Hedges, Mary S.

Abstract Pharmacogenomic (PGx) biomarkers integrated using machine learning can be embedded within the electronic health record (EHR) to provide clinicians with individualized predictions of drug treatment outcomes. Currently, however, drug alerts in the EHR are largely generic (not patient‐specific) and contribute to increased clinician stress and burnout. Improving the usability of PGx alerts is an urgent need. Therefore, this work aimed to identify principles for optimal PGx alert design through a health‐system‐wide, mixed‐methods study. Clinicians representing multiple practices and care settings ( N = 1062) in urban, rural, and underserved regions were invited to complete an electronic survey comparing the usability of three drug alerts for citalopram, as a case study. Alert 1 contained a generic warning of pharmacogenomic effects on citalopram metabolism. Alerts 2 and 3 provided patient‐specific predictions of citalopram efficacy with varying depth of information. Primary outcomes included the System's Usability Scale score (0–100 points) of each alert, the perceived impact of each alert on stress and decision‐making, and clinicians' suggestions for alert improvement. Secondary outcomes included the assessment of alert preference by clinician age, practice type, and geographic setting. Qualitative information was captured to provide context to quantitative information. The final cohort comprised 305 geographically and clinically diverse clinicians. A simplified, individualized alert (Alert 2) was perceived as beneficial for decision‐making and stress compared with a more detailed version (Alert 3) and the generic alert (Alert 1) regardless of age, practice type, or geographic setting. Findings emphasize the need for clinician‐guided design of PGx alerts in the era of digital medicine.

Introduction: This study evaluated patient preference of physician attire both before and after the coronavirus disease 2019 (COVID-19) global pandemic began. The primary outcome was patient preference of physician attire in 2017 compared to 2022 survey cohorts. Methods: An observational cross-sectional study performed at a single-site academic institution in the United States using patient survey materials. In total, 339 patients were included in the study, 161 from 2017 and 178 from 2022. Key Points: There was a statistically significant decrease in patient preference for formal attire in the clinical settings of primary care, hospital, and overall. Male patient preference for formal attire declined in primary care, emergency room, and overall; whereas female patient preference for formal attire declined in the hospital setting. For all genders, the odds ratio was statistically significantly lower in the settings of primary care clinic, hospital, and overall clinical settings. Conclusions: Patient preference for physicians wearing formal attire has decreased significantly since the COVID-19 global pandemic began.

Abstract Background: Home telemonitoring has been shown to reduce 30-day readmissions patients at high risk for return to the hospital. The reason for this remains unclear. The aim of this study was to explore the association of nurse contact with 30-day hospital readmission in these high risk patients. Methods: This study was a subgroup analysis from a prior randomized control comparing home telemonitoring for readmission for 30 days to usual care at discharge. Patients randomized to the home telemonitoring who had vital signs outside a preset range, triggered an alert flag for the monitoring nurse, which generated a contact to the patient. We compared patients who had at least one nurse contact to those who had none to see if the contact reduced the rate of readmissions in patients being monitored. Results: Of 449 patients, 292 (65.0%) received 1 or more telemonitoring flags. Single variable and multivariable logistic regression models exploring the association of flag type with hospital 30-day readmission did not find any statistically significant associations of telemonitoring flags with hospital 30-day readmission (all unadjusted P≥0.13, all adjusted P≥0.18). Conclusion: While post-hospitalization home telemetry has been shown to reduce 30-day readmission, our subset analysis did not show that the nurse contact was the factor that reduced readmission in these patients. Trial registration: ClinicalTrials.gov identifier: NCT02136186, registration date May 12, 2014.

Abstract The pandemic of COVID-19 has presented several diagnostic challenges in both recognition of acute disease and also the temporal presentation of disease convalescence with return to normal activity. We present a case of delayed clinical progression of COVID-19 associated respiratory failure on day 25 after initial symptom onset and, notably, after initial full resolution of symptoms and negative RT-PCR nasopharyngeal testing. The patient’s delayed presentation of exertional dyspnea and the utilization of specific characteristics of chest radiography in confirmation with laboratory cytokine measurement allowed for clinical re-categorization of the patient’s status to active COVID-19 clinical disease and changed acute management. COVID-19 positive patients should be advised to continue to monitor for respiratory deterioration for a greatly extended period of time, even if RT-PCR testing is negative and initial clinical symptoms have resolved. Frontline healthcare workers, including first responders and primary care providers, also need to be aware to monitor for and recognize this delayed presentation.