Ian Brown's research while affiliated with Stanford University and other places

Objective: Unscheduled low-acuity care options are on the rise and are often expected to reduce emergency department (ED) visits. We opened an ED-staffed walk-in clinic (WIC) as an alternative care location for low-acuity patients at a time when ED visits exceeded facility capacity and the impending flu season was anticipated to increase visits further, and we assessed whether low-acuity ED patient visits decreased after opening the WIC. Methods: In this retrospective cohort study, we compared patient and clinical visit characteristics of the ED and WIC patients and conducted interrupted time-series analyses to quantify the impact of the WIC on low-acuity ED patient visit volume and the trend. Results: There were 27,211 low-acuity ED visits (22.7% of total ED visits), and 7,058 patients seen in the WIC from February 26, 2018, to November 17, 2019. Low-acuity patient visits in the ED reduced significantly immediately after the WIC opened (P = 0.01). In the subsequent months, however, patient volume trended back to pre-WIC volumes such that there was no significant impact at 6, 9, or 12 months (P = 0.07). Had WIC patients been seen in the main ED, low-acuity volume would have been 27% of the total volume rather than the 22.7% that was observed. Conclusion: The WIC did not result in a sustained reduction in low-acuity patients in the main ED. However, it enabled emergency staff to see low-acuity patients in a lower resource setting during times when ED capacity was limited.

Background: Chest pain (CP) is the hallmark symptom for acute coronary syndrome (ACS) but is not reported in 20-30% of patients, especially women, elderly, non-white patients, presenting to the emergency department (ED) with an ST-segment elevation myocardial infarction (STEMI). Methods: We used a retrospective 5-year adult ED sample of 279,132 patients to explore using CP alone to predict ACS, then we incrementally added other ACS chief complaints, age, and sex in a series of multivariable logistic regression models. We evaluated each model's identification of ACS and STEMI. Results: Using CP alone would recommend ECGs for 8% of patients (sensitivity, 61%; specificity, 92%) but missed 28.4% of STEMIs. The model with all variables identified ECGs for 22% of patients (sensitivity, 82%; specificity, 78%) but missed 14.7% of STEMIs. The model with CP and other ACS chief complaints had the highest sensitivity (93%) and specificity (55%), identified 45.1% of patients for ECG, and only missed 4.4% of STEMIs. Conclusion: CP alone had highest specificity but lacked sensitivity. Adding other ACS chief complaints increased sensitivity but identified 2.2-fold more patients for ECGs. Achieving an ECG in 10 min for patients with ACS to identify all STEMIs will be challenging without introducing more complex risk calculation into clinical care.

Objectives Here we report the clinical performance of COVID-19 curbside screening with triage to a drive-through care pathway versus main emergency department (ED) care for ambulatory COVID-19 testing during a pandemic. Patients were evaluated from cars to prevent the demand for testing from spreading COVID-19 within the hospital. Methods We examined the effectiveness of curbside screening to identify patients who would be tested during evaluation, patient flow from screening to care team evaluation and testing, and safety of drive-through care as 7-day ED revisits and 14-day hospital admissions. We also compared main ED efficiency versus drive-through care using ED length of stay (EDLOS). Standardized mean differences (SMD) >0.20 identify statistical significance. Results Of 5931 ED patients seen, 2788 (47.0%) were walk-in patients. Of these patients, 1111 (39.8%) screened positive for potential COVID symptoms, of whom 708 (63.7%) were triaged to drive-through care (with 96.3% tested), and 403 (36.3%) triaged to the main ED (with 90.5% tested). The 1677 (60.2%) patients who screened negative were seen in the main ED, with 440 (26.2%) tested. Curbside screening sensitivity and specificity for predicting who ultimately received testing were 70.3% and 94.5%. Compared to the main ED, drive-through patients had fewer 7-day ED revisits (3.8% vs 12.5%, SMD = 0.321), fewer 14-day hospital readmissions (4.5% vs 15.6%, SMD = 0.37), and shorter EDLOS (0.56 vs 5.12 hours, SMD = 1.48). Conclusion Curbside screening had high sensitivity, permitting early respiratory isolation precautions for most patients tested. Low ED revisit, hospital readmissions, and EDLOS suggest drive-through care, with appropriate screening, is safe and efficient for future respiratory illness pandemics.

Background Pediatric trauma patients undergo fewer computed tomography (CT) scans when evaluated at pediatric trauma centers (PTC) versus adult trauma centers (ATC) with no change in clinical outcome. Factors contributing to this difference are unclear. We sought to identify whether the training background of physicians, specifically emergency medicine (EM) versus pediatric emergency medicine (PEM), affected the CT rate of pediatric trauma patients within one institution. Methods A single-center retrospective study of CT utilization based on attending physicians’ training in trauma patients <18 years between November 2018 and November 2020. Attendings were categorized into two groups: EM residency with no PEM fellowship, or pediatrics/EM residency with PEM fellowship. Primary outcomes measured were the proportion of patients receiving a CT and CT positivity rate. Results Of 463 study patients, CTs were obtained in 145/228 (64%) patients by EM, and 130/235 (55%) by PEM (p=.07). CT positivity rate was 21% and 19% in EM and PEM, respectively (p=.46). The mean number of CTs per patient in EM was 2.8 compared to 2.1 in PEM (p<.01), and for patients with an injury severity score (ISS) >15, mean number of CTs per patient increased to 4.9 in EM versus 2.4 in PEM (p=.01). Conclusions The mean number of CTs ordered per patient was statistically higher for EM attendings. The differences between CT rates highlight future opportunities for ongoing development of pediatric trauma imaging guidelines and radiation exposure reduction.

Introduction: In March 2020, shelter-in-place orders were enacted to attenuate the spread of coronavirus 2019 (COVID-19). Emergency departments (EDs) experienced unexpected and dramatic decreases in patient volume, raising concerns about exacerbating health disparities. Methods: We queried our electronic health record to describe the overall change in visits to a two-ED healthcare system in Northern California from March-June 2020 compared to 2019. We compared weekly absolute numbers and proportional change in visits focusing on race/ethnicity, insurance, household income, and acuity. We calculated the z-score to identify whether there was a statistically significant difference in proportions between 2020 and 2019. Results: Overall ED volume declined 28% during the study period. The nadir of volume was 52% of 2019 levels and occurred five weeks after a shelter-in-place order was enacted. Patient demographics also shifted. By week 4 (April 5), the proportion of Hispanic patients decreased by 3.3 percentage points (pp) (P = 0.0053) compared to a 6.2 pp increase in White patients (P = 0.000005). The proportion of patients with commercial insurance increased by 11.6 pp, while Medicaid visits decreased by 9.5 pp (P < 0.00001) at the initiation of shelter-in-place orders. For patients from neighborhoods <300% federal poverty levels (FPL), visits were -3.8 pp (P = 0.000046) of baseline compared to +2.9 pp (P = 0.0044) for patients from ZIP codes at >400% FPL the week of the shelter-in-place order. Overall, 2020 evidenced a consistently elevated proportion of high-acuity Emergency Severity Index (ESI) level 1 patients compared to 2019. Increased acuity was also demonstrated by an increase in the admission rate, with a 10.8 pp increase from 2019. Although there was an increased proportion of high-acuity patients, the overall census was decreased. Conclusion: Our results demonstrate changing ED utilization patterns circa the shelter-in-place orders. Those from historically vulnerable populations such as Hispanics, those from lower socioeconomic areas, and Medicaid users presented at disproportionately lower rates and numbers than other groups. As the pandemic continues, hospitals should use operations data to monitor utilization patterns by demographic, in addition to clinical indicators. Messaging about availability of emergency care and other services should include vulnerable populations to avoid exacerbating healthcare disparities.

BACKGROUND Telemedicine has been deployed by healthcare systems in response to the COVID-19 pandemic to enable healthcare workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown. OBJECTIVE To use real-time locating systems (RTLS) to evaluate the impact of telemedicine on in-person interaction between healthcare workers and patients. METHODS The RTLS platform was used to collect movement data for nursing and physician staff in each patient room of the emergency department. Movement data was captured between March 2nd, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20th, 2020. A new telemedicine platform was released to clinicians on March 29th, 2020. Number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and post-implementation phases and compared with t-tests to determine statistical significance. RESULTS There were 15,741 RTLS events linked to 2,662 encounters for patients screened for COVID-19. There was no significant change in number of in-person interactions between the pre- and post-implementation phases for both nurses (5.7 vs 7.0 entrances per patient, p=0.07) and physicians (1.3 vs 1.5 entrances per patient, p=0.12). Total duration of in-person interaction did not change (56.4 vs 55.2 minutes per patient, p=0.74) despite an increase in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, p<0.01 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, p<0.01 for change in daily average). CONCLUSIONS Telemedicine was rapidly adopted with the intent of minimizing pathogen exposure to healthcare workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline healthcare clinicians.

Background: Telemedicine has been deployed by healthcare systems in response to the COVID-19 pandemic to enable healthcare workers to provide remote care for both outpatients and inpatients. Although it is reasonable to suspect telemedicine visits limit unnecessary personal contact and thus decrease the risk of infection transmission, the impact of the use of such technology on clinician workflows in the emergency department is unknown. Objective: To use real-time locating systems (RTLS) to evaluate the impact of a new telemedicine platform, which permitted clinicians located outside patient rooms to interact with patients who were under isolation precautions in the emergency department, on in-person interaction between healthcare workers and patients. Methods: A pre-post analysis was conducted using a badge-based RTLS platform to collect movement data including entrances and duration of stay within patient rooms of the emergency department for nursing and physician staff. Movement data was captured between March 2nd, 2020, the date of the first patient screened for COVID-19 in the emergency department, and April 20th, 2020. A new telemedicine platform was deployed on March 29th, 2020. Number of entrances and duration of in-person interactions per patient encounter, adjusted for patient length of stay, were obtained for pre- and post-implementation phases and compared with t-tests to determine statistical significance. Results: There were 15,741 RTLS events linked to 2,662 encounters for patients screened for COVID-19. There was no significant change in number of in-person interactions between the pre- and post-implementation phases for both nurses (5.7 vs 7.0 entrances per patient, p=0.07) and physicians (1.3 vs 1.5 entrances per patient, p=0.12). Total duration of in-person interaction did not change (56.4 vs 55.2 minutes per patient, p=0.74) despite significant increases in telemedicine videoconference frequency (0.6 vs 1.3 videoconferences per patient, p<0.01 for change in daily average) and duration (4.3 vs 12.3 minutes per patient, p<0.01 for change in daily average). Conclusions: Telemedicine was rapidly adopted with the intent of minimizing pathogen exposure to healthcare workers during the COVID-19 pandemic, yet RTLS movement data did not reveal significant changes for in-person interactions between staff and patients under investigation for COVID-19 infection. Additional research is needed to better understand how telemedicine technology may be better incorporated into emergency departments to improve workflows for frontline healthcare clinicians.

Pediatric head injury is a common presenting complaint in the emergency department (ED), often requiring neuroimaging or ED observation for diagnosis. However, the traditional diagnostic neuroimaging modality, head computed tomography (CT), is associated with radiation exposure while prolonged ED observation impacts patient flow and resource utilization. Recent scientific literature supports abbreviated, or focused and shorter, brain magnetic resonance imaging (MRI) as a feasible and accurate diagnostic alternative to CT for traumatic brain injury. However, this is a relatively new application and its use is not widespread. The aims of this review are to describe the science and applications of abbreviated brain MRI and report a model protocol's development and ED implementation in the evaluation of children with head injury for replication in other institutions.

Introduction: ED overcrowding is an issue that is affecting every emergency department and every hospital. The inability to maintain patient flow into and out of the emergency department paralyzes the ability to provide effective and timely patient care. Many solutions have been proposed on how to mitigate the effects of ED overcrowding. Solutions involve either hospital-wide initiatives or ED-based solutions. In this article, the authors seek to describe and provide metrics for a patient flow methodology that targets ESI 3 patients in a vertical flow model. Methods: In the Stanford Emergency Department, a vertical flow model was created from existing ED space by removing fold-down horizontal stretchers and replacing them with multiple chairs that allowed for assessment and medical management in an upright sitting position. The model was launched and sustained through frequent interdisciplinary huddles, detailed inclusion and exclusion criteria, scripted text on how to promote the flow model to patients, and close analytics of metrics. Metrics for success included patient length of stay (LOS) for those triaged to the vertical flow area compared with ESI 3 patients triaged to the traditional emergency department as a comparison group. The secondary outcome is the total number of patients seen in the vertical flow area. This was a 6-month-September 2014, to February 2015-retrospective pre- and postintervention study that examined LOS as a marker for effective launch and implementation of a vertical patient workflow model. Results: The patients triaged to the vertical flow area in the study period tended to be younger than in the control period (43 years versus 52 years, P = 0.00). There was a significant decrease in our primary end point: the total LOS for ESI 3 patients triaged to the vertical flow area (270 minutes versus 384 minutes, P = 0.00). Conclusion: Implementation of a vertical patient flow strategy can decrease LOS for the vertical ESI 3 patients based upon the inclusion and exclusion criteria. Furthermore, this is accomplished with minimal financial investment within the physical constraints of an existing emergency department.