Improving Clinical Documentation with Artificial Intelligence: A Systematic Review.
Clinicians dedicate significant time to clinical documentation, incurring opportunity cost. Artificial intelligence (AI) tools promise to improve documentation quality and efficiency. This systematic review overviews peer-reviewed AI tools to understand how AI may reduce opportunity cost. PubMed, Em...
| Publicado en: | Perspectives in Health Information Management Vol. 21; no. 2; pp. 3 - 4 |
|---|---|
| Autores principales: | , , , |
| Formato: | research systematic review Journal Article |
| Publicado: |
American Health Information Management Association
Summer/Fall2024
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=180714680&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 180714680 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 15594122 2QEL jtl: Perspectives in Health Information Management issn: 15594122 maglogo: N pubinfo: dt: Summer/Fall2024 vid: 21 iid: 2 pid: 6825 pub: American Health Information Management Association place: Chicago, Illinois artinfo: ui: 180714680 180714680 180714680 180714680 ppf: 3 ppct: 1 formats: fmt: @attributes: type: T tig: atl: Improving Clinical Documentation with Artificial Intelligence: A Systematic Review. aug: au: Perkins, Scott W. Muste, Justin C. Alam, Taseen Singh, Rishi P. sug: subj: Clinical Documentation Improvement Artificial Intelligence Automation Medical Informatics Human Systematic Review PubMed Embase Artificial Intelligence, Generative Natural Language Processing Quality Assessment Cost Benefit Analysis Descriptive Statistics Software ab: Clinicians dedicate significant time to clinical documentation, incurring opportunity cost. Artificial intelligence (AI) tools promise to improve documentation quality and efficiency. This systematic review overviews peer-reviewed AI tools to understand how AI may reduce opportunity cost. PubMed, Embase, Scopus, and Web of Science databases were queried for original, English language research studies published during or before July 2024 that report a new development, application, and validation of an AI tool for improving clinical documentation. 129 studies were extracted from 673 candidate studies. AI tools improve documentation by structuring data, annotating notes, evaluating quality, identifying trends, and detecting errors. Other AI-enabled tools assist clinicians in real-time during office visits, but moderate accuracy precludes broad implementation. While a highly accurate end-to-end AI documentation assistant is not currently reported in peer-reviewed literature, existing techniques such as structuring data offer targeted improvements to clinical documentation workflows. pubtype: Academic Journal doctype: research systematic review Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
|---|