The Impact of Manipulated Clinical Decision Support Algorithm on Opioid Prescribing Decision

We document that interactions with manipulated clinical decision support (CDS) systems can induce not only short-term, but also long-term changes in physicians’ opioid prescribing behavior. Physicians in our sample adopted electronic health record software from a list of federally certified vendors in 2011. Between 2016 and Spring 2019, one vendor secretly embedded a biased CDS function designed to promote extended-release opioid sales. Affected physicians not only increased opioid claims relative to the control group during the treatment window, but also maintained a higher propensity to prescribe opioids, even after the biased function was removed. This long-term behavioral change persisted even after affected physicians moved to new locations, changed their affiliations, or faced stricter state-level opioid regulations. Increasing physician awareness helped mitigate this impact. Using machine-learning algorithms, we estimate that decision-making distortion accounts for approximately 54% of the treatment effects in a physician decision model with dynamic learning.

This paper was accepted by Hemant Bhargava, information systems.

Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2024.07930.