Predictive Value of Point-of-care Lactate Measurement in Patients Meeting Level II and III Trauma Team Activation Criteria that Present to the Emergency Department: A Prospective Study.

BACKGROUND: The aim of this study was to investigate the utility of early point-of-care (POC) lactate levels to help predict injury severity and ultimate emergency department (ED) disposition for trauma patients meeting Level II and III activation criteria. METHODS: This was a blinded, prospective cohort study including a convenience sample of patients meeting our triage criteria for Level II or III team activation with stable vital signs. Bedside lactate samples were collected during the secondary survey. Clinical care/disposition was at the discretion of physicians who remained blinded to the bedside lactate result. An elevated lactate was defined as >2.0 mmol/L. RESULTS: Ninety-six patients were in the study group; mean age was 41 ± 17 years, 26% were female, 57% were Hispanic, and 60% admitted. We found no difference in initial mean POC lactate levels (mmol/L) for admitted versus discharged groups and Injury Severity Score (ISS) ≥9 versus ISS <9 groups (3.71 [95% confidence interval (CI): 3.1-4.4] vs. 3.85 [95% CI: 2.8-4.9]; P = 0.99 and 3.54 [95% CI: 2.7-4.4] vs. 3.89 [95% CI: 3.1-4.6]; P = 0.60, respectively). Performance characteristics of early elevated lactate levels were poor both to predict need for hospital admission (sensitivity = 77% [65%-87%]; specificity = 26% [13%-43%]; negative predictive value [NPV] = 43% [27%-61%]; and positive predictive value [PPV] = 62% [56%-67%]) and to identify patients with ISS scores ≥9 (sensitivity = 76% [59%-89%]; specificity = 24% [14%-37%]; NPV = 65% [47%-80%]; and PPV = 36% [30%-41%]). CONCLUSIONS: For Level II/III, we found that early bedside lactate levels were not predictive of ISS ≥9 or the need for admission. LEVEL OF EVIDENCE: III (diagnostic test).

Sensitivity of urinary pathogens for patients discharged from the emergency department compared with the hospital antibiogram.

BACKGROUND: Data for hospital antibiograms are typically compiled from all patients, regardless of disposition, demographics and other comorbidities. OBJECTIVE: We hypothesized that the sensitivity patterns for urinary pathogens would differ significantly from the hospital antibiogram in patients that were discharged from the emergency department (ED). METHODS: We evaluated a retrospective cohort of all adult patients with positive urine cultures treated in the 2016 calendar year at an inner-city academic ED. Positive urine cultures defined by our institution's microbiology department. Investigators conducted a structured review of an electronic medical record (EMR) to collect demographic, historical and microbiology records. We utilized a one-sample test of proportion to compare the sensitivity of each organism for discharged patients to the hospital published antibiogram. Alpha set at 0.05. RESULTS: During the study period, 414 patients were discharged from the ED and found to have positive urine cultures; 20% age > 60 years old, 85% female, 79% Hispanic, 33% diabetic. The most common organisms was E. coli (78%). E. coli was sensitive to Trimethoprim-Sulfamethoxazole for 59% vs. 58% in our antibiogram (p = 0.77), Ciprofloxacin 81% vs. 69% (p < 0. 001), Nitrofurantoin 96% vs 95%; (p = 0.25). K. pneumoniae was sensitive to Trimethoprim-Sulfamethoxazole 87% vs. 80% in our antibiogram (p = 0.26), Ciprofloxacin 100% vs. 92% (p = 0.077), Nitrofurantoin 86% vs 41% (p < 0.001). CONCLUSIONS: For our predominantly Hispanic study group with a high prevalence of diabetes, we found that our hospital antibiogram had relatively good value in guiding antibiotic therapy though for some organism/antibiotic combinations sensitivities were higher than expected.

Increased door to admission time is associated with prolonged throughput for ED patients discharged home.

BACKGROUND: Emergency Department (ED) service evaluations are typically based on surveys of discharged patients. Physicians/administrators benefit from data that quantifies system-based factors that adversely impact the experience of those who represent the survey cohort. OBJECTIVE: While investigators have established that admitted patient boarding impacts overall ED throughput times, we sought to specifically quantify the relationship between throughput times for patients admitted (EDLOS) versus discharged home from the ED (DCLOS). METHODS: We performed a prospective analysis of consecutive patient encounters at an inner-city ED. Variables collected: median daily DCLOS for ED patients, ED daily census, left without being seen (LWBS), median door to doctor, median room to doctor, and daily number admitted. Admitted patients divided into 2 groups based on daily median EDLOS for admits (<6 hours, ≥6 hours). Continuous variables analyzed by t-tests. Multivariate regression utilized to identify independent effects of the co-variants on median daily DCLOS. RESULTS: We analyzed 24,127 patient visits. ED patient DCLOS was longer for patients seen on days with prolonged EDLOS (193.7 minutes, 95%CI 186.7-200.7 vs. 152.8, 144.9-160.5, P< .0001). Variables that were associated with increased daily median EDLOS for admits included: daily admits (P= 0.01), room to doctor time (P< .01), number of patients that left without being seen (P< .01). When controlling for the covariate daily census, differences in DCLOS remained significant for the ≥6 hours group (189.4 minutes, 95%CI 184.1-194.7 vs. 164.8, 155.7-173.9 (P< .0001). CONCLUSION: Prolonged ED stays for admitted patients were associated with prolonged throughput times for patients discharged home from the ED.

Prior CT imaging history for patients who undergo PAN CT for acute traumatic injury.

Objective. A single PAN scan may provide more radiation to a patient than is felt to be safe within a one-year period. Our objective was to determine how many patients admitted to the trauma service following a PAN scan had prior CT imaging within our six-hospital system. Methods. We performed a secondary analysis of a prospectively collected trauma registry. The study was based at a level-two trauma center and five affiliated hospitals, which comprise 70.6% of all Emergency Department visits within a twelve county region of southern Texas. Electronic medical records were reviewed dating from the point of trauma evaluation back to December 5, 2005 to determine evidence of prior CT imaging. Results. There were 867 patients were admitted to the trauma service between January 1, 2012 and December 31, 2012. 460 (53%) received a PAN scan and were included in the study group. The mean age of the study group was 37.7 ± 1.54 years old, 24.8% were female, and the mean ISS score was 13.4 ± 1.07. The most common mechanism of injury was motor vehicle collision (47%). 65 (14%; 95% CI [11-18]%) of the patients had at least one prior CT. The most common prior studies performed were: CT head (29%; 19-42%), CT Face (29%; 19-42%) and CT Abdomen and Pelvis (18%; 11-30%). Conclusion. Within our trauma registry, 14% of patients had prior CT imaging within our hospital system before their traumatic event and PAN scan.

Hospital factors impact variation in emergency department length of stay more than physician factors.

INTRODUCTION: To analyze the correlation between the many different emergency department (ED) treatment metric intervals and determine if the metrics directly impacted by the physician correlate to the "door to room" interval in an ED (interval determined by ED bed availability). Our null hypothesis was that the cause of the variation in delay to receiving a room was multifactorial and does not correlate to any one metric interval. METHODS: We collected daily interval averages from the ED information system, Meditech©. Patient flow metrics were collected on a 24-hour basis. We analyzed the relationship between the time intervals that make up an ED visit and the "arrival to room" interval using simple correlation (Pearson Correlation coefficients). Summary statistics of industry standard metrics were also done by dividing the intervals into 2 groups, based on the average ED length of stay (LOS) from the National Hospital Ambulatory Medical Care Survey: 2008 Emergency Department Summary. RESULTS: Simple correlation analysis showed that the doctor-to-discharge time interval had no correlation to the interval of "door to room (waiting room time)", correlation coefficient (CC) (CC=0.000, p=0.96). "Room to doctor" had a low correlation to "door to room" CC=0.143, while "decision to admitted patients departing the ED time" had a moderate correlation of 0.29 (p <0.001). "New arrivals" (daily patient census) had a strong correlation to longer "door to room" times, 0.657, p<0.001. The "door to discharge" times had a very strong correlation CC=0.804 (p<0.001), to the extended "door to room" time. CONCLUSION: Physician-dependent intervals had minimal correlation to the variation in arrival to room time. The "door to room" interval was a significant component to the variation in "door to discharge" i.e. LOS. The hospital-influenced "admit decision to hospital bed" i.e. hospital inpatient capacity, interval had a correlation to delayed "door to room" time. The other major factor affecting department bed availability was the "total patients per day." The correlation to the increasing "door to room" time also reflects the effect of availability of ED resources (beds) on the patient evaluation time. The time that it took for a patient to receive a room appeared more dependent on the system resources, for example, beds in the ED, as well as in the hospital, than on the physician.

Impact of resident physicians on emergency department throughput.

OBJECTIVE: Evaluate the impact of adding emergency medicine residents to a medium-size urban hospital by comparing emergency department (ED) admission rate, total census, length of stay (LOS), and proportion of patients who left without being seen (LWBS). METHODS: Using the student t-test, the study compared commonly used ED metrics for a mid-sized urban hospital (annual census 43,000) for the four-month period prior to (March-June 2006) and after (March-June 2007) residents began providing 24-hour coverage at the institution. RESULTS: There was no significant difference in the number of patients seen (NPS) in the two time periods, 14,471 and 14,699 patients respectively (p=0.507). Analysis of the NPS and LWBS was not statistically significant. The percentage of patients who LWBS decreased with the presence of residents (6.5% to 5.8%, p=0.531), and the overall ED LOS was similar (210 min vs. 219 min, p=0.56). Admission rate data demonstrated that residents had a similar admission rate (17.5% vs. 18%, p =0.332). CONCLUSION: ED flow depends on a number of variables with complex interactions. When comparing two similar time periods in consecutive years, the presence of resident physicians in the ED had no effect on the number of patients seen, patient LOS in the ED, or LWBS, thus supporting the conclusion that residents did not adversely affect the patient flow within the ED.