NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH
loading...

Predicting High-Risk Opioid Prescriptions Before they are Given

Justine S. Hastings, Mark Howison, Sarah E. Inman

NBER Working Paper No. 25791
Issued in April 2019, Revised in August 2019
NBER Program(s):The Health Care Program, The Health Economics Program, The Public Economics Program

Misuse of prescription opioids is a leading cause of premature death in the United States. We use new state government administrative data and machine learning methods to examine whether the risk of future opioid dependence, abuse, or poisoning can be predicted in advance of an initial opioid prescription. Our models accurately predict these outcomes and identify particular prior non-opioid prescriptions, medical history, incarceration, and demographics as strong predictors. Using our model estimates, we simulate a hypothetical policy which restricts new opioid prescriptions to only those with low predicted risk. The policy’s potential benefits likely outweigh costs across demographic subgroups, even for lenient definitions of “high risk.” Our findings suggest new avenues for prevention using state administrative data, which could aid providers in making better, data-informed decisions when weighing the medical benefits of opioid therapy against the risks.

You may purchase this paper on-line in .pdf format from SSRN.com ($5) for electronic delivery.

Access to NBER Papers

You are eligible for a free download if you are a subscriber, a corporate associate of the NBER, a journalist, an employee of the U.S. federal government with a ".GOV" domain name, or a resident of nearly any developing country or transition economy.

If you usually get free papers at work/university but do not at home, you can either connect to your work VPN or proxy (if any) or elect to have a link to the paper emailed to your work email address below. The email address must be connected to a subscribing college, university, or other subscribing institution. Gmail and other free email addresses will not have access.

E-mail:

Machine-readable bibliographic record - MARC, RIS, BibTeX

Document Object Identifier (DOI): 10.3386/w25791

 
Publications
Activities
Meetings
NBER Videos
Themes
Data
People
About

National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138; 617-868-3900; email: info@nber.org

Contact Us