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Dataset: Master Beneficiary Summary File (MBSF) Chronic Condition Segment (CCS) (MBSF-CCS)

Basic Information
Dataset Full Name Master Beneficiary Summary File (MBSF) Chronic Condition Segment (CCS)
Dataset Acronym MBSF-CCS
Summary

The Chronic Condition Segment (CCS) is one of five segments available in the Chronic Conditions Data Warehouse (CCW) Master Beneficiary Summary File (MBSF). The Chronic Condition Segment (CCS) includes identifiers for 27 chronic health 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 Chronic Condition Segment contains 27 Chronic Conditions  for which 3 data points per condition are provided: 


  1. End-of-Year Indicator- whether or not the patient met CCW criteria for the condition at end of calendar year
  2. Mid-Year Indicator- whether or not the patient met CCW criteria for the condition on July 1 of specified year
  3. Ever – the date a beneficiary first met claims criteria for the chronic condition


There are four other data segments available in the Master Beneficiary Summary File that can be requested and linked to the Chronic Condition Segment (CCS) data:

Key Terms Beneficiaries, Chronic Conditions, Medicare, Medical costs, Medical payments
Study Design Longitudinal
Data Type(s) Administrative
Sponsoring Agency/Entity

Department of Health and Human Services (HHS);

Center for Medicare and Medicaid Services (CMS)
Health Conditions/Disability Measures
Health Condition(s)

The health conditions data in the CCS contains conditions that are 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).

Further, by linking with other "Other Chronic or Potentially Disabling Conditions" these additional conditions are available:

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
Disability Measures

Mental health disability, Visual disability, Hearing disability, Cognitive disability, Intellectual disability, Ambulatory disability,

Learning disabilities

Measures/Outcomes of Interest
Topics Comorbidity, Chronic conditions
Sample
Sample Population
Medicare beneficiaries:
  • 100% Medicare: 1999-2016
  • 100% Part D Prescription Drug Event: 2006-2016
Sample Size/Notes
For calendar year 2016: 
  • Medicare- 57 million
  • Part D: 41.2 million
Unit of Observation Individual/Patient
Continent(s)

North America

Countries

United States

Geographic Coverage

National (U.S.)

Geographic Specificity Zip Code (of beneficiary’s mailing address)
Special Population(s)

Medicare beneficiaries

Data Collection
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
Strengths
  • Very large sample size
  • Files can be requested for a predefined or customized chronic condition cohort
  • Population-based dataset (includes all beneficiaries)
  • Can be linked  via unique beneficiary ID to the other Master Beneficiary Summary File (MBSF) segments:
  • Can be used to perform cross-state and within-state comparisons
Limitations
  • Beneficiaries are only flagged as having a condition once they receive treatment for the specified condition paid for by Medicare
  • Care must be taken in utilizing the data to calculate population statistics (see Technical Guidance for more information)
  • Requires high computational and data analytical capabilities   
    • CMS Virtual Research Data Center (VRDC) that includes SAS for performing analysis 

Data Details
Primary Website https://www.ccwdata.org
Data Access https://www.resdac.org/research-identifiable-files-rif-requests
Data Access Requirements

Data Use agreement, $ Cost

Link to Data Pricing Calculator

Summary Tables/Reports

Medicare Chronic Condition Prevalence Charts:

https://www.ccwdata.org/web/guest/medicare-charts/medicare-chronic-condition-charts


Medicare Tables & Reports - Chronic Condition Statistics:

https://www.ccwdata.org/web/guest/medicare-tables-reports

Data Components
Similar/Related Dataset(s)

Other Master Beneficiary Summary File (MBSF) segments:

Selected Papers
Other Papers

White papers and presentations:

https://www.ccwdata.org/web/guest/white-papers-presentations

Technical

User Documentation:

https://www.ccwdata.org/web/guest/user-documentation


CCW Medicare Administrative Data User Guide:

https://www.ccwdata.org/documents/10280/19002246/ccw-medicare-data-user-guide.pdf


Data Dictionaries:

https://www.ccwdata.org/web/guest/data-dictionaries


Technical Guidance Documentation:



Study size sample estimator (user can specify parameters and estimator outputs approximate sample available):

FAQ:

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:

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.

For questions or comments please contact disabilitystatistics@cornell.edu