Dataset Information

Algorithm for the diagnosis of anaphylaxis and its validation using population-based data on emergency department visits for anaphylaxis in Florida.

ABSTRACT: Epidemiologic studies of anaphylaxis have been limited by significant underdiagnosis.The purpose of this study was to develop and validate a method for capturing previously unidentified anaphylaxis cases by using International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) based datasets.Florida emergency department data for the years 2005 and 2006 from the Florida Agency for Health Care Administration were used. Patients with anaphylaxis were identified by using ICD-9-CM codes specifically indicating anaphylaxis or an ICD-9-CM algorithm based on the definition of anaphylaxis proposed at the 2005 National Institute of Allergy and Infectious Disease and the Food Allergy and Anaphylaxis Network symposium. Cases ascertained with the algorithm were compared with the traditional case-ascertainment method. Comparisons included demographic and clinical risk factors, proportion of monthly visits, and age/sex-specific rates. Cases ascertained with anaphylaxis ICD-9-CM codes were excluded from those ascertained with the algorithm.One thousand one hundred forty-nine patients were identified by using anaphylaxis ICD-9-CM codes, and 1,602 patients were identified with the algorithm. The clinical risk factors and demographics of cases were consistent between the 2 methods. However, the algorithm was more likely to identify older subjects (P < .0001), those with hypertension or heart disease (P < .0001), and subjects with venom-induced anaphylaxis (P < .0001).This study introduces and validates an ICD-9-CM-based diagnostic algorithm for the diagnosis of anaphylaxis to capture subjects missed by using the ICD-9-CM anaphylaxis codes. Fifty-eight percent of anaphylaxis cases would be missed without the use of the algorithm, including 88% of venom-induced cases.

SUBMITTER: Harduar-Morano L

PROVIDER: S-EPMC4158741 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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Algorithm for the diagnosis of anaphylaxis and its validation using population-based data on emergency department visits for anaphylaxis in Florida.

Harduar-Morano Laurel L Simon Michael R MR Watkins Sharon S Blackmore Carina C

The Journal of allergy and clinical immunology 20100611 1

<h4>Background</h4>Epidemiologic studies of anaphylaxis have been limited by significant underdiagnosis.<h4>Objective</h4>The purpose of this study was to develop and validate a method for capturing previously unidentified anaphylaxis cases by using International Classification of Disease, Ninth Revision, Clinical Modification (ICD-9-CM) based datasets.<h4>Methods</h4>Florida emergency department data for the years 2005 and 2006 from the Florida Agency for Health Care Administration were used. P ...[more]

PMID: 20541247

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Project description:ObjectiveTo characterize and validate the landscape of algorithms that use International Classification of Disease (ICD) codes to identify low-acuity emergency department (ED) visits.Data sourcesPublicly available ED data from the National Hospital Ambulatory Medical Care Survey (NHAMCS).Study designWe systematically searched for studies that specify algorithms consisting of ICD codes that identify preventable or low-acuity ED visits. We classified ED visits in NHAMCS according to these algorithms and compared agreements using the Jaccard index. We then evaluated the performance of each algorithm using positive predictive value (PPV) and sensitivity, with the reference group specified using low-acuity composite (LAC) criteria consisting of both triage and clinical components. In sensitivity analyses, we repeated our primary analysis using only triage or only clinical criteria for reference.Data collectionWe used the 2011-2017 NHAMCS data, totaling 163,576 observations before survey weighting and after dropping observations missing a primary diagnosis. We translated ICD-9 codes (years 2011-2015) to ICD-10 using a standard crosswalk.Principal findingsWe identified 15 papers with an original list of ICD codes used to identify preventable or low-acuity ED presentations. These papers were published between 1992 and 2020, cited an average of 310 (SD 360) times, and included 968 (SD 1175) codes. Pairwise Jaccard similarity indices (0 = no overlap, 1 = perfect congruence) ranged from 0.01 to 0.82, with mean 0.20 (SD 0.13). When validated against the LAC reference group, the algorithms had an average PPV of 0.308 (95% CI [0.253, 0.364]) and sensitivity of 0.183 (95% CI [0.111, 0.256]). Overall, 2.1% of visits identified as low acuity by the algorithms died prehospital or in the ED, or needed surgery, critical care, or cardiac catheterization.ConclusionsExisting algorithms that identify low-acuity ED visits lack congruence and are imperfect predictors of visit acuity.

Project description:Reduction in emergency department (ED) use is frequently viewed as a potential source for cost savings. One consideration has been to deny payment if the patient's diagnosis upon ED discharge appears to reflect a "nonemergency" condition. This approach does not incorporate other clinical factors such as chief complaint that may inform necessity for ED care.To determine whether ED presenting complaint and ED discharge diagnosis correspond sufficiently to support use of discharge diagnosis as the basis for policies discouraging ED use.The New York University emergency department algorithm has been commonly used to identify nonemergency ED visits. We applied the algorithm to publicly available ED visit data from the 2009 National Hospital Ambulatory Medical Care Survey (NHAMCS) for the purpose of identifying all "primary care-treatable" visits. The 2009 NHAMCS data set contains 34,942 records, each representing a unique ED visit. For each visit with a discharge diagnosis classified as primary care treatable, we identified the chief complaint. To determine whether these chief complaints correspond to nonemergency ED visits, we then examined all ED visits with this same group of chief complaints to ascertain the ED course, final disposition, and discharge diagnoses.Patient demographics, clinical characteristics, and disposition associated with chief complaints related to nonemergency ED visits.Although only 6.3% (95% CI, 5.8%-6.7%) of visits were determined to have primary care-treatable diagnoses based on discharge diagnosis and our modification of the algorithm, the chief complaints reported for these ED visits with primary care-treatable ED discharge diagnoses were the same chief complaints reported for 88.7% (95% CI, 88.1%-89.4%) of all ED visits. Of these visits, 11.1% (95% CI, 9.3%-13.0%) were identified at ED triage as needing immediate or emergency care; 12.5% (95% CI, 11.8%-14.3%) required hospital admission; and 3.4% (95% CI, 2.5%-4.3%) of admitted patients went directly from the ED to the operating room.Among ED visits with the same presenting complaint as those ultimately given a primary care-treatable diagnosis based on ED discharge diagnosis, a substantial proportion required immediate emergency care or hospital admission. The limited concordance between presenting complaints and ED discharge diagnoses suggests that these discharge diagnoses are unable to accurately identify nonemergency ED visits.

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Project description:Background and objectivesIn 2011, there were approximately 131 million visits to an emergency department in the United States. Emergency department visits have increased over time, far outpacing growth of the general population. There is a paucity of data evaluating emergency department visits among kidney transplant recipients. We sought to evaluate the incidence and risk factors for emergency department visits after initial hospital discharge after transplantation in the United States.Design, setting, participants, & measurementsWe identified 10,533 kidney transplant recipients from California, New York, and Florida between 2009 and 2012 using the State Inpatient and Emergency Department Databases included in the Healthcare Cost and Utilization Project. We used multivariable Poisson and Cox proportional hazard models to evaluate adjusted incidence rates and time to emergency department visits after transplantation.ResultsThere were 17,575 emergency department visits over 13,845 follow-up years (overall rate =126.9/100 patient-years; 95% confidence interval, 125.1 to 128.8). The cumulative incidences of emergency department visits at 1, 12, and 24 months were 12%, 40%, and 57%, respectively, with median time =19 months; 48% of emergency department visits led to hospital admission. Risk factors for higher emergency department rates included younger age, women, black and Hispanic race/ethnicity, public insurance, depression, diabetes, peripheral vascular disease, and emergency department use before transplant. There was wide variation in emergency department visits by individual transplant center (10th percentile =70.0/100 patient-years; median =124.6/100 patient-years; and 90th percentile =187.4/100 patient-years).ConclusionsThe majority of kidney transplant recipients will visit an emergency department in the first 2 years post-transplantation, with significant variation by patient characteristics and individual centers. As such, coordination of care through the emergency department is a critical component of post-transplant management, and specific acumen of transplant-related care is needed among emergency department providers. Additional research assessing best processes of care for post-transplant management and health care expenditures and outcomes associated with emergency department visits for transplant recipients are warranted.

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Dataset Information

Algorithm for the diagnosis of anaphylaxis and its validation using population-based data on emergency department visits for anaphylaxis in Florida.

Publications

Algorithm for the diagnosis of anaphylaxis and its validation using population-based data on emergency department visits for anaphylaxis in Florida.

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