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Berlin Brandenburg

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  • 1
    In: Medical Care, 2009, Vol.47(2), pp.154-160
    Description: BACKGROUND:: Disease management programs have grown in popularity over the past decade as a strategy to curb escalating healthcare costs for persons with chronic diseases. OBJECTIVES:: To evaluate the effect of the Indiana Chronic Disease Management Program (ICDMP) on the longitudinal changes in Medicaid claims statewide. RESEARCH DESIGN:: Phased implementation of a chronic disease management program in 3 regions of the state. Fourteen repeated cohorts of Medicaid members were drawn over a period of 3.5 years and the trends in claims were evaluated using a repeated measures model. SUBJECTS:: A total of 44,218 Medicaid members with diabetes and/or congestive heart failure in 3 geographic regions in Indiana. RESULTS:: Across all 3 regions and both disease classes, we found a flattening of cost trends between the pre- and post-ICDMP-initiation periods. This change in the slopes was significant for all of the models except for congestive heart failure in southern Indiana. Thus, the average per member claims paid was increasing at a faster rate before ICDMP but slowed once the program was initiated. To distinguish shorter and longer-term effects related to ICDMP, we estimated annual slopes within the pre- and post-ICDMP- time periods. A similar pattern was found in all regions: claims were increasing before ICDMP, flattened in the years around program initiation, and remained flat in the final year of follow-up. CONCLUSIONS:: This analysis shows that the trend in average total claims changed significantly after the implementation of ICDMP, with a decline in the rate of increase in claims paid observed for targeted Medicaid program populations across the state of Indiana.
    Keywords: Medicine ; Public Health;
    ISSN: 0025-7079
    E-ISSN: 15371948
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  • 2
    In: Medical Care, 2005, Vol.43(10), pp.979-984
    Description: OBJECTIVE:: The objective of this study was to compare the ability of risk stratification models derived from administrative data to classify groups of patients for enrollment in a tailored chronic disease management program. SUBJECTS:: This study included 19,548 Medicaid patients with chronic heart failure or diabetes in the Indiana Medicaid data warehouse during 2001 and 2002. MEASURES:: To predict costs (total claims paid) in FY 2002, we considered candidate predictor variables available in FY 2001, including patient characteristics, the number and type of prescription medications, laboratory tests, pharmacy charges, and utilization of primary, specialty, inpatient, emergency department, nursing home, and home health care. METHODS:: We built prospective models to identify patients with different levels of expenditure. Model fit was assessed using R statistics, whereas discrimination was assessed using the weighted kappa statistic, predictive ratios, and the area under the receiver operating characteristic curve. RESULTS:: We found a simple least-squares regression model in which logged total charges in FY 2002 were regressed on the log of total charges in FY 2001, the number of prescriptions filled in FY 2001, and the FY 2001 eligibility category, performed as well as more complex models. This simple 3-parameter model had an R of 0.30 and, in terms in classification efficiency, had a sensitivity of 0.57, a specificity of 0.90, an area under the receiver operator curve of 0.80, and a weighted kappa statistic of 0.51. CONCLUSION:: This simple model based on readily available administrative data stratified Medicaid members according to predicted future utilization as well as more complicated models.
    Keywords: Medicine ; Public Health;
    ISSN: 0025-7079
    E-ISSN: 15371948
    Library Location Call Number Volume/Issue/Year Availability
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