Carley A. Maak, MD

To determine pneumonia admission care components that are most affected by emergency department (ED) crowding.

 Secondary analysis of a crosssectional observational survey.

 The setting was a 29-bed academic ED with 39,000 visits per year and state-mandated ratios of nurses to patients. The patients were ED admissions with pneumonia, January 1, 2004, to June 30, 2005. From ED medical records and databases, we abstracted the times of arrival, room placement, ordering of chest radiograph and when obtained, ordering of blood culture and when obtained, and ordering of antibiotic and when administered. We assessed associations between ED volume at the time of arrival of a patient with pneumonia and component durations using multivariate linear regression.

 For 407 ED admissions with pneumonia, the median component durations (in minutes) were as follows: 20 for arrival to room placement, 44 for arrival to chest radiograph order, 10 for chest radiograph order to radiograph obtained, 120 for room placement to antibiotic order, 10 for blood culture order to culture obtained, 30 for antibiotic order to antibiotic administered, and 195 for arrival to antibiotic administered. Sixtyone percent of patients received antibiotic within 4 hours. We estimate that for every 10 additional ED patients the time from arrival to ordering of a chest radiograph was prolonged by 14.3 minutes and from ordering of antibiotic to administration by 9.3 minutes.

Despite compliance with mandated ratios of nurses to patients, the time from antibiotic ordering to administration (a nursing task) was prolonged with higher ED volumes, as were throughput measures. Targeting these may expedite treatment under crowded ED conditions.

	Multivariate analyses associated increased emergency department (ED) volume with delayed nursing-dependent care for patients with pneumonia (time from antibiotic  ordering to administration), despite compliance with required ratios of nurses to patients.

		In our academic ED with strict ratios of nurses to patients, the time from antibiotic ordering to administration (which reflects ED nursing workload) was prolonged in association with increased ED volume.

		If these findings are reproduced in other settings, EDs may want to focus on nursing processes to find ways to maintain performance during periods of high ED volume, in addition to looking at measures to decrease ED crowding.

	Emergency department (ED) crowding delays the time to first antibiotic dose for patients admitted with communityacquired pneumonia.

 Pneumonia was one of the initial areas identified by The Joint Commission (TJC) and the Centers for Medicaid and Medicare Services (CMS) as a hospital core measure for quality care. In 2002, TJC and CMS established a target of time to first antibiotic dose within 4 hours of hospital arrival (changed to 6 hours in April 2007) for this publicly reported benchmark and have indicated that hospital and individual physician funding may someday depend on performance on this and other core measures.

 Hospitals and physicians attempting to improve performance need to direct limited resources to aspects of care requiring improvement, without sacrificing care provided to others or disrupting processes that work well. It is likely that determining which   admission care components are most affected by increasing volume will provide insight into areas for improvement for the care of all ED patients, not just those with pneumonia.

	Emergency departments are closely scrutinized for their ability to meet the target to first antibiotic dose, yet the effect of ED volume is just beginning to be recognized.

 If a connection between ED volume and particular care components can be established, specific processes could be targeted for quality improvement efforts, without requiring a large influx of resources. This is critical as EDs become increasingly responsible for more time-sensitive interventions (ie, those for patients with trauma, sepsis, stroke, and acute coronary syndrome) and as healthcare dollars shrink. The objective of this investigation was to determine care components provided to patients with pneumonia who were admitted through the ED that were most affected by increasing ED patient volume.

	This is a secondary analysis of a cross-sectional observational survey of patients admitted through a university tertiary care hospital ED and discharged between January 1, 2004, and June 30, 2005, after an inpatient hospitalization for pneumonia.

 We determined the effect of concurrent ED volume on the duration of care components provided to patients admitted with pneumonia. The study was approved by the committee on human research at our institution.

	Our 29-bed academic ED has an annual census of 39,000 and is staffed by emergency medicine, internal medicine, pediatric, and psychiatry residents, as well as nurse  practitioners and physician assistants. Patients are seen according to triage acuity. Patient care is supervised 24 hours a day by board-eligible and board-certified emergency physicians. Our ED adheres to a strict ratio of nurses to patients (1:4) as mandated by state law. Dedicated ED radiology technicians are present 24 hours per day. Emergency department triage and physician notes are electronically documented (File-Maker Pro, version 7; FileMaker, Inc, Santa Clara, California). Emergency department orders and nursing notes are handwritten. Physicians and clerical staff notify ED nurses of pending orders by posting an icon on the electronic patient tracking board (GE Centricity; GE Healthcare UK Ltd, Buckinghamshire, England) or by calling with portable phones. These handwritten orders and nursing notes are electronically scanned and stored after the ED visit and are accessible for quality assurance and research.

	As part of ongoing quality assurance and TJC/CMS core measure reporting at our institution, an outside vendor (University HealthSystem Consortium, Oak Brook, Illinois) (UHC) reviews medical records of inpatients eligible for TJC/ CMS core measure PN-5b4 (as detailed in a prior study1). The UHC reviewed medical records of all patients meeting

	the eligibility criteria from January 1, 2004, through December 31, 2004, in accord with TJC/CMS reporting requirements. Thereafter, the TJC/CMS reporting requirements were revised, and UHC selected a random sample of 75 patients per calendar quarter using a computerized random number generator (SAS version 9.1; SAS Institute Inc, Cary, North Carolina). The UHC excluded patients in accord with TJC/CMS core measure PN-5b exclusion criteria

). Medical records of all remaining patients were reviewed by UHC for antibiotic timing, and the results were reported to our institution. From this group of patients, we selected those admitted through the ED. Analyses were restricted to patients with available data on the time of antibiotic administration.

	Collected from administrative databases were patient demographic and presenting characteristics (age, sex, race/ ethnicity, and mode of arrival [self or ambulance]), triage acuity (1-4, where 1 is emergent), and level of care to which the patient was admitted (intensive care unit or not).

 Using a structured data collection form, we reviewed each patient’s ED medical record to obtain the following: date and time of ED presentation (from the ED triage notes), time of room placement (from the ED nursing notes), time when a chest radiograph was ordered (from the ED orders) and obtained (from the radiology records), time when a blood culture was ordered (from the ED orders) and obtained (from the ED  nursing notes), and time when an antibiotic was ordered (from the ED orders) and administered (from the ED nursing notes). For patients with missing or illegible scanned data, we made 3 attempts to obtain the archived paper medical record before reporting the data as unavailable. All data abstraction was performed by 2 of us (CF and CAM), who were not blinded to the study hypothesis but were blinded to ED volume data.

	An ED database permits calculation of the hourly ED census on any prior date. From this database, we determined the total number of ED patients who were present at the time of arrival of each patient with pneumonia.

	All data were entered into an electronic spreadsheet. Microsoft Excel 97 (Microsoft Corporation, Redmond, Washington) was used.

	We calculated the duration of the following care components: ED arrival to ED room placement, ED arrival to chest radiograph order, chest radiograph order to radiograph obtained, blood culture order to culture obtained, room placement to antibiotic order, and antibiotic order to antibiotic administered. We classified care components as related to system  hroughput (arrival to room placement and arrival to chest radiograph order) or by provider discipline as follows: radiology technician (chest radiograph order to radiograph obtained), physician (room placement to antibiotic order), and nurse (blood culture order to culture obtained and antibiotic order to antibiotic administered) (

). We chose not to calculate time from room placement to chest radiograph order (a potential marker of physician workload), as chest radiographs may be ordered by triage and bedside nurses and physicians at our institution by preestablished protocols; therefore, this care component does not solely reflect physician or nursing workload. Similarly, we did not include time from room placement to blood culture order because nurses often obtain (but do not send) blood cultures before the physician sees the patient and writes this order.

	Intervals longer than 600 minutes were analyzed as equal to 600 minutes to limit their influence on the overall results, while still including them as very long intervals. This value was chosen because it was the mean total length of stay of admitted ED patients. If the task was performed before the time of order, we set order times to equal the time of order completion to eliminate negative intervals.

	The primary outcome was the time from antibiotic order to antibiotic administered (a nursing task). We chose this a priori based on casual observation that nursing staff seemed busier than physician staff during times of ED crowding. Secondary outcomes included times to completion of each care component.

	We assessed the association of total ED volume with the duration of each care component using multivariate linear regression analysis to control for demographic and presenting characteristics. We also controlled for the time from arrival to the start of the care component to control for the possibility that subsequent intervals would be affected by the previous  intervals. For example, if providers were cognizant of delays preceding their involvement, those providers may have behaved differently, either to expedite care intervals to maintain compliance with the antibiotic timing measure or to direct care to sicker patients, having decided that the target could not be met. Patients who had missing values were excluded from the analysis.

	Analyses were conducted using commercially available statistical software (SAS version 9.1; SAS Institute, Cary, North Carolina). We used linear regression analysis because results are most meaningfully and interpretably estimated as effects on the mean duration of the measured care component. Because many care components had skewed distributions that resulted in violation of the normality assumption for residuals from the models, we used bias-corrected accelerated bootstrapping to obtain valid confidence intervals (CIs).

 We tested the linearity assumption for continuous predictors by adding quadratic terms. For predictors with strong evidence of nonlinearity, we categorized them into quartiles.

	A total of 731 of 898 patients discharged from our hospital with a primary or secondary diagnosis of pneumonia during the study period met eligibility criteria for measure PN-5b and were chosen by UHC for review (

). Of this total, 245 (33%) met exclusion criteria. For 79 patients, we could not ascertain the time of antibiotic administration, leaving 407 patients for the final analysis. The initial study

 for which these data were abstracted consisted of 405 patients. Further investigation resulted in 2 additional patients with known time to antibiotic administration. Demographic and presenting characteristics of the study sample are given in Table 1. The median number of ED patients present at the time of arrival of the patients with pneumonia was 24.5 (interquartile range, 17-30; range, 3-52).

	The mean (SD) and median (interquartile range) durations of care components for the study population are given in 

. The median time from ED arrival to antibiotic administration was 195 minutes (61% received antibiotics within 4 hours of ED arrival). For nursing-dependent intervals (

), for every 10 additional ED patients present at the time of arrival of the patients with pneumonia, the time from antibiotic order to antibiotic administered was prolonged by an estimated 9.3 (95% CI, 1.4-19.0) minutes, while the time from blood culture order to culture obtained was not prolonged (−0.4 minutes [95% CI, −7.2 to 7.4]). For system throughput intervals, the time from arrival to chest radiograph order was prolonged by 14.3 (95% CI, 6.5- 24.0) minutes, while the time from arrival to room placement seemed nonlinearly associated and was prolonged most (by 26.0 [95% CI, 10.6-49.0] minutes) at the highest quartile of ED volume. For provider-specific intervals (Tables 4, 5, and 6), the time from chest radiograph order to radiograph obtained (radiology  technician dependent) seemed nonlinearly associated with ED volume and was actually reduced (−9.5 [95% CI, −19.1 to −2.0] minutes) in association with the third quartile of ED volume. For each additional 10 patients in the ED, the time from room placement to antibiotic order (physician dependent) was prolonged by 18.1 minutes (95% CI, −5.1 to 43.0), butthis did not reach statistical significance. 

	This is a retrospective single-center study, and the findings may not apply to other settings. Two of us not blinded to the study hypothesis performed the medical record abstraction. We do not believe that this biased the results because the abstractors were blinded to the ED volume data. In addition, we did not conduct a random independent audit  of medical records to determine the accuracy of the abstraction process.

	We chose to use ED volume as a marker of crowding rather than a more complicated derived score because this replicated our prior work and was readily available. Furthermore, there is no compelling evidence that the derived scores outperform simple measures of occupancy.

	Although we categorized pneumonia care components by provider discipline, many components, if not all, are dependent on more than 1 type of provider. We could have categorized arrival to chest radiograph order (which was significantly prolonged at the highest ED volume quartile) as a physician-dependent care component. However, times from arrival to  chest radiograph order are not solely reflective of the ED physician’s efficiency, as this component may be disproportionately prolonged by delays in rooming patients (system throughput) or abbreviated if the chest radiograph was ordered by the triage or bedside nurse, as per a standing protocol at our ED. Therefore, we categorized this component as  related to overall system throughput. In addition, as awareness of the TJC/CMS benchmark increased, physicians were encouraged to order antibiotics along with their initial orders (for intravenous access, laboratory studies, radiographic studies, etc) rather than after reviewing the results of the initial investigations if the diagnosis of pneumonia was certain. This change in practice could have artificially prolonged the time from antibiotic order to antibiotic administered as nurses went through the steps necessary for antibiotic delivery. However, in our prior study

 among this same sample, we did not find a differential effect of crowding over the duration of the investigation.

	Our models did not account for physician or nursing staffing levels, which were unavailable. It is possible that small increases in patient volume are magnified during periods of lesser staffing. In addition, missing data for variables that were included in the models may have altered the results. The influence of the number of ED patients present at arrival on the chance of being excluded from the models in Tables 3, 4, 5, and 6 seemed to be small (all odds ratios were <1.14 per additional 10 patients, and all CIs extended down to at least 0.92).

	Our findings must be tempered by the fact that we conducted multiple analyses and that this is a secondary analysis. Our results suggest that ED volume affects nursing care and throughput measures more so than other care components, but these associations need to be confirmed in further work.

Articles

Multivariate analyses associate increased emergency department volume with delayed nursing-dependent care for patients with pneumonia, despite high ratios of nurses to patients.

Carley A. Maak, MD

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Effect of Emergency Department Crowding on Pneumonia Admission Care Components