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Health Care Utilization Following Interventions to Improve Social Well-Being: A Systematic Review and Meta-analysis
Neta HaGani1,2, Daniel L Surkalim1,2, Philip J Clare1,3,2
1Prevention Research Collaboration, Sydney School of Public Health, The University of Sydney, Sydney, Australia.
Importance:
It has been suggested that interventions that aim to improve social well-being may contribute to decreased health care use; however, such evidence has not been fully systematically synthesized.
Objective:
To systematically review and meta-analyze available evidence on the associations between psychosocial interventions and health care utilization.
Data Sources:
Medline, Embase, PsycInfo, Cumulated Index to Nursing and Allied Health Literature, Cochrane, Scopus, Google Scholar, and reference lists of systematic reviews were searched from inception until November 31, 2022.
Study Selection:
Included studies were randomized clinical trials reporting on both health care utilization and social well-being outcomes.
Data Extraction And Synthesis:
The reporting of the systematic review adhered to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Full-text and quality assessments were conducted by 2 reviewers independently. Multilevel random-effects meta-analyses were used to synthesize the data. Subgroup analyses were conducted to examine the characteristics associated with decreased health care use.
Main Outcomes And Measures:
The outcome of interest was health care utilization, including primary, emergency, inpatient, and outpatient care services. Social well-being was measured as social support, social participation, social relationships, community support, social integration, or loneliness.
Results:
A total of 41 studies were retrieved from 18 969 citations; 37 studies were eligible for meta-analysis. Data were analyzed for 7842 participants, including 2745 older adults, 1579 young women considered to be at risk of social and mental health disadvantages, 1118 people with chronic illnesses, 1597 people with mental illnesses, and 803 caregivers. The odds ratio (OR) random-effects model showed an overall reduction in health care use (OR, 0.75; 95% CI, 0.59 to 0.97), but the standardized mean difference (SMD) random effect model showed no association. An improvement in health care utilization was observed in association with social support interventions (SMD, 0.25; 95% CI, 0.04 to 0.45) but not in loneliness interventions. Subgroup analysis indicated a reduced length of inpatient visits (SMD, -0.35; 95% CI, -0.61 to -0.09) and number of emergency care visits (OR, 0.64; 95% CI, 0.43 to 0.96) following the intervention. However, an increase in outpatient care associated with psychosocial interventions was observed (SMD, 0.34; 95% CI, 0.05 to 0.62). The largest reductions in health care use were associated with interventions among caregivers (OR, 0.23; 95% CI, 0.07 to 0.71) and individuals with mental illnesses (OR, 0.31; 95% CI, 0.13 to 0.74).
Conclusions:
These findings suggest that psychosocial interventions were associated with most measures of health care utilization. As the association differed by participant and intervention delivery characteristics, these characteristics should be considered in the design of future interventions.
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