Impact of a Psychological Opioid-Risk Evaluation on Opioid Prescribing in Primary Care
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Published on: May 15, 2020
Alison M Vargovich1, Daniel W McNeil, Kimberly P Foley
1Department of Family Medicine, West Virginia University.
Background And Objectives:
The misuse and abuse of opioids has increased across the United States in recent years, associated with a rise in opioid-related overdose deaths. Physicians report having difficulty discerning substance abuse or drug diversion, which can lead to over- or under-prescribing of opioids and poor pain management. Additionally, research suggests that patient characteristics (eg, sex, ethnicity/race, age) may unduly influence the pain management decisions of health care providers. This investigation aimed to assist in physicians' prescribing decisions and reduce prescribing bias through the assistance of mental health professionals.
Methods:
This study utilized 151 chronic pain patients being considered for chronic opioid therapy to determine if a psychological opioid-risk evaluation influenced physicians' opioid prescribing. The evaluation resulted in an opioid-risk level (ie, low, moderate, high) being assigned to each patient representing their potential risk for misusing or abusing opioid medication. A record review was conducted on each patient, abstracting information about opioid prescribing, and several other factors, which were included in logistic regression analyses.
Results:
Risk status and substance abuse history significantly predicted opioid prescribing, with a lower risk status associated with greater likelihood of opioid prescribing and those with a history of substance abuse being less likely to be prescribed an opioid; however, substance abuse did not significantly improve the overall model and was removed. Demographic variables were not significant predictors of prescribing contrary to findings in other studies.
Conclusions:
These findings suggest that providing physicians with additional information about their patients' opioid abuse potential aids in prescribing decisions and may reduce prescribing bias based on demographic factors.
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