{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,9]],"date-time":"2026-02-09T14:22:44Z","timestamp":1770646964867,"version":"3.49.0"},"reference-count":11,"publisher":"Georg Thieme Verlag KG","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Appl Clin Inform"],"published-print":{"date-parts":[[2022,10]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>\n          Objectives\u2003Critical care services (CCS) documentation affects billing, operations, and research. No studies exist on documentation decision support (DDS) for CCS in the emergency department (ED). We describe the design, implementation, and evaluation of a DDS tool built to improve CCS documentation at an academic ED.<\/jats:p><jats:p>\n          Methods\u2003This quality improvement study reports the prospective design, implementation, and evaluation of a novel DDS tool for CCS documentation at an academic ED. CCS-associated ED diagnoses triggered a message to appear within the physician note attestation workflow for any patient seen in the adult ED. The alert raised awareness of CCS-associated diagnoses without recommending specific documentation practices. The message disappeared from the note automatically once signed. We measured current procedural terminology (CPT) codes 99291 or 99292 (representing CCS rendered) for 8 months before and after deployment to identify CCS documentation rates. We performed state-space Bayesian time-series analysis to evaluate the causal effect of our intervention on CCS documentation capture. We used monthly ED volume and monthly admission rates as covariate time-series for model generation.<\/jats:p><jats:p>\n          Results\u2003The study included 92,350 ED patients with an observed mean proportion CCS of 3.9% before the intervention and 5.8% afterward. The counterfactual model predicted an average response of 3.9% [95% CI 3.5\u20134.3%]. The estimated absolute causal effect of the intervention was 2.0% [95% CI 1.5\u20132.4%] (p\u2009=\u20090.001).<\/jats:p><jats:p>\n          Conclusion\u2003A DDS tool measurably increased ED CCS documentation. Attention to user workflows and collaboration with compliance and billing teams avoided alert fatigue and ensures compliance.<\/jats:p>","DOI":"10.1055\/a-1950-9032","type":"journal-article","created":{"date-parts":[[2022,9,26]],"date-time":"2022-09-26T23:09:25Z","timestamp":1664233765000},"page":"1100-1107","source":"Crossref","is-referenced-by-count":3,"title":["Decision Support to Improve Critical Care Services Documentation in an Academic Emergency Department"],"prefix":"10.1055","volume":"13","author":[{"given":"Robert W.","family":"Turer","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine and Clinical Informatics Center, UT Southwestern Medical Center, Dallas, Texas, United States"}]},{"given":"John C.","family":"Champion","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Brian S.","family":"Rothman","sequence":"additional","affiliation":[{"name":"Department of Anesthesiology, Vanderbilt Medical Center, Nashville, Tennessee, United States"},{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Heather S.","family":"Dunn","sequence":"additional","affiliation":[{"name":"Department of Finance, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Kenneth M.","family":"Jenkins","sequence":"additional","affiliation":[{"name":"Department of Compliance, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Olayinka","family":"Everham","sequence":"additional","affiliation":[{"name":"Health IT, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Tyler W.","family":"Barrett","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Ian D.","family":"Jones","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States"},{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States"},{"name":"Health IT, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]},{"given":"Michael J.","family":"Ward","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States"},{"name":"Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, United States"},{"name":"Geriatric Research, Education, and Clinical Center, Tennessee Valley Healthcare System (Veterans Affairs), Nashville, Tennessee, United States"}]},{"given":"Nathaniel M.","family":"Miller","sequence":"additional","affiliation":[{"name":"Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, United States"}]}],"member":"194","published-online":{"date-parts":[[2022,11,16]]},"reference":[{"key":"ref1","volume-title":"Chapter 12: Physicians\/Nonphysician Practitioners","author":"Medicare Claims Processing Manual"},{"issue":"03","key":"ref4","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1093\/jamia\/ocw151","article-title":"The use of computerized clinical decision support systems in emergency care: a substantive review of the literature","volume":"24","author":"P Bennett","year":"2017","journal-title":"J Am Med Inform Assoc"},{"issue":"02","key":"ref5","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1111\/acem.14379","article-title":"Improving emergency department documentation with noninterruptive clinical decision support: an open-label, randomized clinical efficacy 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AHIMA"},{"issue":"06","key":"ref13","doi-asserted-by":"crossref","first-page":"466","DOI":"10.4037\/ajcc2015455","article-title":"Squire 2.0 (Standards for Quality Improvement Reporting Excellence): revised publication guidelines from a detailed consensus process","volume":"24","author":"G Ogrinc","year":"2015","journal-title":"Am J Crit Care"},{"issue":"01","key":"ref18","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1214\/14-AOAS788","article-title":"Inferring causal impact using Bayesian structural time-series models","volume":"9","author":"K H Brodersen","year":"2015","journal-title":"Ann Appl Stat"}],"container-title":["Applied Clinical 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