ArticleJAMA network open2019
Association of an Electronic Health Record Add-on App for Neonatal Bilirubin Management With Physician Efficiency and Care Quality.
Article in JAMA network open, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled 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.
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.
Who cites it
24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 38 citations in OpenAlex.
- Electronic health record adaptation and innovation among healthcare professionals in hospitals: an integrative framework based on a systematic review.BMC health services research · 2026Pooled it
- The influence of electronic health record design on usability and medication safety: systematic review.BMC health services research · 2025Pooled it
- Association of Qualified Clinical Data Registry Clinician Dashboard Engagement With Performance on Quality-of-Care Measures: Cross-Sectional Analysis.Journal of medical Internet research · 2025Article
- The Development and Appraisal of MELD 3.0 in Liver Diseases: Good Things Never Come Easy.Journal of clinical and translational hepatology · 2025Review
- Evaluation of an electronic health record Drug Interaction Customization Editor (DICE).American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists · 2024Article
- Clinical Decision Support Tool to Promote Adoption of New Neonatal Hyperbilirubinemia Guidelines.Applied clinical informatics · 2024Article
- Article
- Early-Term Neonates Demonstrate a Higher Likelihood of Requiring Phototherapy Compared to Those Born Full-Term.Children (Basel, Switzerland) · 2023Article
- Using event logs to observe interactions with electronic health records: an updated scoping review shows increasing use of vendor-derived measures.Journal of the American Medical Informatics Association : JAMIA · 2022Article
- Coordinated use of Health Level 7 standards to support clinical decision support: Case study with shared decision making and drug-drug interactions.International journal of medical informatics · 2022Article
- "Beyond MELD" - Emerging strategies and technologies for improving mortality prediction, organ allocation and outcomes in liver transplantation.Journal of hepatology · 2022Review
- Evaluation in Life Cycle of Information Technology (ELICIT) framework: Supporting the innovation life cycle from business case assessment to summative evaluation.Journal of biomedical informatics · 2022Review
- SMART on FHIR in spine: integrating clinical prediction models into electronic health records for precision medicine at the point of care.The spine journal : official journal of the North American Spine Society · 2021Article
- New Standards for Clinical Decision Support: A Survey of The State of Implementation.Yearbook of medical informatics · 2021Review
- Workflow analysis for design of an electronic health record-based tobacco cessation intervention in community health centers.JAMIA open · 2021Article
- Establishing a multidisciplinary initiative for interoperable electronic health record innovations at an academic medical center.JAMIA open · 2021Article
- Feeling and thinking: can theories of human motivation explain how EHR design impacts clinician burnout?Journal of the American Medical Informatics Association : JAMIA · 2021Article
- Interests and needs of eye care providers in clinical decision support for glaucoma.BMJ open ophthalmology · 2021Article
- The 21st Century Cures Act: A Competitive Apps Market and the Risk of Innovation Blocking.Journal of medical Internet research · 2020Article
- Integrated displays to improve chronic disease management in ambulatory care: A SMART on FHIR application informed by mixed-methods user testing.Journal of the American Medical Informatics Association : JAMIA · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: The usefulness of electronic health record (EHR) systems could be significantly enhanced by innovative, third-party EHR add-on apps. Objective: To evaluate whether an EHR add-on app for neonatal bilirubin management can save clinicians time and improve patient care. Design, Setting, and Participants: This quality improvement study was conducted at the University of Utah Health Well Baby nursery and outpatient clinics and consisted of 4 substudies: (1) time savings were estimated in an experimental task-timing study comparing the time required for physicians to manage newborns' bilirubin levels with and without the add-on app, (2) app use was estimated from app logs, (3) health care use measures and guideline compliance were compared retrospectively before and after the intervention, and (4) clinician-perceived usability was measured through System Usability Scale surveys. The study took place between April 1, 2016, and September 3, 2019. Data analyses were conducted from October 30, 2018, to September 23, 2019. Interventions: At baseline, clinicians used a manual approach to ensure compliance with an evidence-based clinical guideline for neonatal bilirubin management. To facilitate guideline compliance, an EHR add-on app that automatically retrieves, organizes, and visualizes relevant patient data was developed. The app provides patient-specific assessments and recommendations, including the risk of rebound hyperbilirubinemia following phototherapy based on a predictive model. The add-on app was integrated with the University of Utah Health EHR on April 12, 2017. Main Outcomes and Measures: Clinician time savings, app use, health care use measures, guideline-compliant phototherapy ordering, and perceived usability as measured by the System Usability Scale survey. The survey is composed of 10 statements with responses ranging from 1 (strongly disagree) to 5 (strongly agree). The survey results in a single score ranging from 0 to 100, with ratings described as worst imaginable (mean System Usability Scale score, 12.5), awful (20.3), poor (35.7), okay (50.9), good (71.4), excellent (85.5), and best imaginable (90.9). Results: In 2018, the application was used 20 516 times by clinicians for 91.84% of eligible newborns. Use of the app saved 66 seconds for bilirubin management tasks compared with a commonly used tool (95% CI, 53-79 seconds; P < .001). Following the intervention, health care use rates remained stable, while orders for clinically appropriate phototherapy during hospitalization increased for newborns with bilirubin levels above the guideline-recommended threshold (odds ratio, 1.84; 95% CI, 1.16-2.90; P = .009). Surveys indicated excellent usability (System Usability Scale score, 83.90; 95% CI, 81.49-86.31). Conclusions and Relevance: Well-designed EHR add-on apps may save clinicians time and improve patient care. If time-saving apps, such as the bilirubin app, were implemented widely across institutions and care domains, the potential association with improved patient care and clinician efficiency could be significant. The University of Utah Health bilirubin app is being prepared for release into EHR app stores as free-to-use software.
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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.