Faculty Bibliography

BACKGROUND:The assessment of clinical guideline adherence for the evaluation of pulmonary embolism (PE) via computed tomography pulmonary angiography (CTPA) currently requires either labor-intensive, retrospective chart review or prospective collection of PE risk scores at the time of CTPA order. The recording of clinical data in a structured manner in the electronic health record (EHR) may make it possible to automate the calculation of a patient's PE risk classification and determine whether the CTPA order was guideline concordant. OBJECTIVES/OBJECTIVE:The objective of this study was to measure the performance of automated, structured-data-only versions of the Wells and revised Geneva risk scores in emergency department encounters during which a CTPA was ordered. The hypothesis was that such an automated method would classify a patient's PE risk with high accuracy compared to manual chart review. METHODS:We developed automated, structured-data-only versions of the Wells and revised Geneva risk scores to classify 212 emergency department (ED) encounters during which a CTPA was performed as "PE Likely" or "PE Unlikely." We then combined these classifications with D-dimer ordering data to assess each encounter as guideline concordant or discordant. The accuracy of these automated classifications and assessments of guideline concordance were determined by comparing them to classifications and concordance based on the complete Wells and revised Geneva scores derived via abstractor manual chart review. RESULTS:The automatically derived Wells and revised Geneva risk classifications were 91.5% and 92% accurate compared to the manually determined classifications, respectively. There was no statistically significant difference between guideline adherence calculated by the automated scores as compared to manual chart review (Wells: 70.8 vs. 75%, p = 0.33 | Revised Geneva: 65.6 vs. 66%, p = 0.92). CONCLUSION/CONCLUSIONS:The Wells and revised Geneva score risk classifications can be approximated with high accuracy using automated extraction of structured EHR data elements in patients who received a CTPA. Combining these automated scores with D-dimer ordering data allows for the automated assessment of clinical guideline adherence for CTPA ordering in the emergency department, without the burden of manual chart review.

The risk of severe precipitated opioid withdrawal (POW) is amplified when precipitated by a long-acting opioid antagonist. IM extended release naltrexone (XRNTX;Vivitrol®) is an FDA approved therapy to prevent relapse of opioid and alcohol abuse. Two cases of precipitated opioid withdrawal from XRNTX are presented that illustrate different patient reactions to POW. A 56-year-old woman developed a hypertensive emergency and required continuous intravenous vasodilator, clonidine, and intensive care monitoring after re-initiation of XRNTX following opioid relapse. A 25-year-old man developed agitation and altered mental status after receipt of XRNTX at the conclusion of a twelve-day detoxification program during which he continued surreptitious use of heroin. The patient received benzodiazepines and haloperidol without adequate affect, and required intubation with propofol, lorazepam, and dexmedetomidine infusions. Management of POW from XRNTX is a challenge to emergency providers and protocols to guide management do not exist. Recommended therapies include intravenous fluids, anti-emetics, clonidine, or benzodiazepines as well as therapy tailored to the organ system affected. To minimize risk of POW it is important for providers instituting XRNTX to adhere to the manufacturers warnings and clinic protocols including a naloxone challenge and ensure an adequate opioid free period prior to administration of XRNTX.

OBJECTIVE:Older adults are a potentially medically vulnerable population with increased mortality rates during and after disasters. To evaluate the impact of a natural disaster on this population, we performed a temporal and geospatial analysis of emergency department (ED) use by adults aged 65 years and older in New York City (NYC) following Hurricane Sandy's landfall. METHODS:We used an all-payer claims database to analyze demographics, insurance status, geographic distribution, and health conditions for post-disaster ED visits among older adults. We compared ED patterns of use in the weeks before and after Hurricane Sandy throughout NYC and the most afflicted evacuation zones. RESULTS:We found significant increases in ED utilization by older adults (and disproportionately higher in those aged ≥85 years) in the 3 weeks after Hurricane Sandy, especially in NYC evacuation zone one. Primary diagnoses with notable increases included dialysis, electrolyte disorders, and prescription refills. Secondary diagnoses highlighted homelessness and care access issues. CONCLUSIONS:Older adults display heightened risk for worse health outcomes with increased ED visits after a disaster. Our findings suggest the need for dedicated resources and planning for older adults following a natural disaster by ensuring access to medical facilities, prescriptions, dialysis, and safe housing and by optimizing health care delivery needs to reduce the burden of chronic disease. (Disaster Med Public Health Preparedness. 2018;12:184-193).

BACKGROUND: Testing for venous thromboembolism (VTE) is associated with cost and risk to patients (e.g. radiation). To assess the appropriateness of imaging utilization at the provider level, it is important to know that provider's diagnostic yield (percentage of tests positive for the diagnostic entity of interest). However, determining diagnostic yield typically requires either time-consuming, manual review of radiology reports or the use of complex and/or proprietary natural language processing software. OBJECTIVES: The objectives of this study were twofold: 1) to develop and implement a simple, user-configurable, and open-source natural language processing tool to classify radiology reports with high accuracy and 2) to use the results of the tool to design a provider-specific VTE imaging dashboard, consisting of both utilization rate and diagnostic yield. METHODS: Two physicians reviewed a training set of 400 lower extremity ultrasound (UTZ) and computed tomography pulmonary angiogram (CTPA) reports to understand the language used in VTE-positive and VTE-negative reports. The insights from this review informed the arguments to the five modifiable parameters of the NLP tool. A validation set of 2,000 studies was then independently classified by the reviewers and by the tool; the classifications were compared and the performance of the tool was calculated. RESULTS: The tool was highly accurate in classifying the presence and absence of VTE for both the UTZ (sensitivity 95.7%; 95% CI 91.5-99.8, specificity 100%; 95% CI 100-100) and CTPA reports (sensitivity 97.1%; 95% CI 94.3-99.9, specificity 98.6%; 95% CI 97.8-99.4). The diagnostic yield was then calculated at the individual provider level and the imaging dashboard was created. CONCLUSIONS: We have created a novel NLP tool designed for users without a background in computer programming, which has been used to classify venous thromboembolism reports with a high degree of accuracy. The tool is open-source and available for download at http://iturrate.com/simpleNLP. Results obtained using this tool can be applied to enhance quality by presenting information about utilization and yield to providers via an imaging dashboard.