دورية أكاديمية
أعرض في EDS

Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial.

التفاصيل البيبلوغرافية
العنوان: Autonomous artificial intelligence increases real-world specialist clinic productivity in a cluster-randomized trial.
المؤلفون: Abramoff MD; University of Iowa, Iowa City, Iowa, USA. michael-abramoff@uiowa.edu.; Digital Diagnostics Inc, Coralville, Iowa, USA. michael-abramoff@uiowa.edu.; Iowa City Veterans Affairs Medical Center, Iowa City, Iowa, USA. michael-abramoff@uiowa.edu.; Department of Biomedical Engineering, The University of Iowa, Iowa City, USA. michael-abramoff@uiowa.edu.; Department of Electrical and Computer Engineering, The University of Iowa, Iowa City, Iowa, USA. michael-abramoff@uiowa.edu., Whitestone N; Orbis International, New York, New York, USA., Patnaik JL; Orbis International, New York, New York, USA.; Department of Ophthalmology, University of Colorado School of Medicine, Aurora, Colorado, USA., Rich E; Orbis International, New York, New York, USA.; Centre for Public Health, Queen's University Belfast, Belfast, UK., Ahmed M; Orbis Bangladesh, Dhaka, Bangladesh., Husain L; Orbis Bangladesh, Dhaka, Bangladesh., Hassan MY; Orbis Bangladesh, Dhaka, Bangladesh., Tanjil MSH; Deep Eye Care Foundation, Rangpur, Bangladesh., Weitzman D; Digital Diagnostics Inc, Coralville, Iowa, USA., Dai T; Carey Business School, Johns Hopkins University, Baltimore, Maryland, USA.; Hopkins Business of Health Initiative, Johns Hopkins University, Baltimore, Maryland, USA.; School of Nursing, Johns Hopkins University, Baltimore, Maryland, USA., Wagner BD; Department of Ophthalmology, University of Colorado School of Medicine, Aurora, Colorado, USA.; Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, Colorado, USA., Cherwek DH; Orbis International, New York, New York, USA., Congdon N; Orbis International, New York, New York, USA.; Centre for Public Health, Queen's University Belfast, Belfast, UK.; Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China., Islam K; Deep Eye Care Foundation, Rangpur, Bangladesh.
المصدر: NPJ digital medicine [NPJ Digit Med] 2023 Oct 04; Vol. 6 (1), pp. 184. Date of Electronic Publication: 2023 Oct 04.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101731738 Publication Model: Electronic Cited Medium: Internet ISSN: 2398-6352 (Electronic) Linking ISSN: 23986352 NLM ISO Abbreviation: NPJ Digit Med Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: [London] ; New York : Nature Publishing Group, [2018]-
مستخلص: Autonomous artificial intelligence (AI) promises to increase healthcare productivity, but real-world evidence is lacking. We developed a clinic productivity model to generate testable hypotheses and study design for a preregistered cluster-randomized clinical trial, in which we tested the hypothesis that a previously validated US FDA-authorized AI for diabetic eye exams increases clinic productivity (number of completed care encounters per hour per specialist physician) among patients with diabetes. Here we report that 105 clinic days are cluster randomized to either intervention (using AI diagnosis; 51 days; 494 patients) or control (not using AI diagnosis; 54 days; 499 patients). The prespecified primary endpoint is met: AI leads to 40% higher productivity (1.59 encounters/hour, 95% confidence interval [CI]: 1.37-1.80) than control (1.14 encounters/hour, 95% CI: 1.02-1.25), p < 0.00; the secondary endpoint (productivity in all patients) is also met. Autonomous AI increases healthcare system productivity, which could potentially increase access and reduce health disparities. ClinicalTrials.gov NCT05182580.
(© 2023. Springer Nature Limited.)
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سلسلة جزيئية: ClinicalTrials.gov NCT05182580
تواريخ الأحداث: Date Created: 20231004 Latest Revision: 20231123
رمز التحديث: 20231215
مُعرف محوري في PubMed: PMC10550906
DOI: 10.1038/s41746-023-00931-7
PMID: 37794054
قاعدة البيانات: MEDLINE
الوصف
تدمد:2398-6352
DOI:10.1038/s41746-023-00931-7