Quality and safety implications of emergency department information systems.

The Health Information Technology for Economic and Clinical Health Act of 2009 and the Centers for Medicare & Medicaid Services "meaningful use" incentive programs, in tandem with the boundless additional requirements for detailed reporting of quality metrics, have galvanized hospital efforts to implement hospital-based electronic health records. As such, emergency department information systems (EDISs) are an important and unique component of most hospitals' electronic health records. System functionality varies greatly and affects physician decisionmaking, clinician workflow, communication, and, ultimately, the overall quality of care and patient safety. This article is a joint effort by members of the Quality Improvement and Patient Safety Section and the Informatics Section of the American College of Emergency Physicians. The aim of this effort is to examine the benefits and potential threats to quality and patient safety that could result from the choice of a particular EDIS, its implementation and optimization, and the hospital's or physician group's approach to continuous improvement of the EDIS. Specifically, we explored the following areas of potential EDIS safety concerns: communication failure, wrong order-wrong patient errors, poor data display, and alert fatigue. Case studies are presented that illustrate the potential harm that could befall patients from an inferior EDIS product or suboptimal execution of such a product in the clinical environment. The authors have developed 7 recommendations to improve patient safety with respect to the deployment of EDISs. These include ensuring that emergency providers actively participate in selection of the EDIS product, in the design of processes related to EDIS implementation and optimization, and in the monitoring of the system's ongoing success or failure. Our recommendations apply to emergency departments using any type of EDIS: custom-developed systems, best-of-breed vendor systems, or enterprise systems.

Association of a Geriatric Emergency Department Innovation Program With Cost Outcomes Among Medicare Beneficiaries.

Importance: There has been a significant increase in the implementation and dissemination of geriatric emergency department (GED) programs. Understanding the costs associated with patient care would yield insight into the direct financial value for patients, hospitals, health systems, and payers. Objective: To evaluate the association of GED programs with Medicare costs per beneficiary. Design, Setting, and Participants: This cross-sectional study included data on Medicare fee-for-service beneficiaries at 2 hospitals implementing Geriatric Emergency Department Innovations in Care Through Workforce, Informatics, and Structural Enhancement (GEDI WISE) (Mount Sinai Medical Center [MSMC] and Northwestern Memorial Hospital [NMH]) from January 1, 2013, to November 30, 2016. Analyses were conducted and refined from August 28, 2018, to November 20, 2020, using entropy balance to account for observed differences between the treatment and comparison groups. Interventions: Treatment included consultation with a transitional care nurse (TCN) or a social worker (SW) trained for the GEDI WISE program at a beneficiary's first ED visit (index ED visit). The comparison group included beneficiaries who were never seen by either a TCN or an SW during the study period. Main Outcomes and Measures: The main outcome evaluated was prorated total Medicare payer expenditures per beneficiary over 30 and 60 days after the index ED visit encounter. Results: Of the total 24 839 unique Medicare beneficiaries, 4041 were seen across the 2 EDs; 1947 (17.4%) at MSMC and 2094 (15.4%) at the NMH received treatment from either a GED TCN and/or a GED SW. The mean (SD) age of beneficiaries at MSMC was 78.8 (8.5) years and at NMH was 76.4 (7.7) years. Most patients at both hospitals were female (6821 [60.8%] at MSMC and 8023 [58.9%] at NMH) and White (7729 [68.9%] at MSMC and 9984 [73.3%] at NMH). Treatment was associated with statistically significant mean savings per beneficiary of $2436 (95% CI, $1760-$3111; P < .001) at one ED and $2905 (95% CI, $2378-$3431; P < .001) at the other ED in the 30 days after the index ED visit. The association between treatment and mean cumulative savings at 60 days after the index ED visit per beneficiary was also significant: $1200 (95% CI, $231-$2169; P = .02) at one ED and $3202 (95% CI, $2452-$3951; P < .001) at the other ED. Conclusions and Relevance: Among Medicare fee-for-service beneficiaries, receipt of ED-based geriatric treatment by a TCN and/or an SW was associated with lower Medicare expenditures. These estimated cost savings may be used when calculating or considering the bundled value and potential reimbursement per patient for GED care programs.

Clinical information system and process redesign improves emergency department efficiency.

BACKGROUND: Fueled by a decade-long increase in emergency department (ED) visits with a concomitant decrease in hospital bed capacity and the number of hospital EDs, ED crowding has reached crisis proportions. Robust information systems and process redesign are two strategies to improve the safety and quality of emergency care. At the ED at the Mount Sinai Medical Center, an urban, tertiary care academic medical center in New York City, elements of departmental work flow were redesigned to streamline patient throughput before implementation of a fully integrated emergency department information system (EDIS) with patient tracking, computerized charting and order entry, and direct access to patient historical data from the hospital data repository. Pre- and postintervention data were analyzed to examine the impact on (ED) efficiency. RESULTS: The length of stay for all patients (arrival to time patient left ED) decreased by 1.94 hours, from 6.69 (n = 508) pre-intervention to 4.75 (n = 691) postintervention (p < .001); doctor-to-disposition time (first doctor-patient contact to disposition decision) decreased by 1.90 hours, from 3.64 (n = 508) to 1.74 (n = 691; p < .001); door-to-doctor time (triage to first doctor-patient contact) decreased by 0.54 hours, from 1.22 (n = 508) to 0.68 (n = 691; p < .001). X-ray turnaround time (TAT) decreased by 0.18 hours from 0.92 (n = 60) to 0.74 (n = 108; p = .179); computerized tomography (CT) scan TAT decreased by 1.56 hours, from 3.89 (n = 40) to 2.33 (n = 29; p < .001), lab TAT decreased by 0.59 hours, from 2.03 (n = 121) to 1.44 (n = 271; p = .006). CONCLUSIONS: Increasing the clinical information available at the bedside and improving departmental work flow through EDIS implementation and process redesign led to decreased patient throughput times and improved ED efficiency.

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.

The emergency department occupancy rate: a simple measure of emergency department crowding?

STUDY OBJECTIVE: We examine the validity of the emergency department (ED) occupancy rate as a measure of crowding by comparing it to the Emergency Department Work Index Score (EDWIN), a previously validated scale. METHODS: A multicenter validation study was conducted according to ED visit data from 6 academic EDs for a 3-month period in 2005. Hourly ED occupancy rate (ie, total number of patients in ED divided by total number of licensed beds) and EDWIN scores were calculated. The correlation between the scales was determined and their validity evaluated by their ability to discriminate between hours when 1 or more patients left without being seen and hours when the ED was on ambulance diversion, using area under the curve (AUC) statistics estimated from the bootstrap method. RESULTS: We calculated the ED occupancy rate and EDWIN for 2,208 consecutive hours at each of the 6 EDs. The overall correlation between the 2 scales was 0.58 (95% confidence interval [CI] 0.56 to 0.60). The ED occupancy rate (AUC=0.73; 95% CI 0.65 to 0.80) and the EDWIN (AUC=0.65; 95% CI 0.58 to 0.72) did not differ significantly in correctly identifying hours when patients left without being seen. The ED occupancy rate (AUC=0.78; 95% CI 0.75 to 0.80) and the EDWIN (AUC=0.70; 95% CI 0.59 to 0.81) performed similarly for ED diversion hours. CONCLUSION: The ED occupancy rate and the EDWIN classified leaving without being seen and ambulance diversion hours with moderate accuracy. Although the ED occupancy rate is not ideal, its simplicity makes real-time assessment of crowding feasible for more EDs nationwide.

Redesigned geriatric emergency care may have helped reduce admissions of older adults to intensive care units.

Charged with transforming geriatric emergency care by applying palliative care principles, a process improvement team at New York City's Mount Sinai Medical Center developed the GEDI WISE (Geriatric Emergency Department Innovations in Care through Workforce, Informatics, and Structural Enhancements) model. The model introduced workforce enhancements for emergency department (ED) and adjunct staff, including role redefinition, retraining, and education in palliative care principles. Existing ED triage nurses screened patients ages sixty-five and older to identify those at high risk of ED revisit and hospital readmission. Once fully trained, these nurses screened all but 6 percent of ED visitors meeting the screening criteria. Newly hired ED nurse practitioners identified high-risk patients suitable for and desiring palliative and hospice care, then expedited referrals. Between January 2011 and May 2013 the percentage of geriatric ED admissions to the intensive care unit fell significantly, from 2.3 percent to 0.9 percent, generating an estimated savings of more than $3 million to Medicare. The decline in these admissions cannot be confidently attributed to the GEDI WISE program because other geriatric care innovations were implemented during the study period. GEDI WISE programs are now running at Mount Sinai and two partner sites, and their potential to affect the quality and value of geriatric emergency care continues to be examined.

Automating research data collection.

This article reviews the capabilities, advantages, and disadvantages of three forms of automated data collection-scannable data forms, Web-based forms, and handheld computers-compared with the current standard of data entry by hand on paper forms. Each of these methods is reviewed with respect to ease of use, experience required of designer, end-user training requirements, costs, flexibility, speed, accuracy/error rate, potential for data loss, need for technical support, and equipment and/or software requirements. A discussion of their appropriate application to various kinds of studies is included, followed by examples of research studies using each of these methods.

Care and Respect for Elders in Emergencies program: a preliminary report of a volunteer approach to enhance care in the emergency department.

Older adults who present to an emergency department (ED) generally have more-complex medical conditions with complicated care needs and are at high risk for preventable adverse outcomes during their ED visit. The Care and Respect for Elders with Emergencies (CARE) volunteer initiative is a geriatric-focused volunteer program developed to help prevent avoidable complications such as falls, delirium and use of restraints, and functional decline in vulnerable elders in the ED. The CARE program consists of bedside volunteer interventions ranging from conversation to various short activities designed to engage and reorient high-risk, older, unaccompanied individuals in the ED. This article describes the development and characteristics of the CARE program, the services provided, the experiences of the elderly patients and their volunteers, and the growth of the program over time. CARE volunteers provide elders with the additional attention needed in an often chaotic, unfamiliar environment by enhancing their care, improving satisfaction, and preventing potential decline.

Electronic collaboration: using technology to solve old problems of quality care.

The participants of the Electronic Collaboration working group of the 2010 Academic Emergency Medicine consensus conference developed recommendations and research questions for improving regional quality of care through the use of electronic collaboration. A writing group devised a working draft prior to the meeting and presented this to the breakout session at the consensus conference for input and approval. The recommendations include: 1) patient health information should be available electronically across the entire health care delivery system from the 9-1-1 call to the emergency department (ED) visit through hospitalization and outpatient care, 2) relevant patient health information should be shared electronically across the entire health care delivery system, 3) Web-based collaborative technologies should be employed to facilitate patient transfer and timely access to specialists, 4) personal health record adoption should be considered as a way to improve patient health, and 5) any comprehensive reform of regionalization in emergency care must include telemedicine. The workgroup emphasized the need for funding increases so that research in this new and exciting area can expand.

Emergency department information system implementation and process redesign result in rapid and sustained financial enhancement at a large academic center.

OBJECTIVES: The objectives were to measure the financial impact of implementing a fully integrated emergency department information system (EDIS) and determine the length of time to "break even" on the initial investment. METHODS: A before-and-after study design was performed using a framework of analysis consisting of four 15-month phases: 1) preimplementation, 2) peri-implementation, 3) postimplementation, and 4) sustained effects. Registration and financial data were reviewed. Costs and rates of professional and facility charges and receipts were calculated for the phases in question and compared against monthly averages for covariates such as volume, collections rates, acuity, age, admission rate, and insurance status with an autoregressive time series analysis using a segmented model. The break-even point was calculated by measuring cumulative monthly receipts for the last three study phases in excess of the average monthly receipts from the preimplementation phase, corrected for change in volume, and then plotting this against cumulative overall cost. RESULTS: Time to break even on the initial EDIS investment was less than 8 months. Total revenue enhancement at the end of the 5-year study period was $16,138,953 with an increase of 69.40% in charges and 70.06% in receipts. This corresponds to an increase in receipts per patient from $50 to $90 for professional services and $131 to $183 for facilities charges. Other than volume, there were no significant changes in trends for covariates between the preimplementation and sustained-effects periods. CONCLUSIONS: A comprehensive EDIS implementation with process redesign resulted in sustained increases in professional and facility revenues and a rapid initial break-even point. .

Knowledge translation of the American College of Emergency Physicians' clinical policy on syncope using computerized clinical decision support.

AIMS: To influence physician practice behavior after implementation of a computerized clinical decision support system (CDSS) based upon the recommendations from the 2007 ACEP Clinical Policy on Syncope. METHODS: This was a pre-post intervention with a prospective cohort and retrospective controls. We conducted a medical chart review of consecutive adult patients with syncope. A computerized CDSS prompting physicians to explain their decision-making regarding imaging and admission in syncope patients based upon ACEP Clinical Policy recommendations was embedded into the emergency department information system (EDIS). The medical records of 410 consecutive adult patients presenting with syncope were reviewed prior to implementation, and 301 records were reviewed after implementation. Primary outcomes were physician practice behavior demonstrated by admission rate and rate of head computed tomography (CT) imaging before and after implementation. RESULTS: There was a significant difference in admission rate pre- and post-intervention (68.1% vs. 60.5% respectively, p = 0.036). There was no significant difference in the head CT imaging rate pre- and post-intervention (39.8% vs. 43.2%, p = 0.358). There were seven physicians who saw ten or more patients during the pre- and post-intervention. Subset analysis of these seven physicians' practice behavior revealed a slight significant difference in the admission rate pre- and post-intervention (74.3% vs. 63.9%, p = 0.0495) and no significant difference in the head CT scan rate pre- and post-intervention (42.9% vs. 45.4%, p = 0.660). CONCLUSIONS: The introduction of an evidence-based CDSS based upon ACEP Clinical Policy recommendations on syncope correlated with a change in physician practice behavior in an urban academic emergency department. This change suggests emergency medicine clinical practice guideline recommendations can be incorporated into the physician workflow of an EDIS to enhance the quality of practice.