Toolkit for calculating opioid levels and identifying patients at risk of misuse or overdose: R and SQL programming code

Toolkit for calculating opioid levels and identifying patients at risk of misuse or overdose: R and SQL programming code

Collection:
Health Policy and Services Research
Contributor(s):
United States. Department of Health and Human Services. Office of Inspector General. Office of Evaluation and Inspections, issuing body.
Publication:
[Washington, D.C.] : U.S. Department of Health and Human Services, Office of Inspector General, May 2020
Language(s):
English
Format:
Text
Subject(s):
Government Regulation
Morphine -- administration & dosage
Opioid-Related Disorders -- diagnosis
Software
United States
United States. Department of Health and Human Services
Genre(s):
Technical Report
Abstract:
What is the toolkit? This toolkit provides detailed steps for using prescription drug claims data to analyze patients’ opioid levels and identify certain patients who are at risk of opioid misuse or overdose. The toolkit includes R and Structured Query Language (SQL) programming code. R is a free programming language and software program for statistical computing. SQL is a programming language used in many software programs. This toolkit is a companion to the previously released Office of Inspector General (OIG) Toolkit: Using Data Analysis To Calculate Opioid Levels and Identify Patients At Risk of Misuse or Overdose, which includes SAS programming code. Similar to the previous one, this toolkit is based on the methodology that OIG developed for its extensive work on opioid use in Medicare Part D. This toolkit provides highly technical information to assist our public and private sector partners— such as Medicare Part D plan sponsors, private health plans, and State Medicaid Fraud Control Units—with analyzing their own prescription drug claims data to help combat the opioid crisis. Why did OIG create the toolkit? The opioid crisis remains a public health emergency. In 2018 alone, there were 46,802 opioid-related overdose deaths in the United States. As one of the lead Federal agencies fighting health care fraud, OIG is committed to supporting our public and private partners in their efforts to curb the opioid epidemic. This toolkit builds on OIG’s previous toolkit by providing programming code in two additional languages—R and SQL. In response to the first toolkit, our partners expressed interest in OIG providing this code in these additional programming languages. This toolkit and the accompanying code can be used to analyze claims data for prescription drugs and identify patients who may be misusing or abusing prescription opioids and may be in need of additional case management or other follow-up. The toolkit and accompanying code can also be used to answer research questions about opioid utilization. OIG most recently analyzed opioid levels in Medicare Part D in a data brief entitled, Opioid Use Decreased in Medicare Part D, While Medication-Assisted Treatment Increased (OEI-02-19-00390). The data brief identified almost 49,000 Part D beneficiaries who were at serious risk of misuse or overdose. Some of these beneficiaries received extreme amounts of opioids. Others appeared to be “doctor shopping”—i.e., receiving high amounts of opioids from multiple prescribers and multiple pharmacies. The analysis identified beneficiaries who are at risk by calculating their opioid levels using Part D prescription drug data.
Copyright:
The National Library of Medicine believes this item to be in the public domain. (More information)
Extent:
1 online resource (1 PDF file (33 pages))
NLM Unique ID:
9918282078806676 (See catalog record)
Permanent Link:
http://resource.nlm.nih.gov/9918282078806676