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PREDICTIVE PERFORMANCE OF ASTHMA QUALITY OF CARE MEASURES – A
COMPARISON UNDER SKEWED OUTCOME AND COST DISTRIBUTIONS
by
Thomas Tencer
A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PHARMACEUTICAL ECONOMICS AND POLICY)
May 2010
Copyright 2010 Thomas Tencer
Object Description
| Title | Predictive performance of asthma quality of care measures – a comparison under skewed outcome and cost distributions |
| Author | Tencer, Thomas |
| Author email | ttence@hotmail.com; tencer@usc.edu |
| Degree | Doctor of Philosophy |
| Document type | Dissertation |
| Degree program | Pharmaceutical Economics & Policy |
| School | School of Pharmacy |
| Date defended/completed | 2009-11-19 |
| Date submitted | 2010 |
| Restricted until | Unrestricted |
| Date published | 2010-01-15 |
| Advisor (committee chair) | Johnson, Kathleen |
| Advisor (committee member) |
Doctor, Jason Azen, Stanley |
| Abstract | Objective: To evaluate potential measures of quality-of-care in asthma as predictors ofsubsequent emergency hospital care under skewed class and cost distributions.; Methods: The California Medicaid (Medi-Cal) claims data from January 2004 to December 2006 was analyzed. Patients with persistent asthma were identified using the Health Employers Data Information Set (HEDIS) criteria and were stratified into high (≥ 6 reliever medication claims) and low-reliever (< 6 reliever claims) cohorts. The dependent variable was the occurrence of an asthma-related hospitalization or emergency department visit. Asthma quality-of-care measures assessed include the HEDIS performance measure of any asthma controller fill, a controller-to-total asthma medication ratio ≥ 0.5, proportion days covered (PDC) ≥ 0.8, and the number of controller fills. Covariates included demographic variables, prior medication and healthcare service use, and comorbidities. The quality-of-care measures were evaluated cross-sectionally over a one year period as well as longitudinally using quarterly assessments. Models were estimated using logistic regression in the cross-sectional study, and generalized estimating equations (GEE) in the longitudinal study. The k-fold cross-validation procedure was used to assess the internal validity of the predictive models. The ROC Convex Hull method and decision curve analysis were used to account for unequal error costs and skewed outcome distributions.; Results A PDC ≥ 0.8 and a controller to total asthma medication ratio ≥ 0.5 were associatedwith decreased risk of subsequent emergency hospital care in the cross-sectional andlongitudinal studies. Any controller dispensing and number of controller fills were not consistently associated with decreased hospitalizations and may reflect underlying severity. An asthma controller/total medication ratio >=0.5 was the best predictor of asthma related emergency hospital care as it had the greatest AUC in both the cross-sectional and longitudinal studies; however, the predictive power was modest (<0.6 in all analyses). The predictive performance of the baseline covariates was significantly higher, with the AUC ranging between 0.7 and 0.8. No asthma performance measure improved the AUC when added to the baseline covariates. Application of the ROC convex hull method suggests that these models are better than the “do nothing” strategy only when the cost of false negatives exceeds the cost of false positives. Similarly, application of decision curve analysis yields the greatest net benefit at low probability thresholds, implying the greatest utility occurs when the cost of a false negative exceeds the cost of a false positive. The low incidence of emergency hospital in each quarter of the longitudinal study yields a minimum cost classifier with only marginally better performance than the strategy of “assume all are patients are negative”.; Conclusion: Two potential quality-of-care measures, the asthma medication ratio andproportion days’ covered, appear to be superior to the current HEDIS performance measure of any controller dispensing. However, prediction models that incorporate demographics and prior resource use data have significantly better ability to identify patients at high-risk for asthma-related emergency hospital care than the asthma quality-of-care measures alone. The low incidence of emergency hospital care suggests that identifying high-risk patients based on accuracy alone may result in suboptimal outcomes. The cost of false negatives must exceed the cost of false positives for these models to be useful. |
| Keyword | asthma; decision curve analysis; HEDIS; prediction models; quality of care; ROC convex hull |
| Language | English |
| Part of collection | University of Southern California dissertations and theses |
| Publisher (of the original version) | University of Southern California |
| Place of publication (of the original version) | Los Angeles, California |
| Publisher (of the digital version) | University of Southern California. Libraries |
| Provenance | Electronically uploaded by the author |
| Type | texts |
| Legacy record ID | usctheses-m2800 |
| Rights | Tencer, Thomas |
| Repository name | Libraries, University of Southern California |
| Repository address | Los Angeles, California |
| Repository email | http://www.usc.edu/isd/libraries/services/ask_a_librarian/email/ |
| Filename | etd-Tencer-3403 |
| Archival file | uscthesesreloadpub_Volume44/etd-Tencer-3403.pdf |
Description
| Title | Page 1 |
| Full text | PREDICTIVE PERFORMANCE OF ASTHMA QUALITY OF CARE MEASURES – A COMPARISON UNDER SKEWED OUTCOME AND COST DISTRIBUTIONS by Thomas Tencer A Dissertation Presented to the FACULTY OF THE USC GRADUATE SCHOOL UNIVERSITY OF SOUTHERN CALIFORNIA In Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY (PHARMACEUTICAL ECONOMICS AND POLICY) May 2010 Copyright 2010 Thomas Tencer |
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