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Rehabilitation Dataset Directory: Dataset Profile


Dataset: Minimum Data Set (MDS (v.3.0))

Basic Information
Dataset full name: Minimum Data Set
Dataset acronym MDS (v.3.0)
Summary The MDS is a standardized screening and clinical assessment tool of the health and functional status of all residents (regardless of payer types) in skilled nursing facilities (long-term care facilities) certified by Medicare and Medicaid. The MDS 3.0 was implemented in October 2010 replacing the MDS 2.0 version. The MDS measures the health status of residents in the following domains: Hearing, Speech, and Vision; Cognitive Patterns; Mood; Behavior; Preferences for Customary Routine and Activities; Functional Status (including Activities of Daily Living); Bladder and Bowel; Medical Diagnosis; Health Conditions; Skin Conditions; Medications; Special Treatment and Procedures; Participation in Assessment and Goal Settings; and Therapy Supplement for Prospective Payment System.
Key Terms Outcomes in the following areas: Hearing, Speech, and Vision; Cognitive Patterns; Mood; Behavior; Preferences for Customary Routine and Activities; Functional Status (including Activities of Daily Living); Bladder and Bowel; Medical Diagnosis; Health Conditions; Skin Conditions; Medications; Special Treatment and Procedures; Participation in Assessment and Goal Settings; and Therapy Supplement for Prospective Payment System.
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) Any/All
Disability Measures Any/All
Measures/outcomes of interest
Topics Hearing, Speech, and Vision; Cognitive patterns; Mood; Behavior; Preferences for customary routine and activities; Functional status (including Activities of Daily Living); Bladder and bowel; Medical diagnosis; Health conditions; Skin conditions; Medications; Special treatment and procedures; Participation in assessment and goal settings; Therapy supplement for prospective payment system.
Sample
Sample Population Residents of Medicare and Medicaid certified Skilled Nursing Facilities
Sample Size/Notes ~2,500,000 (±) Medicare patients qualified to receive post-acute care at nursing facilities
Unit of Observation Patient
Geographic Coverage National
Geographic specificity Zip Code
Data Collection
Data Collection Mode Administrative
Years Collected 1999-2009
Data Collection Frequency Annual
Strengths and limitations
Strengths Large sample size, longitudinal functional status data. Can be linked with claims and/or other CMS non-CMS data. Includes quality indicators. Adequate and appropriate documentation is available regarding use of data/variables.
Limitations No rehabilitation intervention details. Lacks other clinical information/observation details.
Data details
Primary Website http://www.cms.gov/NursingHomeQualityInits/25_NHQIMDS30.asp#TopOfPage
Data Access http://www.resdac.org/Medicare/requesting_data.asp
Data Access Requirements Data Use agreement, $ Cost
Summary Tables/reports http://www.medicare.gov/NHCompare/Include/Data
Dataset components (where applicable) NA
Selected papers
Technical MDS 3.0 Record Layout MDS 2.0 Record Layout Linking the Nursing Home Minimum Data Set (MDS) with Other CMS Facility Data. Technical Brief, ResDAC Publication Number TN-007, April 2005. Research Data Assistance Center, University of Minnesota, Minneapolis, MN. http://www.resdac.umn.edu.
Other Papers



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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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