Ambulances Required to Relieve Overcapacity Hospitals: A Novel Measure of Hospital Strain During the COVID-19 Pandemic in the United States.

STUDY OBJECTIVE: One in 4 deaths from COVID-19 has been attributed to hospital crowding. We simulated how many ambulances would be required to rebalance hospital load through systematic interhospital transfers. We assessed the potential feasibility of such a strategy and explored whether transfer requirement was a helpful measure and visualization of regional hospital crowding during COVID-19 surges. METHODS: Using data from the United States hospitals reporting occupancy to the Department of Health and Human Services from July 2020 to March 2022 and road network driving times, we estimated the number of ambulances required weekly to relieve overcapacity hospitals. RESULTS: During the peak week, which ended on January 8, 2021, approximately 1,563 ambulances would be needed for 15,389 simulated patient transports, of which 6,530 (42%) transports involved a 1-way driving time of more than 3 hours. Transfer demands were dramatically lower during most other weeks, with the median week requiring only 134 ambulances (interquartile range, 84 to 295) and involving only 116 transports with 1-way driving times above 3 hours (interquartile range, 4 to 548). On average, receiving hospitals were larger and located in more rural areas than sending hospitals. CONCLUSION: This simulation demonstrated that for most weeks during the pandemic, ambulance availability and bed capacity were unlikely to have been the main impediments to rebalancing hospital loads. Our metric provided an immediately available and much more complete measure of hospital system strain than counts of hospital admissions alone.

E-scooter related injuries: Using natural language processing to rapidly search 36 million medical notes.

BACKGROUND: Shareable e-scooters have become popular, but injuries to riders and bystanders have not been well characterized. The goal of this study was to describe e-scooter injuries and estimate the rate of injury per e-scooter trip. METHODS AND FINDINGS: Retrospective review of patients presenting to 180 clinics and 2 hospitals in greater Los Angeles between January 1, 2014 and May 14, 2020. Injuries were identified using a natural language processing (NLP) algorithm not previously used to identify injuries, tallied, and described along with required healthcare resources. We combine these tallies with municipal data on scooter use to report a monthly utilization-corrected rate of e-scooter injuries. We searched 36 million clinical notes. Our NLP algorithm correctly classified 92% of notes in the testing set compared with the gold standard of investigator review. In total, we identified 1,354 people injured by e-scooters; 30% were seen in more than one clinical setting (e.g., emergency department and a follow-up outpatient visit), 29% required advanced imaging, 6% required inpatient admission, and 2 died. We estimate 115 injuries per million e-scooter trips were treated in our health system. CONCLUSIONS: Our observed e-scooter injury rate is likely an underestimate, but is similar to that previously reported for motorcycles. However, the comparative severity of injuries is unknown. Our methodology may prove useful to study other clinical conditions not identifiable by existing diagnostic systems.

Quantifying Emergency Physician Interruptions due to Electrocardiogram Review.

BACKGROUND: Interruptions are recognized as potentially harmful to safety and efficiency, and are especially prevalent in the emergency department (ED) setting. Policies urging immediate review of all electrocardiograms (ECGs) may lead to numerous and frequent interruptions. OBJECTIVE: We assessed the role of ECG review as a source of ED interruptions to characterize a potential target for interventions. METHODS: We analyzed emergency physician time use during the course of a clinical shift using a time-and-motion design. A research assistant observed a convenience sample of shifts, observing and logging transitions between different tasks using an electronic device. Instances of ECG review were tallied, with start and ending times of ECG review recorded to the nearest second. An ECG review was considered an interruption if the immediate prior and subsequent tasks were the same. RESULTS: Twenty shifts were observed for a total of 149 h. There were 211 ECG reviews, (mean rate 1.4 per hour), with more frequent review among physicians staffing a zone with higher-acuity patients (2.8 per hour), where clustering of multiple ECG reviews in succession was more common. Seventy-five percent of ECG reviews required < 30 s. Of all 211 ECG reviews, 102 (48%) were an interruption. The tasks most frequently interrupted were electronic medical record system use (68 of 102, 67%) and communicating with ED staff in person (18 of 102, 18%). CONCLUSIONS: Review of ECGs was a substantial driver of interruptions for emergency physicians. Interventions to integrate ECG review more naturally into physician workflow may improve patient safety by reducing these interruptions.

Not all HEART scores are created equal: identifying "low-risk" patients at higher risk.

OBJECTIVE: We sought to identify sub-groups of "low-risk" HEART score patients (history, ECG, age, risk factors, and troponin) at elevated risk of acute myocardial infarction or death within 30 days. METHODS: We performed a secondary analysis of prospective emergency department (ED) encounters for suspected acute coronary syndrome in a large health system with low-risk HEART scores (0-5 points). Logistic regression using the 5 components of the HEART score analyzed the increase risk attributable to points from each of the 5 score components. RESULTS: Of 30,971 encounters among 28,992 unique patients, 135 (0.44%, 95% confidence interval [CI] = 0.37-0.51) experienced acute myocardial infarction or death. Risk increased for each component of the HEART score from 0 to 1 to 2 points (history, 0.4% to 0.5% to 0.6%; ECG, 0.3% to 0.7% to 0.7%; age, 0.2% to 0.3% to 0.7%; risk factors, 0.1% to 0.4% to 0.8%), except troponin, which had the highest risk with 1 point (troponin, 0.4% to 2.7% to 0.9%). Odds ratios from our regression, which adjusts for other components, showed a similar pattern (from 1 vs 0 and 2 vs 0 points, respectively: history, 1.0 and 1.8; ECG, 2.2 and 3.5; age, 1.2 and 2.1; risk factors, 2.4 and 4.2; and troponin, 6.0 and 3.6). CONCLUSION: Among "low-risk" suspected acute coronary syndrome encounters, increasing points within each of the 5 categories demonstrated small increases in risk of death or acute myocardial infarction, with the troponin and ECG components representing the largest risk increases.

Impact of a Direct Bedding Initiative on Left Without Being Seen Rates.

BACKGROUND: Left without being seen (LWBS) rates have become a key metric of emergency department (ED) flow, and high rates have been associated with poor patient outcomes, especially at busy urban, academic hospitals. OBJECTIVE: To assess a triage intervention's impact on LWBS rates among Emergency Severity Index (ESI) level 2 patients especially at risk for adverse outcomes. METHODS: We conducted a retrospective review at an urban academic center of LWBS rates prior to and after a "direct bedding" intervention, which directed patients triaged to ESI level 2 to be immediately placed in any available ED area, including those typically reserved for lower-acuity complaints. Our primary analysis employs an adjusted difference-in-difference-in-difference (DDD) approach using controls from the previous year and a nearby affiliate community hospital that did not participate in the intervention. RESULTS: Mean daily patient volume increased from 275 to 298 arrivals after the intervention. In the primary DDD analysis, odds of LWBS were lower after the intervention (adjusted odds ratio [OR] 0.56, 95% confidence interval [CI] 0.45-0.70, p < 0.001). LWBS was higher in the unadjusted analysis (unadjusted OR 1.39, 95% CI 1.31-1.49, p < 0.001), but still lower among ESI 1 or 2 patients targeted by the intervention (unadjusted OR 0.56, 95% CI 0.43-0.74, p < 0.001). CONCLUSIONS: "Direct bedding" of ESI 2 patients may expedite care for the sickest patients, reducing potential harm to patients who might otherwise LWBS, without compromising care for patients triaged to less acute ESI levels.

Measuring Emergency Care Survival: The Implications of Risk Adjusting for Race and Poverty.

OBJECTIVES: We determined the impact of including race, ethnicity, and poverty in risk adjustment models for emergency care-sensitive conditions mortality that could be used for hospital pay-for-performance initiatives. We hypothesized that adjusting for race, ethnicity, and poverty would bolster rankings for hospitals that cared for a disproportionate share of nonwhite, Hispanic, or poor patients. METHODS: We performed a cross-sectional analysis of patients admitted from the emergency department to 157 hospitals in Pennsylvania with trauma, sepsis, stroke, cardiac arrest, and ST-elevation myocardial infarction. We used multivariable logistic regression models to predict in-hospital mortality. We determined the predictive accuracy of adding patient race and ethnicity (dichotomized as non-Hispanic white vs. all other Hispanic or nonwhite patients) and poverty (uninsured, on Medicaid, or lowest income quartile zip code vs. all others) to other patient-level covariates. We then ranked each hospital on observed-to-expected mortality, with and without race, ethnicity, and poverty in the model, and examined characteristics of hospitals with large changes between models. RESULTS: The overall mortality rate among 170,750 inpatients was 6.9%. Mortality was significantly higher for nonwhite and Hispanic patients (adjusted odds ratio [aOR] = 1.27, 95% confidence interval [CI] = 1.19-1.36) and poor patients (aOR = 1.21, 95% CI = 1.12-1.31). Adding race, ethnicity, and poverty to the risk adjustment model resulted in a small increase in C-statistic (0.8260 to 0.8265, p = 0.002). No hospitals moved into or out of the highest-performing decile when adjustment for race, ethnicity, and poverty was added, but the three hospitals that moved out of the lowest-performing decile, relative to other hospitals, had significantly more nonwhite and Hispanic patients (68% vs. 11%, p < 0.001) and poor patients (56% vs. 10%, p < 0.001). CONCLUSIONS: Sociodemographic risk adjustment of emergency care-sensitive mortality improves apparent performance of some hospitals treating a large number of nonwhite, Hispanic, or poor patients. This may help these hospitals avoid financial penalties in pay-for-performance programs.

The educational value of emergency department teaching: it is about time.

There is a paucity of research on the quality and quantity of clinical teaching in the emergency department (ED) setting. While many factors impact residents' perceptions of attending physicians' educational skill, the authors hypothesized that the amount of time residents spend with attending in direct teaching is a determinant of residents' perception of their shift's educational value. Researchers shadowed emergency medicine (EM) attendings during ED shifts, and recorded teaching time with each resident. Residents were surveyed on their assessment of the educational value (EV) of the shift and potential confounders, as well as the attending physician's teaching quality using the ER Scale. The study was performed in the EDs of two urban teaching hospitals affiliated with an EM residency program. Subjects were EM residents and rotators from other specialties. The main outcome measure was the regression of impact of teaching time on EV. Researchers observed 20 attendings supervising 47 residents (mean 2.35 residents per attending, range 2-3). The correlation between teaching time in minutes (mean 60.8, st.dev 25.6, range 7.6-128.1) and EV (mean 3.45 out of 5, st. dev 0.75, range 2-5) was significant (r = 0.302, r 2 = 0.091, p < 0.05). No confounders had a significant effect. The study shows a moderate correlation between the total time attendings spend directly teaching residents and the residents' perception of educational value over a single ED shift. The authors suggest that mechanisms to increase the time attending physicians spend teaching during clinical shifts may result in improved resident education.

Patterns of HIV Treatment Adherence do not Differ Between Male and Female Adolescents in Botswana.

We hypothesized that longer and more frequent dosing gaps among boys in Botswana taking antiretroviral therapy (ART) for human immunodeficiency virus (HIV) infection compared to girls could account for previously seen gender-specific differences in outcomes. We monitored 154 male and 134 female adolescents for 2 years with medication event monitoring systems (MEMS). Median adherence was 95.6 % for males and 95.7 % for females (p = 0.40). There were no significant gender differences in the number of ≥7 day (p = 0.55) and ≥14 day (p = 0.48) dosing gaps. The median maximal gap was 7.7 days for males and 8.0 days for females (p = 0.47). These findings are not consistent with clinically meaningful gender differences in adherence.