Evidence map›Paper›PMID 23346473›Full record

ArticleHealthcare informatics research2012

Human Factors Engineering in HI: So What? Who Cares? and What's in It for You?

Peter L Elkin

Abstract read
In one paragraph

Article in Healthcare informatics research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

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

  1. Pooled it
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  4. Biomedical Informatics Investigator.Studies in health technology and informatics · 2018
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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.

Peter L ElkinInternational Health Data Solutions, New York, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesHuman factors engineering is a discipline that deals with computer and human systems and processes and provides a methodology for designing and evaluating systems as they interact with human beings. This review article reviews important current and past efforts in human factors engineering in health informatics in the context of the current trends in health informatics.

methodsThe methodology of human factors engineering and usability testing in particular were reviewed in this article.

resultsThis methodology arises from the field of human factors engineering, which uses principles from cognitive science and applies them to implementations such as a computer-human interface and user-centered design.

conclusionsPatient safety and best practice of medicine requires a partnership between patients, clinicians and computer systems that serve to improve the quality and safety of patient care. People approach work and problems with their own knowledge base and set of past experiences and their ability to use systems properly and with low error rates are directly related to the usability as well as the utility of computer systems. Unusable systems have been responsible for medical error and patient harm and have even led to the death of patients and increased mortality rates. Electronic Health Record and Computerized Physician Order Entry systems like any medical device should come with a known safety profile that minimizes medical error and harm. This review article reviews important current and past efforts in human factors engineering in health informatics in the context of the current trends in health informatics.

Indexed as

Health InformaticsHuman Factors EngineeringPatient SafetyUsability TestingUser-Centered Design

Identifiers

PMID23346473
PMCPMC3548152

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.