Nicholas Genes

Leveraging Social Networks for Toxicovigilance

The landscape of drug abuse is shifting. Traditional means of characterizing these changes, such as national surveys or voluntary reporting by frontline clinicians, can miss changes in usage the emergence of novel drugs. Delays in detecting novel drug usage patterns make it difficult to evaluate public policy aimed at altering drug abuse. Increasingly, newer methods to inform frontline providers to recognize symptoms associated with novel drugs or methods of administration are needed. The growth of social networks may address this need. The objective of this manuscript is to introduce tools for using data from social networks to characterize drug abuse. We outline a structured approach to analyze social media in order to capture emerging trends in drug abuse by applying powerful methods from artificial intelligence, computational linguistics, graph theory, and agent-based modeling. First, we describe how to obtain data from social networks such as Twitter using publicly available automated programmatic interfaces. Then, we discuss how to use artificial intelligence techniques to extract content useful for purposes of toxicovigilance. This filtered content can be employed to generate real-time maps of drug usage across geographical regions. Beyond describing the real-time epidemiology of drug abuse, techniques from computational linguistics can uncover ways that drug discussions differ from other online conversations. Next, graph theory can elucidate the structure of networks discussing drug abuse, helping us learn what online interactions promote drug abuse and whether these interactions differ among drugs. Finally, agent-based modeling relates online interactions to psychological archetypes, providing a link between epidemiology and behavior. An analysis of social media discussions about drug abuse patterns with computational linguistics, graph theory, and agent-based modeling permits the real-time monitoring and characterization of trends of drugs of abuse. These tools provide a powerful complement to existing methods of toxicovigilance.

High-Frequency Users of Emergency Department Care

BACKGROUND The heterogeneous group of patients who frequently use the Emergency Department (ED) have been of interest in public health care reform debate, but little is known about the subgroup of the highest frequency users. STUDY OBJECTIVES We sought to describe the demographic and utilization characteristics of patients who visit the ED 20 or more times per year. METHODS We retrospectively studied patients who visited a large, urban ED over a 1-year period, identifying all patients using the department 20 or more times. Age, gender, insurance, psychosocial factors, chief complaint, and visit disposition were described for all visits. Inferential tests assessed associations between demographic variables, insurance status, and admission rates. RESULTS Of the 59,172 unique patients to visit the ED between December 1, 2009 and November 30, 2010, 31 patients were identified as high-frequency ED users, contributing 1.1% of all visits. Patients were more likely to be 30-59 years of age (52%), stably insured (81%), and have at least one significant psychosocial cofactor (65%). Their admission rate was 15%, as compared to 21% for all other patients. CONCLUSIONS High-frequency users are patients with significant psychiatric and social comorbidities. Given their small proportion of visits, lower admission rates, and favorable insurance status, the impact of high-frequency users of the ED may be out of proportion to common perceptions.

The Asthma Mobile Health Study, a large-scale clinical observational study using ResearchKit

The feasibility of using mobile health applications to conduct observational clinical studies requires rigorous validation. Here, we report initial findings from the Asthma Mobile Health Study, a research study, including recruitment, consent, and enrollment, conducted entirely remotely by smartphone. We achieved secure bidirectional data flow between investigators and 7,593 participants from across the United States, including many with severe asthma. Our platform enabled prospective collection of longitudinal, multidimensional data (e.g., surveys, devices, geolocation, and air quality) in a subset of users over the 6-month study period. Consistent trending and correlation of interrelated variables support the quality of data obtained via this method. We detected increased reporting of asthma symptoms in regions affected by heat, pollen, and wildfires. Potential challenges with this technology include selection bias, low retention rates, reporting bias, and data security. These issues require attention to realize the full potential of mobile platforms in research and patient care.

A conceptual framework for improved analyses of 72-hour return cases

For more than 25 years, emergency medicine researchers have examined 72-hour return visits as a marker for high-risk patient visits and as a surrogate measure for quality of care. Individual emergency departments frequently use 72-hour returns as a screening tool to identify deficits in care, although comprehensive departmental reviews of this nature may consume considerable resources. We discuss the lack of published data supporting the use of 72-hour return frequency as an overall performance measure and examine why this is not a valid use, describe a conceptual framework for reviewing 72-hour return cases as a screening tool, and call for future studies to test various models for conducting such quality assurance reviews of patients who return to the emergency department within 72 hours.

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.

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.

Signs & Symptoms of Dextromethorphan Exposure from YouTube

Detailed data on the recreational use of drugs are difficult to obtain through traditional means, especially for substances like Dextromethorphan (DXM) which are available over-the-counter for medicinal purposes. In this study, we show that information provided by commenters on YouTube is useful for uncovering the toxicologic effects of DXM. Using methods of computational linguistics, we were able to recreate many of the clinically described signs and symptoms of DXM ingestion at various doses, using information extracted from YouTube comments. Our study shows how social networks can enhance our understanding of recreational drug effects.

Enhancing a Geriatric Emergency Department Care Coordination Intervention Using Automated Health Information Exchange-Based Clinical Event Notifications

Purpose: In a health care system where patients often have numerous providers and multiple chronic medical conditions, interoperability of health information technology (HIT) is of paramount importance. Regional health information organizations (RHIO) often provide a health information exchange (HIE) as a solution, which gives stakeholders access to clinical data that they otherwise would not otherwise have. A secondary use of preexisting HIE infrastructure is clinical event notification (CEN) services, which send automated notifications to stakeholders. This paper describes the development and implementation of a CEN service enabled by a RHIO in the New York metropolitan area to improve care coordination for patients enrolled in a geriatric emergency department care coordination program. Innovation: This operational CEN system incorporates several innovations that to our knowledge have not been implemented previously. They include the near real-time notifications and the delivery of notifications via multiple pathways: electronic health record (EHR) “in-baskets,” email, text message to internet protocol-based “zone” phones, and automated encounter entry into the EHR. Based on these alerts the geriatric care coordination team contacts the facility where the patient is being seen and offers additional information or assistance with disposition planning with the goal of decreasing potentially avoidable admissions and duplicate testing. Findings: During the nearly one-year study period, the CEN program enrolled 5722 patients and sent 497 unique notifications regarding 206 patients. Of these notifications, 219 (44%) were for emergency department (ED) visits; 121 (55%) of those notifications were received during normal business hours when the care coordination team was available to contact the ED where the patient was receiving care. Hospital admissions resulted from 45% of ED visits 17.8% of these admissions lasted 48 hours or less, suggesting some might potentially be avoidable. Conclusions and Discussion: This study demonstrates the potential of CEN systems to improve care coordination by notifying providers of the occurrence of specific events. Although it could not directly be demonstrated here, we believe that widespread use of CEN systems have potential to reduce potentially avoidable admissions and duplicate testing, likely leading to decreased costs.

An Unusual Presentation of Twiddler’s Syndrome

A 64-year-old man presented to the Emergency Department complaining of 2 days of right upper quadrant abdominal pain that he characterized as ‘‘spasms.’’ His medical history was significant for hypertension, coronary artery disease with bypass surgery, mitral valve replacement, and atrial fibrillation with implantable cardioverter-defibrillator (ICD) and pacemaker placement 4 months prior. He denied chest pain and shortness of breath, and review of systems was otherwise negative. Vital signs were within normal limits. Physical examination revealed frequent visible and palpable spasms to the right side of the patient’s abdomen. There was no other abnormality. A chest radiograph (Figure 1) and electrocardiogram were obtained.

Usability Improvement of a Clinical Decision Support System

This paper focuses on improving the usability of an electronic health record (EHR) embedded clinical decision support system (CDSS) targeted to treat pain in elderly adults. CDSS have the potential to impact provider behavior. Optimizing CDSS-provider interaction and usability may enhance CDSS use. Five CDSS interventions were developed and deployed in test scenarios within a simulated EHR that mirrored typical Emergency Department (ED) workflow. Provider feedback was analyzed using a mixed methodology approach. The CDSS interventions were iteratively designed across three rounds of testing based upon this analysis. Iterative CDSS design led to improved provider usability and favorability scores.