Evidence map›Paper›PMID 24194799›Full record

SynthesisOntario health technology assessment series2013

Electronic tools for health information exchange: an evidence-based analysis.

Health Quality Ontario

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in Ontario health technology assessment series, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Review
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  7. Review
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  9. Article
  10. Technology-assisted congestive heart failure care.Current heart failure reports · 2015
    Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

1 author.

Health Quality Ontario

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAs patients experience transitions in care, there is a need to share information between care providers in an accurate and timely manner. With the push towards electronic medical records and other electronic tools (eTools) (and away from paper-based health records) for health information exchange, there remains uncertainty around the impact of eTools as a form of communication.

objectiveTo examine the impact of eTools for health information exchange in the context of care coordination for individuals with chronic disease in the community. DATA SOURCES: A literature search was performed on April 26, 2012, using OVID MEDLINE, OVID MEDLINE In-Process and Other Non-Indexed Citations, OVID EMBASE, EBSCO Cumulative Index to Nursing & Allied Health Literature (CINAHL), the Wiley Cochrane Library, and the Centre for Reviews and Dissemination database, for studies published until April 26, 2012 (no start date limit was applied). REVIEW

methodsA systematic literature search was conducted, and meta-analysis conducted where appropriate. Outcomes of interest fell into 4 categories: health services utilization, disease-specific clinical outcomes, process-of-care indicators, and measures of efficiency. The quality of the evidence was assessed individually for each outcome. Expert panels were assembled for stakeholder engagement and contextualization.

resultsEleven articles were identified (4 randomized controlled trials and 7 observational studies). There was moderate quality evidence of a reduction in hospitalizations, hospital length of stay, and emergency department visits following the implementation of an electronically generated laboratory report with recommendations based on clinical guidelines. The evidence showed no difference in disease-specific outcomes; there was no evidence of a positive impact on process-of-care indicators or measures of efficiency. LIMITATIONS: A limited body of research specifically examined eTools for health information exchange in the population and setting of interest. This evidence included a combination of study designs and was further limited by heterogeneity in individual technologies and settings in which they were implemented.

conclusionsThere is evidence that the right eTools in the right environment and context can significantly impact health services utilization. However, the findings from this evidence-based analysis raise doubts about the ability of eTools with care-coordination capabilities to independently improve the quality of outpatient care. While eTools may be able to support and sustain processes, inefficiencies embedded in the health care system may require more than automation alone to resolve. PLAIN LANGUAGE SUMMARY: Patients with chronic diseases often work with many different health care providers. To ensure smooth transitions from one setting to the next, health care providers must share information and coordinate care effectively. Electronic medical records (eTools) are being used more and more to coordinate patient care, but it is not yet known whether they are more effective than paper-based health records. In this analysis, we reviewed the evidence for the use of eTools to exchange information and coordinate care for people with chronic diseases in the community. There was some evidence that eTools reduced the number of hospital and emergency department visits, as well as patients' length of stay in the hospital, but there was no evidence that eTools improved the overall quality of patient care.

Indexed as

Information DisseminationAmbulatory CareChronic DiseaseEmergency Service, HospitalEvidence-Based PracticeHealth Information SystemsHealth ServicesHospitalizationHumansLength of StayMedical Records Systems, ComputerizedQuality of Health Care

Identifiers

PMID24194799
PMCPMC3814806

What OpenQuestion holds

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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.