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Dataset: Medicare-Medicaid Linked Enrollee Analytic Data Source (MMLEADS)

Basic Information
Dataset Full Name Medicare-Medicaid Linked Enrollee Analytic Data Source
Dataset Acronym MMLEADS
Summary

The Medicare-Medicaid Linked Enrollee Analytic Data Source (MMLEADS) is a relatively new (2012) comprehensive dataset for researchers investigating health services utilization patterns and associated outcomes for dual enrollees, especially individuals with disabilities. It is developed by the Centers for Medicare and Medicaid Services (CMS) and contains person-level information for Medicare and/or Medicaid beneficiaries (duel enrollees). MMLEADS offers files at two levels: individual-level (extracted from Medicare and Medicaid beneficiary-level files), and service-level (extracted from Medicare and Medicaid service-level files).


It includes 27 individual-level chronic and clinical conditions as defined by the Chronic Condition Warehouse (CCW) including: cardiovascular conditions, cancer, musculoskeletal disorders, pulmonary conditions, metabolic syndrome, and mental health disorders. For more information on the CCW, see: https://www.ccwdata.org/web/guest/condition-categories
Key Terms Eligibility of benefits, Enrollment status, Health services utilization, Cost, Physical conditions, Mental conditions, Chronic and clinical conditions
Study Design Longitudinal
Data Type(s) Administrative
Sponsoring Agency/Entity

Department of Health and Human Services (HHS)

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

 ADD/ADHD, Alzheimer's/dementia, Anxiety disorders, Autism spectrum disorders, Bipolar disorder, Blood disorder, Body mass index (BMI)/obesity, Cancer, Cardiovascular conditions,Congenital conditions, Depression, Diabetes, Epilepsy or seizure disorder, Eye diseases, Heart attack, Infectious diseases, Kidney/renal condition, Migraine or frequent headaches, Multiple sclerosis, Muscular dystrophy, Orthopedic conditions, Osteoporosis, Post traumatic stress disorder (PTSD), Schizophrenia, Spinal cord injury (SCI), Stroke, Thyroid disease,  Traumatic brain injury (TBI)
Disability Measures Cognitive disability, Developmental disabilities, Hearing disability, Intellectual disability, Mental health disability, Visual disability
Measures/Outcomes of Interest
Topics Medicare/Medicaid beneficiaries, Enrollment status on a monthly basis, Institutional service utilization (acute care, post-acute care, and long term care), Outpatient service utilization (including prescription of durable medical equipment), Health outcomes, Medicare, Medicaid, Dual category monthly and annual payment summaries.
Sample
Sample Population Medicare and/or Medicaid beneficiaries
Sample Size/Notes

2015 data:

58.4 million unique individuals:

  • 11.4 million with dual eligibility (Medicare and Medicaid)
  • 47 million Medicare only
  • 4.8 million Medicare only with disability
Unit of Observation Individual
Continent(s) North America
Countries

United States
Geographic Coverage United States
Geographic Specificity State and Zip Code
Special Population(s)

Medicare and Medicaid beneficiaries
Data Collection
Data Collection Mode Administrative linking
Years Collected 2006-present
Data Collection Frequency Ongoing
Strengths and Limitations
Strengths Very large sample size. Contains a variety of chronic health and disability-related conditions including mental health diagnoses. Permits examination of health service cost and utilization patterns for individuals with disabilities. Linked structure allows examination of long-term care services access/utilization and continuity of care. Can be linked with assessment data from post-acute care settings (IRF-PAI, MDS, OASIS), other CMS data, and non-CMS data (Census, Area Health Resource File).
Limitations Managed Care service utilization and sometimes spending information is NOT included. If full benefit Medicare-Medicaid enrollees’ participation in Medicare or Medicaid managed care is 35% or more in a state, ALL of that state's data is excluded from MMLEADS files. Limited technical documentation for research purposes and little research currently exists. Research design and analysis is complicated due to state level variations in Medicaid infrastructure and programs.
Data Details
Primary Website https://www.resdac.org/cms-data/files/mmleads
Data Access

Accessing PUF and RIF:

https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/DataStatisticalResources/DataToolsResearchers.html


PUF:

https://www.cms.gov/Research-Statistics-Data-and-Systems/Downloadable-Public-Use-Files/MMLEADS/index.html


RIF:

https://www.resdac.org/cms-data/request/research-identifiable-files
Data Access Requirements

Public Use File

Data Use Agreement, No cost -- Research Identifiable File (RIF) 
Summary Tables/Reports

NA
Data Components
  • Medicare beneficiary-level file
  • Medicaid beneficiary-level file
  • Medicare service-level file
  • Medicaid service-level file
  • Individual-level Chronic/Clinical condition file (person level)
Selected Papers
Other Papers

Data Analysis Brief:

https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/Downloads/Dual_Enrollment_2006-2011_Final_Document.pdf
Technical

CCW MMLEADS V2 User Guide

https://www2.ccwdata.org/documents/10280/19002246/mmleads-user-guide-v2-0.pdf 


MMLEADS Public Use File : A Methodological Overview:

https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/Downloads/MMLEADS_PUF_UserGuide_MethodologicalOverview_042017.pdf 


MMLEADS Public Use File: A Methodological Overview, April 2017

https://www.cms.gov/Medicare-Medicaid-Coordination/Medicare-and-Medicaid-Coordination/Medicare-Medicaid-Coordination-Office/Downloads/MMLEADS_PUF_UserGuide_MethodologicalOverview_042017.pdf

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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).

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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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