Understanding the High Prevalence of Low-Prevalence Chronic Disease Combinations: Databases and Methods for Research. Centers for Medicare & Medicaid Services Datasets

09/20/2013

CMS Chronic Conditions Warehouse

References:

Chronic Conditions Data Warehouse. 2013. https://www.ccwdata.org/web/guest/home

Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations
Sponsorship: Centers for Medicare & Medicaid Services
Description: The Chronic Condition Data Warehouse (CCW) is a research database designed to make Medicare, Medicaid, Assessments, and Part D Prescription Drug Event data more readily available to support research designed to improve the quality of care and reduce costs and utilization for chronic disease patients. Data is available across beneficiaries’ continuum of care.
Database: (Scope, Size, Setting, Population, Age Range) National-Population-specific; All Medicare patients.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) The CMS Chronic Condition Warehouse is an amalgamation of linked datasets, including Medicare, Medicaid, and Part D Claims and Assessment data.
Database Source/Origin:

CCW contains the following 100% Medicare files for years 1999–2010:

  • Fee-for-service institutional and non-institutional claims
  • Enrollment/eligibility
  • Assessment data

100% Medicaid files for years 1999–2008 and 2009/partial states available. 100% Part D Prescription Drug Event data for years 2006–2010

  • Plan characteristics
  • Pharmacy characteristics
  • Prescriber characteristics
Date or Frequency of Data Collection: Ongoing; Data from 1999–2010.
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: CCW data are linked by a unique, unidentifiable beneficiary key, which allows researchers to analyze information across the continuum of care.
Sampling Strategy: All Medicare beneficiaries.
Unit of Analysis: Medicare Beneficiary
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis) CCW has a specific condition algorithm to determine chronic condition categories. For each chronic condition category, specific primary, principal or secondary diagnosis codes are used to “flag” the event.
Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9, CPT4, HCPCS codes
Number of Diagnoses Captured: Twenty-seven chronic conditions are maintained in the CCW.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) Medicare & Medicare Claims; Part D Prescription Drug Costs
Measures of Healthcare Utilization: (Number of Visits, Any Procedures/Number of Procedures/Type of Procedure, Number of Admission/Type of Admission, Length of Stay, Hospitalizations, Emergency Department Utilization, etc.) Number of Claims, Number of Visits, and Type of Procedure.
Measures of Healthcare Access: CCW includes an Access to Care File.
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Sex, Race, Insurance Type, Dual Eligibility Status, Age, preferred language, marital status, etc.
Clinical Information: (BMI, Medical Conditions [high blood pressure], Smoker Status, History of Various Conditions, Preventative Health Measures , Activities of Daily Living, Instrumental Activities of Daily Living) n/a
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) Zip code
Site of Service Information: CCW includes information on site of service (hospital, nursing home, etc.)
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions) Mortality, morbidity, Mobility, functional status, quality of life, quality measures, quality of care.
Strengths, Limitations & Feasibility
Data Strengths: Links beneficiaries across multiple care settings and representative of all Medicare patients.
Data Limitations: Since claims for most services provided to Medicare beneficiaries in managed care do not reach the claim data files, the CCW Medicare claims should be viewed as providing utilization information primarily for the fee- for-service population.
Data Access Restrictions: CCW data files may be requested for any of the predefined chronic condition cohorts, or users may request a customized cohort(s) specific to research focus areas.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) CCW files can be linked together via a single unique identifier for each beneficiary.
Related Grouping Systems: ICD-based grouping systems.

 

CMS Medicare Provider Analysis and Review (MedPAR) File

References:

CMS MedPAR Hospital Data File. 2013. http://www.healthdatastore.com/cms-medpar-hospital-data-file.aspx#

Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations
Sponsorship: Centers for Medicare & Medicaid Services
Description: The Medicare Provider Analysis and Review (MEDPAR) File contains data from claims for all services provided to beneficiaries admitted to Medicare certified inpatient hospitals and skilled nursing facilities (SNF).
Database: (Scope, Size, Setting, Population, Age Range) National; representative of Medicare patients; 12 million in-patient visits
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) Medicare Claims
Database Source/Origin: Medicare claims for inpatient visits from over 6,000 hospitals.
Date or Frequency of Data Collection: 1991–2012; updated yearly.
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: The Centers for Medicare and Medicaid Services (CMS) collects and releases data for all U.S. hospital inpatient stays for Medicare beneficiaries. Each record in the MedPAR file represents an inpatient stay during the calendar year of the file and has information on diagnosis, procedure, charge, payment, provider and patient for the claim.
Sampling Strategy: All Medicare related inpatient hospital stays.
Unit of Analysis: Inpatient Stay
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis)

Principal Diagnosis

Admission Diagnosis

Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9-CM
Number of Diagnoses Captured: Up to 9 diagnoses and 6 surgical procedure codes are captured in the MedPAR file.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs)

Total Charges

Total Payments

Measures of Healthcare Utilization: (Number of Visits, Any Procedures/Number of Procedures/Type of Procedure, Number of Admission/Type of Admission, Length of Stay, Hospitalizations, Emergency Department Utilization, etc.)

Number of Inpatients Visits

Length of Stay

Measures of Healthcare Access: n/a
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Age, Gender and Race.
Clinical Information: (BMI, Medical Conditions [high blood pressure], Smoker Status, History of Various Conditions, Preventative Health Measures , Activities of Daily Living, Instrumental Activities of Daily Living) n/a
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) State, Country Zip Code
Site of Service Information: Hospital provider number can be used to identify geographic region.
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions) Discharge Status
Strengths, Limitations & Feasibility
Data Strengths: Representative of all Medicare-related hospital inpatient admissions.
Data Limitations: MedPAR data is generally available with one year lag time and covers around one-third of all hospital inpatients; and almost all of its patients are 65 plus. Consequently, some specialties such as Pediatrics and Obstetrics are practically absent.
Data Access Restrictions: Because of data use restrictions, CMS cannot sell access to the raw data, but can provide a wide array of tabulations and descriptive statistics.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) n/a
Related Grouping Systems: ICD-based grouping systems.

 

Medicare Health Outcomes Survey

References:

Medicare Health Outcomes Survey. 2013. http://www.hosonline.org/Content/Default.aspx

Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations
Sponsorship: Centers for Medicare & Medicaid Services
Description: The Medicare HOS is the first outcomes measure used in Medicare managed care programs. The goal of the Medicare HOS program is to gather valid and reliable health status data in Medicare managed care for use in quality improvement activities, plan accountability, public reporting, and improving health. The Medicare HOS 2.0 contains four major components:
  • the Veterans RAND 12 Item Health Survey (VR-12)
  • questions to gather information for case-mix and risk-adjustment
  • four HEDIS® Effectiveness of Care measures
  • additional health questions
Database: (Scope, Size, Setting, Population, Age Range) Medicare beneficiaries 18 years or older enrolled in Medicare Advantage Organizations with a minimum of 500 enrollees.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) Survey
Database Source/Origin: Patient Survey Data
Date or Frequency of Data Collection: Once a year, starting in 1998.
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: Data is collected from participating Medicare Advantage Organizations (MAOs) with a minimum of 500 enrollees.
Sampling Strategy: Each spring a random sample of Medicare beneficiaries is drawn from each participating MAO, that has a minimum of 500 enrollees and is surveyed (i.e., a survey is administered to a different baseline cohort, or group, each year). Two years later, these same respondents are surveyed again. Effective 2007, the MAO sample size is increased to twelve hundred.
Unit of Analysis: Respondent, MAO’s, etc.
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis) Self-reported diagnosis
Diagnosis Codes: (ICD-9, ICD-10, SNOMED) Self-reported diagnosis
Number of Diagnoses Captured: Hypertension or high blood pressure, Angina pectoris or coronary artery disease, Congestive heart failure, Myocardial infarction or heart attack, Other heart conditions such as problems with heart valves or the rhythm of heartbeat, Stroke, Emphysema, or asthma, or COPD, Crohn’s disease, ulcerative, colitis, or inflammatory bowel disease, Arthritis of the hip or knee, Arthritis of the hand or wrist, Osteoporosis, Sciatica, Diabetes, high blood sugar, or sugar in the urine, Any cancer other than skin cancer, and Poor eyesight.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) n/a
Measures of Healthcare Utilization: (Number of Visits, Any Procedures/Number of Procedures/Type of Procedure, Number of Admission/Type of Admission, Length of Stay, Hospitalizations, Emergency Department Utilization, etc.)

Enrollment duration

Caregiving for others in household

Measures of Healthcare Access: Difficulty of getting around
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Age, Gender, Marital Status, Race, and Education.
Clinical Information: (BMI, Medical Conditions [high blood pressure], Smoker Status, History of Various Conditions, Preventative Health Measures , Activities of Daily Living, Instrumental Activities of Daily Living)

BMI, Depression screen indicator, History of pain, Height

History of falls, Comorbid Medical Conditions (Beneficiary reported)

Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location)

Annual household income

English language skills

Household size

Place of residence

Site of Service Information: n/a
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions)

Health Status

Activity Level

Strengths, Limitations & Feasibility
Data Strengths: Data can be used to assess the performance of MAOs and to reward high performers. Data can be used by health researchers to advance the state of the science in functional health outcomes measurement. Data can be used by managed care organizations, providers, and quality improvement organizations to monitor and improve health care quality.
Data Limitations: Lacks cost information. Lacks information on chronic conditions besides the ones specifically inquired about.
Data Access Restrictions: Several types of Medicare HOS data files are available for research purposes. Medicare HOS data files are available as public use files, limited data sets, and research identifiable files.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) Beneficiaries are identified through their health insurance claims numbers. However, a beneficiary’s HIC number can change through special circumstances.
Related Grouping Systems: n/a

 

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