Evidence map›Paper›PMID 29653922›Full record

ArticleJMIR medical informatics2018

Agile Acceptance Test-Driven Development of Clinical Decision Support Advisories: Feasibility of Using Open Source Software.

Mujeeb A Basit, Krystal L Baldwin, Vaishnavi Kannan, Emily L Flahaven, Cassandra J Parks, Jason M Ott, Duwayne L Willett

Abstract read
In one paragraph

Article in JMIR medical informatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. User stories as lightweight requirements for agile clinical decision support development.Journal of the American Medical Informatics Association : JAMIA · 2019
    Article
  3. Article
  4. 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

7 authors.

Mujeeb A BasitUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0002-4948-6158
Krystal L BaldwinUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0003-2567-3941
Vaishnavi KannanUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0002-3042-5427
Emily L FlahavenUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0002-2303-4807
Cassandra J ParksUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0002-2787-7588
Jason M OttUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0002-8725-1771
Duwayne L WillettUniversity of Texas Southwestern Medical Center, Dallas, TX, United States.ORCID http://orcid.org/0000-0002-3087-4193

Funding

UT Southwestern Center for Translational Medicine (UL1/KL2/TL1)UL1TR001105 · NCATS · UT SOUTHWESTERN MEDICAL CENTER · PI TOTO, ROBERT DANIEL · 2013 to 2017
$24.5M
NCATS NIH HHS UL1 TR001105
6 · The paper itself

Abstract

backgroundMoving to electronic health records (EHRs) confers substantial benefits but risks unintended consequences. Modern EHRs consist of complex software code with extensive local configurability options, which can introduce defects. Defects in clinical decision support (CDS) tools are surprisingly common. Feasible approaches to prevent and detect defects in EHR configuration, including CDS tools, are needed. In complex software systems, use of test-driven development and automated regression testing promotes reliability. Test-driven development encourages modular, testable design and expanding regression test coverage. Automated regression test suites improve software quality, providing a "safety net" for future software modifications. Each automated acceptance test serves multiple purposes, as requirements (prior to build), acceptance testing (on completion of build), regression testing (once live), and "living" design documentation. Rapid-cycle development or "agile" methods are being successfully applied to CDS development. The agile practice of automated test-driven development is not widely adopted, perhaps because most EHR software code is vendor-developed. However, key CDS advisory configuration design decisions and rules stored in the EHR may prove amenable to automated testing as "executable requirements."

objectiveWe aimed to establish feasibility of acceptance test-driven development of clinical decision support advisories in a commonly used EHR, using an open source automated acceptance testing framework (FitNesse).

methodsAcceptance tests were initially constructed as spreadsheet tables to facilitate clinical review. Each table specified one aspect of the CDS advisory's expected behavior. Table contents were then imported into a test suite in FitNesse, which queried the EHR database to automate testing. Tests and corresponding CDS configuration were migrated together from the development environment to production, with tests becoming part of the production regression test suite.

resultsWe used test-driven development to construct a new CDS tool advising Emergency Department nurses to perform a swallowing assessment prior to administering oral medication to a patient with suspected stroke. Test tables specified desired behavior for (1) applicable clinical settings, (2) triggering action, (3) rule logic, (4) user interface, and (5) system actions in response to user input. Automated test suite results for the "executable requirements" are shown prior to building the CDS alert, during build, and after successful build.

conclusionsAutomated acceptance test-driven development and continuous regression testing of CDS configuration in a commercial EHR proves feasible with open source software. Automated test-driven development offers one potential contribution to achieving high-reliability EHR configuration. Vetting acceptance tests with clinicians elicits their input on crucial configuration details early during initial CDS design and iteratively during rapid-cycle optimization.

Indexed as

agile methodsclinical decision support systemselectronic health recordssoftware validationsoftware verificationtest driven development

Identifiers

PMID29653922
PMCPMC5924365

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.