcomes was determined by applying the Grading of Recommendations Assessment, Development and Evaluation (GRADE) criteria [33]. The overall GRADE quality of evidence from the tables takes into account three factors which include (i) the average quality across the studies for each particular outcome, (ii) the level of heterogeneity between the studies, and (iii) the total number of studies reporting a particular outcome.

Outcomes
Outcomes identified from the studies include changes in mean differences or proportion of patients achieving recommended levels in (1). Biomedical outcomes-blood pressure (BP); glycated haemoglobin (HbA1c); low density lipoprotein cholesterol (LDL-C); high density lipoprotein cholesterol (HDL-C); and serum total cholesterol. (2). Self-reported health assessments (using validated questionnaires)-depression; HRQoL (overall, mental and physical functioning components); and self-management. (3). Health utilisation outcomes-hospital admissions; emergency department visits; and medications use. (4). Economic outcomes-incremental cost-effectiveness ratio (ICER) which is defined as the difference in total cost of an intervention (compared to standard care) divided by the difference in health outcome measure [22].

Data Analysis
Data of included studies were pooled together using the inverse-variance method of random-effects meta-analysis [34]. Standardised mean differences (SMD) for continuous data and odds ratios (ORs) for dichotomous data, with 95% confidence intervals (CI), were calculated and graphically presented as forest plots. Statistical heterogeneity was calculated using I 2 and Cochran's Q statistics. Subgroup analyses were considered for outcomes with substantial heterogeneity (I 2 ≥ 85%). Publication bias for outcomes with at least 6 studies was assessed using funnel plots and Egger's test of asymmetry [35]. All analyses were conducted using RevMan version 5.3 (The Nordic Cochrane Centre, Copenhagen, Denmark) and R version 4.0 software (R Foundation for Statistical Computing, Vienna, Austria).

Literature Search
The electronic database search resulted in 13,820 citations and an additional 16 citations from hand searching key systematic reviews. After exclusion of duplicate records, 6416 articles were screened by titles and abstracts with 201 articles determined to be eligible for full-text assessment. Of these, 85 studies met the eligibility criteria and were included in our systematic review. Flowchart of the selection process from initial identification to inclusion is shown in Figure 2. Main reasons for exclusion included patients treated in non-primary care settings, not meeting minimum PCMH components or focused on intervention other than PCMH model, lack of control group, and other reasons (list of excluded articles; see Table A2). components or focused on intervention other than PCMH model, lack of control group, and other reasons (list of excluded articles; see Table A2).

Descriptive Data Synthesis
The characteristics of included studies are presented in the Appendix A Tables A3 and A4. Of the 85 studies included in the review, 78 studies were RCTs [13,14,16,[18][19][20]22, and 7 studies were of non-RCTs, including quasi trials [17,21,107,108] or cohort studies with a control group [109][110][111]. The 85 studies enrolled a total of 60,617 patients with sample sizes ranging from 40 to 8366. Whilst 79 studies had sufficient data for quantitative data synthesis, 6 studies [81,85,95,97,103,107] did not have usable data and therefore, the findings were narratively summarised.
The common inclusion criteria for all 85 studies was primary care patients with diagnosis of one or more chronic conditions, whereas the predominant reason for exclusion was patients with cognitive impairment and terminal illness. In terms of the chronic disease profile of the participants in the included articles, 46% of articles were based on participants with single chronic condition whereas 54% reported on one or more conditions. The most prevalent conditions were mental illness (59%), type 2 diabetes (33%), cardiovascular diseases (CVD) including hypertension (20%), musculoskeletal disorders (6%), and chronic obstructive pulmonary disease (COPD) (6%) (Tables A3  and A4).
More than half the studies (52%) were conducted in the United States. The mean age of patients ranged between 30 and 83 years. In terms of gender distribution, most of the studies had slightly more women than men, except for studies conducted in Veterans Affairs (VA) primary care settings [16,50,52,53,56]. The duration of follow-up varied from 3 to 48 months. Out of 85 articles included for review, in addition to MDT care, 95% of studies reported coordinated care, patient engagement and education, and self-management; 20% reported continuity of care and long-term patient provider relationship; and only 9% of studies included data driven quality of care (Tables A3 and A4). Studies included in the quantitative synthesis (metaanalysis) (n = 85)

Full-text articles excluded with reasons
Participants less than 18 years/non-primary care setting = 30 Intervention with less than adequate PCMH components or emphasis other than PCMH model = 16 Did not have a control group = 11 Irrelevant outcome = 6 Studies reporting on secondary data analyses using same sample and outcomes/conference abstracts/non-English language/duplicates = 53 Records excluded (n = 6,215) by title and abstract screening

Descriptive Data Synthesis
The characteristics of included studies are presented in the Appendix A Tables A3 and A4. Of the 85 studies included in the review, 78 studies were RCTs [13,14,16,[18][19][20]22, and 7 studies were of non-RCTs, including quasi trials [17,21,107,108] or cohort studies with a control group [109][110][111]. The 85 studies enrolled a total of 60,617 patients with sample sizes ranging from 40 to 8366. Whilst 79 studies had sufficient data for quantitative data synthesis, 6 studies [81,85,95,97,103,107] did not have usable data and therefore, the findings were narratively summarised.
The common inclusion criteria for all 85 studies was primary care patients with diagnosis of one or more chronic conditions, whereas the predominant reason for exclusion was patients with cognitive impairment and terminal illness. In terms of the chronic disease profile of the participants in the included articles, 46% of articles were based on participants with single chronic condition whereas 54% reported on one or more conditions. The most prevalent conditions were mental illness (59%), type 2 diabetes (33%), cardiovascular diseases (CVD) including hypertension (20%), musculoskeletal disorders (6%), and chronic obstructive pulmonary disease (COPD) (6%) (Tables A3 and A4).
More than half the studies (52%) were conducted in the United States. The mean age of patients ranged between 30 and 83 years. In terms of gender distribution, most of the studies had slightly more women than men, except for studies conducted in Veterans Affairs (VA) primary care settings [16,50,52,53,56]. The duration of follow-up varied from 3 to 48 months. Out of 85 articles included for review, in addition to MDT care, 95% of studies reported coordinated care, patient engagement and education, and self-management; 20% reported continuity of care and long-term patient provider relationship; and only 9% of studies included data driven quality of care (Tables A3 and A4).

Quality Assessment and Risk of Bias
Quality assessment and risk of bias for individual studies are reported in the Appendix A Tables A5-A8. The overall quality of studies ranged from "fair" to "good" by meeting at least 60% of items on the checklist. Two studies [62,104] were rated as poor due to general lack of information on randomisation, unclear methodology, and clarity of results. Given the nature of PCMH-based intervention, most trials employed a cluster randomisation method where a group of patients were seen by the same GP or same general practice providing PCMH care. Thereby, blinding of patients or GPs was not applicable and, as a result, items related to blinding were not necessarily graded down. However, only 32 studies reported blinding of outcome assessment whilst other studies were graded down in quality. The quality of evidence across included studies assessed using GRADE approach is presented in Table 1.
Six studies reported that PCMH care was associated with significantly increased odds of remission of depression with pooled OR 1.79 (95% CI 1.46, 2.21; p-value < 0.001) ( Figure 3). Additionally, one other study [85] reported significant improvements among patients with anxiety and mood disorders with an effect size of 0.30 (95% CI 0.05, 0.55; p-value = 0.02) compared to standard care. Given most studies consistently reported improvements, the GRADE of evidence was classified as moderate quality (Table 1).

Figure 5.
Forest plots of blood pressure outcomes between the PCMH care and Standard GP care. BP control refers to blood pressure levels within the guideline's recommended range.

Glycated Haemoglobin Outcomes
Ten studies [16,17,39,43,64,68,71,77,82,96] reported on the effect of PCMH care on HbA1c outcomes. HbA1c levels were recorded among patients with a positive diagnosis of Type 2 diabetes. Three studies reported that PCMH care was associated with increased odds of glycaemic control with pooled OR 2.37 (95% CI 0.86, 6.51; p-value = 0.100). However, the pooled estimate was not statistically significant ( Figure 6). The substantial heterogeneity of 87% in the three studies reporting ORs was due to a shorter follow-up duration of three months reported by Bogner et al. [43] compared to the other two studies which had follow-up duration of 12 to 13 months. Seven studies reported significant improvements in HbA1c, in favour of PCMH care with pooled estimates of SMD −0.26 (95% CI −0.43, −0.08; p-value = 0.004) ( Figure 6). Given the substantial amount of heterogeneity, the GRADE of evidence was classified as low quality (Table 1).

Blood pressure control
Systolic blood pressure Diastolic blood pressure Figure 5. Forest plots of blood pressure outcomes between the PCMH care and Standard GP care. BP control refers to blood pressure levels within the guideline's recommended range.

Glycated Haemoglobin Outcomes
Ten studies [16,17,39,43,64,68,71,77,82,96] reported on the effect of PCMH care on HbA1c outcomes. HbA1c levels were recorded among patients with a positive diagnosis of Type 2 diabetes. Three studies reported that PCMH care was associated with increased odds of glycaemic control with pooled OR 2.37 (95% CI 0.86, 6.51; p-value = 0.100). However, the pooled estimate was not statistically significant ( Figure 6). The substantial heterogeneity of 87% in the three studies reporting ORs was due to a shorter follow-up duration of three months reported by Bogner et al. [43] compared to the other two studies which had follow-up duration of 12 to 13 months. Seven studies reported significant improvements in HbA1c, in favour of PCMH care with pooled estimates of SMD −0.26 (95% CI −0.43, −0.08; p-value = 0.004) ( Figure 6). Given the substantial amount of heterogeneity, the GRADE of evidence was classified as low quality (Table 1).

Cholesterol Outcomes
For LDL-cholesterol outcomes, five studies [17,64,68,71,96] reported significant improvements in favour of PCMH care with pooled SMD of −0.16 (95% CI −0.33, −0.00; p-value = 0.05) compared to standard GP care. Test for subgroup difference between follow-up and change scores showed no statistical significance (I 2 = 16.8%, p-value = 0.27) ( Figure 7A). For total cholesterol outcomes, two studies [17,82] reported a non-significant increase in total cholesterol with a pooled SMD of 0.07 (95% CI −0.08, 0.23; p-value = 0.34) ( Figure 7B). The GRADE of evidence of both LDL and total cholesterol outcomes were classified as low quality given the limited number of studies (Table 1)

Cholesterol Outcomes
For LDL-cholesterol outcomes, five studies [17,64,68,71,96] reported significant improvements in favour of PCMH care with pooled SMD of −0.16 (95% CI −0.33, −0.00; p-value = 0.05) compared to standard GP care. Test for subgroup difference between follow-up and change scores showed no statistical significance (I 2 = 16.8%, p-value = 0.27) ( Figure 7A). For total cholesterol outcomes, two studies [17,82] reported a non-significant increase in total cholesterol with a pooled SMD of 0.07 (95% CI −0.08, 0.23; p-value = 0.34) ( Figure 7B). The GRADE of evidence of both LDL and total cholesterol outcomes were classified as low quality given the limited number of studies (Table 1).

Hospital Admissions
Five studies [20,21,48,54,111] reported that PCMH care was associated with significant reduction in hospital admissions compared to standard care with pooled OR 0.83 (95% CI 0.70, 0.98; p-value = 0.02) ( Figure 8). Additionally, one study [110] reported a reduction in mean hospital admission rates related to diabetic complications 12 months after PCMH based care compared to standard care. Nonetheless, the change in mean difference failed to meet statistical significance. The GRADE of evidence was classified as moderate quality (Table 1).

Hospital Admissions
Five studies [20,21,48,54,111] reported that PCMH care was associated with significant reduction in hospital admissions compared to standard care with pooled OR 0.83 (95% CI 0.70, 0.98; p-value = 0.02) ( Figure 8). Additionally, one study [110] reported a reduction in mean hospital admission rates related to diabetic complications 12 months after PCMH based care compared to standard care. Nonetheless, the change in mean difference failed to meet statistical significance. The GRADE of evidence was classified as moderate quality (Table 1).

Self-Management Outcomes
Three studies [14,72,89] reported significant improvements in self-management scores in favour of PCMH care compared to standard care with pooled estimates of SMD 0.24 (95% CI 0.03, 0.44; p-value < 0.001) ( Figure 9). Given the substantial amount of heterogeneity (I 2 = 83%), the GRADE of evidence was classified as low quality (Table 1)

Self-Management Outcomes
Three studies [14,72,89] reported significant improvements in self-management scores in favour of PCMH care compared to standard care with pooled estimates of SMD 0.24 (95% CI 0.03, 0.44; pvalue < 0.001) ( Figure 9). Given the substantial amount of heterogeneity (I 2 = 83%), the GRADE of evidence was classified as low quality (Table 1).

Economic Outcomes
A total of 18 studies [13,22,37,44,46,52,[58][59][60]65,66,69,73,79,80,92,98,108] reported costeffectiveness of PCMH-based models of care compared to standard care. To avoid bias in analysis, all currencies were converted to US Dollars at the time of the respective trials and cost effectiveness was measured in terms of incremental cost of intervention. The incremental cost of PCMH care was small but significantly higher than standard care with a pooled estimate of 0.17 (95% CI 0.08, 0.26; pvalue < 0.001) ( Figure 10). The substantial heterogeneity of 81% was due to higher costs of intervention reported by Bosanquet et al. [46]. The GRADE of evidence was classified as low quality (Table 1).
A summary of results from meta-analyses (where possible) and individual studies from randomised and non-randomised controlled trials are presented in Table 2.

Economic Outcomes
A total of 18 studies [13,22,37,44,46,52,[58][59][60]65,66,69,73,79,80,92,98,108] reported cost-effectiveness of PCMH-based models of care compared to standard care. To avoid bias in analysis, all currencies were converted to US Dollars at the time of the respective trials and cost effectiveness was measured in terms of incremental cost of intervention. The incremental cost of PCMH care was small but significantly higher than standard care with a pooled estimate of 0.17 (95% CI 0.08, 0.26; p-value < 0.001) ( Figure 10). The substantial heterogeneity of 81% was due to higher costs of intervention reported by Bosanquet et al. [46]. The GRADE of evidence was classified as low quality (Table 1).
A summary of results from meta-analyses (where possible) and individual studies from randomised and non-randomised controlled trials are presented in Table 2.        Figure 10 NA-not applicable; SMD-Standard Mean Difference; OR-Odds ratio; ‡ Egger's test was conducted only for outcomes with at least 6 studies. Note: The slight discrepancy in the effect sizes in this table to that reported in the manuscript and figures is because the effects sizes are classified based on their study design. I 2 describes the percentage of total variation across studies that is due to heterogeneity rather than chance. A value of 0% indicates no observed heterogeneity, and larger values show increasing heterogeneity.

Publication Bias
Six or more articles with similar outcomes were inspected for publication bias visually by using funnel plots and statistically by determining the significance from Egger's test of asymmetry. Visual inspection of included studies reporting similar outcomes did not indicate any obvious sign of asymmetry (Figures 11 and 12). Consistent with visual findings, no evidence of publication bias was detected with Egger's test, as all outcomes had p > 0.05, showing evidence of funnel plot symmetry ( Table 2).

Publication Bias
Six or more articles with similar outcomes were inspected for publication bias visually by using funnel plots and statistically by determining the significance from Egger's test of asymmetry. Visual inspection of included studies reporting similar outcomes did not indicate any obvious sign of asymmetry (Figures 11 and 12). Consistent with visual findings, no evidence of publication bias was detected with Egger's test, as all outcomes had p > 0.05, showing evidence of funnel plot symmetry ( Table 2).

Summary of Findings
This systematic review comprehensively summarised current evidence on the effectiveness of PCMH-based models on chronic disease management among primary care patients. Compared to standard GP care, PCMH-based care led to significant improvements in depression episodes, quality of life, HbA1c, LDL cholesterol, hospital admissions, and self-management outcomes. Whilst PCMH care was significantly associated with increased odds of blood pressure control, reductions in both pooled estimates of SBP and DBP were not statistically significant. In contrast, the findings suggest that PCMH-based interventions have higher costs and was not cost-effective when compared to standard care. Additionally, the narrative synthesis of studies also corroborated with pooled estimates of the meta-analyses.

Consistency with Other Systematic Reviews
The most commonly reported PCMH principles in the included studies were patient engagement through education and self-management, and care coordination in addition to team-based care. Findings of this review, underscoring these PMCH elements in primary care, are consistent with previous systematic reviews reporting quality of care and overall patient experiences [26,112]. In terms of study outcomes, depression and HRQoL were frequently reported outcomes in the included studies. Systematic reviews focusing on depression outcomes as a result of collaborative care reported similar improvements, which were consistent with our pooled estimates of SMDs and ORs [113,114]. Similarly, our review showed small but significant improvements in the self-reported HRQoL and self-management scores, which is consistent with previous reviews [115,116]. Variabilities in the duration of intervention and baseline severity of chronic illness may explain smaller pooled estimates of HRQoL outcome.
Changes in biomedical outcomes are common measures employed in evaluating the effectiveness of chronic disease management interventions. With the exception of total cholesterol outcomes, findings of our studies were consistent with previous reviews [117,118], showing improvements in biomedical outcomes in favour of PCMH-based care compared to standard care. In terms of cost-effectiveness of PCMH-based models, some meta-analytic reviews on economic evaluations showed that PCMH care was associated with decreases in total costs compared to standard care [119,120]. However, our review supports evidence from prior reviews [115,121], suggesting that PCMH-based care was not associated with improvement in cost outcomes compared to standard care. This discordance could be due to the variability in the initial and sustained amount of costs incurred as a result of additional staffing and other infrastructure as well as the sample of patients and their comorbidity profile in the included trials [121].

Strengths and Limitations
Quality assessment for risk of bias was assessed within and across studies of similar outcomes. As aforementioned, blinding of patients and GPs was not possible due to the nature of intervention and design of trials, as reported in other systematic reviews conducted in primary care settings [114,122]. A substantial amount of heterogeneity was observed for measures of depression, HbA1c, and incremental cost of intervention, justifying the choice of random effects model. Higher heterogeneity is expected when pooling results of complex interventions, given the varying levels of intensity of different interventions, follow-up times, chronic disease profile of participants, and country's primary care setting [115]. Nonetheless, pooled estimates are to be interpreted with caution given unexplained variation observed in outcomes with higher heterogeneity. The review did not consider unpublished data or non-English language studies given the exhaustive number of citations identified. This may have had potential impact on effect size estimates.
Whilst previous reviews and meta-analyses on collaborative care for either single specific disease or multimorbidity have been studied, this review provides a comprehensive current evidence with quantitative synthesis on the effectiveness of PCMH-based care models exclusively on primary care patients with one or more chronic diseases. Other strengths include a registered and published protocol, with a peer-reviewed search strategy, conducted on a wide range of electronic databases.

Patient, Provider, and Policy-Level Implications and Future Directions
Findings of our systematic review have important implications at patient, practice, and policy-level. The evidence may inform patients on the enhanced biomedical outcomes and quality of life resulting from improved education and self-management support. The transformational changes at practice level may enable GPs to better target and deliver care according to the level and complexity of different patients [123]. Additionally, our study findings may also impact policy and implementation guidelines given the growing advocacy towards patient-centred care. Future research should focus on evaluating sustained benefits of PCMH-based care as well as supporting holistic experiences of patients receiving patient-centred care.

Conclusions
Current evidence suggests that PCMH-based care showed significant improvements in depression, HRQoL, self-management, biomedical, and health utilisation outcomes compared to standard GP care. Whilst studies included for pooled estimates showed consistent trend for several outcomes, high heterogeneity in some outcomes resulted in low to moderate grade of evidence, limiting firmer conclusion from the pooled evidence. Further research is needed to evaluate the long-term cost-effectiveness of PCMH-based care after the initial higher costs incurred for intervention, which may prove to be more cost-effective than standard care.

Acknowledgments:
The authors would like to express their gratitude to Katrina Chaudhary (Librarian, School of Science and Health, Western Sydney University) and Lily Collison (Librarian, School of Medicine, Western Sydney University) for their help in developing search terms and guidance during the initial search process. We are also particularly grateful to Evan Atlantis for his valuable expertise and feedback provided for this study.

Conflicts of Interest:
The authors declare no conflict of interest. (patient adj centred adj medical adj home *).tw. 4