Barriers to Electronic Health Record Adoption: a Systematic Literature Review

J Med Syst. 2016 Dec;40(12):252. doi: 10.1007/s10916-016-0628-9. Epub 2016 Oct 6.


Federal efforts and local initiatives to increase adoption and use of electronic health records (EHRs) continue, particularly since the enactment of the Health Information Technology for Economic and Clinical Health (HITECH) Act. Roughly one in four hospitals not adopted even a basic EHR system. A review of the barriers may help in understanding the factors deterring certain healthcare organizations from implementation. We wanted to assemble an updated and comprehensive list of adoption barriers of EHR systems in the United States. Authors searched CINAHL, MEDLINE, and Google Scholar, and accepted only articles relevant to our primary objective. Reviewers independently assessed the works highlighted by our search and selected several for review. Through multiple consensus meetings, authors tapered articles to a final selection most germane to the topic (n = 27). Each article was thoroughly examined by multiple authors in order to achieve greater validity. Authors identified 39 barriers to EHR adoption within the literature selected for the review. These barriers appeared 125 times in the literature; the most frequently mentioned barriers were regarding cost, technical concerns, technical support, and resistance to change. Despite federal and local incentives, the initial cost of adopting an EHR is a common existing barrier. The other most commonly mentioned barriers include technical support, technical concerns, and maintenance/ongoing costs. Policy makers should consider incentives that continue to reduce implementation cost, possibly aimed more directly at organizations that are known to have lower adoption rates, such as small hospitals in rural areas.

Keywords: Adoption: implementation; Barriers; Challenges; Electronic health records.

Publication types

  • Review
  • Systematic Review

MeSH terms

  • Confidentiality
  • Costs and Cost Analysis
  • Electronic Health Records / economics
  • Electronic Health Records / statistics & numerical data*
  • Hospital Administration / economics
  • Hospital Administration / statistics & numerical data*
  • Humans
  • Inservice Training
  • Time Factors
  • United States
  • Workflow