Kirk D Wyatt1, Brian N Willaert2, Peter J Pallagi3, Richard A Uribe4, James A Yiannias5, Thomas R Hellmich1,6. 1. Department of Pediatric and Adolescent Medicine, Mayo Clinic, Rochester, MN, USA. 2. Information Technology, Mayo Clinic, Rochester, MN, USA. 3. Media Support Services, Mayo Clinic, Scottsdale, AZ, USA. 4. Information Technology, Mayo Clinic, Scottsdale, AZ, USA. 5. Department of Dermatology, Mayo Clinic, Scottsdale, AZ, USA. 6. Department of Emergency Medicine, Mayo Clinic, Rochester, MN, USA.
Abstract
BACKGROUND: Mayo Clinic developed an internal iOS-based, point-of-care clinical image capture application for clinicians. We aimed to assess the adoption and utilization of the application at Mayo Clinic. METHODS: Metadata of 22,784 photos of 6417 patients taken by 606 users over 8040 clinical encounters between 3/1/2015 and 10/31/2015 were analyzed. A random sample of photos from 100 clinical encounters was assessed for quality using a five-item rubric. Use of traditional medical photography services before and after application launch were compared. RESULTS: The largest group of users was residents/fellows, accounting for 31% of users but only 18% of all photos. Attending physicians accounted for 29% of users and 30% of photos. Nurses accounted for 14% of users and 28% of photos. Surgical specialties had the most users (36% of users), followed by dermatology (14% of users); however, dermatology accounted for 54% of all photos, and surgery accounted for 26% of photos. Images received an average of 91% of possible points on the quality scoring rubric. Most frequent reasons for missing points were the location on the body not clearly being demonstrated (19% of encounters) and the perspective/scale not being clearly demonstrated (12% of encounters). There was no discernible pre-post effect of the application's launch on use of traditional medical photography services. CONCLUSIONS: Point-of-care clinical photography is a growing phenomenon with potential to become the new standard of care. Patient and provider attitudes and the impact on patient outcomes remain unclear.
BACKGROUND:Mayo Clinic developed an internal iOS-based, point-of-care clinical image capture application for clinicians. We aimed to assess the adoption and utilization of the application at Mayo Clinic. METHODS: Metadata of 22,784 photos of 6417 patients taken by 606 users over 8040 clinical encounters between 3/1/2015 and 10/31/2015 were analyzed. A random sample of photos from 100 clinical encounters was assessed for quality using a five-item rubric. Use of traditional medical photography services before and after application launch were compared. RESULTS: The largest group of users was residents/fellows, accounting for 31% of users but only 18% of all photos. Attending physicians accounted for 29% of users and 30% of photos. Nurses accounted for 14% of users and 28% of photos. Surgical specialties had the most users (36% of users), followed by dermatology (14% of users); however, dermatology accounted for 54% of all photos, and surgery accounted for 26% of photos. Images received an average of 91% of possible points on the quality scoring rubric. Most frequent reasons for missing points were the location on the body not clearly being demonstrated (19% of encounters) and the perspective/scale not being clearly demonstrated (12% of encounters). There was no discernible pre-post effect of the application's launch on use of traditional medical photography services. CONCLUSIONS: Point-of-care clinical photography is a growing phenomenon with potential to become the new standard of care. Patient and provider attitudes and the impact on patient outcomes remain unclear.
Authors: Richmond M Castillo; Grace Y Kim; Kirk D Wyatt; Christine M Lohse; Thomas R Hellmich Journal: Appl Clin Inform Date: 2019-11-20 Impact factor: 2.342
Authors: Kirk D Wyatt; Brian N Willaert; Christine M Lohse; Peter J Pallagi; James A Yiannias; Thomas R Hellmich Journal: Appl Clin Inform Date: 2020-02-12 Impact factor: 2.342
Authors: Jennifer L Pecina; Kirk D Wyatt; Nneka I Comfere; Matthew E Bernard; Frederick North Journal: JMIR Mhealth Uhealth Date: 2017-11-08 Impact factor: 4.773
Authors: Anders Klingberg; Lee Alan Wallis; Marie Hasselberg; Po-Yin Yen; Sara Caroline Fritzell Journal: JMIR Mhealth Uhealth Date: 2018-10-19 Impact factor: 4.773
Authors: Kirk D Wyatt; Anissa Finley; Richard Uribe; Peter Pallagi; Brian Willaert; Steve Ommen; James Yiannias; Thomas Hellmich Journal: J Med Internet Res Date: 2020-05-12 Impact factor: 5.428
Authors: Julia C Cambron; Kirk D Wyatt; Christine M Lohse; Page Y Underwood; Thomas R Hellmich Journal: JMIR Mhealth Uhealth Date: 2019-12-03 Impact factor: 4.773