Electronic health record functions differ between best and worst hospitals

Am J Manag Care. 2011 Apr;17(4):e121-47.

Abstract

Objective: To determine whether patterns of electronic health record (EHR) adoption and “meaningful use” vary between high-, intermediate-, and low-quality US hospitals.

Study design: We used data from the Hospital Quality Alliance program to designate hospitals as high quality (performance in the top decile nationally), low quality (bottom decile), and intermediate quality (all others). We examined EHR adoption and meaningful use using national survey data.

Methods: We used logistic regression models to determine the frequency with which hospitals in each group adopted individual EHR functions and met meaningful use criteria, and factor analyses to examine adoption patterns in high- and low-quality hospitals.

Results: High-quality hospitals were more likely to have all clinical decision support functions. High-quality hospitals were also more likely to have computerized physician order entry for medications compared with intermediate- and low-quality hospitals. Among those who had not yet implemented components of clinical decision support, two-thirds of low-quality hospitals reported no concrete plans for adoption. Finally, high-quality hospitals were more likely to meet many of the meaningful use criteria such as reporting quality measures, implementing at least 1 clinical decision support rule, and exchanging key clinical data.

Conclusions: We found higher rates of adoption of key EHR functions among high-quality hospitals, suggesting that high quality and EHR adoption may be linked. Most low-quality hospitals without EHR functions reported no plans to implement them, pointing to challenges faced by policy makers in achieving widespread EHR adoption while simultaneously improving quality of care.

Publication types

  • Comparative Study
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • American Hospital Association
  • Data Collection
  • Diffusion of Innovation*
  • Electronic Health Records / statistics & numerical data*
  • Hospitals / classification
  • Hospitals / standards*
  • Humans
  • Logistic Models
  • Practice Patterns, Physicians' / statistics & numerical data*
  • Quality of Health Care*
  • United States