Edward R. Melnick

CT overuse for mild traumatic brain injury

BACKGROUND Multiple, validated, evidence-based guidelines exist to inform the appropriate use of computed tomography (CT) to differentiate mild traumatic brain injury (MTBI) from clinically important brain injury and to prevent the overuse of CT. Yet, CT use is growing rapidly, potentially exposing patients to unnecessary ionizing radiation risk and costs. A study was conducted to quantify the overuse of CT in MTBI on the basis of current guideline recommendations. METHODS A retrospective analysis of secondary data from a prospective observational study was undertaken at an urban, Level I emergency department (ED) with more than 90,000 visits per year. For adult patients with minor head injury receiving CT imaging at the discretion of the treating physician, the proportion of cases meeting criteria for CT on the basis of the Canadian CT Head Rule (CCHR), American College of Emergency Physicians (ACEP) Clinical Policy, New Orleans Criteria (NOC), and National Institute for Health and Clinical Excellence (NICE) guidelines was reported. RESULTS All 346 patients enrolled in the original study were included in the analysis. The proportion of cases meeting criteria for CT for each of the guidelines was: CCHR 64.7% (95% confidence interval [CI], 0.60-0.70), ACEP 74.3% (95% CI, 0.70-0.79), NICE 86.7% (95% CI, 0.83-0.90), and NOC 90.5% (95% CI, 0.87-0.94). The odds ratio of the guidelines for predicting positive head CT findings were also reported. DISCUSSION Some 10%-35% of CTs obtained in the ED for MTBI were not recommended according to the guidelines. Successful implementation of existing guidelines could decrease CT use in MTBI by up to 35%, leading to a significant reduction in radiation-induced cancers and health care costs.

Portable ultrasound for remote environments, Part I: Feasibility of field deployment.

BACKGROUND In field medical operations, rapid diagnosis and triage of seriously injured patients is critical. With significant bulk and cost constraints placed on all equipment, it is important that any medical devices deployed in the field demonstrate high utility, durability, and ease of use. When medical ultrasound was first used in patient care, machine cost, bulk, and steep learning curves prevented use outside of the radiology department. Now, lightweight portable ultrasound is widely employed at the bedside by emergency physicians. The techniques and equipment have recently been extrapolated out of the hospital setting in a wide variety of environments in an effort to increase diagnostic accuracy in the field. OBJECTIVES In this review, deployment of lightweight portable ultrasound in the field (by emergency medical services, military operations, disaster relief, medical missions, and expeditions to austere environments) is examined. The feasibility of field deployment and experiences of clinicians using ultrasound in a host of environments are detailed. In addition, special technological considerations such as telemedicine and machine characteristics are reviewed. CONCLUSIONS The use of lightweight portable ultrasound shows great promise in augmenting clinical assessment for field medical operations. Although the feasibility of the technology has been demonstrated in certain medical and trauma applications, further research is needed to determine the utility of ultrasound use for medical illness in the field.

Prediction of In-hospital Mortality in Emergency Department Patients With Sepsis: A Local Big Data-Driven, Machine Learning Approach.

OBJECTIVES Predictive analytics in emergency care has mostly been limited to the use of clinical decision rules (CDRs) in the form of simple heuristics and scoring systems. In the development of CDRs, limitations in analytic methods and concerns with usability have generally constrained models to a preselected small set of variables judged to be clinically relevant and to rules that are easily calculated. Furthermore, CDRs frequently suffer from questions of generalizability, take years to develop, and lack the ability to be updated as new information becomes available. Newer analytic and machine learning techniques capable of harnessing the large number of variables that are already available through electronic health records (EHRs) may better predict patient outcomes and facilitate automation and deployment within clinical decision support systems. In this proof-of-concept study, a local, big data-driven, machine learning approach is compared to existing CDRs and traditional analytic methods using the prediction of sepsis in-hospital mortality as the use case. METHODS This was a retrospective study of adult ED visits admitted to the hospital meeting criteria for sepsis from October 2013 to October 2014. Sepsis was defined as meeting criteria for systemic inflammatory response syndrome with an infectious admitting diagnosis in the ED. ED visits were randomly partitioned into an 80%/20% split for training and validation. A random forest model (machine learning approach) was constructed using over 500 clinical variables from data available within the EHRs of four hospitals to predict in-hospital mortality. The machine learning prediction model was then compared to a classification and regression tree (CART) model, logistic regression model, and previously developed prediction tools on the validation data set using area under the receiver operating characteristic curve (AUC) and chi-square statistics. RESULTS There were 5,278 visits among 4,676 unique patients who met criteria for sepsis. Of the 4,222 patients in the training group, 210 (5.0%) died during hospitalization, and of the 1,056 patients in the validation group, 50 (4.7%) died during hospitalization. The AUCs with 95% confidence intervals (CIs) for the different models were as follows: random forest model, 0.86 (95% CI = 0.82 to 0.90); CART model, 0.69 (95% CI = 0.62 to 0.77); logistic regression model, 0.76 (95% CI = 0.69 to 0.82); CURB-65, 0.73 (95% CI = 0.67 to 0.80); MEDS, 0.71 (95% CI = 0.63 to 0.77); and mREMS, 0.72 (95% CI = 0.65 to 0.79). The random forest model AUC was statistically different from all other models (p ≤ 0.003 for all comparisons). CONCLUSIONS In this proof-of-concept study, a local big data-driven, machine learning approach outperformed existing CDRs as well as traditional analytic techniques for predicting in-hospital mortality of ED patients with sepsis. Future research should prospectively evaluate the effectiveness of this approach and whether it translates into improved clinical outcomes for high-risk sepsis patients. The methods developed serve as an example of a new model for predictive analytics in emergency care that can be automated, applied to other clinical outcomes of interest, and deployed in EHRs to enable locally relevant clinical predictions.

Clinical Policy: Critical Issues in the Evaluation and Management of Adult Patients Presenting to the Emergency Department With Seizures

This clinical policy from the American College of Emergency Physicians is the revision of a 2004 policy on critical issues in the evaluation and management of adult patients with seizures in the emergency department. A writing subcommittee reviewed the literature to derive evidence-based recommendations to help clinicians answer the following critical questions: (1) In patients with a first generalized convulsive seizure who have returned to their baseline clinical status, should antiepileptic therapy be initiated in the emergency department to prevent additional seizures? (2) In patients with a first unprovoked seizure who have returned to their baseline clinical status in the emergency department, should the patient be admitted to the hospital to prevent adverse events? (3) In patients with a known seizure disorder in which resuming their antiepileptic medication in the emergency department is deemed appropriate, does the route of administration impact recurrence of seizures? (4) In emergency department patients with generalized convulsive status epilepticus who continue to have seizures despite receiving optimal dosing of a benzodiazepine, which agent or agents should be administered next to terminate seizures? A literature search was performed, the evidence was graded, and recommendations were given based on the strength of the available data in the medical literature.

Portable Ultrasound for Remote Environments, Part II: Current Indications

BACKGROUND With recent advances in ultrasound technology, it is now possible to deploy lightweight portable imaging devices in the field. Techniques and studies initially developed for hospital use have been extrapolated out of the hospital setting in a wide variety of environments in an effort to increase diagnostic accuracy in austere or prehospital environments. OBJECTIVES This review summarizes current ultrasound applications used in out-of-hospital arenas and highlights existing evidence for such use. The diversity of applications and environments is organized by indication to better inform equipment selection as well as future directions for research and development. DISCUSSION Trauma evaluation, casualty triage, and assessment for pneumothorax, acute mountain sickness, and other applications have been studied by field medical teams. A wide range of outcomes have been reported, from alterations in patient care to determinations of accuracy compared to clinical judgment or other diagnostic modalities. CONCLUSIONS The use of lightweight portable ultrasound shows great promise in augmenting clinical assessment for field medical operations. Although some studies of diagnostic accuracy exist in this setting, further research focused on clinically relevant outcomes data is needed.

Delphi Consensus on the Feasibility of Translating the ACEP Clinical Policies Into Computerized Clinical Decision Support

Clinical practice guidelines are developed to reduce variations in clinical practice, with the goal of improving health care quality and cost. However, evidence-based practice guidelines face barriers to dissemination, implementation, usability, integration into practice, and use. The American College of Emergency Physicians (ACEP) clinical policies have been shown to be safe and effective and are even cited by other specialties. In spite of the benefits of the ACEP clinical policies, implementation of these clinical practice guidelines into physician practice continues to be a challenge. Translation of the ACEP clinical policies into real-time computerized clinical decision support systems could help address these barriers and improve clinician decision making at the point of care. The investigators convened an emergency medicine informatics expert panel and used a Delphi consensus process to assess the feasibility of translating the current ACEP clinical policies into clinical decision support content. This resulting consensus document will serve to identify limitations to implementation of the existing ACEP Clinical Policies so that future clinical practice guideline development will consider implementation into clinical decision support at all stages of guideline development.

International Emergency Medicine : A Review of the Literature from 2007

The subspecialty of international emergency medicine (IEM) continues to grow within the United States, just as the specialty of emergency medicine (EM) continues to spread to both developed and developing countries around the world. One of the greatest obstacles, however, faced by IEM researchers and practitioners alike, remains the lack of a high-quality, consolidated, and easily accessible evidence-base of literature. In response to this perceived need, members of the Emergency Medicine Resident Association (EMRA) International Emergency Medicine Committee, in conjunction with members of the Society for Academic Emergency Medicine (SAEM) International Health Interest Group, have embarked on the task of creating a recurring review of IEM literature. This publication represents the third annual review, covering the top 30 IEM research articles published in 2007. Articles were selected for the review according to explicit, predetermined criteria that included both methodologic quality and perceived impact of the research. It is hoped that this annual review will act as a forum for disseminating best practices, while also stimulating further research in the field of IEM.

Shared Decisionmaking in the Emergency Department: A Guiding Framework for Clinicians

&NA; Shared decisionmaking has been proposed as a method to promote active engagement of patients in emergency care decisions. Despite the recent attention shared decisionmaking has received in the emergency medicine community, including being the topic of the 2016 Academic Emergency Medicine Consensus Conference, misconceptions remain in regard to the precise meaning of the term, the process, and the conditions under which it is most likely to be valuable. With the help of a patient representative and an interaction designer, we developed a simple framework to illustrate how shared decisionmaking should be approached in clinical practice. We believe it should be the preferred or default approach to decisionmaking, except in clinical situations in which 3 factors interfere. These 3 factors are lack of clinical uncertainty or equipoise, patient decisionmaking ability, and time, all of which can render shared decisionmaking infeasible. Clinical equipoise refers to scenarios in which there are 2 or more medically reasonable management options. Patient decisionmaking ability refers to a patient’s capacity and willingness to participate in his or her emergency care decisions. Time refers to the acuity of the clinical situation (which may require immediate action) and the time that the clinician has to devote to the shared decisionmaking conversation. In scenarios in which there is only one medically reasonable management option, informed consent is indicated, with compassionate persuasion used as appropriate. If time or patient capacity is lacking, physician‐directed decisionmaking will occur. With this framework as the foundation, we discuss the process of shared decisionmaking and how it can be used in practice. Finally, we highlight 5 common misconceptions in regard to shared decisionmaking in the ED. With an improved understanding of shared decisionmaking, this approach should be used to facilitate the provision of high‐quality, patient‐centered emergency care.

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

AimsTo 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.MethodsThis 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.ResultsThere 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).ConclusionsThe 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.

Improving emergency physician performance using audit and feedback: a systematic review

BACKGROUND Audit and feedback can decrease variation and improve the quality of care in a variety of health care settings. There is a growing literature on audit and feedback in the emergency department (ED) setting. Because most studies have been small and not focused on a single clinical process, systematic assessment could determine the effectiveness of audit and feedback interventions in the ED and which specific characteristics improve the quality of emergency care. OBJECTIVE The objective of the study is to assess the effect of audit and feedback on emergency physician performance and identify features critical to success. METHODS We adhered to the PRISMA statement to conduct a systematic review of the literature from January 1994 to January 2014 related to audit and feedback of physicians in the ED. We searched Medline, EMBASE, PsycINFO, and PubMed databases. We included studies that were conducted in the ED and reported quantitative outcomes with interventions using both audit and feedback. For included studies, 2 reviewers independently assessed methodological quality using the validated Downs and Black checklist for nonrandomized studies. Treatment effect and heterogeneity were to be reported via meta-analysis and the I2 inconsistency index. RESULTS The search yielded 4332 articles, all of which underwent title review; 780 abstracts and 131 full-text articles were reviewed. Of these, 24 studies met inclusion criteria with an average Downs and Black score of 15.6 of 30 (range, 6-22). Improved performance was reported in 23 of the 24 studies. Six studies reported sufficient outcome data to conduct summary analysis. Pooled data from studies that included 41,124 patients yielded an average treatment effect among physicians of 36% (SD, 16%) with high heterogeneity (I2=83%). CONCLUSION The literature on audit and feedback in the ED reports positive results for interventions across numerous clinical conditions but without standardized reporting sufficient for meta-analysis. Characteristics of audit and feedback interventions that were used in a majority of studies were feedback that targeted errors of omission and that was explicit with measurable instruction and a plan for change delivered in the clinical setting greater than 1 week after the audited performance using a combination of media and types at both the individual and group levels. Future work should use standardized reporting to identify the specific aspects of audit or feedback that drive effectiveness in the ED.