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Elizabeth Grossman

Publications and source records attributed to Elizabeth Grossman.

2 recordsLinked to original sources
PubMed2005

Developing a computer algorithm to identify epilepsy cases in managed care organizations.

The goal of this study was to develop an algorithm for detecting epilepsy cases in managed care organizations (MCOs). A data set of potential epilepsy cases was constructed from an MCO's administrative data system for all health plan members continuously enrolled in the MCO for at least 1 year within the study period of July 1, 1996 through June 30, 1998. Epilepsy status was determined using medical record review for a sample of 617 cases. The best algorithm for detecting epilepsy cases was developed by examining combinations of diagnosis, diagnostic procedures, and medication use. The best algorithm derived in the exploratory phase was then applied to a new set of data from the same MCO covering the period of July 1, 1998 through June 30, 2000. A stratified sample based on ethnicity and age was drawn from the preliminary algorithm-identified epilepsy cases and non-cases. Medical record review was completed for 644 cases to determine the accuracy of the algorithm. Data from both phases were combined to permit refinement of logistic regression models and to provide more stable estimates of the parameters. The best model used diagnoses and antiepileptic drugs as predictors and had a positive predictive value of 84% (sensitivity 82%, specificity 94%). The best model correctly classified 90% of the cases. A stable algorithm that can be used to identify epilepsy patients within MCOs was developed. Implications for use of the algorithm in other health care settings are discussed.

Adult↗
PubMed2005

Estimating prevalence, incidence, and disease-related mortality for patients with epilepsy in managed care organizations.

PURPOSE: The purpose of the present study was to apply computer algorithms to an administrative data set to identify the prevalence of epilepsy, incidence of epilepsy, and epilepsy-related mortality of patients in a managed care organization (MCO). METHODS: The study population consisted of members enrolled in Lovelace Health Plan, a component of Lovelace Health Systems, a statewide MCO headquartered in Albuquerque, New Mexico. Patient records were obtained from July 1996 to June 2001. Four logistic regression models with high sensitivity and specificity were applied to 1-, 3-, and 5-year time frames in which members were continuously enrolled in the MCO. Incidence was defined for patients who did not have an epilepsy-associated code in the 18 months before the first diagnosis entry. Mortality estimates in the population also were assessed by using a matched control group and linkage to a statewide death registry. RESULTS: The data yielded estimated prevalence rates of 7-10 per 1,000, depending on age, sex, ethnicity, and time interval. Annualized incidence was 47 per 100,000 for members continuously enrolled for 3 years and 71 per 100,000 for members continuously enrolled for 5 years. Crude mortality rates were 2-2.5 times higher for epilepsy patients identified with the algorithms than for the matched controls. Conditional logistic regression indicated that the odds of death for epilepsy patients as compared with controls ranged from 1.24 to 2.06. CONCLUSIONS: Accurate estimation of prevalence, incidence, and mortality rates for epilepsy is an essential component of disease management in MCOs. The algorithms in this project can be used to monitor trends in prevalence, incidence, and mortality to inform decisions critical to improving the health care needs and quality of life for patients with epilepsy.

Adult↗