Ontology highlight
ABSTRACT: Objective
To evaluate physician characteristics associated with pharmaceutical industry transfers and prescribing behavior after public reporting under the Sunshine Act.Data sources
2014-2016 secondary data on industry transfers to physicians from the Open Payments Dataset supplemented with Medicare Part D prescription data, Medicare service data, and practice attributes from the Physician Compare Database.Study design
Using regression analysis with county/physician fixed effects, this study examines characteristics associated with the probability/magnitude of transfers and the association between transfers and prescriptions.Data collection
Using an iterative matching approach, this study identifies physicians who delivered outpatient Medicare services in 2014 (n = 409 041) and tracks their annual transfers between 2014 and 2016 (N = 1 227 123) across six transfer categories. In addition, it examines their Medicare Part D prescription behavior between 2014 and 2015 (N = 741 659).Principal findings
Industry transfers dramatically declined in 2015 and 2016. Transfers are significantly associated with increased prescription costs, branded prescribing, and prescribing for High-Risk Medications (HRMs).Conclusions
Industry transfers have declined after public reporting. Transfers are associated with higher prescription costs and incidence of HRMs. Future research is needed to determine the causal impact on quality and cost-effectiveness of prescribed medications.
SUBMITTER: Brunt CS
PROVIDER: S-EPMC6505404 | biostudies-literature | 2019 Jun
REPOSITORIES: biostudies-literature
Health services research 20181001 3
<h4>Objective</h4>To evaluate physician characteristics associated with pharmaceutical industry transfers and prescribing behavior after public reporting under the Sunshine Act.<h4>Data sources</h4>2014-2016 secondary data on industry transfers to physicians from the Open Payments Dataset supplemented with Medicare Part D prescription data, Medicare service data, and practice attributes from the Physician Compare Database.<h4>Study design</h4>Using regression analysis with county/physician fixed ...[more]