A Multi-Site Randomized Trial of a Clinical Decision Support Intervention to Improve Problem List Completeness

Authors

Adam Wright
Richard Schreiber
David W Bates
Skye Aaron
Angela Ai
Raja Arul Cholan
Akshay Desai
Miguel Divo
David A Dorr
Thu-Trang Hickman
Salman Hussain
Shari Just
Brian Koh
Stuart Lipsitz
Dustin Mcevoy
Trent Rosenbloom
Elise Russo
David Yut-Chee Ting
Asli Weitkamp
Dean F Sittig

Publication Date

4-19-2023

Journal

Journal of the American Medical Informatics Association

Abstract

OBJECTIVE: To improve problem list documentation and care quality.

MATERIALS AND METHODS: We developed algorithms to infer clinical problems a patient has that are not recorded on the coded problem list using structured data in the electronic health record (EHR) for 12 clinically significant heart, lung, and blood diseases. We also developed a clinical decision support (CDS) intervention which suggests adding missing problems to the problem list. We evaluated the intervention at 4 diverse healthcare systems using 3 different EHRs in a randomized trial using 3 predetermined outcome measures: alert acceptance, problem addition, and National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) clinical quality measures.

RESULTS: There were 288 832 opportunities to add a problem in the intervention arm and the problem was added 63 777 times (acceptance rate 22.1%). The intervention arm had 4.6 times as many problems added as the control arm. There were no significant differences in any of the clinical quality measures.

DISCUSSION: The CDS intervention was highly effective at improving problem list completeness. However, the improvement in problem list utilization was not associated with improvement in the quality measures. The lack of effect on quality measures suggests that problem list documentation is not directly associated with improvements in quality measured by National Committee for Quality Assurance Healthcare Effectiveness Data and Information Set (NCQA HEDIS) quality measures. However, improved problem list accuracy has other benefits, including clinical care, patient comprehension of health conditions, accurate CDS and population health, and for research.

CONCLUSION: An EHR-embedded CDS intervention was effective at improving problem list completeness but was not associated with improvement in quality measures.

Keywords

Humans, Decision Support Systems, Clinical, Electronic Health Records, Quality of Health Care, problem list, clinical decision support, electronic health record

Comments

Supplementary Materials

PMID: 36806929