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Patient-centered medical homes in integrated health systems (high-risk population)

Healthcare: Healthcare System Efficiency
  Literature review updated December 2016.

The patient-centered medical home (PCMH) model attempts to make health care more efficient by implementing a set of changes to primary care. Medical homes are designed to provide comprehensive care, treating both acute needs and promoting population health. The medical home model emphasizes care coordination across providers, patient engagement, evidence-based care, use of health information technology, and enhanced patient access.

This category includes only PCMH programs we reviewed that were implemented in integrated health systems. The results are for higher risk, older patients.
 
ALL
META-ANALYSIS
CITATIONS

*The effect size for this outcome indicates percentage change, not a standardized mean difference effect size.

Meta-analysis is a statistical method to combine the results from separate studies on a program, policy, or topic to estimate its effect on an outcome. WSIPP systematically evaluates all credible evaluations we can locate on each topic. The outcomes measured are the program impacts measured in the research literature (for example, impacts on crime or educational attainment). Treatment N represents the total number of individuals or units in the treatment group across the included studies.

An effect size (ES) is a standard metric that summarizes the degree to which a program or policy affects a measured outcome. If the effect size is positive, the outcome increases. If the effect size is negative, the outcome decreases. See Estimating Program Effects Using Effect Sizes for additional information on how we estimate effect sizes.

The effect size may be adjusted from the unadjusted effect size estimated in the meta-analysis. Historically, WSIPP adjusted effect sizes to some programs based on the methodological characteristics of the study. For programs reviewed in 2024 or later, we do not make additional adjustments, and we use the unadjusted effect size whenever we run a benefit-cost analysis.

Research shows the magnitude of effects may change over time. For those effect sizes, we estimate outcome-based adjustments, which we apply between the first time ES is estimated and the second time ES is estimated. More details about these adjustments can be found in our Technical Documentation.

Meta-Analysis of Program Effects
Outcomes measured No. of effect sizes Treatment N Effect sizes (ES) and standard errors (SE) Unadjusted effect size (random effects model)
ES SE Age ES p-value
Healthcare costs*
Percent change in total medical costs.
75 2 37989 -0.071 0.014 75 -0.071 0.001

Citations Used in the Meta-Analysis

Liss, D.T., Fishman, P.A., Rutter, C.M., Grembowski, D., Ross, T.R., Johnson, E.A., & Reid, R.J. (2013). Outcomes among chronically ill adults in a medical home prototype. The American Journal of Managed Care, 19(10), 348-58.

Maeng, D.D., Khan, N., Tomcavage, J., Graf, T.R., Steele, G.D., & Davis, D.E. (2015). Reduced acute inpatient care was largest savings component of geisinger health system's patient-centered medical home. Health Affairs, 34(4), 636-644.