Using a mixed-effect model with a parameter-space of heterogenous dimension to evaluate whether accountable care organizations are associated with greater uniformity across constituent practices

Stat Med. 2022 Sep 20;41(21):4215-4226. doi: 10.1002/sim.9506. Epub 2022 Jun 27.

Abstract

Accountable care organization (ACO) legislation was designed to improve patient outcomes by inducing greater coordination of care and adoption of best practices. Therefore, it is of interest to assess whether greater uniformity occurs among practices comprising an ACO post ACO formation. We develop a mixed-effect model with a difference-in-difference design to evaluate the effect of a patient receiving care from an ACO on patient outcomes and adapt this model to examine whether an ACO is associated with increased uniformity across its constituent practices. The task is complicated by the organizations within an ACO forming an additional layer in the multilevel model, due to medical practices and hospitals that form an ACOs being nested within the ACO, making the number of levels of the model variable and the dimension of the parameter space time-varying. We develop the model and a procedure for testing the hypothesis that ACO formation was associated with increased uniformity among its constituent practices. We apply our procedure to a cohort of medicare beneficiaries followed over 2009-2014. Although there is extensive heterogeneity of becoming an ACOs across practices, we find that the formation of an ACO appears to be associated with greater uniformity of patient outcomes among its constituent practices.

Keywords: accountable care organization; between-group variability; difference-in-difference analysis; mixed-effect model; time-varying parameter-space.

Publication types

  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Accountable Care Organizations*
  • Aged
  • Cohort Studies
  • Hospitals
  • Humans
  • Medicare
  • United States