From the Health IT Buzz Blog – Since 2021, the Assistant Secretary for Technology Policy and Office of the National Coordinator for Health IT and the American Board of Family Medicine have collaborated to develop and field survey questions designed to better understand family physicians’ experience using health IT in primary care.
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The thought leaders in our community are good about sharing their thoughts on the issues of today. Here are the top read and shared guest posts of July that we think deserve sharing again.
From the Health IT Buzz Blog – A decade ago, as EHRs were rapidly implemented across the country, ONC sought to make sure these newly implemented technologies were interoperable. Since 2014, ONC has tracked progress toward widespread interoperability among hospitals and physicians by measuring…
The world is better off and getting better, compared to popular opinion and what’s broadcast on the news, says Hans Rosling and his co-authors, using simple, comprehensive measures, in Factfulness. Sometimes taking a step back and looking at the big picture (and the data) is important.
From The Health IT Buzz blog – Many hospitals have adopted systems for interoperable patient data exchange and are connected to national networks. However, ONC has consistently found that rates of interoperable exchange for smaller, rural, and independent hospitals have notably lagged behind other hospitals.
By Jordan Everson & Dan Healy – In a recent study in the Journal of the American Medical Informatics Association, we leveraged data from the 2020 American Hospital Association Information Technology Supplement gathered from April-June 2021, shortly after the initial applicability date of the information blocking regulations (April 5, 2021).
By Jordan Everson & Kimberly Tavernia – According to a recent American Hospital Association survey, most hospitals know about the Trusted Exchange Framework and Common Agreement (TEFCA) and, among those, very few plan on sitting out.
By Kathryn Marchesini, Jeff Smith, & Jordan Everson – As we’ve previously discussed, algorithms—step by step instructions (rules) to perform a task or solve a problem, especially by a computer—have been widely used in health care for decades. One clear use of these algorithms is through evidence-based, clinical decision support interventions.
By Kathryn Marchesini, Jeff Smith, & Jordan Everson – When talking about artificial intelligence today, people are usually referring to predictive models—often driven by machine learning techniques—that “learn” from historic data and make predictions, recommendations, or classifications (outputs) which inform or drive decision making.