Linkage of Public Health and All Payer Claims Data for Population-Level Opioid Research

Document Type

Article

Publication Date

4-29-2021

Publication Title

Pharmacoepidemiology and Drug Safety

Volume

30

Issue

7

First page number:

927

Last page number:

933

Abstract

Objective: Our objective is to describe how we combine, at an individual level, multiple administrative datasets to create a Comprehensive Opioid Risk Registry (CORR). The CORR will characterize the role that individual characteristics, household characteristics, and community characteristics have on an individual's risk of opioid use disorder or opioid overdose. Data Sources: Study data sources include the voluntary Oregon All Payer Claims Database (APCD), American Community Survey Census Data, Oregon Death Certificate data, Oregon Hospital Discharge Data (HDD), and Oregon Prescription Drug Monitoring (PDMP) Data in 2013–2018. Study Design: To create the CORR we first prepared the APCD data set by cleaning and geocoding addresses, creating a community grouper and adding census indices, creating household grouper, and imputing patient race. Then we deployed a probabilistic linkage methodology to incorporate other data sources maintaining compliance with strict data governance regulations. Data Collection/Extraction Methods: Administrative datasets were obtained through an executed data use agreement with each data owner. The APCD served as the population universe to which all other data sources were linked. Principal Findings: There were 3 628 992 unique people in the APCD over the entire study period. We identified 968 767 unique households in 2013 and 1 209 236 in 2018, and geocoded patient addresses representing all census tracts in Oregon. Census, death certificate, HDD, and PDMP datasets were successfully linked to this population universe. Conclusions: This methodology can be replicated in other states and may also apply to a broad array of health services research topics.

Disciplines

Public Health | Substance Abuse and Addiction

Language

English

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