Skip to main content

Primary care team and its association with quality of care for people with multimorbidity: a systematic review

Abstract

Background

Multimorbidity is posing an enormous burden to health systems, especially for primary healthcare system. While primary care teams (PCTs) are believed to have potentials to improve quality of primary health care (PHC), less is known about their impact on the quality of care for people with multimorbidity. We assessed the characteristics of PCTs and their impact on the quality of care for people with multimorbidity and the mechanisms. 

Methods

We searched PubMed, MEDLINE, EMBASE, ProQuest for published studies from January 2000 to October 2021 for studies in English. Following through PRISMA guidelines, two reviewers independently abstracted data and reconciled by consensus with a third reviewer. Titles, abstracts, and full texts were evaluated to identify relevant studies. Studies were categorized by types of interventions, the impact of interventions on outcome measures, and mechanisms of interventions. 

Results

Seventeen studies (13 RCT, 3 cohort studies, and 1 non-randomized trial) were identified. PCTs were summarized into three types—upward PCTs, downward PCTs and traditional PCTs according to the skill mix. The upward PCTs included primary care workers and specialists from upper-level hospitals, downward PCTs involving primary care workers and lay health workers, and traditional PCTs involving physicians and care managers. PCTs improved patients’ mental and psychological health outcomes greatly, and also improved patients’ perceptions towards care including satisfaction with care, sense of improvement, and patient-centeredness. PCTs also improved the process of care and changed providers’ behaviors. However, PCTs showed mixed effects on clinical outcome measures.

Conclusions

PCTs have improved mental and psychological health outcomes, the process of care, patients’ care experiences, and satisfaction towards care for patients with multimorbidity. The effect of PCTs on clinical outcomes and changes in patient behaviors need to be further explored.

Peer Review reports

Introduction

Chronic diseases have become an enormous burden to society and global health systems [1]. People with chronic conditions are likely to have more than one disease, which is referred to as multimorbidity. Multimorbidity is becoming increasingly common both in high-income countries and low-and-middle income countries. One-fourth of people in the United States and the United Kingdom have multimorbidity, and at least two-thirds among adults aged 65 and over [2, 3]. In China, more than 40% of adults aged 60 and over in the mainland have multimorbidity [4]. People with multimorbidity are likely to have worse health outcomes and increased mortality [5], calling for greater recognition of its impact on individuals affected [2, 6]. Multimorbidity challenges the traditional healthcare system that focuses on managing individual diseases [7]. A people-centered and integrated healthcare delivery system has been promoted increasingly to enhance quality and meet the needs of people with multimorbidity [8].

Strengthening primary health care (PHC) system has been proposed as the key to improve health outcomes for people with multimorbidity due to their comprehensive healthcare needs and prevention services needs that episodic specialized care cannot meet [9]. PHC, with the characteristics of continuity, comprehensiveness and coordination, is associated with higher value care at the whole-person level, better health, greater equity, lower costs at the level of populations [10, 11].

Primary care teams (PCTs) incorporating interdisciplinary collaboration have proved potential to deal with complex patients [12, 13]. Many developed countries are seeing PCTs as new directions of healthcare reform, such as the patient-centered medical home in US [14], the primary care home in UK, and the family health team model in Canada [15]. These initiatives seek to improve access to care of high quality, transition care from emphasizing volume to value and increase effectiveness through task-shifting [15, 16]. However, there are gaps of their implementation and organizational arrangements, especially concerning patients with complex conditions with more healthcare need.

This systematic review aims to synthesize existing evidence, identify and evaluate the impact of interventions in PCTs designed to improve care among people with multiple chronic conditions on quality of care. Based on this objective, we try to answer the following research questions:

  1. 1.

    What are the characteristics of PCTs designed to improve care for people with multimorbidity?

  2. 2.

    What are the impacts of PCTs on the quality of care among people with multimorbidity in primary health care?

  3. 3.

    What are the mechanisms by which PCTs influence the quality of care among people with multimorbidity in primary health care?

The findings of this paper can inform the development of PCTs and enhance better management of people with multimorbidity.

Methods

This systematic review was performed according to the PRISMA guidelines. Our review is registered with the PROSPERO database (PROSPERO CRD42021284242). No protocol was published. A comprehensive search was conducted of the online databases: PubMed, MEDLINE, EMBASE, ProQuest for studies in English using indexed and free text words for the past twenty years (January 2000-October 2021). The keywords and MeSH terms used were “multimorbidity” “patient care teams” and “primary health care”. The step-by-step search strategies for the four databases are presented in the supplementary file 1. Reference lists of retrieved studies and systematic reviews were also examined for relevant studies. Companion documents were also searched to obtain more information on the detailed PCTs interventions, including protocols, supplementary files for each publication, website pages, etc.

Definitions of terms and eligibility criteria

Types of population

The participants are people or populations with multimorbidity receiving care in primary or community care settings. The most widely used definition for multimorbidity is the co-occurrence of two or more chronic health conditions in the same individual [17, 18]. Multimorbidity is often used interchangeably with comorbidity, which refers to a specific pair of diseases beyond the index disease under study, so we also included studies using “comorbidity” in this review. In this paper, we adopted “multimorbidity” according to the widely-used definition by Van den Akker and colleagues [8, 19, 20]. To increase the homogeneity of the sample and comparability of PCTs characteristics across studies, the homeless population, children, pregnant women, the oldest-old population were excluded. Studies that focused on one single disease were also excluded.

Types of interventions

There is no consistent definition for PCTs currently. Basically, PCTs refer to a group of health-related workers working together to provide health services. Chevillard and Mousquès defined PCTs as “multiprofessional group practices with at least two GPs and one paramedic, delivering primary care and services based on cooperation and coordination” [21]. As more health workers from other disciplines join in PCTs, a growing change to the definition of PCTs has sparked renewed interests. Wranik et al. narrowed the definition of PCTs down to interprofessional PCTs (IPPC team) – “consisting of healthcare providers from different disciplines working together to address the health needs of populations through the creation of comprehensive care options, increased continuity, and coordination of care” [13]. The origin of PCTs dated back to 1950s in the UK, when general practitioners (GPs) in the primary health system usually worked single-handed back then. The concept of PCTs first appeared in the UK with the arrival of NHS in the 1950s, when the College of Practitioners encouraged a team approach in primary health care [22], followed by Finland and Netherlands [23]. A group practice model was gradually formed. PCTs only included a GP and a nurse at first, but it has expanded over the years, incorporating other healthcare professionals, managers [24], pharmacists [25], social workers [26], mental health workers [27], nutritionists [28], etc.

PCTs have often been used interchangeably with “primary healthcare teams” or “primary health teams”. The healthcare services provided by the primary care teams are “team-based care”, which is also often used in studies. We also included these terms in the review process.

Types of outcomes

Currently, there is no consensus in understanding of “quality of care” and disagreements remain about what it encompasses. The classic definition for quality of care was developed by Donabedian in 1966. He built on the concept of “input–process–output” used in industrial manufacturing, and proposed the triad of “structure-process-outcome” for quality of care [29]. This definition has been widely accepted and used in describing and evaluation quality of care [30].

Vast literature discussed and tried to define quality of care in various contexts after Donabedian’s work. In 1984, the American Medical Association defined care of high-quality as care “which consistently contributes to improvement or maintenance of the quality and/or duration of life” [31]. The association also specified eight essential elements of quality, emphasizing health outcomes, disease prevention, health promotion, timeliness, patient participation, the scientific basis of medicine, attention to patients’ psychological conditions, efficient use of resources, and sufficiently documented medical records. In 1990, the Institute of Medicine (IoM) defined quality as “the degree to which health care services for individuals and populations increase the likelihood of desired outcomes and are consistent with current professional knowledge” [32]. The definition of IoM is also widely acknowledged for its emphasis on health of populations, patients’ comprehensive wellbeing and the limitation of medicine.

Based on the most widely used definitions for quality of care above, we focused on the quality of process and outcome, which included 1) clinical outcome measures of patient health outcomes such as physical or psychological outcomes, 2) subjective measures of health outcomes like patient-reported outcomes and experiences, 3) measures of changes in patient health behaviors, 4) process measures like prescription patterns.

Data extraction and quality appraisal

Two reviewers (ML and HT) independently abstracted data using the eligibility criteria and discussed disagreements. Before the review process, a screening exercise was performed for two reviewers to make sure that the evaluation process was reliable. Titles and abstracts were first evaluated, and ineligible studies were excluded. Full texts were evaluated of the selected studies afterward. Discrepancies at any time were solved by a third reviewer (XL) and within the research team. The following information was extracted using a standardized data extraction tool: author (year) county, title, study design, study aims, settings, sample size, disease types, inclusion criteria, exclusion criteria, team composition, roles of team members, intervention training, communication and supervision, control group, study phase, outcomes, results. The synthesis was conducted in Microsoft Excel 2019. The review methodology followed through PRISMA guidelines for systematic reviews. For studies of RCT, risk of bias was reported based on the Cochrane criteria (supplementary file 2). The Mixed Methods Appraisal Tool (MMAT) was used to assess the methodological quality for each study, and the quality of the studies was rated at a five-point scale (supplementary file 2) [33].

Results

Study characteristics

Overall, 9263 unique records were identified, of which 9100 records were excluded based on title and abstract screening. One hundred sixty-three records were assessed in full-text for eligibility, among which 92 were excluded because they did not contain outcome measures, 38 were excluded because they focused on a single disease, 5 were excluded because they were not in primary care settings, 2 were excluded for language, 6 were excluded because only protocols were available, and 3 were excluded because of abstracts only (Fig. 1). Therefore, seventeen studies (13 RCTs, 3 cohort studies, and 1 non-randomized trial) were included. Among these studies, seven were conducted in the United States, 4 in the United Kingdom, 1 in Germany, 1 in Taiwan China, 2 in South Africa, 1 in Australia, and 1 in Spain. The sample size of the included studies ranged from 142 to 5 337 377. Eleven studies studied depression comorbid with other diseases, such as hypertension, diabetes, or coronary heart disease, 5 studies studied other chronic diseases, 1 studied multimorbidity in general. Sixteen models of primary care teams were identified in the included studies, among which two studies assessed the same intervention at different times. All studies were based on complex and multifaceted interventions or policies, and no study linked quality change in a single intervention component (Table 1).

Fig. 1
figure 1

PRISMA flow diagram of the studies selection process

Table 1 Characteristics of the studies

Primary care teams

The PCTs in the included studies were summarized below. A detailed description of the interventions was presented in table S2 (supplementary file 3). Basically, PCTs involved in the included studies can be broadly summarized into three categories based on the skill mix of the team: 1) upward collaborative PCTs involving primary care workers and specialists from upper-level hospitals [51], 2) downward PCTs involving primary care workers and lay health workers such as community health workers, and 3) traditional PCTs involving primary care physicians and care managers (Fig. 2). Some PCTs, such as TEAMcare, also emphasized the roles of patients in the team and their collaborative work with other team members [41].

Fig. 2
figure 2

Classifications of primary care teams

The upward collaborative PCTs included 5 models in 7 articles [40, 41, 44, 46, 48, 49, 52]. In this model, health workers from primary care clinics worked together with hospital specialists, such as psychiatrists, psychologists, internists, etc. The specialists trained primary health workers with essential knowledge and skills, supervised, and gave recommendations for the care process. In the TEAMcare study, a weekly meeting was arranged among nurses, primary care physicians, a psychiatrist, and a psychologist to review new cases and patient progress [40, 41]. In the multi-site study on the US-Mexico border, the integration and collaboration among multiple healthcare providers were emphasized by introducing warm-handoffs, transportation support, and a transitional nurse [49]. However, this study was piloted in various places, and the interventions were tailored to the local organizations' context, setting, and population. Multiple professionals emerged in different places, including physicians and nurses from different primary care clinics, community health workers, or specialists from local hospitals.

The downward collaborative PCTs included 2 models in 2 articles [43, 47]. In this model, primary care workers worked collaboratively with lay workers from the community, such as community health workers or lay counselors. A collaborative care model for patients comorbid with mental disorders and chronic conditions in South Africa was composed of primary care nurses, GPs, and lay counsellors [43]. The primary care nurses were trained to provide person-centered care and supplementary mental health training. The lay counselors were trained and delivered group-based counseling services drawing on cognitive behavioral therapy techniques and also referred patients for further counseling. In the SUCCEED trial targeting patients with transient ischemic attack with multimorbidity, the community health worker (CHW) was the core member of the team who served as a liaison between the patient and the health system [47]. They reinforced and enhanced health literacy, risk factor control, self-management, and lifestyle changes for patients. The CHW and the physicians meet frequently to discuss patients’ progress and needs.

The traditional PCTs included 8 models in 8 articles [34,35,36,37,38, 42, 45, 50]. In this model, primary care physicians and nurses/medical assistants (care managers) were the main members. Basically, the care managers had close contact with patients to help them manage their conditions within daily life and build a bridge between patients and the healthcare system. In the DROP program, the care managers regularly monitored patients by phone, provided therapeutic advice, and reminded them about upcoming appointments. They also delivered a cognitive-behavioral psychoeducational program for patients, promoting awareness and self-management [34]. The care managers and primary care physicians were loosely connected by information system. A computerized decision support system, integrated in the clinical electronic medical record system in primary care clinics, can generate general recommendations to support physicians’ decision-making. Care managers annotated these suggestions in the clinical record of each patient as delivery. The Teamlet model was also a typical one. It was a small team composed of three persons—a primary care physician and two health coaches (care managers) who were trained from medical assistants or health workers [35]. Under this small team, a clinical encounter was extended to four parts: a pre-visit by the coach, a visit by the physician together with the coach, a post-visit by the coach, and between-visit care by the coach. The coach provided guidance on managing their diseases and emotional support to patients. They also monitored patients’ progress, solved their problems, and navigated the healthcare system.

The impact of PCTs on quality of care

The impact of PCTs on quality of care can be summarized as follows: first, PCTs improved patients’ mental and psychological health outcomes significantly. The majority of depression-related measurements like SCL-90, SCL-20, PHQ-9 or GAD-7, showed significant improvements; Second, PCTs improved patients’ perceptions towards care. Patients’ satisfaction with care, perceptions of improvement, and patient-centeredness all showed significant improvements; Third, PCTs have changed the process of care. Although providing examinations showed mixed results, patients had more consultations with PCTs, and the continuity of care also increased. More medication adjustment made by physicians was also observed. Lastly, PCTs showed mixed effects on clinical outcome measures. The results of changes in BP, HbA1c, or LDL were mixed.

Clinical outcome measures

All the 17 studies reported clinical outcome measures (Table 2). The effect of PCTs on improving blood pressure (BP), hemoglobin A1c (HbA1c), low-density lipoprotein cholesterol levels (LDL) were mixed. Two studies reported statistically significant improvements in BP [40, 50], but the other four studies reported no significant improvements [35, 44, 47, 49]. Katon et al. found that patients systolic BP decreased by 5.1 mmHg (P < 0.001) compared with the control group [40], and Wood et al. found that 65% of patients attained the goal of reaching less than 140/90 mmHg compared with 55% in the control group (95%CI = 0.6–20.2, P = 0.04) [50]. Two studies reported significant improvement in HbA1c [40, 49], and three studies did not find significant improvements [35, 47, 52]. One study found significant improvement in BMI [35], two studies found no significant improvements [44, 47], and one study found no significant improvement in waist circumference [44]. Two studies reported significant improvements in LDL [35, 40], and two studies reported no significant improvements [47, 50].

Table 2 Study phase and results of the included studies

Ten studies presented data on mental health outcomes (Table 2). All of the ten studies showed significant improvements in depression-related measurements. Four studies reported statistically significant improvements in depression severity [34, 46, 52, 53]. Aragonès et al. reported the response rate to antidepressant treatment was 18.9% higher than the control group (OR = 2.74, 95%CI = 1.12–6.67); Katon et al. found that the interventions group was more likely to have a 50% decrease in SCL-90 depression score (OR = 1.62 (95%CI = 0.98–2.67) at 6 months, and OR = 1.47 (95%CI = 0.90–2.39) at 12 months; Sharpe et.al. detected a 50% reduction on SCL-20 (OR = 8.5, 95%CI = 5.5–13.4, P < 0.001), and Walker et al. found a 0.62 decrease in SCL-20 score (95%CI = -0.94–0.29). Seven studies presented data on mean depressive scores or PHQ-9 scores, or SCL-20 depression scores. Only one study showed no significant difference in the reduction in PHQ-9 score [44]. Six studies showed significant improvements in the reduction of mean depressive scores or PHQ-9 scores or SCL-20 depression scores [34, 36, 40, 42, 43, 49]. Three studies showed significant improvements in anxiety [36, 46, 53]. One study showed a significant reduction of the generalized anxiety disorder scale (GAD-7) [36].

Three studies reported results of hospitalizations, mortality, and illness burden (Table 2). One study reported statistically significant lower hospitalization for COPD/asthma (OR = 0.91, 95%CI = 0.87–0.94) and diabetes or its complications (OR = 0.87, 95% CI = 0.83–0.92) [38]. Another two studies both reported no significant difference in the reduction in all-cause hospitalizations [37] or the number of hospital admissions/outpatient attendances or the number of deaths [45].

The three types of PCTs showed mixed results on clinical outcome measures (Table 3). Despite different measures reported, the three types of PCTs all reported important improvements in measures related to mental and psychological health. The differences between three types of PCTs, however, were not able to lead to a consistent result.

Table 3 Quality of care by types of different primary care teams (PCTs)

Patient-reported outcomes and experiences

Seven studies presented patient-reported health outcomes and experiences (Table 2). Four studies reported patients’ satisfaction with care, and all found significant greater satisfaction [34, 36, 39, 40], for example, Katon et al. found that patients receiving care from PCTs were significantly more satisfied with care after 6 months (OR = 2.01; 95% CI = 1.18–3.43) and 12 months (OR = 2.88, 95% CI = 1.67–4.97) [39]. For perceptions of improvement, four studies reported this measure and all found better results in the intervention group [34, 39, 46, 48], although one study found the effect “slight more favorable” because the average point scores lie between categories of “no change” and “a little better” (Mean = 3.52 vs 3.97, P = 0.011) [34]. Studies also found care was more patient-centered delivered by PCTs [36, 45], for example, the standardized difference of patient-centeredness measured by PACIC was 0.39.

Studies of downward PCTs did not present the patient-reported outcomes and experiences, which was subjected to risk of reported bias. The upward PCTs and downward PCTs both performed better in this aspect. Patients were found to have better perceived quality of care [46, 48], and greater satisfaction with care [39, 40]. The traditional PCTs seemed to enhance patient-centeredness better, with two studies reported improvements in this measure [36, 45].

Changes in patient behaviors

Nine studies reported outcomes on patient behaviors (Table 2). Four studies reported medication adherence, and only one study found significant improvement (OR = 2.18, 95%CI = 1.32–3.62) [39]. Seven studies provided results of patients’ lifestyle changes. The three studies that reported smoking status found no significant improvement [44, 47, 50]. Findings on exercises were mixed, Morgan et al. reported a 19% increase in exercise [42], while the other two studies did not find significant improvement [40, 47]. As for diet habits, one study found improvement in self-reported salt intake (Difference = 15.4, 95% CI = 4.4–26.0, P = 0.004) [47]. Another study found that the intervention group reduced saturated fat intake by 17.3% (95%CI = 6.4–28.2, P = 0.009) and increased intake of fruit and vegetables by 37.3% (95%CI = 18.1–56.5, P = 0.004) [50].

Traditional PCTs and downward PCTs had better performance than upward PCTs for patient behaviors. In the traditional PCTs and down PCTs, patients changed their diet habits and exercise. Wood et al. found patients reduced consumption of saturated fat and increased consumption of fruit, vegetables and oily fish, and Towfighi et al. also found patients reported they reduced their salt intake [47, 50].

Process measures

Five studies reported process measures (Table 2). Chen et al. reported that the change in the testing for HbA1c did not differ between the intervention and control group, but testing for LDL was significantly lower in the intervention group (difference = -5.8%, P = 0.001) [35]. For the intervention group, measurement of BMI (+ 85%, P < 0.001), assessing smoking status (+ 82.8%, P < 0.001), making self-management plan (+ 35.6%, P < 0.001) increased significantly compared with baseline. Lin et al. found that initiation and adjustment of medication increased significantly in the intervention group, and the RR was 6.2 (P < 0.001), 1.86 (P < 0.001), and 2.97 (P < 0.001) for antidepressants, antihypertensive drugs, and insulin, respectively. Salisbury reported consultations and continuity of care for process measure [45]. The continuity of care was significantly higher in the intervention group (Difference = 0.08, 95%CI = 0.02–0.13, P = 0.0045). Patients in the intervention group also had more consultations with primary care nurses (Difference = 1.37, 95%CI = 1.17–1.61, P < 0.001) and primary care physicians (Difference = 1.13, 95%CI = 1.02–1.25, P = 0.021), but not in hospital admissions (Deference = 1.04, 95%CI = 0.84–1.30, P = -0.71) and hospital outpatient attendances (Difference = 1.02, 95%CI = 0.92–1.14, P = 0.72). Katon et al. also found that patients in the intervention group were more likely to revive medication adjustment, including insulin (P = 0.006), antihypertensive agents (P < 0.001), and antidepressants (P < 0.001) [40]. Morgan et at. also detected more consultations to mental health workers in the intervention group (+ 17% vs -3%).

Two studies of upward PCTs reported medication adjustments, for example, insulin and antihypertensive medications [40, 41]. For traditional PCTs, Wood et al. found more prescriptions of statins, angiotensin-converting enzyme inhibitors were provided [50]. Studies of traditional PCTs had more process measures reported than the other two types of PCTs, and also found a great deal of changes in processes. Some of the changes, such as increased self-management plan formulation, showed a promising effect for patients with multimorbidity [35].

Mechanisms of PCTs on quality of care

The discussions of the mechanisms of PCTs on quality of care in the seventeen studies were extracted and reported in Table S1 (supplementary file 3). The articles highlighted several common mechanisms by which PCTs achieved effective or ineffective results. First, support for team members and patients from leadership was fundamental and foremost for PCTs implementation and effectiveness [35]. Chen et al. considered that active participation and support from departmental leadership was critical in implementing and sustaining the Teamlet intervention. Second, changing the organization of care played an important role in increasing coordination of care, for example, integrating mental care [36, 49] or cancer care [48] with primary care. Integrating mental care for patients with chronic conditions comorbid with depression reduced depressive symptoms in patients with chronic conditions, but how to integrate mental and physical healthcare in patients with broader multimorbidity was not certain [36]. Third, timely follow-up and medication adjustment were important to enhance medication adherence and achieve treatment goals [40, 41]. Adjusting medication portfolio timely could guarantee a higher chance of improvements in clinical goals and also serve as a reminder for patients’ adherence. Fourth, strong support for patients’ self-management provided by PCTs was reported to contribute strongly to improving quality of care [40,41,42, 47]. Nurses educated patients about essential skills and knowledge in managing their conditions and changing their lifestyle [39].

Discussion

As the chronic disease burden increase and more patients with multimorbidity, primary care faces more challenges in balancing the increasing disease burden and assuring quality of care. PCTs have been examined in developed countries to cope with this transition. This review examined the characteristics of PCTs, the impacts of PCTs on quality of care, and the mechanisms by which PCTs influence quality of care in primary care settings among patients with multimorbidity. First, PCTs designed for people with multimorbidity can be broadly categorized into three types: 1) upward collaborative PCTs (primary care workers and specialists), 2) downward PCTs (primary care workers and lay health workers), and 3) traditional PCTs (primary care physicians and care managers). Second, as for the impact of PCTs on quality of care among people with multimorbidity, PCTs have improved patients’ mental and psychological health outcomes, improved patients’ perceptions towards care, changed the process of care, and showed mixed effects on clinical outcome measures. Third, as for the mechanisms of PCTs on quality of are among people with multimorbidity, 1) support for team members and patients from leadership, 2) re-organization of care, 3) timely follow-up and medication adjustment, and 4) strong support for patients’ self-management provided by PCTs contributed to the effectiveness of PCTs.

A team environment could provide support for the health workers involved as well as enable more efficient sharing of information [54]. In the included studies, different terms were used to describe a range of interventions delivered by several health workers working as a team to provide health services, such as collaborative care, integrated care, group practice, etc. Despite varying content or intensity of interventions, the core was the manner of working as a team.

The three models of PCTs faced different challenges in implementation and achieving desired outcomes. For the upward collaborative PCTs, medical specialists from upper-level hospitals were engaged. The most important role for specialists was to train primary health workers, especially in less developed regions where primary health workers did not have enough capacity to manage patients with complex needs. For ensuring the quality of managing patients with multimorbidity, appropriate training and timely guidance from specialists are especially helpful for GPs and nurses. However, over-reliance on specialists could undermine the roles of GPs in the team and underscore perceptions that the wellbeing of patients is not the team’s responsibility. Specialists are prone to become the team’s center because of the imbalanced power [55], which is inappropriate when they are not engaged in most care delivery or patient contacts in PHC settings.

For the downward collaborative PCTs, the non-clinical procedures in a patient journey were more taken as the health system's responsibility than the other two types of PCTs, which was carried out by the lay health workers. There were several advantages involving lay workers from the community into the team. First, they live near to patients and can have more interactions with patients and thus increase the continuity of care, and also reinforce the effect of self-management [47]. Second, they have more flexible time to help patients with non-medical matters like transportation to hospitals. However, patients may not trust them because they are not medical professionals, which may decrease the team’s effectiveness. In the two studies of the downward collaborative PCTs, the community health workers also provided counseling services, medical education to patients and activated emergency medical services when needed [43, 47], which means that they had to be trained and upskilled about the knowledge for specific disease [56]. Their qualification and scope of providing the services are also of concern. The communication and administration costs also increase as the team becomes larger.

For traditional PCTs, GPs and care managers have already worked collaboratively under the same roof of a clinic. How to mobilize the health workers in a more effective way to improve the quality of care is the renewed interest. The team was used to be led by GP [57], but new PCTs empowered nurses/medical assistants to lead the team. Traditional PCTs used the existing workforce without system-level changes, making the model more generalizable for other places with funding constraints. The smaller scale of the PCTs and shorter distance among team members decrease the communication and administration cost. Besides, a clear division of labor should be determined so that full potential can be brought out of the staff [58]. However, the extra responsibilities, such as giving an overall assessment of patients, helping patients to develop goals, were mostly assigned to nurses or medical assistants. Nurses or medical assistants’ workload increased greatly, especially for patients with multimorbidity who require more attention to manage.

PCTs achieve effectiveness by several mechanisms. First, support for team members and patients from leadership plays an important role in enhancing team members’ confidence and enthusiasm [35, 45]. Second, re-organization of care ensure, including enhancing integration of care [36, 38, 40, 49, 50, 52], accessibility of care comprehensiveness of care and continuity of care [35, 38, 46, 50, 53]. Third, timely follow-up and medication adjustment increase the intensiveness of care [46, 53, 59, 59]. Lastly, PCTs provide strong support for patients’ self-management, which also contribute to the effectiveness of PCTs.

Taking three types of PCTs together, we can see that some extra responsibilities are added to the health system: first, self-management is no longer patients’ own business, but helped and guided by the health system; second, non-clinical procedures in patient journeys are also taken care of by the health system; patients’ wellbeing especially mental health instead of individual disease are emphasized more in improving health. PCTs provided an opportunity to rearrange those extra workloads. Routine patient management was transferred to care managers or coordinators that included nurses, medical assistants, community health workers or lay counselors, etc. Besides non-clinical contact with patients, nurses in some models also took over some therapeutic work from physicians, such as screening and monitoring depression. The efficient implementation of PCTs depends largely on nurses’ capability. They decide appropriate and feasible self-management measures for patients with multimorbidity, and also serve as the link between patients and the health system.

When working as a team, health workers have opportunities to supervise and correct each other in daily clinical practice, which may contribute to the improved process of care. The PCTs also bring more interaction between patients and the health workers. Those increased face-to-care communications can make patients learn more about their conditions and also more about their PCTs, and help them to order the chaos in multiple morbidities [60]. The influence of changes in prescribing behaviors including medication adjustments on quality of care for people with multimorbidity needs to be studied in the future. Timely adjusting medication can have positive effects on patients, but whether increased adjustments will lead to over reliance on medications and overlooking self-management is unclear.

Inadequate collaboration within teams is a primary cause for studies that showed unsatisfactory improvements. PCTs provide an opportunity to learn from other team members and offer holistic, continuous, and comprehensive care for patients with complex needs [13]. However, whether care is actually provided by a team remain questioned. A previous review that examined collaborative care among cancer patients comorbid with depression found that collaborative care is promoted but not achieved. The current models were hospital-based and reliant on medication as the primary treatment [61]. In this review, studies also reported the similar problem. Only 14.5% of participants received the intended full components of interventions [47], and only 49% of intervention participants received full intervention package [45]. There may be defects in the studies’ process, but it also highlights implementation problems in real world. From design to practice, PCTs may take more time and efforts than expected.

The effective implementation of PCTs demands support from external environments, otherwise if would lead to ineffective results. Most studies identified in this review were RCT, but the incentive mechanisms for the team were not well designed in the interventions. This is of concern for a wider implementation, especially when involving health workers outside clinics. Besides, the payment mechanism should also be updated to fit in this new working model. The introduction of computerized tools in PCTs is also noteworthy. Working with multiple people requires communication and coordination. Information acquired from the previous health worker about patients’ needs to be passed quickly and efficiently to the next team member. Some interventions introduced such tools to facilitate the work process by integrating a computerized decision support system and clinical electronic medical record system [34]. It helped all team members to share the information at any time, and served as a complement for routine meetings. This is consistent with the development of care for multimorbidity. Data-informed care has been propelled for managing patient with multimorbidity at both the individual and population level [62]. Besides, governance and management of PCTs are also important to sustain PCTs and allow for continuity of care. The organization of the PHC system varies significantly in different contexts, so there is no one PCTs fit for all regions or health systems. When interpreting the effectiveness of PCTs, it’s important to remember the contexts of that PCTs, especially when implementing it elsewhere.

Limitations

This systematic review was subject to several limitations. First, due to the complexity of interventions, we could not link a specific intervention with the changes in quality of care. Second, the strict inclusion and exclusion criteria of patients and heterogeneity in specific diseases of multimorbidity in the literature limited the generalizability of the results, especially given the complex profile of patients involved in the real world. Third, the quality of training provided as part of the interventions was unable to be assessed in this review. Our analysis of the interventions was limited by the published descriptions of interventions. Although we also searched for published protocols and other information when the descriptions were not detailed, it might still encounter publication bias.

Conclusion

This review has evaluated the PCTs and their impact on quality of care for patients with multimorbidity and suggested major gaps in the evidence that needs to be filled. On the basis of our results, we recommend that future research should further explore the impact of PCTs on clinical outcome measures for patients with multimorbidity. Moreover, the providers’ and patients’ attitudes and acceptability of the PCTs should be examined to inform policy makers of the implementation difficulties. To move from research to practice, policy makers should design incentives for the teams and their members, clarify the job responsibilities for different roles without compromising the quality of care or over-reliance on specialists, and embrace technology to increase efficiency of care delivery.

Availability of data and materials

All data generated during this research are incorporated in the article and its online supplementary material.

Abbreviations

PCTs:

Primary care teams

PHC:

Primary health care

RCT:

Randomized controlled trials

GP:

General practitioners

References

  1. WHO. World health statistics 2020: monitoring health for the SDGs, sustainable development goals. 2020.

    Google Scholar 

  2. Barnett K, Mercer SW, Norbury M, Watt G, Wyke S, Guthrie B. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study. Lancet. 2012;380(9836):37–43. https://doi.org/10.1016/s0140-6736(12)60240-2.

    Article  Google Scholar 

  3. Services UDoHaH. Multiple chronic conditions—a strategic framework: optimum health and quality of life for individuals with multiple chronic conditions. 2010.

    Google Scholar 

  4. Zhang R, Lu Y, Shi L, Zhang S, Chang F. Prevalence and patterns of multimorbidity among the elderly in China: a cross-sectional study using national survey data. BMJ Open. 2019;9(8):e024268. https://doi.org/10.1136/bmjopen-2018-024268.

    Article  Google Scholar 

  5. Farmer C, Fenu E, O’Flynn N, Guthrie B. Clinical assessment and management of multimorbidity: summary of NICE guidance. Bmj. 2016;354:i4843. https://doi.org/10.1136/bmj.i4843.

    Article  Google Scholar 

  6. Salisbury C, Man MS, Bower P, et al. Management of multimorbidity using a patient-centred care model: a pragmatic cluster-randomised trial of the 3D approach. Lancet. 2018;392(10141):41–50. https://doi.org/10.1016/s0140-6736(18)31308-4.

    Article  Google Scholar 

  7. Tinetti ME, Fried TR, Boyd CM. Designing health care for the most common chronic condition–multimorbidity. JAMA. 2012;307(23):2493–4. https://doi.org/10.1001/jama.2012.5265.

    Article  CAS  Google Scholar 

  8. Smith SM, Soubhi H, Fortin M, Hudon C, O’Dowd T. Managing patients with multimorbidity: systematic review of interventions in primary care and community settings. BMJ. 2012;345:e5205. https://doi.org/10.1136/bmj.e5205.

    Article  Google Scholar 

  9. Starfield B, Shi L, Macinko J. Contribution of primary care to health systems and health. Milbank Q. 2005;83(3):457–502. https://doi.org/10.1111/j.1468-0009.2005.00409.x.

    Article  Google Scholar 

  10. Rohde J, Cousens S, Chopra M, et al. 30 years after Alma-Ata: has primary health care worked in countries? The Lancet. 2008;372(9642):950–61.

    Article  Google Scholar 

  11. Stange KC, Ferrer RL. The paradox of primary care. Ann Fam Med. 2009;7(4):293–9. https://doi.org/10.1370/afm.1023.

    Article  Google Scholar 

  12. Hudon C, Chouinard MC, Pluye P, et al. Characteristics of Case Management in Primary Care Associated With Positive Outcomes for Frequent Users of Health Care: A Systematic Review. Ann Fam Med. 2019;17(5):448–58. https://doi.org/10.1370/afm.2419.

    Article  Google Scholar 

  13. Wranik WD, Price S, Haydt SM, et al. Implications of interprofessional primary care team characteristics for health services and patient health outcomes: A systematic review with narrative synthesis. Health Policy. 2019;123(6):550–63. https://doi.org/10.1016/j.healthpol.2019.03.015.

    Article  Google Scholar 

  14. Shi L, Lee DC, Chung M, Liang H, Lock D, Sripipatana A. Patient-centered medical home recognition and clinical performance in US community health centers. Health Serv Res. 2017;52(3):984–1004.

    Article  Google Scholar 

  15. Somé NH, Devlin RA, Mehta N, Zaric GS, Sarma S. Team-based primary care practice and physician’s services: Evidence from Family Health Teams in Ontario. Canada Soc Sci Med. 2020;264:113310. https://doi.org/10.1016/j.socscimed.2020.113310.

    Article  Google Scholar 

  16. Bodenheimer T. Lessons from the trenches–a high-functioning primary care clinic. N Engl J Med. 2011;365(1):5–8. https://doi.org/10.1056/NEJMp1104942.

    Article  CAS  Google Scholar 

  17. Fortin M, Lapointe L, Hudon C, Vanasse A, Ntetu AL, Maltais D. Multimorbidity and quality of life in primary care: a systematic review. Health Qual Life Outcomes. 2004;2:51. https://doi.org/10.1186/1477-7525-2-51.

    Article  Google Scholar 

  18. van den Akker M, Buntinx F, Metsemakers JF, Roos S, Knottnerus JA. Multimorbidity in general practice: prevalence, incidence, and determinants of co-occurring chronic and recurrent diseases. J Clin Epidemiol. 1998;51(5):367–75. https://doi.org/10.1016/s0895-4356(97)00306-5.

    Article  Google Scholar 

  19. Smith SM, Wallace E, O’Dowd T, Fortin M. Interventions for improving outcomes in patients with multimorbidity in primary care and community settings. Cochrane Database Syst Rev. 2021;1(1):CD006560. https://doi.org/10.1002/14651858.CD006560.pub4.

    Article  Google Scholar 

  20. Petersen JJ, Paulitsch MA, Mergenthal K, et al. Implementation of chronic illness care in German primary care practices–how do multimorbid older patients view routine care? A cross-sectional study using multilevel hierarchical modeling. BMC Health Serv Res. 2014;14:336. https://doi.org/10.1186/1472-6963-14-336.

    Article  Google Scholar 

  21. Chevillard G, Mousquès J. Medically underserved areas: are primary care teams efficient at attracting and retaining general practitioners? Soc Sci Med. 2021;287:114358. https://doi.org/10.1016/j.socscimed.2021.114358.

    Article  Google Scholar 

  22. Hasler J. The primary health care team: history and contractual farces. BMJ: British Med J. 1992;305(6847):232.

    Article  CAS  Google Scholar 

  23. Gené-Badia J, Ascaso C, Escaramis-Babiano G, Catalán-Ramos A, Pujol-Ribera E, Sampietro-Colom L. Population and primary health-care team characteristics explain the quality of the service. Health Policy. 2008;86(2–3):335–44. https://doi.org/10.1016/j.healthpol.2007.11.014.

    Article  Google Scholar 

  24. Giannitrapani KF, Rodriguez H, Huynh AK, et al. How middle managers facilitate interdisciplinary primary care team functioning. Healthc (Amst). 2019;7(2):10–5. https://doi.org/10.1016/j.hjdsi.2018.11.003.

    Article  Google Scholar 

  25. Wells WD. Pharmacists are key members of primary health care teams. 1997. p. 1486.

    Google Scholar 

  26. Falloon D. The social worker. A member of the primary care team? West Indian Med J. 1998;47(Suppl 4):28–30.

    Google Scholar 

  27. Corser CM, Ryce SW. Community mental health care: a model based on the primary care team. BMJ. 1977;2(6092):936–8. https://doi.org/10.1136/bmj.2.6092.936.

    Article  CAS  Google Scholar 

  28. Fletcher AM. The nutritionist as the primary care provider in a team approach to obesity. J Am Diet Assoc. 1982;80(3):253–5.

    Article  CAS  Google Scholar 

  29. Donabedian A. Evaluating the quality of medical care. Milbank Mem Fund Q. 1966;44(3):Suppl:166-206.

    Article  CAS  Google Scholar 

  30. Busse R, Klazinga NS, Panteli D, Quentin W. Improving healthcare quality in Europe: Characteristics, effectiveness and implementation of different strategies. Improving healthcare quality in Europe: Characteristics, effectiveness and implementation of different strategies. 2019.

    Google Scholar 

  31. Quality of care. Council on Medical Service. Jama. 1986;256(8):1032–4.

    Google Scholar 

  32. Lohr KN. Medicare: a strategy for quality assurance. National Academy Press; 1990.

  33. Hong Q, Pluye P, Fàbregues S, et al. Mixed Methods Appraisal Tool (MMAT), version 2018. Registration of Copyright (# 1148552), Canadian Intellectual Property Office, Industry Canada. Canadian Intellectual Property Office; 2018.

  34. Aragonès E, Rambla C, López-Cortacans G, et al. Effectiveness of a collaborative care intervention for managing major depression and chronic musculoskeletal pain in primary care: A cluster-randomised controlled trial. J Affective Dis. 2019;252:221–9. https://doi.org/10.1016/j.jad.2019.04.004.

    Article  Google Scholar 

  35. Chen EH, Thom DH, Hessler DM, et al. Using the Teamlet Model to improve chronic care in an academic primary care practice. J Gen Intern Med. 2010;25(Suppl 4):S610–4. https://doi.org/10.1007/s11606-010-1390-1.

    Article  Google Scholar 

  36. Coventry P, Lovell K, Dickens C, et al. Integrated primary care for patients with mental and physical multimorbidity: cluster randomised controlled trial of collaborative care for patients with depression comorbid with diabetes or cardiovascular disease. BMJ (Clinical research ed). 2015;350:h638. https://doi.org/10.1136/bmj.h638.

    Article  Google Scholar 

  37. Freund T, Peters-Klimm F, Boyd CM, et al. Medical Assistant-Based Care Management for High-Risk Patients in Small Primary Care Practices: A Cluster Randomized Clinical Trial. Annals of internal medicine. 2016;164(5):323–30. Comment in: Rev Med Suisse. 2016 Apr 13;12(514):765; https://www.ncbi.nlm.nih.gov/pubmed/27263156. PMID: 27263156. https://doi.org/10.7326/M14-2403

  38. Jan CFJ, Chang CJJ, Hwang SJ, et al. Impact of team-based community healthcare on preventable hospitalisation: A population-based cohort study in Taiwan. BMJ Open. 2021;11(2):e039986. https://doi.org/10.1136/bmjopen-2020-039986.

    Article  Google Scholar 

  39. Katon WJ, Von Korff M, Lin EHB, et al. The Pathways Study: a randomized trial of collaborative care in patients with diabetes and depression. Arch Gen Psychiatry. 2004;61(10):1042–9.

    Article  Google Scholar 

  40. Katon WJMD, Lin EHBMDMPH, Von Korff MS, et al. Collaborative Care for Patients with Depression and Chronic Illnesses. The New England J Med. 2010;363(27):2611–20.

    Article  CAS  Google Scholar 

  41. Lin EHB, Von Korff M, Ciechanowski P, et al. Treatment adjustment and medication adherence for complex patients with diabetes, heart disease, and depression: a randomized controlled trial. Annals Of Family Med. 2012;10(1):6–14. https://doi.org/10.1370/afm.1343https://www.ncbi.nlm.nih.gov/pubmed/22230824. PMID: 22230824

    Article  Google Scholar 

  42. Morgan MA, Coates MJ, Dunbar JA, Reddy P, Schlicht K, Fuller J. The TrueBlue model of collaborative care using practice nurses as case managers for depression alongside diabetes or heart disease: a randomised trial. BMJ Open. 2013;3(1):e002171. https://doi.org/10.1136/bmjopen-2012-002171.

    Article  Google Scholar 

  43. Petersen I, Bhana A, Fairall LR, et al. Evaluation of a collaborative care model for integrated primary care of common mental disorders comorbid with chronic conditions in South Africa. BMC Psychiatry. 2019;19(1):107. https://doi.org/10.1186/s12888-019-2081-z.

    Article  Google Scholar 

  44. Petersen I, Fairall L, Zani B, et al. Effectiveness of a task-sharing collaborative care model for identification and management of depressive symptoms in patients with hypertension attending public sector primary care clinics in South Africa: pragmatic parallel cluster randomised controlled trial. Article J Affective Disorders. 2021;282:112–21.

    Article  Google Scholar 

  45. Salisbury C, Man MS, Bower P, et al. Management of multimorbidity using a patient-centred care model: a pragmatic cluster-randomised trial of the 3D approach. The Lancet. 2018;392(10141):41–50. https://doi.org/10.1016/S0140-6736(18)31308-4.

    Article  Google Scholar 

  46. Sharpe M, Walker J, Hansen CH, et al. Integrated collaborative care for comorbid major depression in patients with cancer (SMaRT Oncology-2): A multicentre randomised controlled effectiveness trial. Lancet. 2014;384(9948):1099–108. https://doi.org/10.1016/S0140-6736(14)61231-9.

    Article  Google Scholar 

  47. Towfighi A, Cheng EM, Ayala-Rivera M, et al. Effect of a Coordinated Community and Chronic Care Model Team Intervention vs Usual Care on Systolic Blood Pressure in Patients with Stroke or Transient Ischemic Attack: The SUCCEED Randomized Clinical Trial. JAMA Network Open. 2021;4(2):e2036227. https://doi.org/10.1001/jamanetworkopen.2020.36227.

    Article  Google Scholar 

  48. Walker J, Hansen CH, Martin P, et al. Integrated collaborative care for major depression comorbid with a poor prognosis cancer (SMaRT Oncology-3): a multicentre randomised controlled trial in patients with lung cancer. The Lancet Oncology. 2014;15(10):1168–76. https://doi.org/10.1016/S1470-2045(14)70343-2https://www.ncbi.nlm.nih.gov/pubmed/25175951. Comment in: Lancet. 2014 Sep 20;384(9948):1076-8; PMID: 25175951

    Article  Google Scholar 

  49. Wolff LS, Flynn A, Xuan Z, Errichetti KS, Tapia Walker S, Brodesky MK. The Effect of Integrating Primary Care and Mental Health Services on Diabetes and Depression: A Multi-site Impact Evaluation on the US-Mexico Border. Medical Care. 2021;59(1):67–76. https://doi.org/10.1097/MLR.0000000000001429.

    Article  Google Scholar 

  50. Wood DA, Kotseva K, Connolly S, et al. Nurse-coordinated multidisciplinary, family-based cardiovascular disease prevention programme (EUROACTION) for patients with coronary heart disease and asymptomatic individuals at high risk of cardiovascular disease: A paired, cluster-randomised controlled trial. The Lancet. 2008;371(9629):1999–2012. https://doi.org/10.1016/S0140-6736(08)60868-5.

    Article  CAS  Google Scholar 

  51. Huang Y, Wei X, Wu T, Chen R, Guo A. Collaborative care for patients with depression and diabetes mellitus: a systematic review and meta-analysis. BMC Psychiatry. 2013;2013(13):260. https://doi.org/10.1186/1471-244X-13-260.

    Article  Google Scholar 

  52. Katon WJ, Von Michael K, Lin EHB, Simon G, et al. The Pathways Study: A Randomized Trial of Collaborative Care in Patients With Diabetes and Depression. Arch Gen Psychiatry. 2004;61(10):1042–9.

    Article  Google Scholar 

  53. Walker J, Hansen CH, Martin P, et al. Integrated collaborative care for major depression comorbid with a poor prognosis cancer (SMaRT Oncology-3): a multicentre randomised controlled trial in patients with lung cancer. Lancet Oncol. 2014;15(10):1168–76. https://doi.org/10.1016/s1470-2045(14)70343-2.

    Article  Google Scholar 

  54. Dieleman SL, Farris KB, Feeny D, Johnson JA, Tsuyuki RT, Brilliant S. Primary health care teams: team members’ perceptions of the collaborative process. J Interprof Care. 2004;18(1):75–8.

    Article  Google Scholar 

  55. Doekhie KD, Buljac-Samardzic M, Strating MMH, Paauwe J. Who is on the primary care team? Professionals’ perceptions of the conceptualization of teams and the underlying factors: a mixed-methods study. BMC Family Practice. 2017;18(1):111. https://doi.org/10.1186/s12875-017-0685-2.

    Article  Google Scholar 

  56. Wagner EH. The role of patient care teams in chronic disease management. BMJ. 2000;320(7234):569–72.

    Article  CAS  Google Scholar 

  57. Freund T, Everett C, Griffiths P, Hudon C, Naccarella L, Laurant M. Skill mix, roles and remuneration in the primary care workforce: who are the healthcare professionals in the primary care teams across the world? Int J Nurs Stud. 2015;52(3):727–43. https://doi.org/10.1016/j.ijnurstu.2014.11.014.

    Article  Google Scholar 

  58. Grumbach K, Bodenheimer T. Can health care teams improve primary care practice? JAMA. 2004;291(10):1246–51.

    Article  CAS  Google Scholar 

  59. Lin EH, Von Korff M, Ciechanowski P, et al. Treatment adjustment and medication adherence for complex patients with diabetes, heart disease, and depression: a randomized controlled trial. Ann Fam Med Jan-Feb. 2012;10(1):6–14. https://doi.org/10.1370/afm.1343.

    Article  Google Scholar 

  60. Haggerty JL. Ordering the chaos for patients with multimorbidity. Editorial BMJ. 2012;345(7876):e5915. https://doi.org/10.1136/bmj.e5915.

    Article  Google Scholar 

  61. Shaw J, Sethi S, Vaccaro L, et al. Is care really shared? A systematic review of collaborative care (shared care) interventions for adult cancer patients with depression. BMC Health Serv Res. 2019;19(1):120. https://doi.org/10.1186/s12913-019-3946-z.

    Article  Google Scholar 

  62. Chiolero A, Rodondi N, Santschi V. High-value, data-informed, and team-based care for multimorbidity. Letter The Lancet Public Health. 2020;5(2):e84. https://doi.org/10.1016/S2468-2667(20)30007-4.

    Article  Google Scholar 

Download references

Acknowledgements

We would like to acknowledge Beibei Yuan for her insightful and constructive guidance.

Funding

National Science and Technology Project on Development Assistance for Technology, Developing China-ASEAN Public Health Research and Development Collaborating Center (No. KY202101004).

Author information

Authors and Affiliations

Authors

Contributions

ML drafted the manuscript. ML and XL developed the search strategy. ML and HT searched and reviewed the literature. All authors read, provided feedback, and approved the final manuscript.

Corresponding author

Correspondence to Xiaoyun Liu.

Ethics declarations

Ethics approval and consent to participate

This study did not need approval for an ethics committee.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1.

Search strategies.

Additional file 2.

Cochrane criteria for risk of bias and outcomes & MMAT check lists.

Additional file 3:

Table S1. Mechanisms for effective results and ineffective results for primary care teams (PCT).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, M., Tang, H. & Liu, X. Primary care team and its association with quality of care for people with multimorbidity: a systematic review. BMC Prim. Care 24, 20 (2023). https://doi.org/10.1186/s12875-023-01968-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12875-023-01968-z

Keywords