Epidemiology and Biostatistics
Epidemiology and Biostatistics at the NIH Clinical Center conduct collaborative clinical research. Examples of current ongoing research are:
Adults with Chronic Health Care Needs
The purpose of this project is to develop population-level profiles and estimates for adults with chronic health care needs, including those with long-lasting health conditions and/or disabilities. These sub-populations are of particular interest because they are expected to have elevated health service needs over an extended period of time. While the current health care system frequently excels at responding to immediate medical needs such as injuries and acute illnesses, it is sometimes less successful providing ongoing care to people with chronic conditions and disabilities in order to improve their day-to-day lives. This stands in considerable contrast to the pediatric health services arena, which made an important transition in the mid 1990s to a population-level, criteria-based definition of children with chronic conditions and/or disabilities, now known as Children with Special Health Care Needs (CSHCNs). The criteria formulated to define this group have been used to develop nationally representative surveys and estimates of need for, access to, use and cost of services in this population. Findings from these studies have been used to inform both policy making (such as the Family Opportunity Act of 2005) and service delivery models (such as the medical home initiative). In addition to conducting analyses of currently available data, the E&B section has convened a national panel of experts on measurement of elevated health care needs among adults with chronic conditions and disabilities which includes several members who helped to fashion the original CSHCN screener. The purpose of the panel is to develop a population-level screening instrument intended for use in health surveys and designed to provide the health services research community with the capacities to: a) identify adults with chronic health care needs in a consistent manner: b) estimate the prevalence, type and level of health care needs in this population and c) provide a vehicle for further study of access, quality, coordination and health care cost among these adults.
Analyzing the SSA Disability Evaluation Process
The Social Security Administration (SSA) continues to seek ways to effectively and efficiently adjudicate its disability claims. Historically, SSA has attempted to provide adjudicators with screening tools designed to expedite claim allowances. One such screening tool is the Listing of Impairments, which identifies categories of medical diagnoses by group. However, evidence suggests that the diagnostic basis for the Listings has become less useful a marker of disability. Data from the SSA indicate that early use of the Listings accounted for more than 90% of allowances, however by 2004, the Listings accounted for only 52% of the allowances. It is in this context that the SSA sought help from the NIH (RMD) to examine existing SSA data to improve screening processes and to explore innovative methods for augmenting their existing disability evaluation process. Thus, this project includes two major lines of research: 1) analysis of existing SSA data, and 2) assessing the feasibility of developing Computer Adaptive Testing (CAT) instruments that can be integrated into the SSA data collection and determination processes. It will be necessary to identify important information gaps, suggest questions that should be asked when claimants first apply for disability benefits, and to identify characteristics of claims that are ultimately allowed in order to inform the screening process. This information will also be used to determine additional content needs for modification of existing CATs or development of new CATs. Preliminary work will help to inform us about project feasibility by evaluating the content, quality, and completeness of information that is collected at the various stages of the SSA evaluation process. Once feasibility has been established, data analysis and CAT development will proceed concurrently for this multi-year project.
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This page last updated on 07/26/2017