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Objective: To estimate the impact of a new, two-sided risk model accountable care network (ACN) on Washington State employees and their families., Data Sources/study Setting: Administrative data (January 2013-December 2016) on Washington State employees., Study Design: We compared monthly health care utilization, health care intensity as measured through proxy pricing, and annual HEDIS quality metrics between the five intervention counties to 13 comparison counties, analyzed separately by age categories (ages 0-5, 6-18, 19-26, 18-64)., Data Collection/extraction Methods: We used difference-in-difference methods and generalized estimating equations to estimate the effects after 1 year of implementation for adults and children., Principal Findings: We estimate a 1-2 percentage point decrease in outpatient hospital visits due to the introduction of ACNs (adults: -1.8, P < .01; age 0-5: -1.2, P = .07; age 6-18: -1.2, P = .06; age 19-26; -1.2, P < .01). We find changes in primary and specialty care office visits; the direction of impact varies by age. Dependents age 19-26 were also responsive with inpatient admissions declines (-0.08 percentage points, P = .02). Despite changes in utilization, there was no evidence of changes in intensity of care and mixed results in the quality measures., Conclusions: Washington's state employee ACN introduction changed health care utilization patterns in the first year but was not as successful in improving quality., (© 2021 Health Research and Educational Trust.)

The Washington State Innovation Models (SIM) $65 million Test Award from the Center for Medicare & Medicaid Services' Innovation Center is a statewide intervention expected to improve population health, quality of care, and cost growth through four initiatives: 1) regional accountable communities of health linking health and social services to address local needs; 2) a practice transformation support hub; 3) four value-based payment reform pilot projects mainly in state employee and Medicaid populations; and 4) data and analytic infrastructure development to support system transformation with common measures. We develop a conceptual model based on diffusion theory and apply the RE-AIM evaluation framework (Reach, Effectiveness, Adoption, Implementation, and Maintenance) to structure our evaluation. We find that in three years (2016-2018), SIM built the infrastructure for system transformation and increased Washington's readiness for health system change in the next decade. However, the initiatives have not spread statewide, which may take over 10 years.