Evidence map›Paper›PMID 31512730›Full record

ArticleJournal of the American Medical Informatics Association : JAMIA2019

User stories as lightweight requirements for agile clinical decision support development.

Vaishnavi Kannan, Mujeeb A Basit, Puneet Bajaj, Angela R Carrington, Irma B Donahue, Emily L Flahaven, Richard Medford, Tsedey Melaku, Brett A Moran, Luis E Saldana and 3 more

Open access · bronzeAbstract read
In one paragraph

Article in Journal of the American Medical Informatics Association : JAMIA, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 21% 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

10 citing papers in PubMed, 32 citations in OpenAlex.

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  9. An Integrated Process for Co-Developing and Implementing Written and Computable Clinical Practice Guidelines.American journal of medical quality : the official journal of the American College of Medical Quality
    Article
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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

13 authors at 3 institutions in 1 country.

Vaishnavi KannanClinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.
Mujeeb A BasitClinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.
Puneet BajajDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Angela R CarringtonHealth System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Irma B DonahueHealth System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Emily L FlahavenClinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.
Richard MedfordClinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.
Tsedey MelakuClinical Informatics, Parkland Health and Hospital System, Dallas, Texas, USA.
Brett A MoranDepartment of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Luis E SaldanaClinical Informatics, Texas Health Resources, Arlington, Texas, USA.
Duwayne L WillettClinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.
Josh E YoungbloodHealth System Information Resources Department, University of Texas Southwestern Medical Center, Dallas, Texas, USA.
Seth M ToomayClinical Informatics, University of Texas Southwestern Health System, Dallas, Texas, USA.
The University of Texas Southwestern Medical Center · USParkland Health & Hospital System · USTexas Health Resources Foundation · US

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

objectiveWe sought to demonstrate applicability of user stories, progressively elaborated by testable acceptance criteria, as lightweight requirements for agile development of clinical decision support (CDS). MATERIALS AND

methodsUser stories employed the template: As a [type of user], I want [some goal] so that [some reason]. From the "so that" section, CDS benefit measures were derived. Detailed acceptance criteria were elaborated through ensuing conversations. We estimated user story size with "story points," and depicted multiple user stories with a use case diagram or feature breakdown structure. Large user stories were split to fit into 2-week iterations.

resultsOne example user story was: As a rheumatologist, I want to be advised if my patient with rheumatoid arthritis is not on a disease-modifying anti-rheumatic drug (DMARD), so that they receive optimal therapy and can experience symptom improvement. This yielded a process measure (DMARD use), and an outcome measure (Clinical Disease Activity Index). Following implementation, the DMARD nonuse rate decreased from 3.7% to 1.4%. Patients with a high Clinical Disease Activity Index improved from 13.7% to 7%. For a thromboembolism prevention CDS project, diagrams organized multiple user stories. DISCUSSION: User stories written in the clinician's voice aid CDS governance and lead naturally to measures of CDS effectiveness. Estimation of relative story size helps plan CDS delivery dates. User stories prove to be practical even on larger projects.

conclusionsUser stories concisely communicate the who, what, and why of a CDS request, and serve as lightweight requirements for agile development to meet the demand for increasingly diverse CDS.

Indexed as

Data CollectionDecision Support Systems, ClinicalNarrationElectronic Health RecordsHumansagile developmentclinical decision supportelectronic health recordsimplementationrequirements

Identifiers

PMID31512730
PMCPMC6798563
OpenAlexW2972831657

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.