Comparative effectiveness of generic commercial versus locally customized clinical decision support tools to reduce prescription of nonsteroidal anti-inflammatory drugs for patients with heart failure.
J Am Med Inform Assoc
; 30(9): 1516-1525, 2023 08 18.
Article
in En
| MEDLINE
| ID: mdl-37352404
OBJECTIVE: To compare the effectiveness of 2 clinical decision support (CDS) tools to avoid prescription of nonsteroidal anti-inflammatory drugs (NSAIDs) in patients with heart failure (HF): a "commercial" and a locally "customized" alert. METHODS: We conducted a retrospective cohort study of 2 CDS tools implemented within a large integrated health system. The commercial CDS tool was designed according to third-party drug content and EHR vendor specifications. The customized CDS tool underwent a user-centered design process informed by implementation science principles, with input from a cross disciplinary team. The customized CDS tool replaced the commercial CDS tool. Data were collected from the electronic health record via analytic reports and manual chart review. The primary outcome was effectiveness, defined as whether the clinician changed their behavior and did not prescribe an NSAID. RESULTS: A random sample of 366 alerts (183 per CDS tool) was evaluated that represented 355 unique patients. The commercial CDS tool was effective for 7 of 172 (4%) patients, while the customized CDS tool was effective for 81 of 183 (44%) patients. After adjusting for age, chronic kidney disease, ejection fraction, NYHA class, concurrent prescription of an opioid or acetaminophen, visit type (inpatient or outpatient), and clinician specialty, the customized alerts were at 24.3 times greater odds of effectiveness compared to the commercial alerts (OR: 24.3 CI: 10.20-58.06). CONCLUSION: Investing additional resources to customize a CDS tool resulted in a CDS tool that was more effective at reducing the total number of NSAID orders placed for patients with HF compared to a commercially available CDS tool.
Key words
Full text:
1
Database:
MEDLINE
Main subject:
Decision Support Systems, Clinical
/
Heart Failure
Type of study:
Guideline
/
Observational_studies
/
Prognostic_studies
Limits:
Humans
Language:
En
Journal:
J Am Med Inform Assoc
Journal subject:
INFORMATICA MEDICA
Year:
2023
Type:
Article
Affiliation country:
United States