Using Machine Learning to Efficiently Vaccinate Homebound Patients Against COVID-19: A Real-time Immunization Campaign
Methods Ethics Approval The Icahn School of Medicine at Mount Sinai’s Program for the Protection of Human Subjects approved and granted a waiver of consent for this secondary data analysis study (STUDY- 21-00157) which was conducted in accordance with the Helsinki Declaration. Using the Google Maps...
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Published in | Journal of medical Internet research Vol. 24; no. 7; p. e37744 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Canada
Gunther Eysenbach MD MPH, Associate Professor
12.07.2022
JMIR Publications |
Subjects | |
Online Access | Get full text |
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Summary: | Methods Ethics Approval The Icahn School of Medicine at Mount Sinai’s Program for the Protection of Human Subjects approved and granted a waiver of consent for this secondary data analysis study (STUDY- 21-00157) which was conducted in accordance with the Helsinki Declaration. Using the Google Maps Geocoding application programming interface (API), we obtained latitude/longitude coordinates of patient residences, which served as the input data to our algorithm. Value Patient demographics Patients who are homebound 428 Average age (years) 83.9 Average Elixhauser comorbidity score [6]a 3.8 Sex, n (%) Female 323 (75.5) Male 105 (24.5) Racial/ethnic identity, n (%) White 148 (34.6) Black or African American 63 (14.7) Asian 15 (3.5) Hispanic 108 (25.2) Other 86 (20.1) Unknown 8 (1.9) Patient’s family members and caregivers, n 92 Vaccination campaign statistics Providers vaccinating per day (n), range 3-6 Average number of patients vaccinated per day 22.1 Average duration of provider time spent vaccinating (hours) 4.6 Average duration of individual vaccination (including transit time, vaccine administration, and 15-minute postvaccination observation time; minutes) 52 aElixhauser scores were available for 372 of the patients who are homebound. |
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Bibliography: | SourceType-Scholarly Journals-1 ObjectType-Correspondence-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 1438-8871 1439-4456 1438-8871 |
DOI: | 10.2196/37744 |