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<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:USMC-100921-M-2155E-002.jpg|280px]]</div>
<div style="float: left; margin: 0.5em 0.9em 0.4em 0em;">[[File:Fig1 Čartolovni DigitalHealth2023 9.jpeg|240px]]</div>
A '''[[skilled nursing facility]]''' ('''SNF''', pronounced like the English word "sniff"), as defined by the U.S. Social Security Act, is an institution or distinct part of an institution that provides skilled nursing care to residents or physical rehabilitation care to the injured, disabled, or ill. The skilled nursing facility is primarily a designation driven by the [[Centers for Medicare and Medicaid Services]] (CMS) and its associated billing. To qualify, a SNF must meet certain requirements, including considerations for quality of life, scope, assessment, and training.
'''"[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study]]"'''


The Federal Nursing Home Reform Act in 1987 set new requirements for nursing facilities, including the SNF. These facilities would have to emphasize quality of life and care to residents, create and assess an individual's care plan, provide the right to remain in care even after a hospital stay and the right to choose a personal physician, provide additional opportunities to residents with mental retardation or illness, and function under minimum federal standards or face even stricter penalties. ('''[[Skilled nursing facility|Full article...]]''')<br />
This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for [[artificial intelligence]] (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (''n'' = 12), patients (''n'' = 15), and healthcare managers (''n'' = 11), all of whom are directly related to the adoption of AI in medicine (''n'' = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... ('''[[Journal:Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study|Full article...]]''')<br />
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''Recently featured'':
''Recently featured'': [[Hydroinformatics]], [[Software as a service]], [[Health informatics]]
{{flowlist |
* [[Journal:Judgements of research co-created by generative AI: Experimental evidence|Judgements of research co-created by generative AI: Experimental evidence]]
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Latest revision as of 15:48, 26 May 2024

Fig1 Čartolovni DigitalHealth2023 9.jpeg

"Critical analysis of the impact of AI on the patient–physician relationship: A multi-stakeholder qualitative study"

This qualitative study aims to present the aspirations, expectations, and critical analysis of the potential for artificial intelligence (AI) to transform the patient–physician relationship, according to multi-stakeholder insight. This study was conducted from June to December 2021, using an anticipatory ethics approach and sociology of expectations as the theoretical frameworks. It focused mainly on three groups of stakeholders, namely physicians (n = 12), patients (n = 15), and healthcare managers (n = 11), all of whom are directly related to the adoption of AI in medicine (n = 38). In this study, interviews were conducted with 40% of the patients in the sample (15/38), as well as 31% of the physicians (12/38) and 29% of health managers in the sample (11/38) ... (Full article...)
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