Evidence map›Paper›PMID 16787539›Full record

SynthesisBMC medical informatics and decision making2006

Evidence for handheld electronic medical records in improving care: a systematic review.

Robert C Wu, Sharon E Straus

Abstract readSystematic Review
In one paragraph

Synthesis in BMC medical informatics and decision making, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
–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

11 citing papers in PubMed.

  1. Article
  2. Observational
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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

2 authors.

Robert C WuDivision of General Internal Medicine, University Health Network, Toronto, Ontario, Canada. robert.wu@uhn.on.ca
Sharon E Straus

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHandheld electronic medical records are expected to improve physician performance and patient care. To confirm this, we performed a systematic review of the evidence assessing the effects of handheld electronic medical records on clinical care.

methodsTo conduct the systematic review, we searched MEDLINE, EMBASE, CINAHL, and the Cochrane library from 1966 through September 2005. We included randomized controlled trials that evaluated effects on practitioner performance or patient outcomes of handheld electronic medical records compared to either paper medical records or desktop electronic medical records. Two reviewers independently reviewed citations, assessed full text articles and abstracted data from the studies.

resultsTwo studies met our inclusion criteria. No other randomized controlled studies or non-randomized controlled trials were found that met our inclusion criteria. Both studies were methodologically strong. The studies examined changes in documentation in orthopedic patients with handheld electronic medical records compared to paper charts, and both found an increase in documentation. Other effects noted with handheld electronic medical records were an increase in time to document and an increase in wrong or redundant diagnoses.

conclusionHandheld electronic medical records may improve documentation, but as yet, the number of studies is small and the data is restricted to one group of patients and a small group of practitioners. Further study is required to determine the benefits with handheld electronic medical records especially in assessing clinical outcomes.

Indexed as

Evidence-Based MedicineOutcome and Process Assessment, Health CareClinical Trials as TopicComputers, HandheldDocumentationHumansMedical Records Systems, ComputerizedTime Factors

Identifiers

PMID16787539
PMCPMC1538581

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.