Trends in the use of computerized physician order entry by health-system affiliated ambulatory clinics in the United States, 2014-2016

BMC Health Serv Res. 2020 Sep 7;20(1):836. doi: 10.1186/s12913-020-05679-4.


Background: Computerized provider order entry (CPOE) can help providers deliver better quality care. We aimed to understand recent trends in use of CPOE by health system-affiliated ambulatory clinics.

Methods: We analyzed longitudinal data (2014-2016) for 19,109 ambulatory clinics that participated in all 3 years of the Healthcare Information and Management Systems Society Analytics survey to assess use of CPOE and identify characteristics of clinics associated with CPOE use. We calculated descriptive statistics to examine overall trends in use, location of order entry (bedside vs. clinical station), and system-level use CPOE across all clinics. We used linear probability models to explore the association between clinic characteristics (practice size, practice type, and health system type) and two outcomes of interest: CPOE use at any point between 2014 and 2016, and CPOE use beginning in 2015 or 2016.

Results: Between 2014 and 2016, use of CPOE increased more than 9 percentage points from 58 to 67%. Larger clinics and those affiliated with multi-hospital health systems were more likely to have reported use of CPOE. We found no difference in CPOE use by primary care versus specialty care clinics. When used, most clinics reported using CPOE for most or all of their orders. Health systems that used CPOE usually did so for all system-affiliated clinics.

Conclusions: Small practice size or not being part of a multi-hospital system are associated with lower use of CPOE between 2014 and 2016. Less than optimal use in these environments may be harming patient outcomes.

Keywords: Ambulatory clinics; CPOE; Computerized provider order entry; Health systems.

MeSH terms

  • Ambulatory Care Facilities / statistics & numerical data*
  • Humans
  • Longitudinal Studies
  • Medical Order Entry Systems / statistics & numerical data*
  • Quality of Health Care
  • United States