Cited by 36Electronic Health Records SystemsMobile Health and mHealth ApplicationsClinical practice guidelines implementation

Development and implementation of a mobile device-based pediatric electronic decision support tool as part of a national practice standardization project

Open access
McCulloh, Russell J, Fouquet, Sarah D, Herigon, Joshua, Biondi, Eric A, Kennedy, Brandan, Kerns, Ellen, DePorre, Adrienne, Markham, Jessica L +3 more·2018·Journal of the American Medical Informatics Association

Abstract

Objective: Implementing evidence-based practices requires a multi-faceted approach. Electronic clinical decision support (ECDS) tools may encourage evidence-based practice adoption. However, data regarding the role of mobile ECDS tools in pediatrics is scant. Our objective is to describe the development, distribution, and usage patterns of a smartphone-based ECDS tool within a national practice standardization project. Materials and Methods: We developed a smartphone-based ECDS tool for use in the American Academy of Pediatrics, Value in Inpatient Pediatrics Network project entitled “Reducing Excessive Variation in the Infant Sepsis Evaluation (REVISE).” The mobile application (app), PedsGuide, was developed using evidence-based recommendations created by an interdisciplinary panel. App workflow and content were aligned with clinical benchmarks; app interface was adjusted after usability heuristic review. Usage patterns were measured using Google Analytics. Results: Overall, 3805 users across the United States downloaded PedsGuide from December 1, 2016, to July 31, 2017, leading to 14 256 use sessions (average 3.75 sessions per user). Users engaged in 60 442 screen views, including 37 424 (61.8%) screen views that displayed content related to the REVISE clinical practice benchmarks, including hospital admission appropriateness (26.8%), length of hospitalization (14.6%), and diagnostic testing recommendations (17.0%). Median user touch depth was 5 [IQR 5]. Discussion: We observed rapid dissemination and in-depth engagement with PedsGuide, demonstrating feasibility for using smartphone-based ECDS tools within national practice improvement projects. Conclusions: ECDS tools may prove valuable in future national practice standardization initiatives. Work should next focus on developing robust analytics to determine ECDS tools’ impact on medical decision making, clinical practice, and health outcomes.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/jamia/ocy069

Cites

42 of 42 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 1

  1. [32]Herigon J, McCulloh R, Newland J. Development of a smartphone-based physician decision tool for common pediatric infectious conditions.Infectious Diseases Society of America Annual Conference; 2014; Philadelphia, PA.

Cited by

Sorted by citations

Authors
McCulloh, R. J., Fouquet, S. D., Herigon, J., Biondi, E. A., Kennedy, B., Kerns, E., DePorre, A., Markham, J. L., Chan, Y. R., Nelson, K., & Newland, J. G.
Affiliations
  • Children's Mercy Hospital (US)
  • Boston Children's Hospital (US)
  • Johns Hopkins University (US)
  • Department of Pediatrics, Children’s Mercy Kansas City, Kansas City, Missouri, USA
Corresponding author
McCulloh, Russell J
Venue
Journal of the American Medical Informatics Association
Published
2018-06-07
Volume
25
Issue
9
Pages
1175-1182
ISSN
  • 1067-5027 (ISSN-L)
  • 1527-974X
OpenAlex
W2806887867
Cited by
36
References
42
Citations by year
2026: 2 · 2024: 2 · 2023: 4 · 2022: 6 · 2021: 8 · 2020: 5 · 2019: 9
FWCI
6.94
Type
journal article
Language
en
Open access
Locations
  • Journal of the American Medical Informatics Association (publishedVersion, cc-by-nc)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by-nc)
Funders
Kansas City Area Life Sciences Institute
Topics
  • Health Sciences › Health Professions › Health Information Management › Electronic Health Records Systems
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Clinical practice guidelines implementation
Keywords
electronic clinical decision support, mobile health, mobile application, pediatric sepsis, standardization of practice, evidence-based practice adoption, length of hospital stay, diagnostic testing recommendations, usability, user engagement
MeSH terms
Smartphone, Humans, Infant, Pediatrics, United States, Practice Guidelines as Topic, Sepsis, Guideline Adherence, Decision Support Systems, Clinical, Information Dissemination, Evidence-Based Practice, Mobile Applications

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review