2013
DOI: 10.1111/jems.12023
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Integration and Task Allocation: Evidence from Patient Care

Abstract: Using the universe of patient transitions from inpatient hospital care to skilled nursing facilities and home health care in 2005, we show how integration eliminates task misallocation problems between organizations. We find that vertical integration allows hospitals to shift patient recovery tasks downstream to lower-cost organizations by discharging patients earlier (and in poorer health) and increasing post-hospitalization service intensity. While integration facilitates a shift in the allocation of tasks a… Show more

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Cited by 45 publications
(38 citation statements)
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References 23 publications
(30 reference statements)
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“…They find a small and generally statistically insignificant reduction in prices for integrated organizations. David et al (2011) analyze integration between hospitals and nursing homes and home health care agencies. They note that statutes and regulations against side payments lead to contractual incompleteness (David et al 2011;Leibenluft 2011;Cuellar and Gertler 2006).…”
Section: Transaction Cost Economics and Health Carementioning
confidence: 99%
“…They find a small and generally statistically insignificant reduction in prices for integrated organizations. David et al (2011) analyze integration between hospitals and nursing homes and home health care agencies. They note that statutes and regulations against side payments lead to contractual incompleteness (David et al 2011;Leibenluft 2011;Cuellar and Gertler 2006).…”
Section: Transaction Cost Economics and Health Carementioning
confidence: 99%
“…Specifically, David and colleagues (2013) instrument for a particular hospital owning a SNF by using the rate of SNF ownership by other hospitals in the same market. Using this approach, the authors found lower 60-day hospital readmission rates for patients discharged to a SNF owned by that hospital.…”
Section: Conceptual Framework and Related Researchmentioning
confidence: 99%
“…We matched the patients using age, sex, race, primary procedure, and all 28 AHRQ comorbid defined elements in the NIS database (see Table, Supplemental Digital Content 2, available at http://links. 33 After the match and subsequent patient pruning, the obese and nonobese groups contained equal numbers of patients and are referred to as the "matched comparison group." We used the coarsened exact matching (CEM) algorithm to perform the matching process.…”
mentioning
confidence: 99%