These results are for High-Deductible Health Plans (HDHPs) versus traditional plans. These plans have moderate to high deductibles (at least a $500 individual deductible). They may or may not include health reimbursement arrangements (HRA) or a health savings account (HSA). Preventive services include cancer screening (breast, cervical, colorectal), preventive office visits, and preventive lab tests. The medication adherence effect size is for eight drug classes used to treat diabetes, high blood pressure, high cholesterol and other chronic conditions. The effect is for HDHPs where prescription drug costs are subject to the deductible.

 

^*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	Treatment age	Primary or secondary participant	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.	0	Primary	10	5052573	-0.116	0.026	33	-0.116	0.001
Emergency department costs* Percent change in emergency department costs.	0	Primary	2	52058	-0.071	0.086	33	-0.071	0.407
Emergency department visits* Whether someone visited the emergency department, or the number of times they visited the emergency department.	0	Primary	1	15847	-0.150	0.032	33	-0.150	0.001
Emergency department vists (lower-severity)* Percent change in low-severity emergency department visits, which include visits for non-emergent problems such as upper respiratory tract infections, acute bronchitis, sore throat, and low back pain.	0	Primary	1	15847	-0.196	0.047	33	-0.196	0.001
Emergency department visits (higher-severity)* Percent change in high-severity emergency department visits, which include visits for emergent problems such as kidney stones, cardiac arrhythmias, acute asthma exacerbations, and open head wounds.	0	Primary	1	15847	-0.097	0.098	33	-0.097	0.323
Hospitalization* Hospital admission, for any reason.	0	Primary	1	15847	-0.118	0.091	33	-0.118	0.196
Prescription drug costs* Percent change in prescription drug or pharmaceutical costs.	0	Primary	3	63193	-0.047	0.013	33	-0.047	0.001
Medication adherence Adherence to a specific prescribed medication regimen.	0	Primary	8	4865	-0.092	0.038	33	-0.092	0.016
Preventive services Preventive healthcare screening services such as mammography, cervical cancer screening, or colorectal cancer screening.	0	Primary	11	152096	-0.046	0.010	33	-0.046	0.001
Primary care visits* Visit to a primary care physician for any reason.	0	Primary	1	7953	-0.090	0.015	45	-0.090	0.001

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Wharam, J.F., Graves, A.J., Zhang, F., Soumerai, S.B., Ross-Degnan, D., & Landon, B.E. (2012). Two-year trends in cancer screening among low socioeconomic status women in an HMO-based high-deductible health plan. Journal of General Internal Medicine, 27(9), 1112-9.