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The role of artificial intelligence for the application of integrating electronic health records and patient-generated data in clinical decision support.
Ye, Jiancheng; Woods, Donna; Jordan, Neil; Starren, Justin.
Affiliation
  • Ye J; Feinberg School of Medicine, Northwestern University, Chicago, USA.
  • Woods D; Feinberg School of Medicine, Northwestern University, Chicago, USA.
  • Jordan N; Feinberg School of Medicine, Northwestern University, Chicago, USA.
  • Starren J; Feinberg School of Medicine, Northwestern University, Chicago, USA.
AMIA Jt Summits Transl Sci Proc ; 2024: 459-467, 2024.
Article in En | MEDLINE | ID: mdl-38827061
ABSTRACT
This narrative review aims to identify and understand the role of artificial intelligence in the application of integrated electronic health records (EHRs) and patient-generated health data (PGHD) in clinical decision support. We focused on integrated data that combined PGHD and EHR data, and we investigated the role of artificial intelligence (AI) in the application. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines to search articles in six databases PubMed, Embase, Web of Science, Scopus, ACM Digital Library, and IEEE Computer Society Digital Library. In addition, we also synthesized seminal sources, including other systematic reviews, reports, and white papers, to inform the context, history, and development of this field. Twenty-six publications met the review criteria after screening. The EHR-integrated PGHD introduces benefits to health care, including empowering patients and families to engage via shared decision-making, improving the patient-provider relationship, and reducing the time and cost of clinical visits. AI's roles include cleaning and management of heterogeneous datasets, assisting in identifying dynamic patterns to improve clinical care processes, and providing more sophisticated algorithms to better predict outcomes and propose precise recommendations based on the integrated data. Challenges mainly stem from the large volume of integrated data, data standards, data exchange and interoperability, security and privacy, interpretation, and meaningful use. The use of PGHD in health care is at a promising stage but needs further work for widespread adoption and seamless integration into health care systems. AI-driven, EHR-integrated PGHD systems can greatly improve clinicians' abilities to diagnose patients' health issues, classify risks at the patient level by drawing on the power of integrated data, and provide much-needed support to clinics and hospitals. With EHR-integrated PGHD, AI can help transform health care by improving diagnosis, treatment, and the delivery of clinical care, thus improving clinical decision support.

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: AMIA Jt Summits Transl Sci Proc Year: 2024 Document type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Language: En Journal: AMIA Jt Summits Transl Sci Proc Year: 2024 Document type: Article Affiliation country: United States
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