CoChat
Sign Up
Cited by 501Electronic Health Records SystemsTechnology and Human Factors in Education and HealthMedical Coding and Health Information

Costs and benefits of health information technology.

Open access
Shekelle, Paul G, Morton, Sally C, Keeler, Emmett B·2006
DOI 10.23970/ahrqepcerta132PMC PMC4781594
Open this paper in CoChat — free account

Abstract

OBJECTIVES: An evidence report was prepared to assess the evidence base regarding benefits and costs of health information technology (HIT) systems, that is, the value of discrete HIT functions and systems in various healthcare settings, particularly those providing pediatric care. DATA SOURCES: PubMed, the Cochrane Controlled Clinical Trials Register, and the Cochrane Database of Reviews of Effectiveness (DARE) were electronically searched for articles published since 1995. Several reports prepared by private industry were also reviewed. REVIEW METHODS: Of 855 studies screened, 256 were included in the final analyses. These included systematic reviews, meta-analyses, studies that tested a hypothesis, and predictive analyses. Each article was reviewed independently by two reviewers; disagreement was resolved by consensus. RESULTS: Of the 256 studies, 156 concerned decision support, 84 assessed the electronic medical record, and 30 were about computerized physician order entry (categories are not mutually exclusive). One hundred twenty four of the studies assessed the effect of the HIT system in the outpatient or ambulatory setting; 82 assessed its use in the hospital or inpatient setting. Ninety-seven studies used a randomized design. There were 11 other controlled clinical trials, 33 studies using a pre-post design, and 20 studies using a time series. Another 17 were case studies with a concurrent control. Of the 211 hypothesis-testing studies, 82 contained at least some cost data. We identified no study or collection of studies, outside of those from a handful of HIT leaders, that would allow a reader to make a determination about the generalizable knowledge of the study's reported benefit. Beside these studies from HIT leaders, no other research assessed HIT systems that had comprehensive functionality and included data on costs, relevant information on organizational context and process change, and data on implementation. A small body of literature supports a role for HIT in improving the quality of pediatric care. Insufficient data were available on the costs or cost-effectiveness of implementing such systems. The ability of Electronic Health Records (EHRs) to improve the quality of care in ambulatory care settings was demonstrated in a small series of studies conducted at four sites (three U.S. medical centers and one in the Netherlands). The studies demonstrated improvements in provider performance when clinical information management and decision support tools were made available within an EHR system, particularly when the EHRs had the capacity to store data with high fidelity, to make those data readily accessible, and to help translate them into context-specific information that can empower providers in their work. Despite the heterogeneity in the analytic methods used, all cost-benefit analyses predicted substantial savings from EHR (and health care information exchange and interoperability) implementation: The quantifiable benefits are projected to outweigh the investment costs. However, the predicted time needed to break even varied from three to as many as 13 years. CONCLUSIONS: HIT has the potential to enable a dramatic transformation in the delivery of health care, making it safer, more effective, and more efficient. Some organizations have already realized major gains through the implementation of multifunctional, interoperable HIT systems built around an EHR. However, widespread implementation of HIT has been limited by a lack of generalizable knowledge about what types of HIT and implementation methods will improve care and manage costs for specific health organizations. The reporting of HIT development and implementation requires fuller descriptions of both the intervention and the organizational/economic environment in which it is implemented.

Integrity signals

Registry

Crossref · 10.23970/ahrqepcerta132

Cites

875 of 875 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Lack of effective leadership to advocate change, set priorities or manage the implementation process, and changes in leadership, were presented as barriers.

    “Conversely, lack of effective leadership to advocate change, set priorities or manage the implementation process; and changes in leadership were presented as barriers [55, 67–69].”

    From Achieving change in primary care—causes of the evidence to practice gap: systematic reviews of reviews (2015) · cites this paper as [69]

  • Personal style, defined as the perceived fit between the intervention and the preferred style of clinical practice, personality, and philosophical opposition to the intervention, was presented exclusively as a barrier.

    “Personal style, defined as the perceived fit between the intervention and the preferred style of clinical practice, such as clinicians’ communication style [78, 79], personality [54] and philosophical opposition to the intervention [69, 76], were presented exclusively as barriers.”

    From Achieving change in primary care—causes of the evidence to practice gap: systematic reviews of reviews (2015) · cites this paper as [69]

  • Resistance to change caused by disagreement with the evidence, negative beliefs about the usefulness or added value of the intervention, or belief that the intervention was not part of their role were commonly described as a barrier to implementation.

    “Resistance to change caused by disagreement with the evidence, negative beliefs about the usefulness or added value of the intervention or belief that the intervention was not part of their role were commonly described as a barrier to implementation [3, 14, 35, 41, 67–70, 76, 77, 80].”

    From Achieving change in primary care—causes of the evidence to practice gap: systematic reviews of reviews (2015) · cites this paper as [69]

  • A lack of knowledge and a limited understanding of benefits afforded by the systems acted as a barrier to implementation.

    “A lack of knowledge and a limited understanding of benefits afforded by the systems acted as a barrier to implementation [49, 52, 53].”

    From Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update) (2016) · cites this paper as [52]

  • Health professionals' perceptions that e-health systems disrupt workflows and the delivery of care are a barrier to both the implementation and use of these systems.

    “Health professionals’ perceptions that e-health systems disrupt workflows, and the delivery of care, are a barrier to both the implementation and use of these systems [23, 49, 52, 56, 57].”

    From Factors that influence the implementation of e-health: a systematic review of systematic reviews (an update) (2016) · cites this paper as [52]

Cites

1 retracted

Flagged first, then by citations

2 of the 877 references couldn’t be matched to a known paper.

Cited by

Sorted by citations

Related

Authors
Shekelle, P. G., Morton, S. C., & Keeler, E. B.
ORCID
Shekelle, Paul G
Publisher
Agency for Healthcare Research and Quality
Published
2006-04
Issue
132
Pages
1-71
DOI
10.23970/ahrqepcerta132
PMC
PMC4781594
OpenAlex
W2169921538
Cited by
501
References
877
Citations by year
2026: 3 · 2025: 5 · 2024: 6 · 2023: 8 · 2022: 12 · 2021: 22 · 2020: 22 · 2019: 21 · 2018: 32 · 2017: 35 · 2016: 35 · 2015: 28 · 2014: 33 · 2013: 41 · 2012: 30
Type
report
Language
en
Open access
Locations
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Technology and Human Factors in Education and Health
  • Health Sciences › Health Professions › Health Information Management › Medical Coding and Health Information
Keywords
health information technology, electronic health records, clinical decision support, computerized physician order entry, pediatric care, outpatient care, inpatient care, quality of care, cost-effectiveness, implementation costs, process change, organizational context, cost-benefit analysis
MeSH terms
Ambulatory Care, Cost-Benefit Analysis, Costs and Cost Analysis, Information Systems, Pediatrics, Quality of Health Care, Technology, Medical Records Systems, Computerized

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review