Precision medicine within health professions education: Defining a research agenda for emergency medicine using a foresight and strategy technique (FaST) review.

Background: Precision medicine, sometimes referred to as personalized medicine, is rapidly changing the possibilities for how people will engage health care in the near future. As technology to support precision medicine exponentially develops, there is an urgent need to proactively improve our understanding of precision medicine and pose important research questions (RQs) related to its inclusion in the education and training of future emergency physicians. Methods: A seven-step process was employed to develop a research agenda exploring the intersection of precision and emergency medicine education/training. A literature search of articles about precision medicine was conducted first, which informed the creation of future four scenarios in which trainees and practicing physicians regularly discuss and incorporate precision medicine tools into their discussions and work. Based on these futurist narratives, potential education RQs were generated by an expert panel. A total of 59 initial questions were subsequently categorized and refined to a priority list through a nominal group voting method. The top/priority questions were presented at the 2023 SAEM Consensus Conference on Precision Medicine, Austin, Texas, for further input. Results: Eight high-value education RQs were developed, reflecting a holistic view of the challenges and opportunities for precision medicine education in the knowledge, skills, and attitudes relevant to emergency medicine. These questions contend with topics such as most effective pedagogical methods; intended resulting outcomes and behaviors; the generational differences between practicing emergency physicians, educators, and future trainees; and the desires and expectations of patients. Conclusions: Emergency medicine and emergency physicians must be prepared to understand precision medicine and incorporate this information into their "toolbox" of thinking, problem solving, and communication with patients and colleagues. This research agenda on how best to educate future emergency physicians in the use of personalized data to provide optimal health care is the focus of this article.

TRIAD VIII: Nationwide Multicenter Evaluation to Determine Whether Patient Video Testimonials Can Safely Help Ensure Appropriate Critical Versus End-of-Life Care.

OBJECTIVE: End-of-life interventions should be predicated on consensus understanding of patient wishes. Written documents are not always understood; adding a video testimonial/message (VM) might improve clarity. Goals of this study were to (1) determine baseline rates of consensus in assigning code status and resuscitation decisions in critically ill scenarios and (2) determine whether adding a VM increases consensus. METHODS: We randomly assigned 2 web-based survey links to 1366 faculty and resident physicians at institutions with graduate medical education programs in emergency medicine, family practice, and internal medicine. Each survey asked for code status interpretation of stand-alone Physician Orders for Life-Sustaining Treatment (POLST) and living will (LW) documents in 9 scenarios. Respondents assigned code status and resuscitation decisions to each scenario. For 1 of 2 surveys, a VM was included to help clarify patient wishes. RESULTS: Response rate was 54%, and most were male emergency physicians who lacked formal advanced planning document interpretation training. Consensus was not achievable for stand-alone POLST or LW documents (68%-78% noted "DNR"). Two of 9 scenarios attained consensus for code status (97%-98% responses) and treatment decisions (96%-99%). Adding a VM significantly changed code status responses by 9% to 62% (P ≤ 0.026) in 7 of 9 scenarios with 4 achieving consensus. Resuscitation responses changed by 7% to 57% (P ≤ 0.005) with 4 of 9 achieving consensus with VMs. CONCLUSIONS: For most scenarios, consensus was not attained for code status and resuscitation decisions with stand-alone LW and POLST documents. Adding VMs produced significant impacts toward achieving interpretive consensus.

Impact of Health Information Exchange on Emergency Medicine Clinical Decision Making.

INTRODUCTION: The objective of the study was to understand the immediate utility of health information exchange (HIE) on emergency department (ED) providers by interviewing them shortly after the information was retrieved. Prior studies of physician perceptions regarding HIE have only been performed outside of the care environment. METHODS: Trained research assistants interviewed resident physicians, physician assistants and attending physicians using a semi-structured questionnaire within two hours of making a HIE request. The responses were recorded, then transcribed for qualitative analysis. The transcribed interviews were analyzed for emerging qualitative themes. RESULTS: We analyzed 40 interviews obtained from 29 providers. Primary qualitative themes discovered included the following: drivers for requests for outside information; the importance of unexpected information; historical lab values as reference points; providing context when determining whether to admit or discharge a patient; the importance of information in refining disposition; improved confidence of provider; and changes in decisions for diagnostic imaging. CONCLUSION: ED providers are driven to use HIE when they're missing a known piece of information. This study finds two additional impacts not previously reported. First, providers sometimes find additional unanticipated useful information, supporting a workflow that lowers the threshold to request external information. Second, providers sometimes report utility when no changes to their existing plan are made as their confidence is increased based on external records. Our findings are concordant with previous studies in finding exchanged information is useful to provide context for interpreting lab results, making admission decisions, and prevents repeat diagnostic imaging.

Magnetic resonance imaging and computed tomography utilization trends in an academic ED.

OBJECTIVE: The objective of this study is to examine the annual utilization trends of emergency department (ED)-ordered magnetic resonance imaging (MRI) and computed tomography (CT) at an urban academic hospital from 2007 to 2011. We hypothesized that MRI and CT use would increase annually over the study period. METHODS: This was a retrospective observational study of ED encounters between January 1, 2007, and December 31, 2011. All patients seen by a provider were identified, and demographics were abstracted. Type of CT and/or MRI examination, clinical indication, and final disposition were collected. Records of patients with an ED-ordered MRI were also examined for presence of a CT within ±3 days of their encounter date. Unadjusted linear regression was used to assess for differences among years for both CT and MRI. Secondary outcomes were descriptively summarized. RESULTS: A total of 7089 MRI (20 per 1000) and 85,673 CT (243 per 1000) examinations were ordered over a 60-month period. Computed tomography use decreased significantly (P=.021). Magnetic resonance imaging use significantly increased (2.2 per 1000 ED visits each year, P=.005). Magnetic resonance imaging of the head was ordered most frequently (10.7 per 1000). The overwhelming majority of MRI images were completed for acute neurologic/behavioral problem. Of patients with an MRI completed, 89.4% had a CT completed within 3 calendar days with most of the CT examinations (81%) completed during the encounter. CONCLUSION: There was a steady increase in MRI testing in our academic ED, with most MRIs ordered for acute neurologic or behavioral changes. There was a corresponding decreasing trend for CT scans.

The impact of electronic health records on care of heart failure patients in the emergency room.

OBJECTIVE: To evaluate if electronic health records (EHR) have observable effects on care outcomes, we examined quality and efficiency measures for patients presenting to emergency departments (ED). MATERIALS AND METHODS: We conducted a retrospective study of 5166 adults with heart failure in three metropolitan EDs. Patients were termed internal if prior information was in the EHR upon ED presentation, otherwise external. Associations of internality with hospitalization, mortality, length of stay (LOS), and numbers of tests, procedures, and medications ordered in the ED were examined after adjusting for age, gender, race, marital status, comorbidities and hospitalization as a proxy for acuity level where appropriate. RESULTS: At two EDs internals had lower odds of mortality if hospitalized (OR 0.55; 95% CI 0.38 to 0.81 and 0.45; 0.21 to 0.96), fewer laboratory tests during the ED visit (-4.6%; -8.9% to -0.1% and -14.0%; -19.5% to -8.1%) as well as fewer medications (-33.6%; -38.4% to -28.4% and -21.3%; -33.2% to -7.3%). At one of these two EDs, internals had lower odds of hospitalization (0.37; 0.22 to 0.60). At the third ED, internal patients only experienced a prolonged ED LOS (32.3%; 6.3% to 64.8%) but no other differences. There was no association with hospital LOS or number of procedures ordered. DISCUSSION: EHR availability was associated with salutary outcomes in two of three ED settings and prolongation of ED LOS at a third, but evidence was mixed and causality remains to be determined. CONCLUSIONS: An EHR may have the potential to be a valuable adjunct in the care of heart failure patients.

Forecasting emergency department crowding: an external, multicenter evaluation.

STUDY OBJECTIVE: We apply a previously described tool to forecast emergency department (ED) crowding at multiple institutions and assess its generalizability for predicting the near-future waiting count, occupancy level, and boarding count. METHODS: The ForecastED tool was validated with historical data from 5 institutions external to the development site. A sliding-window design separated the data for parameter estimation and forecast validation. Observations were sampled at consecutive 10-minute intervals during 12 months (n=52,560) at 4 sites and 10 months (n=44,064) at the fifth. Three outcome measures-the waiting count, occupancy level, and boarding count-were forecast 2, 4, 6, and 8 hours beyond each observation, and forecasts were compared with observed data at corresponding times. The reliability and calibration were measured following previously described methods. After linear calibration, the forecasting accuracy was measured with the median absolute error. RESULTS: The tool was successfully used for 5 different sites. Its forecasts were more reliable, better calibrated, and more accurate at 2 hours than at 8 hours. The reliability and calibration of the tool were similar between the original development site and external sites; the boarding count was an exception, which was less reliable at 4 of 5 sites. Some variability in accuracy existed among institutions; when forecasting 4 hours into the future, the median absolute error of the waiting count ranged between 0.6 and 3.1 patients, the median absolute error of the occupancy level ranged between 9.0% and 14.5% of beds, and the median absolute error of the boarding count ranged between 0.9 and 2.8 patients. CONCLUSION: The ForecastED tool generated potentially useful forecasts of input and throughput measures of ED crowding at 5 external sites, without modifying the underlying assumptions. Noting the limitation that this was not a real-time validation, ongoing research will focus on integrating the tool with ED information systems.

Accuracy of staff-initiated emergency department tracking system timestamps in identifying actual event times.

STUDY OBJECTIVE: Managers use timestamps from computerized tracking systems to evaluate emergency department (ED) processes. This study was designed to determine how accurately these timestamps reflect the actual ED events they purport to represent. METHODS: An observer manually timestamped patient and provider movement events during all hours. The observed timestamps were then systematically matched to equivalent timestamps collected by an active tracking system (timestamps created by staff with keyboard/mouse) and a passive tracking system (timestamps created by sensor badge worn by staff members). The deviation intervals between the matched timestamps were analyzed. RESULTS: The observer noted a total of 901 events; 686 (76%) of these were successfully matched to active system timestamps and 60 (6.7%) were matched to passive system timestamps. For the active system, the median event was recorded 1.8 minutes before it was observed (interquartile range 30.7 minutes before to 2.9 minutes after). Protocol execution difficulties limited the study of the passive system (low number of successfully matched events). The median event was recorded by the passive system 1.1 minutes before it was observed (interquartile range 1.3 minutes before to 0.9 minutes before) (n=60). CONCLUSION: The timestamps recorded by both active and passive tracking systems contain systematic errors and nonnormal distributions. The active system had much lower precision than the passive system but similar accuracy when large numbers of active system observations were used. Medians should be used to represent timestamp and interval data for reporting purposes. Site-specific data validation should be performed before use of data in high-profile situations.

Advanced statistics: developing a formal model of emergency department census and defining operational efficiency.

BACKGROUND: Emergency department (ED) crowding has been a frequent topic of investigation, but it is a concept without an objective definition. This has limited the scope of research and progress toward the development of consistent and meaningful operational responses. OBJECTIVES: To develop a straightforward model of ED census that incorporates concepts of ED crowding, daily patient surge, throughput time, and operational efficiency. METHODS: Using 2005-2006 patient encounter data at a Level 1 urban trauma center, a set of three stylized facts describing daily patterns of ED census was observed. These facts guided the development of a formal, mathematical model of ED census. Using this model, a metric of ED operational efficiency and a forecast of ED census were developed. RESULTS: The three stylized facts of daily ED census were 1) ED census is cyclical, 2) ED census exhibits an input-output relationship, and 3) unexpected shocks have long-lasting effects. These were represented by a three-equation system. This system was solved for the following expression, Census(t) = A(.) + B(.) cos(vT + epsilon) + a(e(t)), that captured the time path of ED census. Using nonlinear estimation, the parameters of this expression were estimated and a forecasting tool was developed. CONCLUSIONS: The basic pattern of ED census can be represented by a straightforward expression. This expression can be quickly adapted to a variety of inquiries regarding ED crowding, daily surge, and operational efficiency.

Developing models for patient flow and daily surge capacity research.

Between 1993 and 2003, visits to U.S. emergency departments (EDs) increased by 26%, to a total of 114 million visits annually. At the same time, the number of U.S. EDs decreased by more than 400, and almost 200,000 inpatient hospital beds were taken out of service. In this context, the adequacy of daily surge capacity within the system is clearly an important issue. However, the research agenda on surge capacity thus far has focused primarily on large-scale disasters, such as pandemic influenza or a serious bioterrorism event. The concept of daily surge capacity and its relationship to the broader research agenda on patient flow is a relatively new area of investigation. In this article, the authors begin by describing the overlap between the research agendas on daily surge capacity and patient flow. Next, they propose two models that have potential applications for both daily surge capacity and hospitalwide patient-flow research. Finally, they identify potential research questions that are based on applications of the proposed research models.

Using online analytical processing to manage emergency department operations.

The emergency department (ED) is a unique setting in which to explore and evaluate the utility of information technology to improve health care operations. A potentially useful software tool in managing this complex environment is online analytical processing (OLAP). An OLAP system has the ability to provide managers, providers, and researchers with the necessary information to make decisions quickly and effectively by allowing them to examine patterns and trends in operations and patient flow. OLAP software quickly summarizes and processes data acquired from a variety of data sources, including computerized ED tracking systems. It allows the user to form a comprehensive picture of the ED from both system-wide and patient-specific perspectives and to interactively view the data using an approach that meets his or her needs. This article describes OLAP software tools and provides examples of potential OLAP applications for care improvement projects, primarily from the perspective of the ED. While OLAP is clearly a helpful tool in the ED, it is far more useful when integrated into the larger continuum of health information systems across a hospital or health care delivery system.