Effect of Implementing a Commercial Electronic Early Warning System on Outcomes of Hospitalized Patients.

Despite the widespread adoption of early warning systems (EWSs), it is uncertain if their implementation improves patient outcomes. The authors report a pre-post quasi-experimental evaluation of a commercially available EWS on patient outcomes at a 700-bed academic medical center. The EWS risk scores were visible in the electronic medical record by bedside clinicians. The EWS risk scores were also monitored remotely 24/7 by critical care trained nurses who actively contacted bedside nurses when a patient's risk levels increased. The primary outcome was inpatient mortality. Secondary outcomes were rapid response team calls and activation of cardiopulmonary arrest (code-4) response teams. The study team conducted a regression discontinuity analysis adjusting for age, gender, insurance, severity of illness, risk of mortality, and hospital occupancy at admission. The analysis included 53,229 hospitalizations. Adjusted analysis showed no significant change in inpatient mortality, rapid response team call, or code-4 activations after implementing the EWS. This study confirms the continued uncertainty in the effectiveness of EWSs and the need for further rigorous examinations of EWSs.

A potential cost savings analysis of a penicillin de-labeling program.

Introduction: Over 95% of patients documented as penicillin allergic can tolerate a penicillin without a reaction. Inaccurate documentation of penicillin allergy leads to more expensive alternative antibiotic prescriptions and an increased incidence of resistant infections. Objective: To understand the potential drug cost savings of a penicillin de-labeling program to a healthcare system. Methods: We evaluated patient visits with documented penicillin allergy who presented to the pediatric Emergency Department (PED) and 22 associated primary care clinics. Patients were included if they were discharged home with a non-penicillin antibiotic when the first-line treatment for the diagnosis would have been a penicillin. The potential cost savings were the sum of all visit-level cost differences between the non-penicillin prescription(s) and a counterfactual penicillin prescription. To factor in a 95% successful patient de-labeling rate, we repeatedly sampled 95% from the patients with the eligible visits 10,000 times to produce an estimate of the potential cost savings. Results: Over the 8-year period, 2,034 visits by 1,537 patients to the PED and 12,349 visits by 6,073 patients to primary care clinics satisfied eligibility criteria. If 95% of the patients could have been successfully de-labeled, it would have generated a cost saving of $618,653 (95% CI $618,617-$618,689) for all the corresponding payers in the system. Conclusions: Implementing a penicillin de-labeling program across a healthcare system PED and its associated primary care clinics would bring significant cost savings. Healthcare systems should rigorously evaluate optimal methods to de-label patients with reported penicillin allergy.

Association Between COVID-19 and Delirium Development in the General Medical Units at an Academic Medical Center.

INTRODUCTION: Evidence suggests that inpatients who develop delirium experience worse outcomes. Although there is reason to believe that COVID-positive patients may be at a higher risk for developing delirium, little is known about the association between COVID-19 and delirium among hospitalized patients outside the intensive care unit (ICU). This study aimed to examine (1) the independent association between COVID-19 infection and the development of delirium among all non-ICU patients and (2) the risk factors associated with developing delirium among patients admitted with COVID-19, with a special focus on presenting symptoms. METHODS: Using electronic health record (EHR) data of adults admitted to any general medical unit at a large academic medical center from July 2020 through February 2021, we used a cross-sectional multivariable logistic regression to estimate the associations, while adjusting for patients' sociodemographic, clinical characteristics, delirium-free length of stay, as well as time fixed effects. RESULTS: Multivariable regression estimates applied to 20 509 patients hospitalized during the study period indicate that COVID-19-positive patients had 72% higher relative risk (odds ratio 1.72; 95% CI, 1.31 - 2.26; P < 0.001) of developing delirium than the COVID-19-negative patients. However, among the subset of patients admitted with COVID-19, having any COVID-19-specific symptoms was not associated with elevated odds of developing delirium compared to those who were asymptomatic, after controlling for potential confounders. CONCLUSIONS: COVID-19 positivity was associated with higher odds of developing delirium among patients during their non-ICU hospitalization. These findings may be helpful in targeting the use of delirium prevention strategies among non-ICU patients.

Hospitalization Outcomes Among Patients With COVID-19 Undergoing Remote Monitoring.

Importance: Health care systems have implemented remote patient monitoring (RPM) programs to manage patients with COVID-19 at home, but the associations between participation and outcomes or resource utilization are unclear. Objective: To assess whether an RPM program for COVID-19 is associated with lower or higher likelihood of hospitalization and whether patients who are admitted present earlier or later for hospital care. Design, Setting, and Participants: This retrospective, observational, cohort study of RPM was performed at Froedtert & Medical College of Wisconsin Health Network, an academic health system in southeastern Wisconsin. Participants included patients with internal primary care physicians and a positive SARS-CoV-2 test in the ambulatory setting between March 30, 2020, and December 15, 2020. Data analysis was performed from February 15, 2021, to February 2, 2022. Exposures: Activation of RPM program. Main Outcomes and Measures: Hospitalizations within 2 to 14 days of a positive test. Inverse propensity score weighting was used to account for differences between groups. Sensitivity analyses were performed looking at usage of the RPM among patients who activated the program. Results: A total of 10 660 COVID-19-positive ambulatory patients were eligible, and 9378 (88.0%) had email or mobile numbers on file and were invited into the RPM program; the mean (SD) age was 46.9 (16.3) years and 5448 patients (58.1%) were women. Patients who activated monitoring (5364 patients [57.2%]) had a mean (SD) of 35.3 (33.0) check-ins and a mean (SD) of 1.27 (2.79) (median [IQR], 0 [0-1]) free-text comments. A total of 878 patients (16.4%) experienced at least 1 alert; 128 of 5364 activated patients (2.4%) and 158 of 4014 inactivated patients (3.9%) were hospitalized (χ21 = 18.65; P < .001). In weighted regression analysis, activation of RPM was associated with a lower odds of hospitalization (odds ratio, 0.68; 95% CI, 0.54-0.86; P = .001) adjusted for demographics, comorbidities, and time period. Monitored patients had a longer mean (SD) time between test and hospitalization (6.67 [3.21] days vs 5.24 [3.03] days), a shorter length of stay (4.44 [4.43] days vs 7.14 [8.63] days), and less intensive care use (15 patients [0.3%] vs 44 patients [1.1%]). Conclusions and Relevance: These findings suggest that activation of an RPM program is associated with lower hospitalization, intensive care use, and length of stay among patients with COVID-19.

Analysis of Clinician and Patient Factors and Completion of Telemedicine Appointments Using Video.

Importance: Telemedicine provides patients access to episodic and longitudinal care. Policy discussions surrounding future support for telemedicine require an understanding of factors associated with successful video visits. Objective: To assess patient and clinician factors associated with successful and with failed video visits. Design, Setting, and Participants: This was a quality improvement study of 137 846 scheduled video visits at a single academic health system in southeastern Wisconsin between March 1 and December 31, 2020, supplemented with patient experience survey data. Patient information was gathered using demographic information abstracted from the electronic health record and linked with block-level socioeconomic data from the US Census Bureau. Data on perceived clinician experience with technology was obtained using the survey. Main Outcomes and Measures: The primary outcome of interest was the successful completion of a scheduled video visit or the conversion of the video visit to a telephone-based service. Visit types and administrative data were used to categorize visits. Mixed-effects modeling with pseudo R2 values was performed to compare the relative associations of patient and clinician factors with video visit failures. Results: In total, 75 947 patients and 1155 clinicians participated in 137 846 scheduled video encounters, 17 190 patients (23%) were 65 years or older, and 61 223 (81%) patients were of White race and ethnicity. Of the scheduled video encounters, 123 473 (90%) were successful, and 14 373 (10%) were converted to telephone services. A total of 16 776 patients (22%) completed a patient experience survey. Lower clinician comfort with technology (odds ratio [OR], 0.15; 95% CI, 0.08-0.28), advanced patient age (66-80 years: OR, 0.28; 95% CI, 0.26-0.30), lower patient socioeconomic status (including low high-speed internet availability) (OR, 0.85; 95% CI, 0.77-0.92), and patient racial and ethnic minority group status (Black or African American: OR, 0.75; 95% CI, 0.69-0.81) were associated with conversion to telephone visits. Patient characteristics accounted for systematic components for success; marginal pseudo R2 values decreased from 23% (95% CI, 21.1%-26.1%) to 7.8% (95% CI, 6.3%-9.4%) with exclusion of patient factors. Conclusions and Relevance: As policy makers consider expanding telehealth coverage and hospital systems focus on investments, consideration of patient support, equity, and friction should guide decisions. In particular, this quality improvement study suggests that underserved patients may become disproportionately vulnerable by cuts in coverage for telephone-based services.