Understanding the High Prevalence of Low-Prevalence Chronic Disease Combinations: Databases and Methods for Research. Agency for Healthcare Research and Quality Datasets

09/20/2013

Consumer Assessment of Healthcare Providers & Systems (CAHPS)
Database Description
White Paper(s): Multiple Chronic Conditions and Disparities
Sponsorship: Agency for Healthcare Research and Quality
Description: CAHPS is a series of surveys that are used to ask consumers and patients about their experiences with healthcare. These surveys cover a wide spectrum of topics, such as provider communication skills and healthcare access. The goal of CAHPS is two-fold: 1) to develop standardized patient surveys that can be used to compare results across providers over time and 2) to generate tools and resources users can use to create comparative information for all stakeholders. There are CAHPS surveys for a variety of different care settings, including hospital, home health care, health plans, and in- center hemodialysis and clinician groups.
Database: (Scope, Size, Setting, Population, Age Range) CAHPS surveys are used at various levels in the healthcare delivery system; anywhere from individual practices to national samples.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) Survey & Program Database. The CAHPS Database is a compilation of survey results from a large pool of healthcare consumers that are maintained in a national database.
Database Source/Origin: Survey Data
Date or Frequency of Data Collection: Annually, since 1995.
Longitudinal vs. Cross-sectional Database: Serial Cross-Sectional Survey
Data Collection Methodology: Data collection methodology varies by CAHPS sponsor and vendors administering the CAHPS survey. Surveys can be completed via the mail, telephone or internet.
Sampling Strategy: Sampling strategies for CAHPS vary by sponsor. CAHPS provides guidelines for sampling, including determining eligibility, calculating the estimated sample size needed for reporting, and creating a sub-sample of a specific patient population.
Unit of Analysis: Multiple (patients, providers, health plan, etc.) and dependent on survey type.
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis) A patient’s principal diagnosis at discharge is used to determine whether he or she falls into a specific service line for CAHPS eligibility. Diagnosis is not capture on the survey itself.
Diagnosis Codes: (ICD-9, ICD-10, SNOMED, CPT) Principal diagnosis ICD-9 codes at discharge.
Number of Diagnoses Captured: Only the principal diagnosis at discharge is used to determine CAHPS eligibility.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) CAHPS does not include measures of cost.
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.) CAHPS does not include measures of healthcare utilization, but the number of survey respondents can be used as a proxy for the number of discharges.
Measures of Healthcare Access: Ease of access to healthcare services.
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Age, Sex, Educational Attainment, Hispanic or Latino, Race/Ethnicity, Language
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) CAHPS does not include additional clinical information.
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) Health Literacy/Understanding
Site of Service Information: Limited - Department Based
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions) Self-reported health status, Self-reported mental health status, Quality of Care, Quality Measures and Patient Satisfaction
Strengths, Limitations & Feasibility
Data Strengths: Select CAHPS datasets contain a large number of minority respondents. Data are collected on key health policy issues, including health status.
Data Limitations: The CAHPS survey is not administered in a consistent fashion. The CAHPS database is a collection of surveys administered at various levels. As such, not all providers participate each year, so the mix of users will vary across years. Sampling and data collection methods also vary by user and are cross-sectional.
Data Access Restrictions: To access CAHPS data, a data release agreement, description of the planned research, and IRB documentation must be submitted to AHRQ. Survey instruments are publically available.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) No unique identifiers. However, CAHPS surveys have been administered to Medicare Fee-for-Service patients, which may have resulted in a linked CAHPS-claim dataset.
Related Grouping Systems: n/a

References:

Agency for Healthcare Research & Quality. Consumer Assessment of Healthcare Providers and Systems (CAPHS). 2013. http://cahps.ahrq.gov/about.htm

 

Healthcare Cost & Utilization Project - Kids’ Inpatient Database
Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations & Multiple Chronic Conditions and Disparities
Sponsorship: Agency for Healthcare Research & Quality
Description: The Kids' Inpatient Database (KID) is a unique and powerful database of hospital inpatient stays for children. The KID was specifically designed to permit researchers to study a broad range of conditions and procedures related to child health issues. Researchers and policymakers can use the KID to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. It is the only all-payer inpatient claims database for children in the U.S.
Database: (Scope, Size, Setting, Population, Age Range) National; Adolescents Only (< 20 years old); 2–3 million records a year.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) A Federal-State-Industry database of Medicare, Medicaid, Private Insurance and Uninsured patient discharges.
Database Source/Origin: Administrative data from 4,121 community, non- rehabilitation hospitals in 44 states.
Date or Frequency of Data Collection: 1997-2009; updated every three years.
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: Discharge data submitted by participating organizations.
Sampling Strategy: Sampling frame is limited to pediatric discharges from community, non-rehabilitation hospitals in participating HCUP partner states. For sampling, pediatric discharges in participating States are stratified by uncomplicated birth, complicated birth, and all other cases. To ensure an accurate representation of each hospital’s case-mix, the discharges are sorted by State, hospital, DRG and a random with each DRG. Systematic random sampling is then used to select 10% of uncomplicated births and 80% of complicated births and other cases form each from hospital
Unit of Analysis: Multiple (patient, region, etc.)
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis)

Number of Chronic Conditions (based on a list of 25 possible chronic condition indicators)

Primary and Secondary Diagnoses

Admission and Discharge Status

Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9-CM codes
Number of Diagnoses Captured: KID contains up to 25 diagnoses per patient per record. This number can vary by State.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs)

Expected Primary and Secondary Payer

Total Charges

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.)

Admission Type

Procedure Type

ED Visits

Length of Stay

Number of Discharges

Measures of Healthcare Access: Database used to evaluate healthcare access through the use of geographic and hospital type variables (i.e. critical access).
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment).

Age at Admission

Gender

Race

Hospital Characteristics

Physician Identifiers

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)

Comorbidity Measures

Birth Weight

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

Place of Residence

Median Household Income

Site of Service Information:

Hospital Location ( e.g., State, zip code, etc.)

Site of Service

Transition Information

Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions)

In-Hospital Mortality

Disposition of Patient

Strengths, Limitations & Feasibility
Data Strengths: Representative of all insurance types. Large sample size that allows researchers to study rare conditions.
Data Limitations: Missing data values can compromise the quality of estimates. If the outcome for discharges with missing values is different from the outcome for discharges with valid values, then sample estimates for that outcome will be biased and inaccurately represent the discharge population. For example, race is missing on 15% of discharges in the 2009 KID because some hospitals and HCUP State Partners do not supply it.
Data Access Restrictions: Access to KIDs is open to users who complete a Data Use Agreement and purchase the data. Uses are limited to research and aggregate statistical reporting.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) The database contains AHA hospital identifiers. However, many states do not report this information.
Related Grouping Systems: HCUP Clinical Classifications System (CCS)

References:

Overview of the Kids’ Inpatient Database (KID). 2013. http://www.hcup-us.ahrq.gov/kidoverview.jsp

Introduction to The HCUP KID’s Inpatient Database (KID) 2009. Healthcare Cost and Utilization Project (HCUP). 2013. http://www.hcup-us.ahrq.gov/db/nation/kid/KID_2009_Introduction.pdf

 

Healthcare Cost & Utilization Project - Nationwide Emergency Department Sample
Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations & Multiple Chronic Conditions and Disparities
Sponsorship: Agency for Healthcare Research & Quality
Description: The Nationwide Emergency Department Sample (NEDS) is a unique and powerful database that yields national estimates of emergency department (ED) visits. The NEDS was created to enable analyses of emergency department (ED) utilization patterns and support public health professionals, administrators, policymakers, and clinicians in their decision-making regarding this critical source of care. NEDS is the largest all-payer ED database in the U.S.
Database: (Scope, Size, Setting, Population, Age Range) National; 25–30 million records
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) A Federal-State-Industry database of Medicare, Medicaid, Private Insurance and Uninsured ED patient discharge records.
Database Source/Origin: As of 2010, NEDS contains administrative data from over 961 hospitals in 28 States.
Date or Frequency of Data Collection: 2006-2010; updated yearly.
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: NEDS is developed from data from ED visits submitted by participating States.
Sampling Strategy: Similar to the design of the Nationwide Inpatient Sample (NIS), NEDS is developed using a 20% stratified sample of institutions; NEDS is a sample of U.S. hospital-based EDS who participate in the program (n=28). Sampling rate is 20% NEDS to Universe and 37.6% NEDS to Frame.
Unit of Analysis: Episode
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis)

Number of Chronic Conditions

Primary and Secondary Diagnoses

Injury Descriptive Variables

Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9-CM, CPT-4
Number of Diagnoses Captured: NEDS contains up to 15 diagnoses per record. This number may differ by State.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) Total ED charges and total hospital charges (for inpatient stays for those ED visits that result in admission)
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.)

ED Event Type/Number of Visits

Length of Stay

Number of Discharges

Measures of Healthcare Access: Database used to evaluate healthcare access through the use of geographic and hospital type variables (i.e. critical access).
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Gender, Age, Urban-Rural designation of resident, expected payment source ( e.g., Medicare, Medicaid, self- pay)
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) ICD-9-CM and CPT-4 procedures and diagnoses Identification of injury-related ED visits including mechanism and intent of injury and severity of injury Discharge status from the ED
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) National quartile of median household income (from patient’s ZIP Code)
Site of Service Information: Hospital location (e.g., State, zip code, etc.) and characteristics (e.g., teaching status, region, ownership type).
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: NEDS is the largest all-payer ED database in the U.S., with many research applications. It includes information on patients covered by all types of insurances.
Data Limitations: The NEDS contains event-level records, not patient-level records. This means that individual patients who visit the ED multiple times in one year may be present in NEDS multiple times. There is no uniform patient identifier available that would allow a patient-level analysis with the NEDS. In contrast, the HCUP state databases may be used for this type of analysis
Data Access Restrictions: Access to NEDS is open to users who complete a Data Use Agreement and purchase the data. Uses are limited to research and aggregate statistical reporting.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) For most States, the NIS includes hospital identifiers that permit linkages to the American Hospital Association Annual Survey Database and county identifiers that permit linkages to the Area Resource File.
Related Grouping Systems: HCUP Clinical Classifications System (CCS)

References:

Overview of the Nationwide Emergency Department Sample (NEDS). 2013. http://www.hcup-us.ahrq.gov/nedsoverview.jsp

 

Name: Healthcare Cost & Utilization Project - Nationwide Inpatient Sample
Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations & Multiple Chronic Conditions and Disparities
Sponsorship: Agency for Healthcare Research & Quality
Description: The Nationwide Inpatient Sample (NIS) is a unique and powerful database of hospital inpatient stays. Researchers and policymakers use the NIS to identify, track, and analyze national trends in health care utilization, access, charges, quality, and outcomes. It is the largest publicly available all-payer patient care database in the U.S.
Database: (Scope, Size, Setting, Population, Age Range) National; Information available on approximately 8 million hospital stays per year.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) A Federal-State-Industry database of Medicare, Medicaid, Private Insurance and Uninsured patient discharges.
Database Source/Origin: Administrative data from 1,051 hospitals from 44 states.
Date or Frequency of Data Collection: 1988–2010; updated yearly
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: NIS contains clinical and resource use information included in a patient discharge abstract and is submitted to HCUP by over 1,000 hospitals in the U.S.
Sampling Strategy: The NIS is a stratified probability sample of hospitals, with sampling probabilities calculated to select 20% of the universe of community, non-rehabilitation hospitals in specific strata for ease of use. The entire sampling frame from 46 states includes >90% of hospitals and >95% of discharges from community hospitals.
Unit of Analysis: Multiple (patient, hospital, region, etc.)
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis) Major Diagnosis Category (MDC) Primary and secondary diagnosis Admission and discharge status Number of Chronic Conditions
Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9
Number of Diagnoses Captured: NIS contains up to 25 diagnoses per record (15 prior to the 2009 NIS). The number of diagnoses varies by State; some states provide as many as 66 diagnoses while other states provide as few as 9 diagnoses.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) Total Charges
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.)

Length of Stay

Type of Admission

Number of Discharges

Measures of Healthcare Access: Database used to evaluate healthcare access through the use of geographic and hospital status variables ( e.g., CAH status).
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status, Disability Status, Language, Insurance Type, Educational Attainment). Gender, age, race, median income for zip code, and Expected Primary and Secondary Payment Sources.
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)

Primary and secondary procedures

Disease Severity Measures

Comorbidity Measures

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

Place of Residence

Median household income for patient’s ZIP Code

Site of Service Information: Hospital location ( e.g., State, zip code, etc.) and characteristics ( e.g., teaching status, region, ownership type).
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions)

Disposition of Patient

In-hospital Death

Strengths, Limitations & Feasibility
Data Strengths: The NIS is the largest publicly available all-payer inpatient care database in the U.S. with information from 45 states, comprising over 96% of the U.S. population. The NIS’ large sample size enables analyses of rare conditions, uncommon treatments, and special patient populations (such as the uninsured).
Data Limitations: Missing data values can compromise the quality of estimates. If the outcome for discharges with missing values is different from the outcome for discharges with valid values, then sample estimates for that outcome will be biased and inaccurately represent the discharge population. For example, race is missing on over 11% of discharges in the 2010 NIS because some hospitals and HCUP State Partners do not supply it. Not all states report patient identifiers and complete diagnostic information.
Data Access Restrictions: Access to NIS is open to users who complete a Data Use Agreement and purchase the data.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) The database contains AHA hospital identifiers. However, many states do not report this information.
Related Grouping Systems: HCUP Clinical Classifications System (CCS)

References:

Overview of Nationwide Inpatient Sample (NIS). 2013. http://www.hcup-us.ahrq.gov/nisoverview.jsp

 

Medical Expenditure Panel Survey
Database Description
White Paper(s): Data Systems and the Prevalence of Chronic Disease Combinations & Multiple Chronic Conditions and Disparities
Sponsorship: Agency for Healthcare Research and Quality
Description: The Medical Expenditure Panel Survey (MEPS) is a set of large-scale surveys of families and individuals, their medical providers, and employers across the United States. MEPS is the most complete source of data on the cost and use of health care and health insurance coverage.
Database: (Scope, Size, Setting, Population, Age Range) National; approximately 35,000 persons interviewed annually.
Database Type: (Survey, Registry, Research Study, Program Database, Claims, Administrative Data, and Clinical Databases) Survey/Interviews

Two Primary Components
  • Household component – collects data from a sample of families and individuals is selected communities in the U.S.
  • Insurance component – collects data from a sample of private and public sector employees on the health insurance plans they offer their employees.
Database Source/Origin: Survey data from a set of large-scale surveys of families and individuals, their medical providers, and employers in the U.S.
Date or Frequency of Data Collection: 1996–2012; updated annually.
Longitudinal vs. Cross-sectional Database: Longitudinal
Data Collection Methodology: For the Household Component, a panel survey design in used to collect data via multiple rounds of interviewing over a two year period of time. For the Insurance component, an annual survey of employers is conducted that collections information on health insurance offerings.
Sampling Strategy: The Household Component collects data from a sample of families and individuals in selected communities across the U.S., drawn from a nationally representative subsample of households that participated in the prior year’s National Health Interview Survey. The Insurance Component collects information from Household Component respondent employers or other non-related employers.
Unit of Analysis: Household or Employer
Diagnosis Information
Diagnosis Variable Type: (Chronic Condition Status, Principal Diagnosis, Primary Diagnosis, Secondary Diagnosis, Admit/Discharge Diagnosis and Self-Reported Diagnosis) Self-Reported Diagnosis transformed into ICD-9 Codes
Diagnosis Codes: (ICD-9, ICD-10, SNOMED) ICD-9
Number of Diagnoses Captured: MEPS identifies specific physical and mental health conditions, accidents, or injuries affecting each respondent. 670 clinical categories are created.
Cost, Utilization & Clinical Information
Measures of Cost: (Claims, Out-of-pocket expenses, Self- reported expenditures, and Prescription Drug Costs) Total Health Care Expenditures, Total Expenditures Paid by Insurance, Hospital Outpatient Expenditures, Hospital Emergency Room Expenditures, Hospital Inpatient Expenditures, Dental Expenditures, Home Health Care Expenditures, Vision Aid Expenditures, Other Medical Equipment and Service Expenditures, and Prescription Drug Expenditures
Measures of Healthcare Utilization: (Number of Visits, Any Procedures/Number of Procedures/Type ofProcedure, Number of Admission/Type ofAdmission, Length of Stay, Hospitalizations, Emergency Department Utilization, etc.) Medical Provider Visits (Physician, etc.), Hospital Outpatient Visits, Hospital Emergency Room Visits, Hospital Inpatient Visits, Dental Visits, Home Health Care Visits, Number of Drugs Prescribed , and Length of Stay
Measures of Healthcare Access: Presence of provider who provides the usual source of care, reasons why members without usual care do not have it, various aspects of satisfaction with usual care providers, and problems experience in obtaining needed health care
Demographic Information: (Sex, Age, Race, Ethnicity, Marital Status,Disability Status, Language, Insurance Type, Educational Attainment). Age, Sex, Race/Ethnicity, Insurance Status, Marital Status, and Disability Status
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) Prescribed Medicine, Pregnancy Detail
Measures of Socioeconomic Status: (Occupation, Employment Status, Income, Wealth, Place of Residence, Household Size & Composition, geographic location) Family Income as Percent of Poverty Line, Employment Status, Total Income, geographic location, and Size of Family
Site of Service Information: Type of Service ( e.g., hospital, nursing home, etc.)
Measures of Healthcare Outcomes: (Mortality, Morbidity, Mobility, Functional Status, Quality of Life, Quality Measures, Quality of Care, Readmissions)

Self-Reported Overall Health Status

Self-Reported Physical Health Status

Self-Reported Mental Health Status

Strengths, Limitations & Feasibility
Data Strengths: MEPS provides a level of breadth and depth of healthcare utilization information that is not captured in other surveys.
Data Limitations: Even after pooling several years of MEPS data, sample size limitations and confidentiality restrictions make MEPS data unsuitable for certain types of analysis. For example, the MEPS data do not support research on rare conditions. Moreover, information on conditions is household-reported and not verified by clinical records. All MEPS data are reported by one designated household respondent.
Data Access Restrictions: Some files are accessible to the public; however only researchers and users with approved access can gain access to restricted files.
Data Linking Feasibility: (Unique identifiers or sufficient demographics to allow for data linkages) Data can only be linked be survey number, which limits the feasibility of linking to non-MEPS-related data sources.
Related Grouping Systems: ICD-based grouping systems.

References:

Medicare Expenditure Panel Survey (MEPS). 2013. http://meps.ahrq.gov/mepsweb/

 

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