Publications by authors named "S Gradwohl"
Article Synopsis
- Hospitalization rates for childhood pneumonia show significant variation, and a study aimed to test if a risk-based clinical decision support (CDS) system could help standardize care in pediatric emergency departments.
- The study involved 536 patient encounters, comparing usual care to an EHR-integrated CDS tool that used a pneumonia severity score; results showed no significant difference in inappropriate patient disposition between the two groups.
- While the CDS tool received positive feedback from clinicians, challenges in implementation and low patient enrollment likely hindered its effectiveness in improving decision-making around ED care for pneumonia.
Objectives: To support a pragmatic, electronic health record (EHR)-based randomized controlled trial, we applied user-centered design (UCD) principles, evidence-based risk communication strategies, and interoperable software architecture to design, test, and deploy a prognostic tool for children in emergency departments (EDs) with pneumonia.
Methods: Risk for severe in-hospital outcomes was estimated using a validated ordinal logistic regression model to classify pneumonia severity. To render the results usable for ED clinicians, we created an integrated SMART on Fast Healthcare Interoperability Resources (FHIR) web application built for interoperable use in two pediatric EDs using different EHR vendors: Epic and Cerner.
Wearable Device Health Data Mapping to Open mHealth and FHIR Data Formats.
Stud Health Technol Inform
June 2023
Health data collected by wearables and apps can be useful as part of patient-generated health data (PGHD) or personal health data for medical diagnosis or general health monitoring. Mobile health apps are more and more accepted, generate evidence and might be increasingly used in personal medicine. Data retrieved from wearables and apps are mostly not following a medical data standard and cannot be retrieved from the vendors in a straightforward way.
View Article and Find Full Text PDFBackground: Decision making in the Emergency Department (ED) requires timely identification of clinical information relevant to the complaints. Existing information retrieval solutions for the electronic health record (EHR) focus on patient cohort identification and lack clinical relevancy ranking. We aimed to compare knowledge-based (KB) and unsupervised statistical methods for ranking EHR information by relevancy to a chief complaint of chest or back pain among ED patients.
View Article and Find Full Text PDFObjective: To assess the role of speech recognition (SR) technology in clinicians' documentation workflows by examining use of, experience with and opinions about this technology.
Materials And Methods: We distributed a survey in 2016-2017 to 1731 clinician SR users at two large medical centers in Boston, Massachusetts and Aurora, Colorado. The survey asked about demographic and clinical characteristics, SR use and preferences, perceived accuracy, efficiency, and usability of SR, and overall satisfaction.