ArticleJournal of the American Medical Informatics Association : JAMIA2020
Using REDCap and Apple ResearchKit to integrate patient questionnaires and clinical decision support into the electronic health record to improve sexually transmitted infection testing in the emergency department.
Article in Journal of the American Medical Informatics Association : JAMIA, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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
6 citing papers in PubMed.
- Designing Survey-Based Mobile Interfaces for Rural Patients With Cancer Using Apple's ResearchKit and CareKit: Usability Study.JMIR formative research · 2024Article
- Impact of risk-based sexually transmitted infection screening in the emergency department.Academic emergency medicine : official journal of the Society for Academic Emergency Medicine · 2022Article
- Leveraging Mobile-Based Sensors for Clinical Research to Obtain Activity and Health Measures for Disease Monitoring, Prevention, and Treatment.Frontiers in digital health · 2022Article
- A Smartphone-Based Technique to Detect Dynamic User Preferences for Tailoring Behavioral Interventions: Observational Utility Study of Ecological Daily Needs Assessment.JMIR mHealth and uHealth · 2020Article
- Towards an effective framework for integrating patient-reported outcomes in electronic health records.Digital healthArticle
- Adapting an Electronic STI Risk Assessment Program for Use in Pediatric Primary Care.Journal of primary care & community healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
Abstract
objectiveAudio-enhanced computer-assisted self-interviews (ACASIs) are useful adjuncts for clinical care but are rarely integrated into the electronic health record (EHR). We created a flexible framework for integrating an ACASIs with clinical decision support (CDS) into the EHR. We used this program to identify adolescents at risk for sexually transmitted infections (STIs) in the emergency department (ED). We provide an overview of the software platform and qualitative user acceptance. MATERIALS AND
methodsWe created an ACASI with a CDS algorithm to identify adolescents in need of STI testing. We offered it to 15- to 21-year-old patients in our ED, regardless of ED complaint. We collected user feedback via the ACASI. These were programmed into REDCap (Research Electronic Data Capture), and an iOS application utilizing Apple ResearchKit generated a tablet compatible representation of the ACASI for patients. A custom software program created an HL7 (Health Level Seven) message containing a summary of responses, CDS recommendations, and STI test orders, which were transmitted to the EHR.
resultsIn the first year, 1788 of 6227 (28.7%) eligible adolescents completed the survey. Technical issues led to decreased use for several months. Patients rated the system favorably, with 1583 of 1787 (88.9%) indicating that they were "somewhat" or "very comfortable" answering questions electronically and 1291 of 1787 (72.2%) preferring this format over face-to-face interviews or paper questionnaires.
conclusionsWe present a novel use for REDCap to combine patient-answered questionnaires and CDS to improve care for adolescents at risk for STIs. Our program was well received and the platform can be used across disparate patients, topics, and information technology infrastructures.
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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.