Testing the Feasibility of a Passive and Active Case Ascertainment System for Multiple Rare Conditions Simultaneously: The Experience in Three US States

Background: Owing to their low prevalence, single rare conditions are difficult to monitor through current state passive and active case ascertainment systems. However, such monitoring is important because, as a group, rare conditions have great impact on the health of affected individuals and the well-being of their caregivers. A viable approach could be to conduct passive and active case ascertainment of several rare conditions simultaneously. This is a report about the feasibility of such an approach. Objective: To test the feasibility of a case ascertainment system with passive and active components aimed at monitoring 3 rare conditions simultaneously in 3 states of the United States (Colorado, Kansas, and South Carolina). The 3 conditions are spina bifida, muscular dystrophy, and fragile X syndrome. Methods: Teams from each state evaluated the possibility of using current or modified versions of their local passive and active case ascertainment systems and datasets to monitor the 3 conditions. Together, these teams established the case definitions and selected the variables and the abstraction tools for the active case ascertainment approach. After testing the ability of their local passive and active case ascertainment system to capture all 3 conditions, the next steps were to report the number of cases detected actively and passively for each condition, to list the local barriers against the combined passive and active case ascertainment system, and to describe the experiences in trying to overcome these barriers. Results: During the test period, the team from South Carolina was able to collect data on all 3 conditions simultaneously for all ages. The Colorado team was also able to collect data on all 3 conditions but, because of age restrictions in its passive and active case ascertainment system, it was able to report few cases of fragile X syndrome. The team from Kansas was able to collect data only on spina bifida. For all states, the implementation of an active component of the ascertainment system was problematic. The passive component appears viable with minor modifications. Conclusions: Despite evident barriers, the joint passive and active case ascertainment of rare disorders using modified existing surveillance systems and datasets seems feasible, especially for systems that rely on passive case ascertainment

Psychology and aggression

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68264/2/10.1177_002200275900300301.pd

Learning your ABDs: Variation in health care utilization across Kansas Medicaid disability groups.

Abstract Background State Medicaid programs provide critical health care access for persons with disabilities and older adults. Aged, Blind and Disabled (ABD) programs consist of important disability subgroups that Medicaid programs are not able to readily distinguish. Objective/hypothesis The purpose of this project was to create an algorithm based principally on eligibility and claims data to distinguish disability subgroups and characterize differences in demographic characteristics, disease burden, and health care expenditures. Methods We created an algorithm to distinguish Kansas Medicaid enrollees as adults with intellectual or developmental delays (IDD), physical disabilities (PD), severe mental illness (SMI), and older age. Results For fiscal year 2009, our algorithm separated 101,464 ABD enrollees into the following disability subgroups: persons with IDD (19.6%), persons with PD (21.0%), older adults (19.7%), persons with SMI (32.8%), and persons not otherwise classified (6.9%). The disease burden present in the IDD, PD, and SMI subgroups was higher than for older adults. Home- and community-based services expenditures were common and highest for persons with IDD and PD. Older adults and persons with SMI had their highest expenditures for long-term care. Mean Medicaid expenditures were consistently higher for adults with IDD followed by adults with PD. Conclusions There are substantial differences between disability subgroups in the Kansas Medicaid ABD population with respect to demographics, disease burden, and health care expenditures. Through this algorithm, state Medicaid programs have the opportunity to collaborate with the most closely aligned service providers reflecting needed services for each disability subgroup