ArticleApplied clinical informatics2024
Implementation of a Real-Time Documentation Assistance Tool: Automated Diagnosis (AutoDx).
Article in Applied clinical informatics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Artificial Intelligence-Based Hospital Malnutrition Screening: Validation of a Novel Machine Learning Model.Applied clinical informatics · 2025Article
- Noninterruptive tool to support provider malnutrition documentation and minimize documentation queries.JAMIA open · 2025Article
- Defining Documentation Burden (DocBurden) and Excessive DocBurden for All Health Professionals: A Scoping Review.Applied clinical informatics · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundClinical documentation improvement programs are utilized by most health care systems to enhance provider documentation. Suggestions are sent to providers in a variety of ways, and are commonly referred to as coding queries. Responding to these coding queries can require significant provider time and do not often align with workflows. To enhance provider documentation in a more consistent manner without creating undue burden, alternative strategies are required.
objectivesThe aim of this study is to evaluate the impact of a real-time documentation assistance tool, named AutoDx, on the volume of coding queries and encounter-level outcome metrics, including case-mix index (CMI).
methodsThe AutoDx tool was developed utilizing tools existing within the electronic health record, and is based on the generation of messages when clinical conditions are met. These messages appear within provider notes and required little to no interaction. Initial diagnoses included in the tool were electrolyte deficiencies, obesity, and malnutrition. The tool was piloted in a cohort of Hospital Medicine providers, then expanded to the Neuro Intensive Care Unit (NICU), with addition diagnoses being added.
resultsThe initial Hospital Medicine implementation evaluation included 590 encounters pre- and 531 post-implementation. The volume of coding queries decreased 57% (
conclusionThe real-time documentation assistance tool led to a significant decrease in coding queries for targeted diagnoses in two unique provider cohorts. This improvement was also associated with a significant increase in CMI during the implementation time period.
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