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Effectiveness of system navigation programs linking primary care with community-based health and social services: a systematic review

BMC Health Services Research volume 23, Article number: 450 (2023) Cite this article

Abstract

Background

Fragmented delivery of health and social services can impact access to high-quality, person-centred care. The goal of system navigation is to reduce barriers to healthcare access and improve the quality of care. However, the effectiveness of system navigation remains largely unknown. This systematic review aims to identify the effectiveness of system navigation programs linking primary care with community-based health and social services to improve patient, caregiver, and health system outcomes.

Methods

Building on a previous scoping review, PsychInfo, EMBASE, CINAHL, MEDLINE, and Cochrane Clinical Trials Registry were searched for intervention studies published between January 2013 and August 2020. Eligible studies included system navigation or social prescription programs for adults, based in primary care settings. Two independent reviewers completed study selection, critical appraisal, and data extraction.

Results

Twenty-one studies were included; studies had generally low to moderate risk of bias. System navigation models were lay person-led (n = 10), health professional-led (n = 4), team-based (n = 6), or self-navigation with lay support as needed (n = 1). Evidence from three studies (low risk of bias) suggests that team-based system navigation may result in slightly more appropriate health service utilization compared to baseline or usual care. Evidence from four studies (moderate risk of bias) suggests that either lay person-led or health professional-led system navigation models may improve patient experiences with quality of care compared to usual care. It is unclear whether system navigation models may improve patient-related outcomes (e.g., health-related quality of life, health behaviours). The evidence is very uncertain about the effect of system navigation programs on caregiver, cost-related, or social care outcomes.

Conclusions

There is variation in findings across system navigation models linking primary care with community-based health and social services. Team-based system navigation may result in slight improvements in health service utilization. Further research is needed to determine the effects on caregiver and cost-related outcomes.

Peer Review reports

Background

Patients and their caregivers often face significant challenges when navigating increasingly complex health and social services. Frequently left to locate and access these siloed services alone [1], adults living with multifaceted health and social needs have described their care as disjointed, confusing, and uncoordinated [2]. Barriers to accessing available health and social services may include restrictive eligibility criteria and wait lists for services, financial constraints, health literacy and communication challenges, lack of transportation, and poor coordination between primary care providers and health and social service agencies [3]. In an effort to overcome this fragmentation and efficiently access the care they need, patients and caregivers often spend an extraordinary amount of time becoming informal system navigators and de facto care coordinators [4]. This can have significant physical, emotional, social, relational, and financial repercussions [1, 4, 5]. Given the rising prevalence of chronic diseases and multimorbidity worldwide [6], in addition to urgent calls to address the social and structural inequities that exist in health systems [7, 8], identifying effective strategies to support individuals in accessing high-quality health and social care is of vital importance.

Over the last 30 years, system navigation programs have gained popularity globally as a person-centred approach to support individuals to access health and social care [9,10,11] . Established initially to overcome health inequities in cancer care [12], system navigation has since expanded into areas such as chronic disease management [13, 14], mental health [15, 16], and to facilitate access to care for marginalized and historically underserved populations (e.g., persons experiencing homelessness, food insecurity, living in low-income countries) [17, 18]. Various terms are used in the literature to describe individuals who provide navigation support, such as patient navigators, community health workers, case managers, and link workers [17, 19]. For this review, system navigation is defined as programs that link the patient’s primary healthcare delivery and community-based health and social services to create integrated, patient-focused care [17, 20]. System navigation can be facilitated by an individual or team of lay and/or healthcare professionals to reduce barriers and facilitate access to continuous, effective, and efficient care for patients, caregivers, and providers [21].

Despite growing interest and calls to expand navigation programs for the general public to enhance integrated care delivery [1, 22], an understanding of the effectiveness of system navigation overall, and characteristics of effective models is largely unknown. A previous scoping review to identify navigation models [17] and factors influencing the implementation of navigation programs linking primary care with community-based health and social services [21] found the key motivators for implementing such programs included improving the delivery of health and social services to meet patient/population health needs and improve quality of life; however, this review included primarily descriptive, observational, and qualitative studies. In conclusion, Valaitis and colleagues [21] recommended a systematic review of primary care-based system navigation programs as a critical next step to determine program effectiveness and inform practice and policy decision-making related to optimal models and impacts.

As the body of literature has grown, this systematic review builds upon the previous scoping review of system navigation programs [17, 21] to identify the effectiveness of system navigation programs linking primary care with community-based health and social services to improve patient, caregiver, and health system outcomes when compared to usual care.

Methods

This systematic review was registered with PROSPERO (CRD42020205050). The reporting of this review is based on PRISMA guidelines [23].

Search strategy

The search strategy was built upon the previous scoping review of navigation programs linking primary care with community-based health and social services [17, 21]. Updating the previously conducted search, the electronic databases PsychInfo, EMBASE, CINAHL, OVID MEDLINE, and Cochrane Clinical Trials Registry were searched from January 1, 2013, to August 10, 2020 (Additional file 1). A health science librarian trained in building searches for systematic reviews consulted on the search strategy. In line with the previous scoping review, database searches were limited to studies published in the English language only.

Study selection

Identified references were uploaded to Covidence (Veritas Health Innovation Ltd., Melbourne, Australia) and duplicates were removed. Titles and abstracts were independently screened by two reviewers for inclusion based on predetermined eligibility criteria. Full texts of potentially relevant studies were retrieved and screened by two independent reviewers. Conflicts were resolved through discussion or with the input of a third reviewer, as needed. Included studies from the previous scoping review [17, 21] were also reviewed independently and in duplicate to determine eligibility, as the previous review included qualitative and observational studies, in addition to intervention studies.

Eligibility criteria

Types of studies

To determine intervention effectiveness, eligible studies were limited to experimental and quasi-experimental designs, including randomized controlled trials (RCTs), non-randomized controlled trials, and single group, pre-test/post-test intervention studies. Mixed methods studies with eligible quantitative designs were also included; however, only quantitative data were extracted. Qualitative, observational, descriptive, and cross-sectional studies were excluded.

Participants

Eligible studies included adults 18 years of age and older utilizing primary care. In contrast to the previous scoping review, studies that focused on disease-specific populations (e.g., cancer, mental health) were excluded to allow broader transferability and inform effective interventions to support health and social care access among general patient populations. However, studies that included patients with a variety of chronic diseases or chronic disease risk factors were eligible, given that the interventions described were not disease specific.

Interventions

System navigation programs based in a primary care setting that aimed to link patients to appropriate community-based health and social services were included. Primary care was defined as care delivered at the entry point into the healthcare system, which is typically provided by a physician or nurse practitioner [9]. Social prescription programs, which link users to community social services that may be considered outside of the healthcare system [9, 24], were eligible. In line with the original scoping review, we initially intended to include system navigation programs linking primary care to other medical specialty care services. However, we later decided to include interventions that went beyond health system navigation alone to focus on integrated, upstream, and community-based approaches. This decision was made in light of mounting evidence that integrated health and social care interventions focused on addressing the social determinants of health can improve health outcomes and reduce the use of costlier health services [25, 26]. Given the distinct role and function of case managers as clinical care providers, which may extend beyond the scope of system navigation [27], interventions that focused exclusively on case management were excluded. However, interventions that included a case management component in addition to system navigation were eligible.

Comparators

Studies that compared an intervention to any non-intervention comparison group were eligible, including pre-intervention data or data from a non-exposed control group.

Outcomes

The primary outcomes of interest were access to care (i.e., timely use of healthcare and/or social services to achieve improved health outcomes) and health and social service utilization. Secondary outcomes included patient-related (e.g., general health and wellbeing, quality of life, self-efficacy) and caregiver outcomes (e.g., caregiver burden, self-efficacy). Upon review of included studies, it became apparent that experience measures (e.g., satisfaction with the quality of care) and cost-related outcomes were also relevant. Thus, these other outcomes were added after the initial PROSPERO registration.

Assessment of methodological quality

Two independent reviewers critically appraised all eligible studies to assess methodological quality using the Joanna Briggs Institute Critical Appraisal tools for experimental and quasi-experimental studies [28]. Conflicts were resolved through discussion between reviewers and input from a third reviewer when needed.

Data extraction

Two independent reviewers extracted data using a pre-tested template; discrepancies were resolved through discussion or input from a third reviewer when needed. The data abstraction template included study characteristics (i.e., aim, study design, country), participant characteristics (i.e., number of participants, population description, age, sex, ethnicity, socioeconomic status), description of any comparator groups, limitations, and conclusions as reported by study authors. The Template for Intervention Description and Replication (TIDieR) checklist guided extraction of intervention components [29]. For relevant outcomes, the measure, effect, variation, and statistical significance were extracted. Authors were contacted to obtain missing data. Data collection forms are available upon request.

Data synthesis

System navigation programs were grouped based on the navigation models identified in the previous scoping review, including lay person-led (i.e., non-healthcare professionals within primary care who perform specific activities related to system navigation), health professional-led (e.g., nurse or social worker who performs specific activities related to system navigation), and team-based (i.e., lay persons and health professionals together, or teams of health professionals) [17]. Results of individual studies were organized into tables by intervention type and outcomes (i.e., type, data collection tool, and measure of effect and significance) to facilitate synthesis and identify possible sources of heterogeneity. A meta-analysis was deemed inappropriate given the wide range of system navigation models and outcomes identified; instead, a narrative approach to synthesis was used [30], with data presented in corresponding tables. Reporting bias was not explored because most studies did not cite trial registrations or protocols. A comprehensive approach to assess the overall certainty of the evidence for each outcome (e.g., GRADE) was not used due to heterogeneity across interventions and outcomes.

Patient and public involvement

Key research partners, including four older adult citizens and one community-based social service provider, were included in the review team. The aim of patient and public involvement in this systematic review was to support the interpretation of the results and identify key takeaways to inform the co-design of a community-based intervention to enhance physical activity, nutrition, and system navigation among older adults experiencing health inequities [31]. This was achieved through virtual working group meetings and the collaborative development of knowledge translation products, including a public-facing infographic and research brief.

Results

Description of included studies

The updated search identified 15,226 unique records (Fig. 1). Following title and abstract screening, 387 full texts were retrieved and assessed for eligibility. A total of 21 studies published between 2009 and 2020 were included (Table 1); 19 of these were newly identified, and 2 were included in the previous scoping review. A list of excluded studies with reasons for exclusion is provided in Additional file 2. Study designs included RCTs (n = 8, 38%) [32,33,34,35,36,37,38,39], single group, pre-test/post-test designs (n = 7, 33%) [40,41,42,43,44,45,46], and two group, non-randomized designs (n = 6, 29%) [47,48,49,50,51,52]. Studies most often took place in the United States of America (n = 9, 43%) [32, 34, 35, 40, 43, 48, 50,51,52] or the United Kingdom (n = 8, 38%) [36, 41, 42, 44,45,46,47, 49]. A total of 10,743 participants (range 19 to 2,325 across studies) are represented, and, when mean ages were reported, the median mean age across studies was 72 years (range 49 to 82 years).

Fig. 1
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PRISMA Flow diagram

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Table 1 Characteristics of included studies (n = 21)
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Primary care-based system navigation program models included 1) lay person-led (n = 10, 48%) [34,35,36, 40, 43,44,45,46, 48, 52], 2) health professional-led (n = 4, 19%) [32, 42, 49, 51], and 3) team-based (n = 6, 29%) [33, 37,38,39, 41, 47]. A fourth model was also identified, which included self-navigation based on a personalized list of local resources with lay support available (n = 1, 5%) [50]. In studies that used a primarily lay person-led model, most (n = 7, 70%) described comprehensive navigator training and employed lay navigators as staff [34, 35, 40, 43, 45, 48, 52]. This training ranged from 3 h of online training [43] to a 16-week community college health coaching course [40]. In studies that used health professional-led models, system navigation was primarily nurse-led [32, 49, 51] or social worker-led [42, 49]; however, in one multi-site study, health professionals varied by setting and also included a nurse practitioner or physician assistant in system navigation roles [49]. The team-based navigation models included either lay person(s) and health professional(s) together [33, 39, 41, 47] or teams of health professionals [37, 38] who provided system navigation support.

Intervention duration and frequency of contact were highly variable across the included studies. The median length of system navigation programs was 6 months (range 2 to 30 months). Of the 17 studies that reported intervention frequency, most programs were delivered variably based on individual patient needs (n = 9, 53%) [33, 36, 41,42,43, 45,46,47, 49], while others occurred monthly (n = 4, 24%) [32, 34, 38, 40], weekly (n = 2, 12%) [35, 48], bi-monthly (n = 1, 6%) [39], or one-time-only (n = 1, 6%) [50]. Theoretical models or frameworks were reported in only 33% (n = 7) of studies to support the rationale for system navigation programs; these included the Chronic Care Model [33, 37, 48, 51], the biopsychosocial model [45], the integral conceptual model of frailty [49], and a theory of community-based primary care [36]. A full description of intervention characteristics based on the TIDieR framework is presented in Table 2.

Table 2 Intervention characteristics
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Methodological quality

Overall, the included studies had generally low to moderate risk of bias. Within the 8 RCTs, the risk of bias was primarily attributed to the absence of blinding among participants and interventionists (Fig. 2). The lack of control groups and incomplete follow-up predominantly contributed to the risk of bias among the 13 quasi-experimental studies (Fig. 3). Full critical appraisal assessments for each study are reported in Additional files 3 and 4 for RCTs and quasi-experimental studies, respectively.

Fig. 2
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Assessed using JBI Critical Appraisal Checklist for Randomized Controlled Trials

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Fig. 3
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Assessed using JBI Critical Appraisal Checklist for Quasi-Experimental Studies (includes single-group, pre-test/post-test and two-group, non-randomized study designs)

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Effectiveness of system navigation programs

A summary of findings by system navigation model and outcome category alongside a summary of the risk of bias is provided in Table 3. Complete data used for analyses for each outcome are provided in Additional files 5–9.

Table 3 Summary of results
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Health and social service access and utilization outcomes

The 13 studies that reported health service utilization evaluated lay person-led (n = 6, 46%) [34, 35, 40, 44, 48, 52], health professional-led (n = 4, 31%) [32, 42, 49, 51], and team-based (n = 3, 23%) [33, 41, 47] system navigation models. Health service utilization was primarily captured through administrative, health record, and/or health insurance data related to the number of primary care visits (n = 10, 77%) [32, 33, 35, 40,41,42, 47, 49, 51, 52], hospital admissions and/or readmissions (n = 9, 69%) [32,33,34,35, 40, 44, 48, 49, 51], emergency care visits (n = 7, 54%) [32, 33, 40, 44, 47, 48, 51], and home care visits (n = 4, 31%) [32, 42, 48, 51] (Additional file 5). None of the included studies reported healthcare access or social service utilization outcomes.

Overall, findings for lay person-led models were mixed. Three studies demonstrated improvements in health service utilization following lay person-led system navigation programs [34, 44, 52]. Compared to baseline, patients at high risk for avoidable hospital admissions due to medical or psychosocial issues who accessed the lay person-led Integrated Care Coordination Service had a statistically significant decrease in emergency department attendance and hospital admissions nine months post-referral (low risk of bias) [44]. Patients living in high-poverty areas who participated in the standardized, 6-month community health worker-led goal setting plus Individualized Management for Patient-Centered Targets (IMPaCT) program (tailored coaching, social support, navigation, advocacy) also had significantly lower odds of repeat admissions, but no difference in overall hospital admissions or length of stay when compared to goal setting plus usual care (low risk of bias) [34]. Compared to usual care, community health worker-led system navigation including patient education, appointment scheduling, and assistance overcoming barriers to healthcare access significantly increased the rate of primary care provider and/or chronic disease nurse visits among patients with chronic health needs who were classified as unengaged with their medical care (i.e., had not seen a primary care physician in last 6 months) (moderate risk of bias) [52]. Further, a higher percentage of these patients visited a primary care provider before seeking other providers for their health needs [52]. However, three studies demonstrated no significant changes following lay person-led system navigation programs when compared to baseline or usual care (moderate risk of bias) [35, 40, 48].

Similarly, the effectiveness of health professional-led system navigation on health service utilization outcomes was unclear. A social worker-led social prescribing program for patients with chronic conditions, polypharmacy, or frequent primary care attendance was associated with a significant decrease in the number of primary care physician visits, but no difference in home visits, telephone visits, or care contacts when compared to usual care in one study (moderate risk of bias) [42]. No significant impacts on health service utilization were observed in three other studies following health professional-led system navigation programs when compared to usual care (low-moderate risk of bias) [32, 49, 51].

In contrast, team-based system navigation models demonstrated some positive impacts on health service utilization across three studies with low risk of bias [33, 41, 47]. In the 6-month Health TAPESTRY program, volunteer-led home visits followed by action planning with the healthcare team and links to community support resulted in a statistically significant increase in primary care visits and reduced rates of hospitalization among older adults, with no significant changes in emergency department visits when compared to usual care [33]. Similarly, social worker and volunteer-led social prescribing to community services resulted in a significantly lower rate of annual general practitioner consultations with no significant impact on emergency department visits among adult patients experiencing social isolation with a history of frequent primary care visits, as compared to matched patients from a neighbouring area [47]. However, it should be noted that this study lacked randomization, and patients assigned to the intervention group had a significantly higher rate of general practitioner consultations at baseline compared to their matched counterparts. Finally, a health coach and link worker-led intervention involving a needs assessment and referral to relevant community services also significantly decreased primary care use over a 3-month time period among patients managing at least one long-term health condition and experiencing social isolation when compared to baseline [41].

Patient-related outcomes

In total, 16 studies captured patient-related outcomes [32,33,34,35,36,37,38,39, 41, 43, 45,46,47, 49,50,51]. These were grouped into four categories: 1) quality of life/health-related quality of life, mental health, and wellbeing, 2) social participation and function, 3) health behaviours, and 4) theoretical constructs related to behaviour change.

Quality of life/health-related quality of life, mental health, and wellbeing

In total, 13 studies investigated the impact of lay person-led (n = 5, 39%) [34,35,36, 46, 57], health professional-led (n = 3, 23%) [32, 49, 51], team-based (n = 4, 31%) [33, 37, 38, 47], and self-navigation with lay support as needed (n = 1, 8%) [50] system navigation models on quality of life/health-related quality of life, mental health, and wellbeing outcomes. These outcomes were most often measured using the 12- or 36-Item Short Form Survey (SF-12, SF-36) (n = 5, 39%) [32, 34, 35, 49, 50], EuroQol-5 Dimension (n = 5, 39%) [33, 36, 37, 46, 51], Hospital Anxiety and Depression Scale (n = 2, 15%) [36, 47], or the Warwick-Edinburgh Mental Wellbeing Scale (n = 2, 15%) [45, 46]. Various other single-item and self-report measures were used (Additional file 6).

Findings for lay person-led system navigation models were mixed. Social prescribing to local community health and wellbeing resources resulted in reduced anxiety and depression, better self-reported health, as well as a statistically and clinically significant improvement in patient wellbeing when compared to baseline in one study (moderate risk of bias) [46]. However, another social prescribing program found a statistically significant, but not clinically significant difference in wellbeing among patients with multiple chronic conditions experiencing social isolation/loneliness when compared to baseline (moderate risk of bias) [57]. Further, no significant changes in wellbeing, anxiety, depression, or health-related quality of life were found following the Community Links Practitioner intervention when compared to usual care (high risk of bias) [36]. The standardized goal setting plus IMPaCT intervention significantly improved health-related quality of life in the mental domain, but not the physical domain of the SF-12 when compared to goal setting plus usual care in one study (moderate risk of bias) [35]. However, no significant changes were observed in physical or mental health-related quality of life in another study evaluating the goal setting plus IMPaCT intervention when compared to usual care (low risk of bias) [34].

Findings for health professional-led system navigation models were also mixed. The Urban Health Centres Europe approach including health assessment, shared decision making, and referral to appropriate health and social service care pathways (led by either a social worker, nurse, nurse practitioner, or physician assistant based on the setting) significantly improved health-related quality of life compared to usual care (low risk of bias) [49]. However, two studies using nurse-led system navigation models did not result in significant improvements in health-related quality of life compared to usual care (low-moderate risk of bias) [32, 51]. None of the team-based or self-navigation with lay support system navigation models significantly improved quality of life/health-related quality of life, mental health, or wellbeing outcomes compared to baseline or usual care (low-moderate risk of bias) [33, 37, 38, 47, 50].

Social participation and function

Social participation and function was evaluated in eight studies including lay person-led (n = 2, 25%) [36, 46], health professional-led (n = 2, 25%) [49, 51], and team-based (n = 4, 50%) [33, 38, 41, 47] system navigation models. Various measures were used, including heterogeneous assessments of loneliness [38, 41, 49], social networks [33, 46], participation in social roles [36, 47, 51], and social group memberships [41] (Additional file 6). Overall, the findings were mixed. Of the lay person-led models, social prescribing by wellbeing coordinators significantly increased social networks compared to baseline in one study (moderate risk of bias) [46]. However, no changes in social participation were found following the Community Links Practitioner intervention compared to usual care in another study (high risk of bias) [36]. Neither of the studies that used a health professional-led model found significant differences in social participation and function outcomes (low risk of bias) [49, 51]. Of the team-based models, the health coach and link worker-led intervention for adults managing long-term health conditions and experiencing social isolation, loneliness, or anxiety significantly improved the number of social group memberships from baseline, but did not impact community belonging or loneliness (low risk of bias) [41]. Three additional studies evaluating team-based system navigation models found no significant differences in social participation and function outcomes (low-moderate risk of bias) [33, 38, 47].

Health behaviours

Health behaviours were assessed in seven studies evaluating lay person-led (n = 4, 57%) [34,35,36, 45], health professional-led (n = 1, 14%) [49], and team-based (n = 2, 29%) [33, 39] system navigation models. Outcomes included heterogeneous measurements of physical activity/exercise [33, 36, 39, 45, 49], cigarette smoking [34, 35, 39], alcohol intake [39, 49], and diet [39] (Additional file 6). Overall, the findings were mixed. Lay person-led social prescribing significantly increased physical activity compared to baseline in one study (moderate risk of bias) [45]. However, three additional studies evaluating lay person-led models found no significant differences in health behaviour outcomes, including cigarette smoking or exercise level (low-moderate risk of bias) [34,35,36]. The study that evaluated a health professional-led model compared to usual care did not find significant differences in healthy lifestyle behaviours (low risk of bias) [49]. Of the team-based system navigation models, an integrated health management intervention with referral to community programs led by community health centre staff and a multidisciplinary care team led to significant improvements in health behaviours including physical activity, alcohol intake, diet, and smoking habits when compared to bimonthly health education (high risk of bias) [39]. However, another team-based model did not significantly impact physical activity levels compared to usual care (low risk of bias) [33].

Patient activation, self-efficacy, and empowerment

Patient activation, self-efficacy, and empowerment were evaluated in five studies including lay person-led (n = 3, 60%) [34, 35, 43], team-based (n = 1, 20%) [33], and self-navigation with lay support as needed (n = 1, 20%) [50] system navigation models. Heterogeneous measurements of self-efficacy [33, 43, 50], patient activation [34, 35], and empowerment [33] were used. Overall, the findings were mixed. Of the lay person-led models, the Cities for Live Program including linkage to community programs following an assessment of needs, barriers, and stage of change significantly improved self-efficacy compared to baseline (moderate risk of bias) [43]. However, the standardized lay person-led goal setting plus IMPaCT intervention did not change patient activation in two studies (low-moderate risk of bias) [34, 35]. No significant changes in goal attainment, self-efficacy, or patient empowerment were observed following team-based system navigation in one study (low risk of bias) [33]. Although limited to evidence from one study evaluating a self-navigation with lay support system navigation model, patients who participated in the “HealtheRx” intervention involving an electronic-medical record generated personalized list of local community resources with access to a community health information specialist as needed were more likely to report higher confidence in finding resources in their community to help manage their health compared to usual care (low risk of bias) [50].

Patient experience outcomes

Patient experience outcomes were reported in five studies, including lay person-led (n = 2, 40%) [34, 35], health professional-led (n = 2, 40%) [32, 51], and team-based (n = 1, 20%) [33] system navigation models. Patient experiences with care quality were measured using the Consumer Assessment of Healthcare Providers and Systems-Patient Centered Medical Home survey [34, 35], Patient Assessment of Chronic Illness Care tool [32, 51], and Canadian Institute for Health Information common indicators [33] (Additional file 7). Both lay person-led and health professional-led system navigation models consistently improved patient experiences with quality of care. The community health worker-led goal setting plus IMPaCT intervention significantly improved care comprehensiveness and self-management supportiveness when compared to goal setting plus usual care in two RCTs (low-moderate risk of bias) [34, 35]. Compared to usual care, the nurse-led Guided Care [32] and Community Connections Program [51] also significantly improved overall patient experiences with the quality of their care (low-moderate risk of bias). Only one study evaluated the impact of team-based system navigation on patient experiences; the Health TAPESTRY program did not significantly improve patient experiences (i.e., level of difficulty accessing healthcare resources, care comprehensiveness, patient-centeredness, satisfaction) when compared to usual care (low risk of bias) [33].

Caregiver outcomes

Caregiver experience and health outcomes were reported in two studies that investigated health professional-led system navigation models [32, 51]. Overall, the findings were unclear. Compared to usual care, caregiver experiences (i.e., perception of patient care quality) improved after the nurse-led Guided Care intervention (moderate risk of bias) [32] but not after the nurse-led Community Connections Program (low risk of bias) [51]. Evidence from only one study demonstrated no impact of the nurse-led Guided Care intervention on caregiver strain and depression (moderate risk of bias) [32] (Additional file 8).

Cost-related outcomes

Only two studies reported on cost-related outcomes; both evaluated a lay person-led system navigation model [44, 48]. The cost of emergency department/hospital visits and emergency care per patient were compared to costs in a matched control group in one study (moderate risk of bias) [48] and projected annual cost savings based on mathematical modelling in another (low risk of bias) [44]. Although both studies reported differences between groups, no formal statistical tests were reported (Additional file 9).

Discussion

Building upon a previous scoping review, this systematic review synthesizes a growing body of evidence regarding the effectiveness of system navigation programs linking primary care with community-based health and social services. Whereas 1,248 records were screened in the original review, our search identified 15,226 new studies published since 2013, suggesting a substantial increase in interest in this field. Overall, there was variation in impacts across models of system navigation programs linking primary care with community-based health and social services on patient, caregiver, and health system outcomes. Evidence from three studies with low risk of bias [33, 41, 47] suggests a team-based system navigation approach may result in slightly more appropriate health service utilization (e.g., increases in primary care use versus use of costlier health services) compared to baseline or usual care. These results may indicate a shift from reactive to more preventative care and self-management support, with health and social needs being better managed at the most appropriate level of care. Evidence from four studies [32, 34, 35, 51] with moderate risk of bias suggests either lay person-led or health professional-led system navigation models may improve patient experiences with the quality of care when compared to usual care. This is consistent with patient descriptions of such programs as empowering, generally meeting their identified needs, and allowing patients to form positive relationships with their healthcare providers [60]. It is unclear whether system navigation may improve patient-related outcomes (e.g., health-related quality of life, mental health and wellbeing, health behaviours). The evidence is very uncertain about the effect of system navigation programs on caregiver and cost-related outcomes as these were evaluated in a small number of studies. Although promising trends were observed, the potential impacts of lay person-led system navigation models on cost-related outcomes are unclear due to limited data, heterogeneous outcome measurements, and a lack of reporting concerning statistical significance.

Our findings are consistent with those of another systematic review that demonstrated inconsistent effects of social prescribing programs in the United Kingdom on healthcare usage outcomes, generally consistent improvements in patient experiences, and limited evidence on costs [61]. Also consistent with our findings, a recent mixed methods systematic review identified variable effectiveness of social prescribing services on health, wellbeing, health-related behaviours, self-confidence, social isolation/loneliness, and daily functioning [62]. Although qualitative findings demonstrated that social prescribing service users generally experienced positive improvements in health/wellbeing and health behaviours, this was not consistently demonstrated by quantitative measures [62], in line with the patient-related findings in our review.

Heterogeneous measurements across patient-related outcomes may explain some of the variation in findings within this category. Further, the presence of wide confidence intervals for many effect measures suggests that small sample sizes may have contributed to the lack of significant findings observed. While it is possible that quantitative measurements alone are insufficient to capture the holistic impact of system navigation, it is also conceivable that interventions focused primarily on linking patients to existing community-based health and social services may be insufficient to influence significant changes in patient-related health and health behaviour outcomes. For example, evidence from a recent systematic review demonstrates that chronic disease/case management and disease prevention initiatives led by registered nurses in primary care settings are effective for improving health outcomes and health-related behaviours such as weight loss, smoking cessation, diet and physical activity, self-efficacy, and social activity [63]. Thus, while team-based system navigation may be effective for improving health service utilization by supporting patients to access the most appropriate services to meet their needs, the lack of clinical care provision within system navigation programs, when compared to primary care-based chronic disease and/or case management interventions [27], may limit the possible impact of system navigation alone on health-related outcomes.

Several studies in this systematic review focused on populations who may face structural barriers to accessing care and found generally positive results. This included patients experiencing social isolation and/or chronic conditions with high use of primary care [41, 42, 47, 51], individuals managing a chronic condition with previously limited engagement with their primary care team [52], patients with multiple chronic conditions living in high-poverty areas [34, 35], and those deemed to be at high risk for avoidable and costly health services use due to medical or psychosocial conditions [32, 44]. These findings suggest that the greatest impacts of system navigation programs may be observed among populations who stand to benefit the most from improved connections to community-based health and social services. This hypothesis is supported by existing evidence that patients with chronic conditions, unmanaged behavioural health needs, and those experiencing health inequities (e.g., poverty, limited social support) tend to be the highest drivers of potentially avoidable and costly health services use [64, 65]. Further research is needed to identify which populations may benefit the most from system navigation.

Several limitations should be considered when interpreting the results of this review. Although the individual studies within the review were appraised as having a generally low to moderate risk of bias, it is important to note that most were quasi-experimental, therefore lacking randomized controlled groups to facilitate strong comparisons. Further, most studies took place in the United States of America or the United Kingdom, which may limit generalizability to other health and social care contexts. Challenges with outcome measurements in the included studies also limited our conclusions. Although the primary outcomes of interest were access to care and health and social service utilization, none of the included studies objectively measured access to care or social service use outcomes, making it difficult to determine intervention effectiveness. For example, while changes in health services utilization were observed in several studies, we cannot definitively say that this was a direct result of increased connections to community-based social services because outcomes were typically only measured in the primary and/or acute care sectors. Another recent systematic review of social prescribing interventions identified similar limitations when analyzing the available evidence, suggesting that it is important to assess community-level changes (e.g., social service use, belonging, social support) and their associated impacts on health services use [66]. Finally, given the generally small number of studies per outcome and high heterogeneity in results, our certainty regarding the effectiveness of system navigation programs on user and health system outcomes is low. The number of intervention studies has notably increased since the original scoping review, in which most studies were descriptive in nature. As more high-quality data becomes available regarding system navigation programs linking primary care with community-based health and social services, more robust and definitive conclusions may be observed.

Implications for research

Our synthesis of the effectiveness of system navigation programs, alongside existing synthesized evidence regarding social prescribing services [62], suggests that the potential impacts of these types of interventions may not be adequately captured through quantitative measurement tools alone. Although the decision to limit included studies to experimental and quasi-experimental designs was justified based on the objective of this systematic review to determine intervention effectiveness, future review authors may want to consider alternate research questions and types of evidence syntheses (e.g., integrative review, realist review) that would allow for the inclusion of both qualitative and quantitative data. This may also help determine the acceptability and feasibility of system navigation programs, given the generally high loss to follow up observed across studies (Table 1) and the lack of reporting concerning intervention adherence and fidelity (Table 2). Although we did not review qualitative data when studies used mixed methods, which may be a limitation, less than one quarter (n = 5) [40, 41, 43, 46, 47] of included studies conducted mixed methods evaluations.

While only one study evaluated a self-navigation model by providing individuals with a personalized list of local services with lay support available [50], further research is warranted to evaluate similar novel approaches to system navigation. Researchers should ensure appropriate facilitation and support are available when designing self-navigation interventions, as this is known to be key for overcoming fluctuating health status concerns in persons managing chronic conditions or challenges with health literacy [67]. Our review also highlights a need for more research related to the impact of system navigation programs on caregiver and cost-related outcomes. Although this review focused on patients’ and caregivers’ perspectives, it would be salient for future research to also consider the health professional perspective, given the rising levels of burnout and strain reported among primary care providers [68].

Implications for practice

Assisting patients and families to navigate and access programs and services is a current mandate for primary care providers [69]. Integration of system navigation within primary care settings is proposed as a potential approach to alleviate some of the current and projected demands on the primary care sector [70]. Providers should consider prioritizing individuals at greater risk for potentially avoidable and costly health services use when implementing system navigation programs. Findings from this review suggest that persons managing chronic conditions, experiencing social isolation, and/or living with health inequities (e.g., low income) may stand to benefit the most from navigation support, although further research is warranted. While this review included adults aged 18 + , the median age of 72 years across included studies also suggests that older adults are key targets for system navigation support, consistent with the complex, multimorbid health and social conditions older adults often face [71, 72].

Implications for policy

Given the current orientation of health systems toward delivering integrated and coordinated health and community services [73, 74], this systematic review is also highly relevant to policy makers. We identified system navigation models that may support outcomes relevant to the Quintuple Aim framework for healthcare improvement [75, 76], which is top of mind for decision makers to advance health equity and improve patient and provider experiences, health system utilization, and cost-effectiveness. Our findings highlight the potential benefit of team-based system navigation as a strategy to improve use of primary healthcare services versus costlier healthcare (e.g., emergency department visits, hospitalizations) and enhance patient experiences with care.

Conclusion

System navigation programs linking primary care with community-based health and social services demonstrated mixed results. The ideal model of system navigation for improving patient, caregiver, and health system outcomes remains unclear. Nevertheless, a multidisciplinary team of healthcare providers and lay persons performing system navigation activities within primary care settings may result in slightly more appropriate health service utilization. Lay person-led or health professional-led system navigation may improve patient experiences with quality of care. Further research is warranted, specifically to understand the impact of system navigation on caregiver and cost-related outcomes, and to identify which populations may benefit the most from integrated health and social service care delivery programs.

Availability of data and materials

All data generated or analysed during this study are included in this published article and its supplementary information files.

Abbreviations

IMPaCT:

Individualized Management for Patient-Centered Targets program

RCT:

Randomized controlled trial

SF-12, SF-36:

12- Or 36-Item Short Form Survey

TIDieR:

Template for Intervention Description and Replication

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Acknowledgements

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Funding

This work is supported by funding received from the Labarge Centre for Mobility in Aging within the McMaster Institute for Research on Aging at McMaster University, the Canadian Institutes of Health Research (Grant number 169395), and in-kind support from the Aging, Community and Health Research Unit at McMaster University. The funders had no role in the design, collection, analysis, interpretation, or writing of this article, or in the decision to submit for publication.

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Authors and Affiliations

  1. School of Nursing, Faculty of Health Sciences, McMaster University, 1280 Main St. W, Hamilton, ON, HSC 3N25L8S 4K1, Canada

    Kylie Teggart, Abbira Nadarajah, Caroline Moore, Nancy Carter, Janet Adams, Kamal Jain, Penelope Petrie, Aref Alshaikhahmed, Shreya Yugendranag & Rebecca Ganann

  2. Department of Health Research Methods, Evidence and Impact, Faculty of Health Sciences, McMaster University, 175 Longwood Rd S, Suite 210a, Hamilton, ON, L8P 0A1, Canada

    Sarah E. Neil-Sztramko

  3. Department of Family Medicine, University of Alberta, 5-16 University Terrace, Edmonton, AB, T6G 2T4, Canada

    Amy Wang

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Contributions

KT: Investigation, Data Curation, Formal Analysis, Visualization, Writing – Original Draft, Writing – Review & Editing. SEN-S: Conceptualization, Methodology, Funding Acquisition, Investigation, Data Curation, Formal Analysis, Supervision, Writing – Review & Editing. AN: Investigation, Data Curation, Visualization, Writing – Initial Draft, Writing – Review & Editing. AW: Investigation, Data Curation, Visualization, Writing – Review & Editing. CM: Investigation, Data Curation, Project Administration, Writing – Review & Editing. NC, JA, KJ, PP, AA, SY: Formal Analysis, Writing - Review & Editing. RG: Conceptualization, Methodology, Funding Acquisition, Investigation, Data Curation, Formal Analysis, Supervision, Writing – Initial Draft, Writing – Review & Editing. The author(s) read and approved the final manuscript.

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Correspondence to Rebecca Ganann.

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Supplementary Information

Additional file 1.

Search Strategies.

Additional file 2.

List of Excluded Studies.

Additional file 3.

JBI Critical Appraisal Checklist for Randomized Controlled Trials.

Additional file 4.

JBI Critical Appraisal Checklist for Quasi-Experimental Studies.

Additional file 5.

Health Service Utilization Outcomes.

Additional file 6.

Patient-Related Outcomes.

Additional file 7.

Patient Experience Outcomes.

Additional file 8.

Caregiver Outcomes.

Additional file 9.

Cost-Related Outcomes.

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Teggart, K., Neil-Sztramko, S.E., Nadarajah, A. et al. Effectiveness of system navigation programs linking primary care with community-based health and social services: a systematic review. BMC Health Serv Res 23, 450 (2023). https://doi.org/10.1186/s12913-023-09424-5

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BMC Health Services Research

ISSN: 1472-6963

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