title: A Generalized Assessment of the Impact of Regionalization and Provider Learning on Patient Outcomes.
abstract: We present a generalized model to assess the impact of regionalization on patient care outcomes in the presence of heterogeneity in provider learning. The model characterizes best regionalization policies as optimal allocations of patients across providers with heterogeneous learning abilities. We explore issues that arise when solving for best regionalization, which depends on statistically estimated provider learning curves. We explain how to maintain the problem's tractability and reformulate it into a binary integer program problem to improve solvability. Using our model, best regionalization solutions can be computed within reasonable time using current-day computers. We apply the model to minimally invasive radical prostatectomy and estimate that, in comparison to current care delivery, within-state regionalization can shorten length of stay by at least 40.8%.
authors.affiliation: University of Michigan Health System, Ann Arbor, MI (YZ)
authors.forename: Yun
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: University of Michigan School of Public Health, Ann Arbor, MI (S-YDL)
authors.forename: Shoou-Yih D
authors.initials: SY
authors.lastname: Lee
authors.affiliation: University of Michigan Health System, Ann Arbor, MI (YZ)|University of North Carolina at Chapel Hill, Chapel Hill, NC (DBG)
authors.forename: Donna B
authors.initials: DB
authors.lastname: Gilleskie
authors.affiliation: LLamasoft, Inc., Ann Arbor, MI (YS)
authors.forename: Yepeng
authors.initials: Y
authors.lastname: Sun
authors.affiliation: University of Michigan, Ann Arbor, MI (AP, JSM, JEM, JTW, BKH)
authors.forename: Arun
authors.initials: A
authors.lastname: Padakandla
authors.affiliation: University of Pittsburgh, PA (BLJ)
authors.forename: Bruce L
authors.initials: BL
authors.lastname: Jacobs
authors.affiliation: University of Michigan, Ann Arbor, MI (AP, JSM, JEM, JTW, BKH)
authors.forename: Jeffery S
authors.initials: JS
authors.lastname: Montgomery
authors.affiliation: University of Michigan, Ann Arbor, MI (AP, JSM, JEM, JTW, BKH)
authors.forename: James E
authors.initials: JE
authors.lastname: Montie
authors.affiliation: University of Michigan Health System, Ann Arbor, MI (YZ)|University of Michigan, Ann Arbor, MI (AP, JSM, JEM, JTW, BKH)
authors.forename: John T
authors.initials: JT
authors.lastname: Wei
authors.affiliation: University of Michigan, Ann Arbor, MI (AP, JSM, JEM, JTW, BKH)
authors.forename: Brent K
authors.initials: BK
authors.lastname: Hollenbeck
mesh_terms: D000368:Aged; D006801:Humans; D007858:Learning; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D008875:Middle Aged; D019060:Minimally Invasive Surgical Procedures / Q000009:adverse effects / Q000379:methods; D008962:Models, Theoretical; D017063:Outcome Assessment, Health Care; D010818:Practice Patterns, Physicians' / Q000706:statistics & numerical data*; D011468:Prostatectomy / Q000009:adverse effects / Q000379:methods; D011471:Prostatic Neoplasms / Q000601:surgery; D012041:Regional Medical Programs / Q000706:statistics & numerical data*; D013997:Time Factors
keywords: binary integer programming; care regionalization; learning; volume-outcome relationship