Large-Scale Telemedicine Implementation for Outpatient Clinicians: Results From a Pandemic-Adapted Learning Collaborative.

Learning collaboratives are seldom used outside of health care quality improvement. We describe a condensed, 10-week learning collaborative ("Telemedicine Hack") that facilitated telemedicine implementation for outpatient clinicians early in the COVID-19 pandemic. Live attendance averaged 1688 participants per session. Of 1005 baseline survey respondents, 57% were clinicians with one-third identifying as from a racial/ethnic minoritized group. Practice characteristics included primary care (71%), rural settings (51%), and community health centers (28%). Of three surveys, a high of 438 (81%) of 540 clinicians had billed ≥1 video-based telemedicine visit. Our learning collaborative "sprint" is a promising model for scaling knowledge during emergencies and addressing health inequities.

Utilization of the TRAIN Learning Network for Online Disaster Medicine and Public Health Training During the COVID-19 Pandemic.

OBJECTIVE: The coronavirus disease 2019 (COVID-19) pandemic dramatically accelerated a growing trend toward online and asynchronous education and professional training, including in the disaster medicine and public health sector. This study analyzed the impact of the COVID-19 pandemic on the growth of the TRAIN Learning Network (TRAIN) for the year 2020 and evaluated pandemic-related changes in use patterns by disaster and public health professionals. METHODS: The TRAIN database was queried to determine the change in the number of registered users, total courses completed, and courses completed related to COVID-19 during 2020. RESULTS: In 2020, a total of 755,222 new users joined the platform - nearly 3 times the average added annually over the preceding 5 y (2015-2019). TRAIN users completed 3,259,074 training courses in 2020, more than double the average number of training courses that were completed annually from 2015-2019. In addition, 17.8% of all newly added disaster and public health training courses in 2020 were specifically related to COVID-19. CONCLUSION: Online education provided by TRAIN is a critical tool for just-in-time disaster health training following a disaster event or public health emergency, including in a global health crisis such as a pandemic.

Profile of the public health workforce: registered TRAIN learners in the United States.

OBJECTIVES: We analyzed data from the TrainingFinder Real-time Affiliate Integrated Network (TRAIN), the most widely used public health workforce training system in the United States, to describe the public health workforce and characteristics of individual public health workers. METHODS: We extracted self-reported demographic data of 405,095 learners registered in the TRAIN online system in 2012. RESULTS: Mirroring the results of other public health workforce studies, TRAIN learners are disproportionately women, college educated, and White compared with the populations they serve. TRAIN learners live in every state and half of all zip codes, with a concentration in states whose public health departments are TRAIN affiliates. TRAIN learners' median age is 46 years, and one third of TRAIN learners will reach retirement age in the next 10 years. CONCLUSIONS: TRAIN data provide a limited but useful profile of public health workers and highlight the utility and limitations of using TRAIN for future research.