Optimizing Best Practice Advisory alerts in electronic medical records with a multi-pronged strategy at a tertiary care hospital in Singapore.
Hannah Jia Hui NgAmit KansalJishana Farhad Abdul NaseerWee Chuan HingCarmen Jia Man GohHermione PohJared Louis Andre D'souzaEr Luen LimGamaliel TanPublished in: JAMIA open (2023)
A significant reduction in interruptive alert volume, and a significant increase in action taken rates despite manifold increase in the number of unique BPAs could be achieved through concentrated efforts focusing on governance, data review, and visualization using a system-embedded tool, combined with the CDS Five Rights framework, to optimize alerts. Improved alert compliance was likely multifactorial-due to decreased repeated alert firing for the same patient; better awareness due to stakeholders' involvement; and less fatigue since unnecessary alerts were removed. Future studies should prospectively focus on patients' clinical chart reviews to assess downstream effects of various actions taken, identify any possibility of harm, and collect end-user feedback regarding the utility of alerts.
Keyphrases
- end stage renal disease
- clinical decision support
- ejection fraction
- newly diagnosed
- primary care
- chronic kidney disease
- healthcare
- peritoneal dialysis
- quality improvement
- quantum dots
- prognostic factors
- electronic health record
- case report
- machine learning
- systematic review
- patient reported outcomes
- current status
- deep learning
- physical activity
- depressive symptoms
- artificial intelligence
- case control
- electron microscopy