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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.
SUBMITTER: Wright A
PROVIDER: S-EPMC10114117 | biostudies-literature | 2023 Apr
REPOSITORIES: biostudies-literature
Wright Adam A Schreiber Richard R Bates David W DW Aaron Skye S Ai Angela A Cholan Raja Arul RA Desai Akshay A Divo Miguel M Dorr David A DA Hickman Thu-Trang TT Hussain Salman S Just Shari S Koh Brian B Lipsitz Stuart S Mcevoy Dustin D Rosenbloom Trent T Russo Elise E Ting David Yut-Chee DY Weitkamp Asli A Sittig Dean F DF
Journal of the American Medical Informatics Association : JAMIA 20230401 5
<h4>Objective</h4>To improve problem list documentation and care quality.<h4>Materials and methods</h4>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 d ...[more]