Does What Happens in the ED Stay in the ED? The Effects of Emergency Department Physician Workload on Post-ED Care Use

PROBLEM DEFINITION

Emergency department (ED) crowding has been a pressing concern in healthcare systems in the U.S. and other developed countries. As such, many researchers have studied its effects on outcomes within the ED. In contrast, we study the effects of ED crowding on system performance outside the ED-specifically, on post-ED care utilization. Further, we explore the mediating effects of care intensity in the ED on post-ED care use.

METHODOLOGY/RESULTS

We utilize a dataset assembled from more than four years of microdata from a large U.S. hospital and exhaustive billing data in an integrated health system. By using count models and instrumental variable analyses to answer the proposed research questions, we find that there is an increasing concave relationship between ED physician workload and post-ED care use. When ED workload increases from its 5th percentile to the median, the number of post-discharge care events (i.e., medical services) for patients who are discharged home from the ED increases by 5% and it is stable afterwards. Further, we identify physician test-ordering behavior as a mechanism for this effect: when the physician is busier, she responds by ordering more tests for less severe patients. We document that this "extra" testing generates "extra" post-ED care utilization for these patients.

MANAGERIAL IMPLICATIONS

This paper contributes new insights on how physician and patient behaviors under ED crowding impact a previously unstudied system performance measure: post-ED care utilization. Our findings suggest that prior studies estimating the cost of ED crowding underestimate the true effect, as they do not consider the "extra" post-ED care utilization.

Comparing emergency department use among individuals with varying levels of cognitive impairment

INTRODUCTION

As the population ages, Alzheimer's disease and related dementias (ADRD) are becoming increasingly common in patients presenting to the emergency department (ED). This study compares the frequency of ED use among a cohort of individuals with well-defined cognitive performance (cognitively intact, mild cognitive impairment (MCI), and ADRD).

METHODS

We performed a retrospective cohort study of English-speaking, community-dwelling individuals evaluated at four health system-based multidisciplinary memory clinics from 2014-2016. We obtained demographic and clinical data, including neuropsychological testing results, through chart review and linkage to electronic health record data. We characterized the frequency and quantity of ED use within one year (6 months before and after) of cognitive evaluation and compared ED use between the three groups using bivariate and multivariate approaches.

RESULTS

Of the 779 eligible patients, 89 were diagnosed as cognitively intact, 372 as MCI, and 318 as ADRD. The proportion of subjects with any annual ED use did not increase significantly with greater cognitive impairment: cognitively intact (16.9%), MCI (26.1%), and ADRD (28.9%) (p = 0.072). Average number of ED visits increased similarly: cognitively intact (0.27, SD 0.72), MCI (0.41, SD 0.91), and ADRD (0.55, SD 1.25) (p = 0.059). Multivariate logistic regression results showed that patients with MCI (odds ratio (OR) 1.62; CI = 0.87-3.00) and ADRD (OR 1.84; CI = 0.98-3.46) did not significantly differ from cognitively intact adults in any ED use. Multivariate negative binomial regression found patients with MCI (incidence rate ratio (IRR) 1.38; CI = 0.79-2.41) and ADRD (IRR 1.76, CI = 1.00-3.10) had elevated but non-significant risk of an ED visit compared to cognitively intact individuals.

CONCLUSION

Though there was no significant difference in ED use in this small sample from one health system, our estimates are comparable to other published work. Results suggested a trend towards higher utilization among adults with MCI or ADRD compared to those who were cognitively intact. We must confirm our findings in other settings to better understand how to optimize systems of acute illness care for individuals with MCI and ADRD.

Maggots, Mucous and Monkey Meat: Does Disgust Sensitivity Affect Case Mix Seen During Residency?

Introduction

Emergency physicians encounter scenarios daily that many would consider “disgusting,” including exposure to blood, pus, and stool. Physicians in procedural specialties such as surgery and emergency medicine (EM) have lower disgust sensitivity overall, but the role this plays in clinical practice is unclear. The objective of this study was to determine whether emergency physicians with higher disgust sensitivity see fewer “disgusting” cases during training.

Methods

All EM residents at a midsize urban EM program were eligible to complete the Disgust Scale Revised (DS-R). We preidentified cases as “disgust elicitors” based on diagnoses likely to induce disgust due to physician exposure to bodily fluids, anogenital anatomy, or gross deformity. The “disgust elicitor” case percent was determined by “disgust elicitor” cases seen as the primary resident divided by the number of cases seen thus far in residency. We calculated Pearson’s r, t-tests and descriptive statistics on resident and population DS-R scores and “disgust elicitor” cases per month.

Results

Mean DS-R for EM residents (n = 40) was 1.20 (standard deviation [SD] 1.24), significantly less than the population mean of 1.67 (SD 0.61, p<0.05). There was no correlation (r = −0.04) between “disgust elicitor” case (n = 2191) percent and DS-R scores. There was no significant difference between DS-R scores for junior residents (31.1, 95% confidence interval [CI], 26.8–35.4) and for senior residents (29.0, 95%CI, 23.4–34.6).

Conclusion

Higher disgust sensitivity does not appear to be correlated with a lower percentage of “disgust elicitor” cases seen during EM residency.

The Effects of Discrete Work Shifts on a Nonterminating Service System

Hospital emergency departments (EDs) provide around-the-clock medical care, and as such are generally modeled as nonterminating queues. However, from the care provider's point of view, ED care is not a never-ending process, but rather occurs in discrete work shifts and may require passing unfinished work to the next care provider at the end of the shift. We use data from a large, academic medical center ED to show that the patients' rate of service completion varies over the course of the physician shift. Further, patients that have experienced a physician handoff have a higher rate of service completion than non-handed off patients. As a result, a patient's expected treatment time is impacted by when in the physician's shift treatment begins. We also show that patients that have been handed off are more likely to revisit the ED within three days, suggesting that patient handoffs lower clinical quality. Lastly, we use simulation to show that shift length and new-patient cutoff rules can be used to reduce handoffs, but at the expense of system throughput.

Using the Hendrich II Inpatient Fall Risk Screen to Predict Outpatient Falls After Emergency Department Visits

OBJECTIVES

To evaluate the utility of routinely collected Hendrich II fall scores in predicting returns to the emergency department (ED) for falls within 6 months.

DESIGN

Retrospective electronic record review.

SETTING

Academic medical center ED.

PARTICIPANTS

Individuals aged 65 and older seen in the ED from January 1, 2013, through September 30, 2015.

MEASUREMENTS

We evaluated the utility of routinely collected Hendrich II fall risk scores in predicting ED visits for a fall within 6 months of an all-cause index ED visit.

RESULTS

For in-network patient visits resulting in discharge with a completed Hendrich II score (N = 4,366), the return rate for a fall within 6 months was 8.3%. When applying the score alone to predict revisit for falls among the study population the resultant receiver operating characteristic (ROC) plot had an area under the curve (AUC) of 0.64. In a univariate model, the odds of returning to the ED for a fall in 6 months were 1.23 times as high for every 1-point increase in Hendrich II score (odds ratio (OR)=1.23 (95% confidence interval (CI)=1.19-1.28). When included in a model with other potential confounders or predictors of falls, the Hendrich II score is a significant predictor of a return ED visit for fall (adjusted OR=1.15, 95% CI=1.10-1.20, AUC=0.75).

CONCLUSION

Routinely collected Hendrich II scores were correlated with outpatient falls, but it is likely that they would have little utility as a stand-alone fall risk screen. When combined with easily extractable covariates, the screen performs much better. These results highlight the potential for secondary use of electronic health record data for risk stratification of individuals in the ED. Using data already routinely collected, individuals at high risk of falls after discharge could be identified for referral without requiring additional screening resources.

The Impact of Emergency Department Census on the Decision to Admit

OBJECTIVE

We evaluated the effect of emergency department (ED) census on disposition decisions made by ED physicians.

METHODS

We performed a retrospective analysis using 18 months of all adult patient encounters seen in the main ED at an academic tertiary care center. Patient census information was calculated at the time of physician assignment for each individual patient and included the number of patients in the waiting room (waiting room census) and number of patients being managed by the patient's attending (physician load census). A multiple logistic regression model was created to assess the association between these census variables and the disposition decision, controlling for potential confounders including Emergency Severity Index acuity, patient demographics, arrival hour, arrival mode, and chief complaint.

RESULTS

A total of 49,487 patient visits were included in this analysis, of whom 37% were admitted to the hospital. Both census measures were significantly associated with increased chance of admission; the odds ratio (OR) per patient increase for waiting room census was 1.011 (95% confidence interval [CI] = 1.001 to 1.020), and the OR for physician load census was 1.010 (95% CI = 1.002 to 1.019). To put this in practical terms, this translated to a modeled rise from 35.3% to 40.1% when shifting from an empty waiting room and zero patient load to a 12-patient wait and 16-patient load for a given physician.

CONCLUSION

Waiting room census and physician load census at time of physician assignment were positively associated with the likelihood that a patient would be admitted, controlling for potential confounders. Our data suggest that disposition decisions in the ED are influenced not only by objective measures of a patient's disease state, but also by workflow-related concerns.

Cherry Picking Patients: Examining the Interval Between Patient Rooming and Resident Self-assignment

OBJECTIVE

We aimed to evaluate the association between patient chief complaint and the time interval between patient rooming and resident physician self-assignment ("pickup time"). We hypothesized that significant variation in pickup time would exist based on chief complaint, thereby uncovering resident preferences in patient presentations.

METHODS

A retrospective medical record review was performed on consecutive patients at a single, academic, university-based emergency department with over 50,000 visits per year. All patients who presented from August 1, 2012, to July 31, 2013, and were initially seen by a resident were included in the analysis. Patients were excluded if not seen primarily by a resident or if registered with a chief complaint associated with trauma team activation. Data were abstracted from the electronic health record (EHR). The outcome measured was "pickup time," defined as the time interval between room assignment and resident self-assignment. We examined all complaints with >100 visits, with the remaining complaints included in the model in an "other" category. A proportional hazards model was created to control for the following prespecified demographic and clinical factors: age, race, sex, arrival mode, admission vital signs, Emergency Severity Index code, waiting room time before rooming, and waiting room census at time of rooming.

RESULTS

Of the 30,382 patients eligible for the study, the median time to pickup was 6 minutes (interquartile range = 2-15 minutes). After controlling for the above factors, we found systematic and significant variation in the pickup time by chief complaint, with the longest times for patients with complaints of abdominal problems, numbness/tingling, and vaginal bleeding and shortest times for patients with ankle injury, allergic reaction, and wrist injury.

CONCLUSIONS

A consistent variation in resident pickup time exists for common chief complaints. We suspect that this reflects residents preferentially choosing patients with simpler workups and less perceived diagnostic ambiguity. This work introduces pickup time as a metric that may be useful in the future to uncover and address potential physician bias. Further work is necessary to establish whether practice patterns in this study are carried beyond residency and persist among attendings in the community and how these patterns are shaped by the information presented via the EHR.

A photoelectric technique for the study of adsorption: the aluminum-oxygen and aluminum-water systems

Gas adsorption on clean metal surfaces may be studied by observing the change in work function of the surface as adsorption proceeds. A photoelectric technique for following these changes by measuring the photocurrent excited by two spectral lines is developed, and a graphical method of analysis of the results is given. This method has the advantage of being much quicker than other photoelectric techniques such as the determination of the retarding-potential characteristic, and may thus be applied to the study of more rapid adsorption processes. As examples of its use, the method has been applied to a study of the adsorption of oxygen and water vapor on films of aluminum evaporated under conditions of ultrahigh vacuum. The work function of the clean aluminum films was 4.27 eV. For small oxygen exposures (up to about 10(18) molecules cm(-2)) the work function of the contaminated aluminum decreased by about 0.05 eV; for larger exposures (up to about 10(20) molecules cm(-2)) the work function increased by about 0.05 eV. Water vapor adsorption causes a reduction in the work function by more than 1 eV for an exposure of about 10(19) molecules cm(-2).