Abstract

Cost trend plays a crucial role in evaluating the outcome of disease management (DM) programs, which typically attempt to manage members who have any of 5 major chronic conditions (the chronic population) through targeted intervention. A widely adopted methodology for evaluating DM outcomes is commonly referred to as the "pre-post" method, also known as the adjusted historical control method. One drawback of the pre-post approach is the need for a valid trend adjustment so that program year and baseline year costs can be compared to determine the impact of the DM program. The trend adjustment plays a crucial role in the pre-post methodology because the estimated cost savings is very sensitive to the variation in the trend estimate. DMAA: The Care Continuum Alliance recommends that the concurrent trend for members who do not have any of the 5 chronic conditions (the non-chronic population) be used to estimate the chronic trend. One major assumption in using this method is that there is a relatively stable relationship between the chronic trend and the non-chronic trend for the same population in the absence of the DM program. In this analysis, the relationship between the two trends is studied based on empirical data. Some key factors that may impact the relationship between the chronic and non-chronic trends are also examined. Medical and pharmacy claims from a large commercial client over a 4-year period were collected for the analysis. This client did not have any robust DM program in place during the 4-year period. The major findings from this study include: (1) The method used to identify the chronic population for calculating the trend has a significant impact on the relationship between the chronic and non-chronic trends. With the Annual Qualification method, in which the chronic members are identified using the claims in a specific time period regardless of whether they have been identified previously or thereafter, the relationship between the non-chronic and chronic trends appears stable over time. With the Prospective method, the non-chronic trend does not serve as a good estimate of the chronic trend. (2) It is important to use risk adjustment when calculating trends to account for risk changes within the population from year to year. The chronic and non-chronic trends converge further when risk adjustment is applied. Based on the empirical evidence from the data used in this study, the concurrent non-chronic trend could be used to help estimate the chronic trend if the proper member selection method (Annual Qualification) is used to select the chronic population and proper steps are taken to adjust the different risk levels from year to year. One should not conclude, however, that such a stable relationship between chronic and non-chronic trend has been universally validated based on this single study. This study highlights the importance of carefully validating trend relationships from a particular population before assuming a stable trend relationship in DM program outcome evaluation.