238615 Analysis of the compassionate allowance (CAL) program: A systematic data-driven approach to identifying potential CAL conditions

Tuesday, November 1, 2011: 11:24 AM

Pei-Shu Ho, PhD , Clinical Research Center, Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD
Minh Huynh, PhD , Clinical Research Center, Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD
Aaron Heuser, PhD , Clinical Research Center, Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD
Andew J. Houtenville, PhD , Department of Economics, University of New Hampshire, Durham, NH
Gloria Wheatcroft, MPH , Office of Analysis and Epidemiology, National Center for Health Statistics, CDC, Hyattsville, MD
Leighton Chan, MD, MPH , Clinical Research Center, Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD
Elizabeth K. Rasch, PT, PhD , Clinical Research Center, Department of Rehabilitation Medicine, National Institutes of Health, Bethesda, MD
Each year over three million individuals apply for Social Security Disability Insurance (DI) and Supplemental Security Income (SSI) disability benefits. Over the years, SSA has instituted procedures to increase the speed of claims processing. Most recently, Compassionate Allowances (CAL) was implemented to identify the most obvious cases for allowances based on minimal objective medical information that could be obtained quickly. Periodically, SSA expands its list of CAL conditions. Through an interagency agreement supporting SSA's efforts, NIH developed a systematic, data-driven approach to identify potential conditions for inclusion on the CAL list similar to current CAL conditions based on survival times using SSA Disability Research Files (1997 - 2006). SSA data linked to the National Health Interview Survey and the National Death Index for the same timeframe were used for benchmarking. We developed survival curves for the existing CAL conditions that could be identified in the data sets. By viewing these survival curves as elements of a Skorokhod space, we constructed a test region whose boundary was defined by these elements. We used a Kolmogorov-Smirnov test statistic to determine whether survival curves from non-CAL condition lie within this region. Using this method, we identified 25 potential CAL conditions whose survival profiles were comparable to those of current CAL conditions. These conditions included cancers, severe forms of liver disease and HIV infection, and cerebral trauma. Although data limitations presented substantial analytic challenges, we demonstrated that SSA data can be used to augment SSA's programmatic decision making processes using innovative analytic approaches.

Learning Areas:
Public health or related public policy
Public health or related research

Learning Objectives:
At the conclusion of the session, participants will be able to: (1) recognize SSAís expedited awards programs and procedures, (2) describe the development of the initial and expanded list of CAL conditions, (3) summarize the data-driven process used to identify potential CAL conditions, (4) describe the strengths and limitations of condition-specific data available in SSA administrative data and NHIS-NDI matched data, and (5) list the benefits and challenges of using SSA data sources to identify potential CAL conditions.

Keywords: Disability Policy, Mortality

Presenting author's disclosure statement:

Qualified on the content I am responsible for because: I am qualified to be an author on the content of this abstract because I have a PhD in health services organization and research, I have extensive experience studying access to care, quality of care, and the health of people with disabilities including disability programs and policies, Iíve published extensively in this area, and I am the project lead for the work described in this abstract.
Any relevant financial relationships? No

I agree to comply with the American Public Health Association Conflict of Interest and Commercial Support Guidelines, and to disclose to the participants any off-label or experimental uses of a commercial product or service discussed in my presentation.