Spatial Non-stationarity in Opioid Prescribing Rates: Evidence from Older Medicare Part D Beneficiaries

Seulki Kim (), Carla Shoff () and Tse-Chuan Yang ()
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Seulki Kim: University at Albany, State University of New York
Carla Shoff: Centers for Medicare & Medicaid Services
Tse-Chuan Yang: University at Albany, State University of New York

Population Research and Policy Review, 2021, vol. 40, issue 2, No 1, 127-136

Abstract: Abstract Previous research that examined spatial patterns of opioid prescribing rates and factors associated with them has mainly relied on a global modeling perspective, overlooking the potential spatial non-stationarity embedded in these associations. In this study, we investigate whether there are spatially non-stationary associations between opioid prescribing rates and key characteristics of older Medicare Part D beneficiaries and their prescribers using several data sources from the Centers for Medicare and Medicaid Services. All measures are aggregated to the ZIP code-level and a total sample size of 18,126 ZIP codes is included in the analyses. Our descriptive results from geographically weighted regression and the Monte Carlo significance test suggest that most of the associations between the characteristics of beneficiaries and prescribers and opioid prescribing rates are spatially non-stationary. Our findings not only challenge the conventional analytic approach by highlighting the importance of a local modeling perspective in opioid prescribing research, but also offer nuanced insight into how opioid prescribing rates are related to possible determinants across space.

Keywords: Opioid prescribing rate; Spatial non-stationarity; Geographically weighted regression; Medicare Part D prescription drug event (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s11113-019-09566-7

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