Turning Artificial Intelligence into Business Intelligence.
The article focuses on the challenges and responsibilities associated with the deployment of artificial intelligence (AI) in healthcare, particularly regarding its impact on clinical data management. It highlights the critical role of health information (HI) professionals in ensuring the accuracy an...
| Publicado en: | Journal of AHIMA |
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| Autor principal: | |
| Formato: | Journal Article |
| Publicado: |
American Health Information Management Association
11/3/2025
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| 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=189080580&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 189080580 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10605487 4BH jtl: Journal of AHIMA issn: 10605487 maglogo: N pubinfo: dt: 11/3/2025 pid: 6825 pub: American Health Information Management Association place: Chicago, Illinois artinfo: ui: 189080580 189080580 ppct: 1 formats: fmt: @attributes: type: T tig: atl: Turning Artificial Intelligence into Business Intelligence. aug: au: Kivi, Dale sug: subj: Artificial Intelligence Business Intelligence Technology, Medical Health Information Management Financial Management Documentation Turnaround Time Profits Investments Voice Recognition Systems Fee for Service Plans Natural Language Processing Billing and Claims ab: The article focuses on the challenges and responsibilities associated with the deployment of artificial intelligence (AI) in healthcare, particularly regarding its impact on clinical data management. It highlights the critical role of health information (HI) professionals in ensuring the accuracy and effectiveness of AI tools, which can sometimes produce erroneous outputs due to their reliance on large language models (LLMs). The text discusses various applications of AI in clinical documentation, coding, clinical documentation improvement (CDI), and billing, emphasizing the need for careful evaluation of vendor offerings and the importance of human oversight to mitigate risks associated with AI-generated data. Ultimately, it underscores that while AI can enhance efficiency and data processing, it is not a substitute for the expertise of HI professionals who are essential for translating AI outputs into actionable insights. pubtype: Periodical doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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