Trends in the Use of Computerized Physician Order Entry by Health-System Affiliated Ambulatory Clinics in the United States, 2014–2016
Sep 11, 2020
Published in: The American Journal of Accountable Care, Volume 7, Number 4, pages 4–10 (December 2019)
Posted on RAND.org on August 25, 2020
Clinical decision support (CDS) is important for delivering high-quality care. We examined the use of 7 functions of CDS and changes over time in US health system–affiliated ambulatory clinics.
We analyzed longitudinal data for 19,209 ambulatory clinics that participated in 3 years (2014–2016) of the Healthcare Information and Management Systems Society Analytics survey to assess use of 7 CDS functions and the characteristics of clinics associated with use of CDS.
We used descriptive statistics and linear probability models to assess the association of clinic characteristics (practice type, health system type, practice size) and 2 outcomes: CDS use during the study period and CDS use beginning in 2015 or 2016.
Use rates increased between 2014 and 2016 for all 7 CDS functions, with increases ranging from 4 percentage points (genetic testing) to 13 percentage points (diagnostic result alerts). In 2016, the rate of use was highest for basic medication screening (61%), clinical guidelines and protocols (54%), and preventive medicine (57%). Lower use rates were observed for diagnostic result alerts (42%), remote device alerts (19%), incorporation of community-based electronic health record data into rules engines (26%), and genomics profiling in orders (9%). More than half of health systems, which included many smaller health systems, reported that none of their affiliated clinics used any CDS function. Affiliation with a multihospital health system and clinic size, but not clinic type (eg, primary care), were associated with a greater likelihood of use for most CDS functions.
Despite federal investment to promote health information technology adoption, substantial gaps remain in the use of CDS among ambulatory clinics, particularly among smaller health systems.