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Indication alerts to improve problem list documentation
Anne Grauer1, Jerard Kneifati-Hayek1, Brian Reuland1
1Department of Medicine, Columbia University Irving Medical Center, New York City, New York, USA.
Journal of the American Medical Informatics Association : JAMIA
|December 27, 2021
Summary
Computerized provider order entry alerts significantly improved problem list accuracy by prompting clinicians to add missing diagnoses for medications. This enhanced patient care by ensuring problem lists accurately reflect patient conditions.
Area of Science:
- Health Informatics
- Clinical Decision Support Systems
- Electronic Health Records
Background:
- Problem lists are crucial for quality patient care but often suffer from inaccuracies and incompleteness.
- Electronic health record (EHR) systems present opportunities to improve problem list management.
- Computerized provider order entry (CPOE) systems can be leveraged to address these deficiencies.
Purpose of the Study:
- To evaluate the effectiveness of integrated alerts in CPOE systems for improving problem list accuracy.
- To assess the impact of alerts designed to prompt problem list additions for medications lacking a clear indication.
- To determine the yield and accuracy of problems added to patient lists via these alerts.
Main Methods:
- A study was conducted across two healthcare systems utilizing an innovative indication alert within their CPOE systems.
- Medication order data was collected from December 2018 to January 2020 (Site 1) and May to June 2021 (Site 2).
- Chart reviews of 100 randomly selected problems added in response to alerts were performed to assess alert yield and problem accuracy.
Main Results:
- Alerts were triggered over 131,134 times (Site 1) and 6,178 times (Site 2), with yields of 83.2% and 46.5%, respectively.
- Problem accuracy was high, with 90% ± 2% of added problems deemed accurate upon chart review.
- Order abandonment rates were low, at 11.1% (Site 1) and 9.6% (Site 2).
Conclusions:
- Indication alerts integrated into CPOE systems are effective tools for populating accurate problem lists.
- These alerts significantly improve the completeness and accuracy of patient problem lists, supporting better clinical decision-making.
- The high accuracy of added problems suggests these alerts enhance the quality of patient care documentation.
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