SISTER (system implementation of select transfers in emergency room) model to reduce ED boarding.

OBJECTIVE: This study describes a novel transfer model implemented between an academic, level 1 trauma center (Hospital A) and a nearby affiliate community hospital (Hospital B). Primary outcome is change in boarding hours and percentage of boarders in the Hospital A emergency department. Secondary objectives of this study include how improved flow in the emergency department to reduce boarding improves length of stay, prevents patients from escalating to more acute acuity levels of care, reduces patient morbidity and mortality and therefore improves health care costs as well. METHODS: A retrospective chart review was conducted over a consecutive 14-months period of all patients that presented to main hospital emergency department who were transferred to the Hospital B for inpatient admission. This included analysis of patient cohort characteristics, hospital LOS, return rate to the Hospital A (boomerang), rates of against medical advice (AMA) dispositions, post-discharge recidivism, in addition to enterprise data on total number of boarders, percent of boarders, and total boarding hours. RESULTS: There was a total of 718 transfer encounters during the study period. Percent boarding decreased from 70.6% in the pre-period to 63.8% in the post-period (p < 0.001). Total boarding hours decreased at both the main hospital and the sister hospital with this transfer process. The median length of stay at the sister hospital was 74 h, with 9 upgrades to ICU admissions. Five patients were dispositioned back to the hospital A after admission to hospital B. CONCLUSION: A distributive model was useful in transferring admissions within a healthcare system, reducing number of boarders, percent of boarders, and boarding hours in Hospital A emergency department. Furthermore, the Hospital B was an appropriate location for transfers, based on the low number of ICU transfers and dispositions back to the main hospital.

Impact of the Closure of a Large, Urban Safety-Net Hospital on a Neighboring Academic Center: A Philadelphia Case Study.

OBJECTIVES: We examined how the closure of 496-bed Hahnemann University Hospital (HUH), a level I trauma and stroke center and safety-net hospital in Philadelphia, Pennsylvania, impacted the emergency department (ED) and radiology workflow in our neighboring hospital (Thomas Jefferson University Hospital) located <1 mile away. METHODS: On June 30, 2019, HUH announced its imminent closure and began diverting trauma patients, with its ED officially closing in mid-August. Trends of our ED and radiology workflow were analyzed using QlikView analytics software for 3 months before and after the closure. Data were compared to workflow from the same time period in 2018. RESULTS: The average monthly number of patients presenting to our ED after the closure increased 20.2% with a corresponding 16% increase in ED imaging studies, primarily in radiographs (+16%) and CT (+20%). Radiology orders by advanced practice providers increased 74%. Turnaround time from imaging order placed to final diagnostic radiology report did not change substantially after the closure. CONCLUSION: Workflow in our ED and radiology department was significantly impacted by the closure of HUH. This study provides insight into how our practice patterns changed and compensated after the closure of a neighboring, large, urban safety-net hospital; it is important for radiologists to be aware of citywide practice patterns to adapt to acute change.

Impact of Emergency Department Tele-intake on Left Without Being Seen and Throughput Metrics.

OBJECTIVES: More than 2 million patients present to a U.S. emergency department (ED) annually and leave without being seen (LWBS) due to delays in initiating care. We evaluated whether tele-intake at the time of presentation would reduce LWBS rates and ED throughput measures. METHODS: We conducted a before-and-after study at an urban community hospital. The intervention was use of a tele-intake physician to triage patients from 11 am to 6 pm, 7 days per week. Tele-intake providers performed a triage history and physical examination, documented findings, and initiated orders in the medical record. We assessed the impact of this program using the domains of the National Quality Forum framework evaluating access, provider experience, and effectiveness of care. The main outcome was 24-hour LWBS rate. Secondary outcomes were overall door to provider and door to disposition times, left without treatment complete (LWTC), left against medical advice (AMA), left without treatment (LWOT), and physician experience. We compared the 6-month tele-intake period to the same period from the prior year (October 1 to April 1, 2017 vs. 2016). Additionally, we conducted a survey of our physicians to assess their experience with the program. RESULTS: Total ED volume was similar in the before and after periods (19,892 patients vs. 19,646 patients). The 24-hour LWBS rate was reduced from 2.30% (95% confidence interval [CI] = 2.0% to 2.5%) to 1.69% (95% CI = 1.51% to 1.87%; p < 0.001). Overall door to provider time decreased (median = 19 [interquartile range {IQR} = 9 to 38] minutes vs. 16.2 [IQR = 7.8 to 34.3] minutes; p < 0.001), but ED length of stay for all patients (defined as door in to door out time for all patients) minimally increased (median = 184 [IQR = 100 to 292] minutes vs. 184.3 [IQR = 104.4 to 300] minutes; p < 0.001). There was an increase in door to discharge times (median = 146 [IQR = 83 to 231] minutes vs. 148 [IQR = 88.2 to 233.6] minutes; p < 0.001) and door to admit times (median = 330 [IQR = 253 to 432] minutes vs. 357.6 [IQR = 260.3 to 514.5] minutes; p < 0.001). We saw an increase in LWTC (0.59% [95% CI = 0.49% to 0.70%] vs. 1.1% [95% CI = 0.9% to 1.2%]; p < 0.001), but no change in AMA (1.4% [95% CI = 1.2% to 1.6%] vs. 1.6% [95% CI = 1.4% to 1.78%]; p = 0.21) or LWOT (4.3% [95% CI = 4.1% to 4.6%] vs. 4.4% [95% CI = 4.1% to 4.7%]; p = 0.7). Tele-intake providers thought tele-intake added value (12/15, 80%) and allowed them to effectively address medical problems (14/15, 95%), but only (10/15, 67%) thought that it was as good as in-person triage. Of the receiving physicians, most agreed with statements that tele-intake did not interfere with care (19/22, 86%), helped complement care (19/21, 90%), and gave the patient a better experience (19/22, 86%). CONCLUSIONS: Remote tele-intake provided in an urban community hospital ED reduced LWBS and time to provider but increased LWTC rates and had no impact on LWOT.

Retained Stingray Barb and the Importance of Imaging.

Stingray envenomation is a common occurrence. X-ray evaluation of stingray wounds is an unnecessarily misunderstood diagnostic concept. We present the case of a patient stung by a stingray with a prolonged and complicated course and permanent disability due to a retained barb. The patient had undergone multiple medical evaluations before an X-ray was obtained.

Pain scores show no monotonic upward or downward trend over time.

BACKGROUND: Self-reported pain scales are commonly used in emergency departments (EDs). The 11-point (0-10) numerical rating scale is a commonly used scale for adults visiting EDs in the United States. Despite their widespread use, little is known about whether distribution of pain scores has remained consistent over time. OBJECTIVES: The objective of this study is to determine if there were upwards or downwards (monotonic) trends in pain scores over time at a single hospital. METHODS: Retrospective chart review for the years 2003-2011. All pain scores for May 1(st) and 2(nd) of those years were collected. Multinomial logistic regression was used to model the probability of a patient rating their pain in each of 11 categories (scores 0 to 10) as a function of the calendar year. Additional analysis was carried out with pain scores grouped into four categories. RESULTS: Data were collected from 2934 patient charts. Pain scores were recorded in 2136 charts, and 1637 of these pain scores were above zero (i.e., 1-10). The pain score distribution differed significantly over time (p = 0.001); however, there was no monotonic (single-direction) trend. CONCLUSION: Although there were significant shifts in pain scores over time, there is not a significant monotonic trend. At this hospital, there was no "inflation" or "deflation" in pain scores over time. Shifts in distribution, even when not in a single direction, may be important for researchers examining pain scores in the ED.