Evidence map›Paper›PMID 27328761›Full record

ArticleJMIR human factors2016

Usability Testing and Adaptation of the Pediatric Cardiovascular Risk Reduction Clinical Decision Support Tool.

Pamela A Williams, Robert D Furberg, Jacqueline E Bagwell, Kenneth A LaBresh

Open access · goldAbstract read
In one paragraph

Article in JMIR human factors, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
2.3field-weighted citation impact, top 10% of its field
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

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 14 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Provider Survey on Automated Clinical Decision Support for Cardiovascular Risk Assessment.Mayo Clinic proceedings. Innovations, quality & outcomes · 2019
    Article
  7. Provider Survey on Automated Clinical Decision Support System for Cardiovascular Risk Assessment.AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science · 2019
    Article
  8. 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 at 1 institution in 1 country.

Pamela A WilliamsRTI International, Social Policy, Health and Economics Research Unit, Research Triangle Park, NC, United States. pamwilliams@rti.org.ORCID http://orcid.org/0000-0002-6040-6972
RTI International · US

Funding

NHLBI NIH HHS HHSN268200900120U
6 · The paper itself

Abstract

backgroundCardiovascular disease (CVD) is 1 of the leading causes of death, years of life lost, and disability-adjusted years of life lost worldwide. CVD prevention for children and teens is needed, as CVD risk factors and behaviors beginning in youth contribute to CVD development. In 2012, the National Heart, Lung, and Blood Institute released their "Integrated Guidelines for Cardiovascular Health and Risk Reduction in Children and Adolescents" for clinicians, describing CVD risk factors they should address with patients at primary care preventative visits. However, uptake of new guidelines is slow. Clinical decision support (CDS) tools can improve guideline uptake. In this paper, we describe our process of testing and adapting a CDS tool to help clinicians evaluate patient risk, recommend behaviors to prevent development of risk, and complete complex calculations to determine appropriate interventions as recommended by the guidelines, using a user-centered design approach.

objectiveThe objective of the study was to assess the usability of a pediatric CVD risk factor tool by clinicians.

methodsThe tool was tested using one-on-one in-person testing and a "think aloud" approach with 5 clinicians and by using the tool in clinical practice along with formal usability metrics with 14 pediatricians. Thematic analysis of the data from the in-person testing and clinical practice testing identified suggestions for change in 3 major areas: user experience, content refinement, and technical deployment. Descriptive statistical techniques were employed to summarize users' overall experience with the tool.

resultsData from testers showed that general reactions toward the CDS tool were positive. Clinical practice testers suggested revisions to make the application more user-friendly, especially for clinicians using the application on the iPhone, and called for refining recommendations to be more succinct and better tailored to the patient. Tester feedback was incorporated into the design when feasible, including streamlining data entry during clinical visits, reducing the volume of results displayed, and highlighting critical results.

conclusionsThis study found support for the usability of our pediatric CVD risk factor tool. Insights shared about this tool may be applicable for designing other mHealth applications and CDS tools. The usability of decision support tools in clinical practice depends critically on receiving (ie, through an accessible device) and adapting the tool to meet the needs of clinicians in the practice setting.

Indexed as

adaptationcardiovascular diseasesclinical decision supportdecision aidsguidelinesmHealthpediatricsrisk factorsusability

Identifiers

PMID27328761
PMCPMC4933802
OpenAlexW2470098665

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.