Research Forum Abstracts

visits and high institutional costs of care, as well as whether they overlap in ways thatwould suggest opportunities for triple aim interventions.

Methods: All 74,644 ED visits to Regions Hospital in 2011 were analyzed using theNYU/Billings ED algorithm. In an attempt to improve on the algorithm’s originalapproach, the ED algorithm was applied to each of up to 5 discharge diagnoses associatedwith an ED visit to determine the probability that each diagnosis was emergent and inneed of ED care. The diagnosis with the highest probability of being emergent was thenselected. Trauma, mental health, and drug/toxicology cases were excluded. Cost figuresfor each visit were obtained from our internal cost-accounting system, including bothED visit costs and associated inpatient costs where applicable. For each ED visit, theprobability that the visit was avoidable, the total and marginal costs for the visit, andother visit characteristics (eg, acuity, disposition) were then aggregated by block group.We then carried out cluster and hotspot analyses using ArcGIS.

Results: Spatial statistical analysis of average acuity, preventability, and cost per visit didnot show any significant differences in these elements between neighborhoods. However,our preliminary GIS analysis demonstrates significant clustering and overlap of bothpotentially avoidable ED visits and high total and marginal costs in a small but significantnumber of block groups.These neighborhoods have similar 2010USCensus characteristicsas well as similar propensities for ED use based on data from theMinnesotaDepartment ofHealth. Notably, they also have significantly fewer primary care resources available.

Conclusion: Geospatial analysis of ED visits for potential preventability and costcan identify opportune neighborhoods for educational, primary care, or alternativehealth care resource interventions to achieve better quality care and lower costs throughimprovements in public health. Our future analyses and modeling will integratepatient-level factors in order to specify which conditions, patients, and neighborhoodsare most likely to benefit from triple aim efforts to reduce potentially avoidable EDvisits and their costs by improving health care access.

Testing Concordance Between Data from Two Health

241 Data Systems Using Kappa ValuesGarg N, Onyile A, Lowery T, Kuperman G, Genes N, DiMaggio C, Richardson L,Shapiro J/Icahn School of Medicine at Mount Sinai, New York, NY; Icahn School ofMedicine at Mount Sinai, New York, NY; Columbia University Medical Center, NewYork, NY

Study Objectives: (1) To validate the use of Health Information Exchange (HIE)data for the application of emergency department (ED) quality measures (frequent EDuser identification and 72-hour returns) by comparing data from an HIE for fourhospitals to data from each hospital’s respective Electronic Health Records (EHR). (2)To study the use of kappa as a measure of data concordance between differentelectronic data sources in the setting of evaluating ED quality measures. To ourknowledge, the use of kappa for this purpose has not been previously published. A highlevel of concordance implies that data from an HIE can potentially be applied tosecondary uses like research, quality measurement and assurance, and public health.

Methods: Data that originally derived from admission, discharge, and transfer (ADT)systems of four different hospital sites was obtained from the Healthix HIE. Algorithmswere applied to these data sets that identified frequent ED users (� 4 visits in 30 days) andearly ED returns (second ED visit in <72 hours). These algorithms were then applied todata sets obtained from the EHRat each of the four sites for the same period. In order to testthe degree of concordance of the results, a kappa test for concordance was then applied onthe numbers of frequent ED users and early ED returns from all four sites.

Preliminary Results: Site 3 had the most 72-hour returns and the most frequentED users. The kappas for each site for frequent ED users and 72-hour returns were allabove 0.99, with Site 4 having the highest concordance in both measures.

Conclusion: Kappa test is a test for concordance that is generally applied tomeasure how well two different entities agree at their task, most commonly used inmedicine to test inter-rater reliability for diagnosing based on reading studies or tests.Our analysis shows that kappa can be functionally applied to test the concordance of

Table. Total counts and Kappas for each site for both frequent ED users and 72 ho

Site 1 Site 2

EHRCount

HIECount Kappa

EHRCount

HIECount Ka

Frequent Users 1,204 1,221 0.99984 1,060 1,035 0.9972 Hour Returns 8,299 8,456 0.99927 7,237 7,093 0.99

S86 Annals of Emergency Medicine

two different electronic data sources. Additionally, our analysis shows that data fromHealthix can be used as a suitable alternative to local hospital EHR data in analyzingtwo ED quality measures such as frequent ED users and early ED returns. Validationof data sources is an essential step prior to using clinical data for secondary purposessuch as quality measurements. Using a data source such as Healthix that aggregates datafrom multiple different health care facilities is both powerful in its potential to moreaccurately reflect patient behavior but also risky because data quality issues from eachsite become compounded with aggregation. Further work should be done to validatethe use of HIE for other quality measures and other secondary uses of HIE data.

The Rise of Advanced Imaging for Bell’s Palsy

242 Osborne AD, Pitts SR/Emory University, Decatur, GA

Background: Few conditions are ruled-in on clinical grounds alone as reliably asBell’s palsy. Expert opinion proposes that brain imaging is largely unnecessary unlessthere is suspicion for an alternative cause, an opinion confirmed by a recentepidemiologic study. We hypothesized that the increased frequency of advancedimaging in the emergency department (ED), justified in many cases by improvedclinical outcomes, has also occurred for patients with Bell’s palsy, with little expectationof benefit.

Study Objective: To analyze the national use of advanced imaging (computedtomography, ultrasound, or magnetic resonance imaging) in ED visits with a dischargediagnosis of Bell’s palsy.

Methods: We aggregated the annual files of the National Hospital AmbulatoryMedical Care Survey (NHAMCS) from 2001 to 2010 to determine the proportion ofvisits with a discharge diagnosis of Bell’s Palsy that received advanced imaging. Inmultivariable logistic regression we adjusted for age category, race, ethnicity, payer, andhospital admission status. Complete details of survey methodology are available onlineand statistical analysis was performed using Stata version 12.

Results: Advanced imaging was performed in 44 percent of 239 visits for Bell’s palsy,compared with 14 percent for other visits, an absolute difference of 30 percent (95% CI20 to 40, using weighted complex survey analysis). The odds of advanced imaging forBell’s palsy rose at a rate of 16 percent per year (95% CI 4 to 28). This was notsignificantly different from the 11% rise in overall ED advanced imaging (Figure).Thisresult implies a national burden of about 34,000 potentially avoidable ED scans annuallyfor a diagnosis that can usually be made securely on clinical grounds.

Conclusions: The imaging boom is occurring nationally, even when there is littleevidence to support it, with the adverse consequences of unneeded radiation exposure,increased cost, and reduced ED throughput efficiency.

ur returns.

Site 3 Site 4

ppaEHRCount

HIECount Kappa

EHRCount

HIECount Kappa

985 1,746 1,708 0.99977 936 924 0.99993933 12,243 12,045 0.99942 5,476 5,431 0.99999

Volume 64, no. 4s : October 2014