Evidence map›Paper›PMID 28838801›Full record

SynthesisJournal of biomedical informatics2017

Optimization of infobutton design and Implementation: A systematic review.

Miguel Teixeira, David A Cook, Bret S E Heale, Guilherme Del Fiol

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of biomedical informatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

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

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Transforming primary medical research knowledge into clinical decision.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2020
    Article
  6. Article
  7. Article
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

4 authors.

Miguel TeixeiraDepartment of Internal Medicine, Mayo Clinic, Rochester, MN, United States; Department of Anesthesiology, Mayo Clinic, Rochester, MN, United States. Electronic address: teixeira.miguel@mayo.edu.
David A CookDepartment of Internal Medicine, Mayo Clinic, Rochester, MN, United States; Mayo Clinic Online Learning, Mayo Clinic College of Medicine and Science, Rochester, MN, United States; Knowledge Delivery Center, Mayo Clinic College of Medicine and Science, Rochester, MN, United States. Electronic address: cook.david33@mayo.edu.
Bret S E HealeDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States. Electronic address: bheale@gmail.com.
Guilherme Del FiolDepartment of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States. Electronic address: guilherme.delfiol@utah.edu.

Funding

UNIVERSITY OF UTAH MEDICAL INFORMATICS TRAININGT15LM007124 · NLM · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · PI Karen Louise Eilbeck · 1997 to 2026
$22.0M
Meeting Clinicians' Information Needs with Highly Tailored Knowledge SummariesR01LM011416 · NLM · UNIVERSITY OF UTAH · PI DEL FIOL, GUILHERME · 2013 to 2016
$1.3M
NLM NIH HHS R01 LM011416NLM NIH HHS T15 LM007124
6 · The paper itself

Abstract

objectiveInfobuttons are clinical decision tools embedded in the electronic health record that attempt to link clinical data with context sensitive knowledge resources. We systematically reviewed technical approaches that contribute to improved infobutton design, implementation and functionality.

methodsWe searched databases including MEDLINE, EMBASE, and the Cochrane Library database from inception to March 1, 2016 for studies describing the use of infobuttons. We selected full review comparative studies, usability studies, and qualitative studies examining infobutton design and implementation. We abstracted usability measures such as user satisfaction, impact, and efficiency, as well as prediction accuracy of infobutton content retrieval algorithms and infobutton adoption/interoperability.

resultsWe found 82 original research studies on infobuttons. Twelve studies met criteria for detailed abstraction. These studies investigated infobutton interoperability (1 study); tools to help tailor infobutton functionality (1 study); interventions to improve user experience (7 studies); and interventions to improve content retrieval by improving prediction of relevant knowledge resources and information needs (3 studies). In-depth interviews with implementers showed the Health Level Seven (HL7) Infobutton standard to be simple and easy to implement. A usability study demonstrated the feasibility of a tool to help medical librarians tailor infobutton functionality. User experience studies showed that access to resources with which users are familiar increased user satisfaction ratings; and that links to specific subsections of drug monographs increased information seeking efficiency. However, none of the user experience improvements led to increased usage uptake. Recommender systems based on machine learning algorithms outperformed hand-crafted rules in the prediction of relevant resources and clinicians' information needs in a laboratory setting, but no studies were found using these techniques in clinical settings. Improved content indexing in one study led to improved content retrieval across three health care organizations.

conclusionBest practice technical approaches to ensure optimal infobutton functionality, design and implementation remain understudied. The HL7 Infobutton standard has supported wide adoption of infobutton functionality among clinical information systems and knowledge resources. Limited evidence supports infobutton enhancements such as links to specific subtopics, configuration of optimal resources for specific tasks and users, and improved indexing and content coverage. Further research is needed to investigate user experience improvements to increase infobutton use and effectiveness.

Indexed as

AlgorithmsDecision Support Systems, ClinicalDiffusion of InnovationElectronic Health RecordsHealth Level SevenDecision support systemsHealth information technologyInfobuttonInformation needsMachine learningMedical informatics applications

Identifiers

PMID28838801
PMCPMC5641258

What OpenQuestion holds

Textmetadata
LicenceTDM
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.