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Dataset: Master Beneficiary Summary File (MBSF) Cost & Use Segment (CUS) (MBSF-CUS)

Basic Information
Dataset Full Name Master Beneficiary Summary File (MBSF) Cost & Use Segment (CUS)
Dataset Acronym MBSF-CUS

The Cost & Use Segment (CUS) is one of five segments available in the Chronic Conditions Data Warehouse (CCW) Master Beneficiary Summary File (MBSF). The Cost and Use segment includes summaries of Medicare payment amounts and services utilization.

The CUS is a segment of the Chronic Conditions Data Warehouse (CCW) Master Beneficiary Summary File (MBSF), 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, tied together with a unique beneficiary key allowing linkages of an individual's data across data types and sources.  It contains 100% Medicare files (1999-present), 100% Medicaid 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 across 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 specific chronic condition cohorts or an investigator-defined sample.

The other data segments available in the Master Beneficiary Summary File can be requested and linked to the Cost and Use segment data:

Key Terms

Beneficiaries, Chronic Conditions, Medicaid, Medicare, Medical costs, Medical payments, Cost & Use Segment (CUS), Covered days,  Length of stay (LOS), Medicaid, Medicare, Re-admissions

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)

Note: Health conditions are NOT available in the Cost & Use Segment (CUS), however the CUS can be requested along with and linked to the Chronic Condition Segment (CCS) that identifies the following chronic conditions:

Data directory tagged conditions in Chronic Condition Segment (CCS):

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

Full list of chronic conditions

The Cost & Use Segment (CUS) data can be also be linked to the "Other Chronic or Potentially Disabling Conditions" segment that identifies the following:

Data directory tagged 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
Disability Measures

No disability measures are available in the  Cost & Use Segment (CUS), however it can be linked to the Chronic Condition Segment (CCS) and the Other Chronic or Potentially Disabling Conditions segment that identify the following disability measures:

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

Learning disabilities

Measures/Outcomes of Interest

Payments, Amounts, Readmission, Length of stay, Events

Sample Population

Medicare and Medicaid beneficiaries:
  • 100% Medicare: 1999-2016
  • 100% Medicaid: 1999-2014
  • 100% Part D Prescription Drug Event: 2006-2016

Sample Size/Notes
For calendar year 2016: 
  • Medicare- 57 million
  • Medicaid- 70.9 million
  • Part D: 41.2 million
Unit of Observation



North America


United States

Geographic Coverage

National (U.S.)

Geographic Specificity

Zip Code

Special Population(s)


Data Collection
Data Collection Mode

Data is collected via billing submitted to CMS by providers, facilities or suppliers.

Years Collected

1999 - present

Data Collection Frequency


Strengths and Limitations
  • 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
  • Requires high computational and data analytical capabilities   
  • No history prior to them as beneficiaries is available in the data.
Data Details
Primary Website

Data Access

Data Access Requirements

Data Use agreement, $ Cost

Link to Data Pricing Calculator

Summary Tables/Reports

Medicare Tables & Reports - Medicare Cost & Utilization Statistics:

Data Components
Similar/Related Dataset(s)

Other Master Beneficiary Summary File (MBSF) segments:

Selected Papers
Other Papers

White papers and presentations:


User Documentation:

CCW Medicare Administrative Data User Guide:

Data Dictionaries:

Technical Guidance Documentation:

User Documentation:

CCW Medicare Administrative Data User Guide:

Data Dictionaries:

Technical Guidance Documentation:

Study size sample estimator (user specifies parameters and interface calculates estimated 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:

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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