A call for better validation of opioid overdose risk algorithms.
J Am Med Inform Assoc
; 30(10): 1741-1746, 2023 Sep 25.
Article
in En
| MEDLINE
| ID: mdl-37428897
ABSTRACT
Clinical decision support (CDS) systems powered by predictive models have the potential to improve the accuracy and efficiency of clinical decision-making. However, without sufficient validation, these systems have the potential to mislead clinicians and harm patients. This is especially true for CDS systems used by opioid prescribers and dispensers, where a flawed prediction can directly harm patients. To prevent these harms, regulators and researchers have proposed guidance for validating predictive models and CDS systems. However, this guidance is not universally followed and is not required by law. We call on CDS developers, deployers, and users to hold these systems to higher standards of clinical and technical validation. We provide a case study on two CDS systems deployed on a national scale in the United States for predicting a patient's risk of adverse opioid-related events the Stratification Tool for Opioid Risk Mitigation (STORM), used by the Veterans Health Administration, and NarxCare, a commercial system.
Full text:
1
Database:
MEDLINE
Type of study:
Etiology_studies
/
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
J Am Med Inform Assoc
Journal subject:
INFORMATICA MEDICA
Year:
2023
Type:
Article
Affiliation country:
United States