Call me Dr Ishmael: trends in electronic health record notes available at emergency department visits and admissions.

Objectives: Numerous studies have identified information overload as a key issue for electronic health records (EHRs). This study describes the amount of text data across all notes available to emergency physicians in the EHR, trended over the time since EHR establishment. Materials and Methods: We conducted a retrospective analysis of EHR data from a large healthcare system, examining the number of notes and a corresponding number of total words and total tokens across all notes available to physicians during patient encounters in the emergency department (ED). We assessed the change in these metrics over a 17-year period between 2006 and 2023. Results: The study cohort included 730 968 ED visits made by 293 559 unique patients and a total note count of 132 574 964. The median note count for all encounters in 2006 was 5 (IQR 1-16), accounting for 1735 (IQR 447-5521) words. By the last full year of the study period, 2022, the median number of notes had grown to 359 (IQR 84-943), representing 359 (IQR 84-943) words. Note and word counts were higher for admitted patients. Discussion: The volume of notes available for review by providers has increased by over 30-fold in the 17 years since the implementation of the EHR at a large health system. The task of reviewing these notes has become commensurately more difficult. These data point to the critical need for new strategies and tools for filtering, synthesizing, and summarizing information to achieve the promise of the medical record.

Academic Detailing as a Health Information Technology Implementation Method: Supporting the Design and Implementation of an Emergency Department-Based Clinical Decision Support Tool to Prevent Future Falls.

BACKGROUND: Clinical decision support (CDS) tools that incorporate machine learning-derived content have the potential to transform clinical care by augmenting clinicians' expertise. To realize this potential, such tools must be designed to fit the dynamic work systems of the clinicians who use them. We propose the use of academic detailing-personal visits to clinicians by an expert in a specific health IT tool-as a method for both ensuring the correct understanding of that tool and its evidence base and identifying factors influencing the tool's implementation. OBJECTIVE: This study aimed to assess academic detailing as a method for simultaneously ensuring the correct understanding of an emergency department-based CDS tool to prevent future falls and identifying factors impacting clinicians' use of the tool through an analysis of the resultant qualitative data. METHODS: Previously, our team designed a CDS tool to identify patients aged 65 years and older who are at the highest risk of future falls and prompt an interruptive alert to clinicians, suggesting the patient be referred to a mobility and falls clinic for an evidence-based preventative intervention. We conducted 10-minute academic detailing interviews (n=16) with resident emergency medicine physicians and advanced practice providers who had encountered our CDS tool in practice. We conducted an inductive, team-based content analysis to identify factors that influenced clinicians' use of the CDS tool. RESULTS: The following categories of factors that impacted clinicians' use of the CDS were identified: (1) aspects of the CDS tool's design (2) clinicians' understanding (or misunderstanding) of the CDS or referral process, (3) the busy nature of the emergency department environment, (4) clinicians' perceptions of the patient and their associated fall risk, and (5) the opacity of the referral process. Additionally, clinician education was done to address any misconceptions about the CDS tool or referral process, for example, demonstrating how simple it is to place a referral via the CDS and clarifying which clinic the referral goes to. CONCLUSIONS: Our study demonstrates the use of academic detailing for supporting the implementation of health information technologies, allowing us to identify factors that impacted clinicians' use of the CDS while concurrently educating clinicians to ensure the correct understanding of the CDS tool and intervention. Thus, academic detailing can inform both real-time adjustments of a tool's implementation, for example, refinement of the language used to introduce the tool, and larger scale redesign of the CDS tool to better fit the dynamic work environment of clinicians.

Identifying the prevalence and characteristics of diversity, equity, and inclusion leaders in academic emergency medicine.

Objectives: Our study aims to better understand and describe the current state of diversity, equity, and inclusion (DEI) leadership in emergency medicine (EM) by identifying the prevalence of department DEI leadership positions, their demographics, and their job duty characteristics. Methods: We disseminated an electronic survey from April to July 2022 to Society for Academic Emergency Medicine (SAEM) Association of Academic Chairs of Emergency Medicine, Academy for Diversity and Inclusion in Emergency Medicine, and the Equity and Inclusion Committee to identify department DEI leads. From July to August 2022, a 45-question survey was sent to all identified DEI leaders on individual characteristics, DEI experience, and DEI lead job description. Results: We received a response from 79 out of 120 academic EM departments identified (65.8%). Of the responding institutions, 59 (74.7%) reported a DEI leader. A total of 74.6% of these DEI leaders responded at least partially to our survey and 57.6% responded in full. The most common titles were vice/associate chair of DEI (34.4%), director of DEI (28.1%), and DEI committee chair (18.8%). Most respondents (84.4%) were the inaugural DEI lead in their department and 84.4% of respondents did not have a formal DEI role in their department previously. On average, respondents have had their DEI title for 2 years (range 0-7 years) with an average of 7 years (range 0-30 years) of experience performing DEI work. Many (63.4%) do not receive any funded effort for their DEI roles. Most DEI leads were not tenure track (72.2%) and most commonly at the rank of assistant professor (47.2%) followed by associate professor (33.3%), full professor (16.7%), and instructor (2.8%). Conclusions: This is the first known study to assess the characteristics of DEI department leaders in EM. EM DEI leadership positions are new, common, and led by diverse personal identities and are often not funded. Future directions could gain qualitative insight into this workforce to guide best practices in EM DEI leadership.

Second- and third-year medical students' clinical encounters in the emergency department.

Background: Experiential learning theory suggests that direct clinical experiences facilitate learning. Previous literature has focused primarily on the experiences of fourth-year medical students. As more students gain early clinical exposure, it is important to understand the types of patients seen by junior students. Objectives: This study aims to categorize the clinical experiences of early (M2 and M3) students in the emergency department (ED). Methods: A retrospective review of the electronic health record of patients seen by M2s and M3s on a 2-week emergency medicine rotation at a single urban academic ED in the Midwest was performed. Data elements extracted included total number of patients seen, Emergency Severity Index (ESI), disposition, and chief complaint. Students were not mandated to see any particular patients. Results: Medical students (248) saw 2994 total patients from 2018 to 2022. The median number of patients seen by each student was 12.0 (range 1-32). Pediatric patients made up 6.5% (n = 194) of total patients. Encounters were primarily ESI 2 or 3, which accounted for 89.4% of all patients (n = 2676). The most encountered complaints were abdominal pain, chest pain, and dyspnea, making up 15.6% (n = 467), 8.7% (n = 260), and 5.5% (n = 165), respectively, of total cases. Obstetrics/gynecology, hematologic, and environmental disorders were the least frequently encountered domains. No students saw all Clerkship Directors in Emergency Medicine (CDEM)-recommended complaints. Conclusions: There is significant variability in the ED encounters of M2s and M3s, with wide ranges of patient volume and presentations. This study provides some evidence that early students may not be meeting CDEM recommendations.

Dashboarding to Monitor Machine-Learning-Based Clinical Decision Support Interventions.

BACKGROUND: Existing monitoring of machine-learning-based clinical decision support (ML-CDS) is focused predominantly on the ML outputs and accuracy thereof. Improving patient care requires not only accurate algorithms but also systems of care that enable the output of these algorithms to drive specific actions by care teams, necessitating expanding their monitoring. OBJECTIVES: In this case report, we describe the creation of a dashboard that allows the intervention development team and operational stakeholders to govern and identify potential issues that may require corrective action by bridging the monitoring gap between model outputs and patient outcomes. METHODS: We used an iterative development process to build a dashboard to monitor the performance of our intervention in the broader context of the care system. RESULTS: Our investigation of best practices elsewhere, iterative design, and expert consultation led us to anchor our dashboard on alluvial charts and control charts. Both the development process and the dashboard itself illuminated areas to improve the broader intervention. CONCLUSION: We propose that monitoring ML-CDS algorithms with regular dashboards that allow both a context-level view of the system and a drilled down view of specific components is a critical part of implementing these algorithms to ensure that these tools function appropriately within the broader care system.

Effectiveness of an Emergency Department-Based Machine Learning Clinical Decision Support Tool to Prevent Outpatient Falls Among Older Adults: Protocol for a Quasi-Experimental Study.

BACKGROUND: Emergency department (ED) providers are important collaborators in preventing falls for older adults because they are often the first health care providers to see a patient after a fall and because at-home falls are often preceded by previous ED visits. Previous work has shown that ED referrals to falls interventions can reduce the risk of an at-home fall by 38%. Screening patients at risk for a fall can be time-consuming and difficult to implement in the ED setting. Machine learning (ML) and clinical decision support (CDS) offer the potential of automating the screening process. However, it remains unclear whether automation of screening and referrals can reduce the risk of future falls among older patients. OBJECTIVE: The goal of this paper is to describe a research protocol for evaluating the effectiveness of an automated screening and referral intervention. These findings will inform ongoing discussions about the use of ML and artificial intelligence to augment medical decision-making. METHODS: To assess the effectiveness of our program for patients receiving the falls risk intervention, our primary analysis will be to obtain referral completion rates at 3 different EDs. We will use a quasi-experimental design known as a sharp regression discontinuity with regard to intent-to-treat, since the intervention is administered to patients whose risk score falls above a threshold. A conditional logistic regression model will be built to describe 6-month fall risk at each site as a function of the intervention, patient demographics, and risk score. The odds ratio of a return visit for a fall and the 95% CI will be estimated by comparing those identified as high risk by the ML-based CDS (ML-CDS) and those who were not but had a similar risk profile. RESULTS: The ML-CDS tool under study has been implemented at 2 of the 3 EDs in our study. As of April 2023, a total of 1326 patient encounters have been flagged for providers, and 339 unique patients have been referred to the mobility and falls clinic. To date, 15% (45/339) of patients have scheduled an appointment with the clinic. CONCLUSIONS: This study seeks to quantify the impact of an ML-CDS intervention on patient behavior and outcomes. Our end-to-end data set allows for a more meaningful analysis of patient outcomes than other studies focused on interim outcomes, and our multisite implementation plan will demonstrate applicability to a broad population and the possibility to adapt the intervention to other EDs and achieve similar results. Our statistical methodology, regression discontinuity design, allows for causal inference from observational data and a staggered implementation strategy allows for the identification of secular trends that could affect causal associations and allow mitigation as necessary. TRIAL REGISTRATION: ClinicalTrials.gov NCT05810064; https://www.clinicaltrials.gov/study/NCT05810064. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/48128.

Health system and patient-level factors associated with multidisciplinary care and patient education among hospitalized, older cancer survivors.

Objective: The purpose of this study was to examine system- and patient-level factors associated with the number of healthcare disciplines involved in delivery of patient education among hospitalized older cancer survivors. Methods: We used electronic health record (EHR) data from a single institution documenting patient education among hospitalized older patients (≥65 years) with a history of cancer between 9/1/2018 and 10/1/2019. We used parametric ordinal logistic regression to assess the number of healthcare disciplines involved in documented education activities. Results: The sample (n = 446) was predominantly male, White, and on average 74 years old. Adjusting for patient and system-level variables, men and larger department units had higher odds of receiving education from fewer healthcare disciplines. Patients with a history of breast or prostate cancer and longer lenths of stay had lower odds of receiving patient education from fewer healthcare disciplines. Conclusion: Hospital size, severity of illness, and cancer type are associated with delivery of multidisciplinary education in this sample. Innovation: EHR provides an opportunity to identify patterns in patient education among cancer survivors. Future research should investigate provider perspectives of the findings to inform provider- and system-level strategies to improve patient education.

Cultural Humility Curriculum to Address Healthcare Disparities for Emergency Medicine Residents.

INTRODUCTION: Emergency medicine (EM) residency programs have variable approaches to educating residents on recognizing and managing healthcare disparities. We hypothesized that our curriculum with resident-presented lectures would increase residents' sense of cultural humility and ability to identify vulnerable populations. METHODS: At a single-site, four-year EM residency program with 16 residents per year, we designed a curriculum intervention from 2019-2021 where all second-year residents selected one healthcare disparity topic and gave a 15-minute presentation overviewing the disparity, describing local resources, and facilitating a group discussion. We conducted a prospective observational study to assess the impact of the curriculum by electronically surveying all current residents before and after the curriculum intervention. We measured attitudes on cultural humility and ability to identify healthcare disparities among a variety of patient characteristics (race, gender, weight, insurance, sexual orientation, language, ability, etc). Statistical comparisons of mean responses were calculated using the Mann-Whitney U test for ordinal data. RESULTS: A total of 32 residents gave presentations that covered a broad range of vulnerable patient populations including those that identify as Black, migrant farm workers, transgender, and deaf. The overall survey response was 38/64 (59.4%) pre-intervention and 43/64 (67.2%) post-intervention. Improvements were seen in resident self-reported cultural humility as measured by their responsibility to learn (mean responses of 4.73 vs 4.17; P < 0.001) and responsibility to be aware of different cultures (mean responses of 4.89 vs 4.42; P < 0.001). Residents reported an increased awareness that patients are treated differently in the healthcare system based on their race (P < 0.001) and gender (P < 0.001). All other domains queried, although not statistically significant, demonstrated a similar trend. CONCLUSION: This study demonstrates increased resident willingness to engage in cultural humility and the feasibility of resident near-peer teaching on a breadth of vulnerable patient populations seen in their clinical environment. Future studies may query the impact this curriculum has on resident clinical decision-making.

Positive oral contrast material for CT evaluation of non-traumatic abdominal pain in the ED: prospective assessment of diagnostic confidence and throughput metrics.

OBJECTIVE: Evaluate the impact of positive oral contrast material (POCM) for non-traumatic abdominal pain on diagnostic confidence, diagnostic rate, and ED throughput. MATERIALS AND METHODS: ED oral contrast guidelines were changed to limit use of POCM. A total of 2,690 abdominopelvic CT exams performed for non-traumatic abdominal pain were prospectively evaluated for diagnostic confidence (5-point scale at 20% increments; 5 = 80-100% confidence) during a 24-month period. Impact on ED metrics including time from CT order to exam, preliminary read, ED length of stay (LOS), and repeat CT scan within 7 days was assessed. A subset of cases (n = 729) was evaluated for diagnostic rate. Data were collected at 2 time points, 6 and 24 months following the change. RESULTS: A total of 38 reviewers were participated (28 trainees, 10 staff). 1238 exams (46%) were done with POCM, 1452 (54%) were performed without POCM. For examinations with POCM, 80% of exams received a diagnostic confidence score of 5 (mean, 4.78 ± 0.43; 99% ≥ 4), whereas 60% of exams without POCM received a score of 5 (mean, 4.51 ± 0.70; 92% ≥ 4; p < .001). Trainees scored 1,523 exams (57%, 722 + POCM, 801 -POCM) and showed even lower diagnostic confidence in cases without PCOM compared with faculty (mean, 4.43 ± 0.68 vs. 4.59 ± 0.71; p < 0.001). Diagnostic rate in a randomly selected subset of exams (n = 729) was 54.2% in the POCM group versus 56.1% without POCM (p < 0.655). CT order to exam time decreased by 31 min, order to preliminary read decreased by 33 min, and ED LOS decreased by 30 min (approximately 8% of total LOS) in the group without POCM compared to those with POCM (p < 0.001 for all). 205 patients had a repeat scan within 7 days, 74 (36%) had IV contrast only, 131 (64%) had both IV and oral contrast on initial exam. Findings were consistent both over a 6-month evaluation period as well as the full 24-month study period. CONCLUSION: Limiting use of POCM in the ED for non-traumatic abdominal pain improved ED throughput but impaired diagnostic confidence, particularly in trainees; however, it did not significantly impact diagnostic rates nor proportion of repeat CT exams.

Exploration of patient and caregiver cancer education using electronic health records.

The objective of this short report was to describe types of education provided to older, hospitalized patients with cancer and their caregivers using electronic health record data. A total of 437 patients, representing 512 inpatient stays (admissions), met the inclusion criteria. The sample were predominately male (58%) and White (95%). The average patient age at first admission was 74 years (SD 6.21 years) and the average length of admission was 5 days (SD 3.41 days). Out of all admissions, 89% included at least one documented education session with a provider. Three important results emerged from this study 1) education on medications is commonly conveyed to cancer patients (77%), 2) nurses are primarily responsible for providing education (65%), and 3) caregivers are infrequently involved (41%) in patient education. Additional educational topics tailored to the long-term needs of older adults with cancer are warranted. These topics should be delivered by an array of interprofessional care providers with demonstrated competency. Lastly, patient education should ensure inclusion of caregivers as part of the interprofessional cancer care team to promote successful management of cancer-related concerns.

Electronic Health Record-Based Surveillance for Community Transmitted COVID-19 in the Emergency Department.

INTRODUCTION: SARS-CoV-2, a novel coronavirus, manifests as a respiratory syndrome (COVID-19) and is the cause of an ongoing pandemic. The response to COVID-19 in the United States has been hampered by an overall lack of diagnostic testing capacity. To address uncertainty about ongoing levels of SARS-CoV-2 community transmission early in the pandemic, we aimed to develop a surveillance tool using readily available emergency department (ED) operations data extracted from the electronic health record (EHR). This involved optimizing the identification of acute respiratory infection (ARI)-related encounters and then comparing metrics for these encounters before and after the confirmation of SARS-CoV-2 community transmission. METHODS: We performed an observational study using operational EHR data from two Midwest EDs with a combined annual census of over 80,000. Data were collected three weeks before and after the first confirmed case of local SARS-CoV-2 community transmission. To optimize capture of ARI cases, we compared various metrics including chief complaint, discharge diagnoses, and ARI-related orders. Operational metrics for ARI cases, including volume, pathogen identification, and illness severity, were compared between the preand post-community transmission timeframes using chi-square tests of independence. RESULTS: Compared to our combined definition of ARI, chief complaint, discharge diagnoses, and isolation orders individually identified less than half of the cases. Respiratory pathogen testing was the top performing individual ARI definition but still only identified 72.2% of cases. From the pre to post periods, we observed significant increases in ED volumes due to ARI and ARI cases without identified pathogen. CONCLUSION: Certain methods for identifying ARI cases in the ED may be inadequate and multiple criteria should be used to optimize capture. In the absence of widely available SARS-CoV-2 testing, operational metrics for ARI-related encounters, especially the proportion of cases involving negative pathogen testing, are useful indicators for active surveillance of potential COVID-19 related ED visits.