Effectiveness of system navigation programs linking primary care with community-based health and social services: a systematic review
Bibliographic record
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.024 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".