The effect of electronic health record implementation on community emergency department operational measures of performance

Electronic medical record implementation in the emergency department in a low-resource country: Lessons learned

OBJECTIVE

There is paucity of information regarding electronic medical record (EMR) implementation in emergency departments in countries outside the United States especially in low-resource settings. The objective of this study is to describe strategies for a successful implementation of an EMR in the emergency department and to examine the impact of this implementation on the department's operations and patient-related metrics.

METHODS

We performed an observational retrospective study at the emergency department of a tertiary care center in Beirut, Lebanon. We assessed the effect of EMR implementation by tracking emergency departments' quality metrics during a one-year baseline period and one year after implementation. End-user satisfaction and patient satisfaction were also assessed.

RESULTS

Our evaluation of the implementation of EMR in a low resource setting showed a transient increase in LOS and visit-to-admission decision, however this returned to baseline after around 6 months. The bounce-back rate also increased. End-users were satisfied with the new EMR and patient satisfaction did not show a significant change.

CONCLUSIONS

Lessons learned from this successful EMR implementation include a mix of strategies recommended by the EMR vendor as well as specific strategies used at our institution. These can be used in future implementation projects in low-resource settings to avoid disruption of workflows.

Definitions and factors associated with emergency physician productivity: a scoping review

PURPOSE

There currently exists no standard productivity measure for emergency physicians. The objectives of this scoping review were to synthesize the literature to identify components of definitions and measurements of emergency physician productivity and to evaluate factors associated with productivity.

METHODS

We searched Medline, Embase, CINAHL, and ProQuest One Business from inception to May 2022. We included all studies that reported on emergency physician productivity. We excluded studies that only reported departmental productivity, studies with non-emergency providers, review articles, case reports, and editorials. Data were extracted into predefined worksheets and a descriptive summary was presented. Quality analysis was performed with Newcastle-Ottawa Scale.

RESULTS

After screening 5521 studies, 44 studies met full inclusion criteria. Components of the definition for emergency physician productivity included: number of patients managed, revenue generated, patient processing time, and a standardization factor. Most studies measured productivity using patients per hour, relative value units per hour, and provider-to-disposition time. The most studied factors influencing productivity included scribes, resident learners, electronic medical record implementation, and faculty teaching scores.

CONCLUSION

Emergency physician productivity is heterogeneously defined, but includes common elements such as patient volume, complexity, and processing time. Commonly reported productivity metrics include patients per hour and relative value units that incorporate patient volume and complexity, respectively. The findings of this scoping review can guide ED physicians and administrators to measure the impact of QI initiatives, promote efficient patient care, and optimize physician staffing.

Benchmarking emergency department prediction models with machine learning and public electronic health records

The demand for emergency department (ED) services is increasing across the globe, particularly during the current COVID-19 pandemic. Clinical triage and risk assessment have become increasingly challenging due to the shortage of medical resources and the strain on hospital infrastructure caused by the pandemic. As a result of the widespread use of electronic health records (EHRs), we now have access to a vast amount of clinical data, which allows us to develop prediction models and decision support systems to address these challenges. To date, there is no widely accepted clinical prediction benchmark related to the ED based on large-scale public EHRs. An open-source benchmark data platform would streamline research workflows by eliminating cumbersome data preprocessing, and facilitate comparisons among different studies and methodologies. Based on the Medical Information Mart for Intensive Care IV Emergency Department (MIMIC-IV-ED) database, we created a benchmark dataset and proposed three clinical prediction benchmarks. This study provides future researchers with insights, suggestions, and protocols for managing data and developing predictive tools for emergency care.

Understanding the impacts of health information systems on patient flow management: A systematic review across several decades of research

Background

Patient flow describes the progression of patients along a pathway of care such as the journey from hospital inpatient admission to discharge. Poor patient flow has detrimental effects on health outcomes, patient satisfaction and hospital revenue. There has been an increasing adoption of health information systems (HISs) in various healthcare settings to address patient flow issues, yet there remains limited evidence of their overall impacts.

Objective

To systematically review evidence on the impacts of HISs on patient flow management including what HISs have been used, their application scope, features, and what aspects of patient flow are affected by the HIS adoption.

Methods

A systematic search for English-language, peer-review literature indexed in MEDLINE and EMBASE, CINAHL, INSPEC, and ACM Digital Library from the earliest date available to February 2022 was conducted. Two authors independently scanned the search results for eligible publications, and reporting followed the PRISMA guidelines. Eligibility criteria included studies that reported impacts of HIS on patient flow outcomes. Information on the study design, type of HIS, key features and impacts was extracted and analysed using an analytical framework which was based on domain-expert opinions and literature review.

Results

Overall, 5996 titles were identified, with 44 eligible studies, across 17 types of HIS. 22 studies (50%) focused on patient flow in the department level such as emergency department while 18 studies (41%) focused on hospital-wide level and four studies (9%) investigated network-wide HIS. Process outcomes with time-related measures such as ‘length of stay’ and ‘waiting time’ were investigated in most of the studies. In addition, HISs were found to address flow problems by identifying blockages, streamlining care processes and improving care coordination.

Conclusion

HIS affected various aspects of patient flow at different levels of care; however, how and why they delivered the impacts require further research.

Impact of Scribes with Flow Coordination Duties on Throughput in an Academic Emergency Department

Introduction

With the increasing influence of electronic health records in emergency medicine came concerns of decreasing operational efficiencies. Particularly worrisome was increasing patient length of stay (LOS). Medical scribes were identified to be in a good position to quickly address barriers to treatment delivery and patient flow. The objective of this study was to investigate patient LOS in the mid- and low-acuity zones of an academic emergency department (ED) with and without medical scribes.

Methods

A retrospective cohort study compared patient volume and average LOS between a cohort without scribes and a cohort after the implementation of a scribe-flow coordinator program. Patients were triaged to the mid-acuity Vertical Zone (primarily Emergency Severity Index [ESI] 3) or low-acuity Fast Track (primarily ESI 4 and 5) at a tertiary academic ED. Patients were stratified by treatment zone, acuity level, and disposition.

Results

The pre-intervention and post-intervention periods included 8900 patients and 9935 patients, respectively. LOS for patients discharged from the Vertical Zone decreased by 12 minutes from 235 to 223 minutes (p<0.0001, 95% confidence interval [CI], −17,−7) despite a 10% increase in patient volume. For patients admitted from the Vertical Zone, volume increased 13% and LOS remained almost the same, increasing from 225 to 228 minutes (p=0.532, 95% CI, −6,12). For patients discharged from the Fast Track, volume increased 14% and LOS increased six minutes, from 89 to 95 minutes (p<0.0001, 95% CI, 4,9). Predictably, only 1% of Fast Track patients were admitted.

Conclusion

Despite substantially increased volume, the use of scribes as patient flow facilitators in the mid-acuity zone was associated with decreased LOS. In the low-acuity zone, scribes were not shown to be as effective, perhaps because rapid patient turnover required them to focus on documentation.

An assessment of emergency department information systems based on the HL7 functional profile

CONTEXT

Emergency Department Information System (EDIS) plays a significant role in supporting the emergency department (ED) workflow. Hence, it is vital to assess the services provided by this system in order to identify its strengths and weaknesses.

AIMS

The study aimed to assess the information systems in use in the ED of 11 teaching hospitals associated with Isfahan University of Medical Sciences (IUMS) so as to identify their strengths and weaknesses and improving the quality of these systems.

SETTINGS AND DESIGN

This study was conducted using descriptive-applied research method.

SUBJECTS AND METHODS

Data collection tool was a checklist developed based on EDIS functional profile. It covered two sections of the profile, namely direct care and supportive functions and their respective subsections.

STATISTICAL ANALYSIS USED

Data were analyzed using descriptive statistics through the estimation of the frequency and frequency percentage for each respective section and subsections using SPSS software v. 20.

RESULTS

The content conformance rate of the information systems in use in the EDs of IUMS' teaching hospitals was found to be 49.72% and 75.25% for the direct care section and supportive functions section, respectively. In addition, the overall conformance rate in the hospitals surveyed was up to 53.15%.

CONCLUSION

As per the findings of this study, it is suggested that some important clinical and administrative functions should be incorporated into the redesigned information systems in use in the EDs under study.

What to expect from electronic patient record system implementation: lessons learned from published evidence

Background

Numerous studies have examined factors related to success, failure and implications of electronic patient record (EPR) system implementations, but usually limited to specific aspects.

Objective

To review the published peer-reviewed literature and present findings regarding factors important in relation to successful EPR implementations and likely impact on subsequent clinical activity.

Method

Literature review.

Results

Three hundred and twelve potential articles were identified on initial search, of which 117 were relevant and included in the review. Several factors were related to implementation success, such as good leadership and management, infrastructure support, staff training and focus on workflows and usability. In general, EPR implementation is associated with improvements in documentation and screening performance and reduced prescribing errors, whereas there are minimal available data in other areas such as effects on clinical patient outcomes. The peer-reviewed literature appears to under-represent a range of technical factors important for EPR implementations, such as data migration from existing systems and impact of organisational readiness.

Conclusion

The findings presented here represent the synthesis of data from peer-reviewed literature in the field and should be of value to provide the evidence-base for organisations considering how best to implement an EPR system.

Modelling attending physician productivity in the emergency department: a multicentre study

Objectives

Emergency physician productivity, often defined as new patients evaluated per hour, is essential to planning clinical operations. Prior research in this area considered this a static quantity; however, our group’s study of resident physicians demonstrated significant decreases in hourly productivity throughout shifts. We now examine attending physicians’ productivity to determine if it is also dynamic.

Methods

This is a retrospective cohort study, conducted from 2014 to 2016 across three community hospitals in the north-eastern USA, with different schedules and coverage. Timestamps of all patient encounters were automatically logged by the sites’ electronic health record. Generalised estimating equations were constructed to predict productivity in terms of new patients per shift hour.

Results

207 169 patients were seen by 64 physicians over 2 years, comprising 9822 physician shifts. Physicians saw an average of 15.0 (SD 4.7), 20.9 (SD 6.4) and 13.2 (SD 3.8) patients per shift at the three sites, with 2.97 (SD 0.22), 2.95 (SD 0.24) and 2.17 (SD 0.09) in the first hour. Across all sites, physicians saw significantly fewer new patients after the first hour, with more gradual decreases subsequently. Additional patient arrivals were associated with greater productivity; however, this attenuates substantially late in the shift. The presence of other physicians was also associated with slightly decreased productivity.

Conclusions

Physician productivity over a single shift follows a predictable pattern that decreases significantly on an hourly basis, even if there are new patients to be seen. Estimating productivity as a simple average substantially underestimates physicians’ capacity early in a shift and overestimates it later. This pattern of productivity should be factored into hospitals’ staffing plans, with shifts aligned to start with the greatest volumes of patient arrivals.

Digital disruption ‘syndromes’ in a hospital: important considerations for the quality and safety of patient care during rapid digital transformation

The digital transformation of hospitals in Australia is occurring rapidly in order to facilitate innovation and improve efficiency. Rapid transformation can cause temporary disruption of hospital workflows and staff as processes are adapted to the new digital workflows. The aim of this paper is to outline various types of digital disruption and some strategies for effective management. A large tertiary university hospital recently underwent a rapid, successful roll-out of an integrated electronic medical record (EMR). We observed this transformation and propose several digital disruption “syndromes” to assist with understanding and management during digital transformation: digital deceleration, digital transparency, digital hypervigilance, data discordance, digital churn and post-digital ‘depression’. These ‘syndromes’ are defined and discussed in detail. Successful management of this temporary digital disruption is important to ensure a successful transition to a digital platform. What is known about this topic? Digital disruption is defined as the changes facilitated by digital technologies that occur at a pace and magnitude that disrupt established ways of value creation, social interactions, doing business and more generally our thinking. Increasing numbers of Australian hospitals are implementing digital solutions to replace traditional paper-based systems for patient care in order to create opportunities for improved care and efficiencies. Such large scale change has the potential to create transient disruption to workflows and staff. Managing this temporary disruption effectively is an important factor in the successful implementation of an EMR. What does this paper add? A large tertiary university hospital recently underwent a successful rapid roll-out of an integrated electronic medical record (EMR) to become Australia’s largest digital hospital over a 3-week period. We observed and assisted with the management of several cultural, behavioural and operational forms of digital disruption which lead us to propose some digital disruption ‘syndromes’. The definition and management of these ‘syndromes’ are discussed in detail. What are the implications for practitioners? Minimising the temporary effects of digital disruption in hospitals requires an understanding that these digital ‘syndromes’ are to be expected and actively managed during large-scale transformation.

A Custom-Developed Emergency Department Provider Electronic Documentation System Reduces Operational Efficiency

STUDY OBJECTIVE

Electronic health record implementation can improve care, but may also adversely affect emergency department (ED) efficiency. We examine how a custom, ED provider, electronic documentation system (eDoc), which replaced paper documentation, affects operational performance.

METHODS

We analyzed retrospective operational data for 1-year periods before and after eDoc implementation in a single ED. We computed daily operational statistics, reflecting 60,870 pre- and 59,337 postimplementation patient encounters. The prespecified primary outcome was daily mean length of stay; secondary outcomes were daily mean length of stay for admitted and discharged patients and daily mean arrival time to disposition for admitted patients. We used a prespecified multiple regression model to identify differences in outcomes while controlling for prespecified confounding variables.

RESULTS

The unadjusted change in length of stay was 8.4 minutes; unadjusted changes in secondary outcomes were length of stay for admitted patients 11.4 minutes, length of stay for discharged patients 1.8 minutes, and time to disposition 1.8 minutes. With a prespecified regression analysis to control for variations in operational characteristics, there were significant increases in length of stay (6.3 minutes [95% confidence interval 3.5 to 9.1 minutes]) and length of stay for discharged patients (5.1 minutes [95% confidence interval 1.9 to 8.3 minutes]). There was no statistically significant change in length of stay for admitted patients or time to disposition.

CONCLUSION

In our single-center study, the isolated implementation of eDoc was associated with increases in overall and discharge length of stay. Our findings suggest that a custom-designed electronic provider documentation may negatively affect ED throughput. Strategies to mitigate these effects, such as reducing documentation requirements or adding clinical staff, scribes, or voice recognition, would be a valuable area of future research.

A Prospective Emergency Department Quality Improvement Project to Improve the Treatment of Vaso-Occlusive Crisis in Sickle Cell Disease: Lessons Learned

BACKGROUND

Guidelines recommend rapid, aggressive management of vaso-occlusive crisis (VOC) for patients with sickle cell disease (SCD). A large prospective research and quality improvement (QI) project was conducted to measure changes in clinical outcomes in two EDs-academic medical centers with emergency medicine residency programs and Level 1 trauma centers-during a 2.5-year time period (October 2011-March 2014).

METHODS

A QI team used a Plan-Do-Study-Act approach to modify and implement changes to opioid analgesic protocols for the emergency department (ED) treatment of VOC. Data were collected quarterly; the team reviewed the results and made modifications to improve outcomes. A structured health record review was conducted to assess clinical outcomes (10 records/quarter/site). Patient interviews were conducted to measure satisfaction with pain management. Outcomes were compared before (T1) and after (T2) implementation of an electronic health record (EHR).

RESULTS

One hundred ninety-six ED health records (118 unique patients, mean age = 32 [standard deviation, 11], 51% male) were analyzed. Before implementation, trends in decreasing time to initial analgesic administration were noted. There was a statistically significant increase in arrival to administration of first analgesic time between T1 and T2 at Site 1 but not at Site 2. Neither site showed significant changes in time between the administration of the first and second opioid doses, total opioid dose administered, or patient satisfaction.

CONCLUSION

While QI efforts initially shortened door-to-analgesic times, these gains were not sustained. The lessons learned can help other EDs improve the timely delivery of analgesics to patients with SCD.

Improving Guideline-Based Care of Acute Asthma in a Pediatric Emergency Department

BACKGROUND AND OBJECTIVE

Rapid repetitive administration of short-acting β-agonists (SABA) is the most effective means of reducing acute airflow obstruction in asthma. Little evidence exists that assesses process measures (ie, timeliness) and outcomes for asthma. We used quality improvement (QI) methods to improve emergency department care in accordance with national guidelines including timely SABA administration and use of asthma severity scores.

METHODS

The Model for Improvement was used and interventions were targeted at 4 key drivers: knowledge, engagement, decision support, and workflow enhancement. Time series analysis was performed and outcomes assessed on statistical process control charts.

RESULTS

Asthma severity scoring increased from 0% to >95% in triage and to >75% for repeat scores. Time to first SABA (T1) improved by 32.8 minutes (47%). T1 for low severity patients improved by 17.6 minutes (28%). T1 for high severity patients improved by 3.1 minutes to 18.1 minutes (15%). Time to third SABA (T3) improved by 30 minutes (24%). T3 for low severity patients improved by 42.5 minutes (29%) and T3 for high severity patients improved by 21 minutes (23%). Emergency department length of stay for low severity patients discharged to home improved by 29.3 minutes (15%). The number of asthma-related visits between 48-hour return hospitalizations increased from 114 to 261. The admission rate decreased 6.0%.

CONCLUSIONS

We implemented standardized asthma severity scoring with high rates of compliance, improved timely administration of β-agonist treatments, demonstrated early improvements in Emergency department length of stay, and reduced admission rates without increasing unplanned return admissions.

Usability Evaluation of a Clinical Decision Support System for Geriatric ED Pain Treatment

BACKGROUND

Older adults are at risk for inadequate emergency department (ED) pain care. Unrelieved acute pain is associated with poor outcomes. Clinical decision support systems (CDSS) hold promise to improve patient care, but CDSS quality varies widely, particularly when usability evaluation is not employed.

OBJECTIVE

To conduct an iterative usability and redesign process of a novel geriatric abdominal pain care CDSS. We hypothesized this process would result in the creation of more usable and favorable pain care interventions.

METHODS

Thirteen emergency physicians familiar with the Electronic Health Record (EHR) in use at the study site were recruited. Over a 10-week period, 17 1-hour usability test sessions were conducted across 3 rounds of testing. Participants were given 3 patient scenarios and provided simulated clinical care using the EHR, while interacting with the CDSS interventions. Quantitative System Usability Scores (SUS), favorability scores and qualitative narrative feedback were collected for each session. Using a multi-step review process by an interdisciplinary team, positive and negative usability issues in effectiveness, efficiency, and satisfaction were considered, prioritized and incorporated in the iterative redesign process of the CDSS. Video analysis was used to determine the appropriateness of the CDS appearances during simulated clinical care.

RESULTS

Over the 3 rounds of usability evaluations and subsequent redesign processes, mean SUS progressively improved from 74.8 to 81.2 to 88.9; mean favorability scores improved from 3.23 to 4.29 (1 worst, 5 best). Video analysis revealed that, in the course of the iterative redesign processes, rates of physicians' acknowledgment of CDS interventions increased, however most rates of desired actions by physicians (such as more frequent pain score updates) decreased.

CONCLUSION

The iterative usability redesign process was instrumental in improving the usability of the CDSS; if implemented in practice, it could improve geriatric pain care. The usability evaluation process led to improved acknowledgement and favorability. Incorporating usability testing when designing CDSS interventions for studies may be effective to enhance clinician use.

Effects of Common Data Errors in Electronic Health Records on Emergency Department Operational Performance Metrics: A Monte Carlo Simulation

OBJECTIVES

The objective was to estimate how data errors in electronic health records (EHRs) can affect the accuracy of common emergency department (ED) operational performance metrics.

METHODS

Using a 3-month, 7,348-visit data set of electronic time stamps from a suburban academic ED as a baseline, Monte Carlo simulation was used to introduce four types of data errors (substitution, missing, random, and systematic bias) at three frequency levels (2, 4, and 7%). Three commonly used ED operational metrics (arrival to clinician evaluation, disposition decision to exit for admitted patients, and ED length of stay for admitted patients) were calculated and the proportion of ED visits that achieved each performance goal was determined.

RESULTS

Even small data errors have measurable effects on a clinical organization's ability to accurately determine whether it is meeting its operational performance goals. Systematic substitution errors, increased frequency of errors, and the use of shorter-duration metrics resulted in a lower proportion of ED visits reported as meeting the associated performance objectives. However, the presence of other error types mitigated somewhat the effect of the systematic substitution error. Longer time-duration metrics were found to be less sensitive to data errors than shorter time-duration metrics.

CONCLUSIONS

Infrequent and small-magnitude data errors in EHR time stamps can compromise a clinical organization's ability to determine accurately if it is meeting performance goals. By understanding the types and frequencies of data errors in an organization's EHR, organizational leaders can use data management best practices to better measure true performance and enhance operational decision-making.

Exploring the Potential of Predictive Analytics and Big Data in Emergency Care

Clinical research often focuses on resource-intensive causal inference, whereas the potential of predictive analytics with constantly increasing big data sources remains largely unexplored. Basic prediction, divorced from causal inference, is much easier with big data. Emergency care may benefit from this simpler application of big data. Historically, predictive analytics have played an important role in emergency care as simple heuristics for risk stratification. These tools generally follow a standard approach: parsimonious criteria, easy computability, and independent validation with distinct populations. Simplicity in a prediction tool is valuable, but technological advances make it no longer a necessity. Emergency care could benefit from clinical predictions built using data science tools with abundant potential input variables available in electronic medical records. Patients' risks could be stratified more precisely with large pools of data and lower resource requirements for comparing each clinical encounter to those that came before it, benefiting clinical decisionmaking and health systems operations. The largest value of predictive analytics comes early in the clinical encounter, in which diagnostic and prognostic uncertainty are high and resource-committing decisions need to be made. We propose an agenda for widening the application of predictive analytics in emergency care. Throughout, we express cautious optimism because there are myriad challenges related to database infrastructure, practitioner uptake, and patient acceptance. The quality of routinely compiled clinical data will remain an important limitation. Complementing big data sources with prospective data may be necessary if predictive analytics are to achieve their full potential to improve care quality in the emergency department.

Reducing emergency department charting and ordering errors with a room number watermark on the electronic medical record display

A survey of Emergency Department (ED) clinicians (ie, physicians, nurses and clinical assistants) at a single hospital in Honolulu, Hawai'i was conducted to assess the frequency of errors in charting, and entering orders on the wrong patient's chart in the electronic medical record (EMR), and clinician opinion was sought on whether a simple watermark of the patient's room number might help reduce the number of these EMR "wrong patient errors." ED clinicians (68 total surveys) were asked if and how often they charted in the wrong patient's chart or entered an order (physicians only) in the wrong patient's chart. Physicians had a combined self-reported average error rate of 1.3%. Mean rate of patient charting errors occurred at 0.5 errors and 0.4 errors per 100 hours, for nurses and clinical assistants, respectively. The majority (81%) of the 68 clinicians surveyed felt that a room number watermark would eliminate most of the wrong patient errors. In conclusion, charting on the wrong patient and order entry on the wrong patient type errors occur with varying frequencies amongst ED clinicians. Nearly all the clinicians believe that a room number watermark might be an effective strategy to reduce these errors.