User-Centered Design and Implementation of an Interoperable FHIR Application for Pediatric Pneumonia Prognostication in a Randomized Trial.

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. We followed a UCD framework, including problem analysis and user research, conceptual design and early prototyping, user interface development, formative evaluation, and postdeployment summative evaluation. RESULTS: Problem analysis and user research from 39 clinicians and nurses revealed user preferences for risk aversion, accessibility, and timing of risk communication. Early prototyping and iterative design incorporated evidence-based design principles, including numeracy, risk framing, and best-practice visualization techniques. After rigorous unit and end-to-end testing, the application was successfully deployed in both EDs, which facilitated enrollment, randomization, model visualization, data capture, and reporting for trial purposes. CONCLUSION: The successful implementation of a custom application for pneumonia prognosis and clinical trial support in two health systems on different EHRs demonstrates the importance of UCD, adherence to modern clinical data standards, and rigorous testing. Key lessons included the need for understanding users' real-world needs, regular knowledge management, application maintenance, and the recognition that FHIR applications require careful configuration for interoperability.

A clinician survey of using speech recognition for clinical documentation in the electronic health record.

OBJECTIVE: 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. Associations between outcomes (e.g., satisfaction) and factors (e.g., error prevalence) were measured using ordinal logistic regression. RESULTS: Most respondents (65.3%) had used their SR system for under one year. 75.5% of respondents estimated seeing 10 or fewer errors per dictation, but 19.6% estimated half or more of errors were clinically significant. Although 29.4% of respondents did not include SR among their preferred documentation methods, 78.8% were satisfied with SR, and 77.2% agreed that SR improves efficiency. Satisfaction was associated positively with efficiency and negatively with error prevalence and editing time. Respondents were interested in further training about using SR effectively but expressed concerns regarding software reliability, editing and workflow. DISCUSSION: Compared to other documentation methods (e.g., scribes, templates, typing, traditional dictation), SR has emerged as an effective solution, overcoming limitations inherent in other options and potentially improving efficiency while preserving documentation quality. CONCLUSION: While concerns about SR usability and accuracy persist, clinicians expressed positive opinions about its impact on workflow and efficiency. Faster and better approaches are needed for clinical documentation, and SR is likely to play an important role going forward.

Intraoperative awareness risk, anesthetic sensitivity, and anesthetic management for patients with natural red hair: a matched cohort study.

PURPOSE: The red-hair phenotype, which is often produced by mutations in the melanocortin-1 receptor gene, has been associated with an increase in sedative, anesthetic, and analgesic requirements in both animal and human studies. Nevertheless, the clinical implications of this phenomenon in red-haired patients undergoing surgery are currently unknown. METHODS: In a secondary analysis of a prospective trial of intraoperative awareness, red-haired patients were identified and matched with five control patients, and the relative risk for intraoperative awareness was determined. Overall anesthetic management between groups was compared using Hotelling's T(2) statistic. Inhaled anesthetic requirements were compared between cohorts by evaluating the relationship between end-tidal anesthetic concentration and the bispectral index with a linear mixed-effects model. Time to recovery was compared using Kaplan-Meier analysis, and differences in postoperative pain and nausea/vomiting were evaluated with Chi square tests. RESULTS: A cohort of 319 red-haired patients was matched with 1,595 control patients for a sample size of 1,914. There were no significant differences in the relative risk of intraoperative awareness (relative risk = 1.67; 95% confidence interval 0.34 to 8.22), anesthetic management, recovery times, or postoperative pain between red-haired patients and control patients. The relationship between pharmacokinetically stable volatile anesthetic concentrations and bispectral index values differed significantly between red-haired patients and controls (P < 0.001), but without clinical implications. CONCLUSION: There were no demonstrable differences between red-haired patients and controls in response to anesthetic and analgesic agents or in recovery parameters. These findings suggest that perioperative anesthetic and analgesic management should not be altered based on self-reported red-hair phenotype.