The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System.
Transitions from one level of care to another are complex processes that pose medical and organizational risks and depend on care integration between different providers. This qualitative study investigated user experiences with an existing digital system for care integration between hospitals and n...
| Publicado en: | Inquiry (00469580) pp. 1 - 12 |
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| Formato: | Artículo |
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Sage Publications Inc.
5/24/2021
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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=hlh&AN=150501458&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 150501458 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00469580 INQ jtl: Inquiry (00469580) issn: 00469580 maglogo: Y pubinfo: dt: 5/24/2021 pid: 344 pub: Sage Publications Inc. artinfo: ui: 150501458 10.1177/00469580211017992 ppf: 1 ppct: 11 formats: tig: atl: The Potential of AI in Care Optimization: Insights from the User-Driven Co-Development of a Care Integration System. aug: au: Schneider-Kamp, Anna affil: University of Southern Denmark, Odense M, Denmark su: Research evaluation Digital technology Information resources management Nursing care plans Artificial intelligence Medical care Interviewing Qualitative research Ethnology research Patients' attitudes Database management Descriptive statistics Research funding sug: subj: Research evaluation Digital technology Information resources management Nursing care plans Artificial intelligence Medical care Interviewing Qualitative research Ethnology research Patients' attitudes Database management Descriptive statistics Research funding keyword: artificial intelligence care integration hospital discharge summary nursing care plan nursing home qualitative health research transitional care user perspective ab: Transitions from one level of care to another are complex processes that pose medical and organizational risks and depend on care integration between different providers. This qualitative study investigated user experiences with an existing digital system for care integration between hospitals and nursing homes, and the potential of artificial intelligence to contribute to its optimization. The findings reveal challenges regarding (a) untimely information, (b) irrelevant information, (c) confusing information, (d) missing information, (e) information overload, and (f) information multiplicity. Artificial intelligence could address these by (i) identifying and verifying low-quality information, (ii) targeting information for different user groups, (iii) visually summarizing relevant information, and (iv) jointly presenting multiple versions. The implications of these findings extend beyond the context of care integration, presenting empirical evidence for the importance of qualitative health research in, and a model for, determining the scope and design of future artificial intelligence solutions to optimize (health)care processes. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2021 holdings: @attributes: islocal: N |
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