FIND Disability Statistics
American Community Survey (ACS)
- Employment Rate
- Not Working but Actively Looking for Work
- Full-Time / Full-Year Employment
- Annual Earnings
- Annual Household Income
- Supplemental Security Income (SSI)
- Educational Attainment
- Veterans Service-Connected Disability
- Health Insurance Coverage (and Type)
Current Population Survey (CPS)
EEOC Charge Data
Rehabilitation Dataset Directory: Dataset Profile
Dataset: Master Beneficiary Summary File (MBSF) Other Chronic or Potentially Disabling Conditions segment (MBSF-OCPDC)
|Dataset Full Name||Master Beneficiary Summary File (MBSF) Other Chronic or Potentially Disabling Conditions segment|
The Other Chronic or Potentially Disabling Conditions is one of five segments available in the Chronic Conditions Data Warehouse (CCW) Master Beneficiary Summary File (MBSF). The OCPDC segment of the MBSF contains 39 chronic health, mental health, substance abuse, and potentially disabling condition categories. These conditions are designed to enhance research of the Medicare-Medicaid dual enrolled population, however they are available for all non-dually enrolled Medicare and Medicaid beneficiaries as well.
The conditions include: 11 mental health and tobacco use conditions, 15 developmental disorder and disability-related conditions, and 9 other chronic physical and behavioral health conditions which were developed by CMS. There is an end of the year version of the variables and an “ever” indicator variable for each of the conditions.
The Chronic Conditions Data Warehouse (CCW) Master Beneficiary Summary File (MBSF) is a research database created by the Center for Medicare and Medicaid Services (CMS) following passage of the Medicare Modernization Act of 2003. CCW data contains CMS administrative data that spans multiple care settings starting in 1999, and includes a unique beneficiary key that allows the linking of an individual's data across data types and sources. It contains 100% Medicare files (1999-present), as well as 100% of Part D Prescription Drug Event data (1999-present).
The design of the CCW linked data allows researchers to analyze information across the continuum of care and multiple care settings. The purpose of the CCW is to help researchers identify and improve the quality of healthcare for chronically ill Medicare beneficiaries.
The Master Beneficiary Summary File (MBSF) is made up of five segments. CCW data are available upon request for a random 5% sample, for a specific chronic condition cohorts or an investigator-defined sample. The Other Chronic or Potentially Disabling Conditions data includes 35 specific health conditions for which 3 data points per condition are provided:
There are four other data segments available in the Master Beneficiary Summary File that can be requested with, and linked to the Other Chronic or Potentially Disabling Conditions data:
|Key Terms||Beneficiaries, Chronic Conditions, Medicare, Medical costs, Medical payments|
Department of Health and Human Services (HHS);Center for Medicare and Medicaid Services (CMS)
|Health Conditions/Disability Measures|
"Other Chronic or Potentially Disabling Conditions" includes the following conditions conditions tagged in this data directory, as well as 35 specific health conditions :
ADD/ADHD, Anxiety disorders, Autism spectrum disorders, Bipolar disorder, Body mass index (BMI)/obesity, Cerebral palsy, Chronic pain, Depressive disorders, Epilepsy or seizure disorder, Migraine or frequent headaches, ICD-9/10 diagnostic codes, Multiple sclerosis, Muscular dystrophy, Post traumatic stress disorder (PTSD), Pulmonary disorders, Schizophrenia, Spinal cord injury (SCI), Traumatic brain injury (TBI)
The 35 specific conditions identified in Other Chronic or Potentially Disabling Conditions segment:
ADHD, Conduct Disorders/and Hyperkinetic Syndrome, Alcohol Use Disorders, Anxiety Disorders, Autism Spectrum Disorders, Bipolar Disorder, Cerebral Palsy, Cystic Fibrosis and Other Metabolic Developmental Disorders, Depressive Disorders, Drug Use Disorders, Epilepsy, Fibromyalgia/Chronic Pain and Fatigue, Human Immunodeficiency Virus and/or Acquired Immunodeficiency Syndrome (HIV/AIDS) , Intellectual Disabilities and Related Conditions, Learning Disabilities, Leukemias and Lymphomas, Liver Disease/Cirrhosis and Other Liver Conditions, Migraine and Chronic Headache, Mobility Impairments, Multiple Sclerosis and Transverse Myelitis, Muscular Dystrophy, Obesity, Other Developmental Delays, Peripheral Vascular Disease (PVD), Personality Disorders, Post-Traumatic Stress Disorder (PTSD), Pressure and Chronic Ulcers, Schizophrenia, Schizophrenia and Other Psychotic Disorders, Sensory - Blindness and Visual Impairment, Sensory - Deafness and Hearing Impairment, Spina Bifida and Other Congenital Anomalies of the Nervous System, Spinal Cord Injury, Tobacco Use, Traumatic Brain Injury and Nonpsychotic Mental Disorders due to Brain Damage, Viral Hepatitis
Further the Chronic Condition Segment (CCS) data can also be linked to the OCPDC data and includes the following health conditions specifically tagged in this data directory, as well as 27 specific chronic health conditions:
Alzheimer's/dementia, Arthritis, Blood disorder, Cancer, Depression, Diabetes, Eye diseases , Heart attack, ICD-9/10 diagnostic codes, Kidney/renal condition, Orthopedic conditions, Osteoporosis, Stroke, Thyroid disease
The 27 specific chronic health conditions identified in CCS:
Acquired Hypothyroidism, Acute Myocardial Infarction, Alzheimer's Disease, Alzheimer's Disease, Related Disorders, or Senile Dementia, Anemia, Asthma, Atrial Fibrillation, Benign Prostatic Hyperplasia, Colorectal Cancer, Endometrial Cancer, Breast Cancer, Lung Cancer, Prostate Cancer, Cataracts, Chronic Kidney Disease, Chronic Obstructive Pulmonary Disease (COPD), Depression, Diabetes, Glaucoma, Heart Failure, Hip / Pelvic Fracture, Hyperlipidemia, Hypertension, Ischemic Heart Disease, Osteoporosis, Rheumatoid Arthritis/Osteoarthritis, Stroke/Transient Ischemic Attack
Complete list of chronic conditions (and criteria used).
Mental health disability, Visual disability, Hearing disability, Cognitive disability, Intellectual disability, Ambulatory disability,
|Measures/Outcomes of Interest|
|Topics||Comorbidity, Chronic conditions||Sample|
For calendar year 2016:
|Unit of Observation||Individual/Patient|
|Geographic Specificity||Zip Code (of beneficiary’s mailing address)|
|Data Collection Mode||Data is collected via billing submitted to CMS by providers, facilities or suppliers.|
|Years Collected||1999 - 2016 (ongoing)|
|Data Collection Frequency||Quarterly||Strengths and Limitations|
|Data Access Requirements||
Data Use agreement, $ Cost
Link to Data Pricing Calculator
Medicare Chronic Condition Prevalence Charts:
Other Master Beneficiary Summary File (MBSF) segments:
White papers and presentations:
CCW Medicare Administrative
Data User Guide:
Technical Guidance Documentation:
Study size sample estimator (user can specify parameters and estimator outputs approximate sample available):
What you need to know before you submit a request CMS data:
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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).
Other CLDR supported resources and collaborative opportunities:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
- Data Sharing & Archiving at CLDR
- Pilot Project Program
- Visiting Scholars Program
Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.
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