# Presentation: 493771

## VA and Non-VA Databases and Their UsesPart 2

- Jennifer Campbell, MS
- Jessica Davila, PhD
- Michael Johnson, PhD
- Nancy Petersen, PhD
- Diana Urbauer, MS
- Iris Wei, DrPH

- February 24, 2004

## Outline

- VA Decision Support System (DSS): Jen Campbell
- VA External Peer Review Program (EPRP): Diana Urbauer
- VA National Surgical Quality Improvement Program:
- 	Mike Johnson
- Medicare and Medicaid: Iris Wei/Mike Johnson
- Surveillance, Epidemiology, and End-Results Program (SEER): Jessica Davila

## DSSVA Decision Support System

- Jen Campbell

## Overview

- Organization/accessibility of DSS NDE files
- Types of costs available
- Linking to National Patient Care Database:  Patient Treatment Files (PTF) and Outpatient Care files (OPC)

## DSS Overview

- DSS is a program used by VA to manage its health care system.
- Combines clinical and financial data from VISTA.
- NDEs created to facilitate access to cost information.
- NDEs report costs of every inpatient and outpatient encounter provided by the VA.

## DSSNDE Cost Files

- 1998-2003 available, 2000-2003 recommended
- Inpatient
- Treating specialty (FY N~1.5 million)
- Discharge (FY N~700,000)
- Outpatient
- Pharmacy (FY N~40 million)
- All other (FY N~60 million)

## DSSCosts in all NDE files

- Patient ID fields
- Location of service
- Date of service
- Total cost of encounter
- Select cost subtotals:  laboratory, pharmacy, surgery, radiology, nursing, other

## DSS NDE Inpatient Files

- Discharge File
- Each record is a discharge in FY
- Includes entire cost of hospital stay
- Information on: admit date, discharge date, days of stay, discharge treating specialty, DRG, diagnosis

**Notes:**
1.  Discharge files may exclude stays that began before DSS implementation.  Should be checked on a per case basis.

## DSS NDE Inpatient Files

- Treating Specialty (Bedsection) File
- One record per bedsection per month
- All care provided during FY, includes ongoing stays
- Information on: bedsection entry date, bedsection exit date, stay admission date (no discharge or length of stay information)

## DSS NDE Outpatient Files

- Total FY N~100 million records
- Multiple files per year-by stop type and VISN, e.g:
- VISN1-5 Clinic Stops file
- VISN1-5 Pharmacy file(Clinic Stop=160) Clinic stops/Pharmacy
*Additional files for VISN 6-10, 11-16, 17-22*

## DSS NDE Outpatient Files

- Records represent all services provided to patient on a given day in a given clinic stop
- Also includes:
- Date of encounter
- DSS identifier (pseudo code) for clinic stops
- Flags for data source

## Linking DSS and NPCD

- NPCD has unique information not in DSS
- More detailed utilization information, procedure codes, demographics, etc
- Merge by SSN, STA3N, event date
- Most still rely on NPCD to measure use

**Notes:**
DSS has utilization variables, although they require careful interpretation.  For example, all pharmacy records in the DSS Outpatient file show a quantity of ‘1’ – this only reflects an encounter with the pharmacy department and does not represent the number of prescriptions obtained.

## DSSConcerns about Quality

- Inpatient medical procedures not captured by all sites
- Variability across facilities with inputs
- Outliers (e.g. pharmacy cost > $100,000)
- HERC validation studies
- Generally, 95%+ match rate of DSS with PTF, OPC (see HERC documentation)

## DSSConcerns about Quality (2)

- FY98-99 considered pilot data, FY2000- recommended
- VA increasingly confident with DSS data
- Users should not rely on DSS data without checking its validity

**Notes:**
Mention about confidence:  HERC may discontinue HERC average data.

## HCQCUS Projects Using DSS

- CHF QUERI Translation Study
- “Pharmacy Use in Patients with Chronic Heart Failure” (M. Johnson)
- “Use of VA Pharmacy Services Among Medicare Enrolled Veterans” (R Morgan.M. Johnson)
- VERA Project (L. Petersen)

## HCQCUS Projects Using DSS

- “Costs Associated with a CHF Coordinated Care Program: A Pilot Project”
- 	Rebecca Beyth, MD, MS, Investigator
- To identify inpatient, outpatient and administrative costs associated with a CCP pilot study of CHF patients.
- To compare inpatient and outpatient use and costs for CHF patients enrolled in a CCP.
- To determine whether a CCP program reduces hospitalizations, decreases costs and improves quality of life for CHF patients.

## DSSResources for Data

- HERC - Research guides and analytical assistance:
- _[http://www.herc.research.med.va.gov/DSS.htm](http://www.herc.research.med.va.gov/DSS.htm)_
- VIReC – Technical documentation and technical assistance:
- _[http://www.virec.research.med.va.gov/databases/dss/DSS.HTM](http://www.virec.research.med.va.gov/databases/dss/DSS.HTM)_

## EPRPExternal Peer Review Program

- Diana Urbauer

## EPRPExternal Peer Review Program

- A system to assess the quality of care delivered in the VHA
- Maintains a comprehensive database to allow comparisons of individual VAMCs and VISNs to the VA system as a whole, to private and public sector hospitals, and to the optimum standard of care

## EPRP Supports Measurement in:

- Cardiovascular
- Diabetes
- Cancer
- Mental Health
- Behavioral Health
- Home Care
- Homelessness
- SCI

- Immunizations
- Hepatitis C
- Respiratory
- Rehabilitation
- Nutrition
- Tobacco
- CBOC Quality

## EPRPExamples of Measures

- Chronic Heart Failure
- Most recent ejection fraction
- Was ACE inhibitor prescribed?
- Hypertension
- Most recent blood pressure
- Number of hypertensive medications
- Diabetes
- Foot inspection within past year?
- Most recent hemoglobin A1c value

## EPRPAvailable Data

- Collection began in FY00
- In FY00 based upon outpatient visits of inpatients randomly selected
- In FY01 maintained separate files for inpatients and for outpatients
- Data collected quarterly
- Information is patient-level

## EPRPData Collection Process

- Cases to be reviewed are sampled monthly
- Abstractors review medical records
- Feedback is provided after reviews are completed
- Data are reported quarterly

## EPRPLimitations

- Variables collected might differ from quarter to quarter
- Definition
- Values
- Name
- No real data dictionary

## Example of HCQCUS Study Using EPRP Data

- Impact of Diastolic Heart Failure on Health Care Utilization and Outcomes
- 	Anita Deswal, MD, MPH, Investigator
- To determine prevalence, baseline characteristics and racial variation among patients with diastolic heart failure
- To compare health care utilization between patients with diastolic and systolic heart failure, especially with regard to race
- To compare mortality between diastolic and systolic heart failure patients, especially with regard to race
- To determine whether ACE inhibitors and β-blockers reduce hospitalizations and mortality , especially with regard to race

## EPRPResources for Data

- http://www.oqp.med.va.gov/cpg/
- Information on clinical practice guidelines and data collection
- http://vaww.oqp.med.va.gov/default.htm
- Summaries by VISN level and by certain demographic groups
- Debby Walder, Director, External Review Program
- Debby.Walder@hq.med.va.gov

## National Surgical Quality Improvement Program (NSQIP)

- Mike Johnson

## National Surgical Quality Improvement Program (NSQIP)

- A national quality assurance program
- Beginning 1991
- Pre-operative, peri-operative, and post-operative measures of risk, processes, and outcomes (morbidity and mortality)
- All 123 VAMCs that perform major surgery participate
- Data coordinating center is at the Colorado Health Outcomes Program (COHO) directed by Bill Henderson, PhD at the UCHSC, Denver.

## NSQIP

- Pre-operative
- 42 cardiac, cns, hepatobiliary, nutritional immune, pulmonary, renal, vascular and general comorbidity information
- 12 laboratory tests
- Operative
- 57 variables for surgical profile
- Post-operative
- 56 variables for complications and outcomes
- 12 laboratory tests

## NSQIP

- Example studies
- Two studies (Collins TC, Johnson ML, Daley J, et al. _Medical Care_, 2002; and Collins TC, Gordon HS, Johnson ML** **et al. _Journal of Vascular Surgery_, 2001 on race/ethnicity effects in PAD and vascular surgery).
- Johnson ML, Gordon HG, Petersen NJ et al. _Medical Care_, 2002 (methods paper on definition of mortality)
- Two studies under review (Gordon HS, Johnson ML, Petersen NP, et al. and Geraci JM, Johnson ML, Petersen NP, et al. (under review _Medical Care_, non-cardiac and cardiac hospital profiles).
- Bush R, Johnson ML, Lin P, Lumsden A. “Role of Endovascular Abdominal Aortic Aneurysm Repair in Reducing Surgical Morbidity and Mortality Among Veterans”, new HCQCUS project.

## Medicare and Medicaid

- Iris Wei
- Mike Johnson

## CMS Data

- Centers for Medicare & Medicaid Services (CMS)
- Formerly the Health Care Financing Administration (HCFA)
- _[http://www.cms.hhs.gov/data](http://www.cms.hhs.gov/data)_

## CMS Data - History

- The Social Security Act of 1965, signed by President Lyndon Johnson, established Medicare and Medicaid
- Medicare is a prepaid health insurance plan to cover most Americans ages 65 or older
- Medicaid provides access to healthcare services for low-income persons
- In 1972, Social Security Amendments expanded coverage to end-stage renal disease persons and disabled persons (SSI disability)

## CMS Data – Tech Support

- The Research Data Assistance Center (ResDAC)
- 	contracted by CMS to provide free assistance to academic and non-profit researchers in the use of Medicare, Medicaid, SCHIP, and MCBS data for research _[http://www.resdac.umn.edu](http://www.resdac.umn.edu/)_
- At HCQCUS, consult Dr. Robert Morgan, Dr. Iris Wei, Dolly John, Raji Sundaravaradan, Louise Henderson, and Dr. Jessica Davila for SEER-Medicare data
- Determinants of Care among VA and Non-VA Using Veterans
- Medicare HMO Enrollment and VA Use by Minority and Low-Income Veterans
- Use of Pharmacy Services by Medicare Enrolled Veterans

## CMS Data Types

- (1)	Beneficiary Encrypted Files (BEFs)
- 	are identifiable files
- (2)	_Limited Data Sets (LDS)_
- 	Data elements that might permit identification of beneficiaries are stripped
- (3) 	_Non-Beneficiary Encrypted Files_
- 	_(Non-BEFs)_

## Beneficiary Encrypted Files (1)

- Denominator File - Abbreviated version of the Enrollment Database (EDB)
- Beneficiary Claim Account Number or CAN (SSN, RRB)
- Beneficiary Identification Code or BIC
- state/county
- Age
- Dob
- Sex
- Race
- Dod
- Entitlement
- monthly buy-in and hmo

## Beneficiary Encrypted Files (2)

- Expanded Modified MEDPAR File
- 	The Medicare Provider Analysis and Review (MEDPAR) file contains records of Medicare beneficiaries who use hospital inpatient services (national, state, and skilled nursing facility)
- Hospital Outpatient Prospective Payment System (OPPS) File
- Standard Analytical Files
- 	(durable medical equipment, home health agency, hospice, inpatient, outpatient, physician/supplier Part B, skilled nursing facility or SNF)

## Beneficiary Encrypted Files (3)

- Group Health Plan Files (GHP)
- 	Contains health plan Contract Number, Part A and Part B Entitlement and Enrollment start and end dates, flags for ESRD, Hospice, and Medicaid
- Cross-Reference Health Insurance Number Files
- 	Health Insurance Claim Account Number (HIC) identifies the Medicare beneficiary; CAN identifies the wage earner under SSA/RRB; Equated BIC identifies the types of relationship between the beneficiary and the primary beneficiary
- Vital Status/Name and Address Files

## CMS Research Data Request

- Requires a well-defined research protocol
- Strict Data Use Agreement (DUA)
- CMS review process
- Technical support: ResDAC
- Cost varies by types of files and number of beneficiaries
- Time Line
- Reuse Letter
- Certification of Destruction

## VA Medicare Data Merge Initiative (1)

- Led by:
- VA Office of Policy & Planning
- 	- Management Science Group (MSG)
- VA Office of Research & Development
- 	- VA Information Resource Center (VIReC)
- 		(also for data request)

## VA Medicare Data Merge Initiative (2)

- Unique VA-user file matched to Medicare data for CY1999, CY2000, and CY2001
- by SSN, sex, and/or dob

## VA Medicare Data Merge Initiative (3)

- CMS files requested:
- Denominator
- MEDPAR
- Facility-based Outpatient
- Physician Supplier Part B
- Home Health Agency
- Skilled Nursing Facility
- Durable Medical Equipment
- Hospice
- Provider of Service
- Group Health Plans (not for CY2002)

## VA Medicare Data Merge Initiative (4) – Unique VA User/Enrollee/Eligible File

| Data Source | Description | Uniq SSNs |
| --- | --- | --- |
| VSSC/PSSG Enrollment file, Dec 1999 | All individuals enrolled in the VHA as of Dec 31, 1999 | 4,423,743 |
| VSSC Compensation & Pension Non-User files, FY97-99 | All veterans who obtained compensation or pension & had no VA healthcare use | 903,231 |
| VSSC Unique Users files, FY97-00 | All veterans who used VHA healthcare | 1,009,880 |
| ARC Pharmacy Only User file, FY97-99 | All veterans who used only pharmacy services | 82,749 |
|  | Cumulative Total | 6,411,210 |
| BIRLS | Veterans deceased prior to Jan 1, 1999 | 231,937 |
|  | VIReC Veterans Cohort | 6,179,273 |
|  | VA Medicare Linked File, # SSNs  | ~ 2.4 mil |

## VA Medicare Data Merge Initiative (5) – Healthcare Use Data Sources

| 1 | -	VA Inpatient, CY99
-	Inpatient Medical SAS datasets,    	FY99-00
-	Fee Basis Inpatient Medical SAS | 4 | -	Medicare Part A Outpatient
-	Outpatient Institutional 	Claims, CY99 |
| --- | --- | --- | --- |
| 2 | -	VA Outpatient, CY99
-	Outpatient Medical SAS datasets, 	FY99-00
-	Fee Basis Contract Medical SAS | 5 | -	Medicare Part B
-	Physician/Supplier/Carrier 	Claims, CY99 |
| 3 | -	Medicare Part A Inpatient 	(MEDPAR)
-	Inpatient Institutional Claims, 	CY99 |  |  |

## CMS Files for Purchase (1)

- Limited Data Sets (LDS)

|  | Cost | Available |
| --- | --- | --- |
| MEDPAR LDS-Hospital (national) | $3,655/y | FY2002 |
| MEDPAR LDS-Hospital (state) | $1,080/y | FY2002 |
| Hospital Outpatient Prospective Payment System (OPPS) LDS | $3,000 | Apr-Dec2002, release 2004 |
| Hospital OPPS Partial Hospitalization Program (PHP) LDS | $1,140 | Apr-Dec2002, release 2004 |
| Inpatient Psychiatric PPS (IPF PPS) LDS | $3,000 | 1999 medpar & cost report |

## CMS Files for Purchase (2)

- Non-Beneficiary Encrypted Files

|  | Cost | Available |
| --- | --- | --- |
| Provider of Services File (POS) | $100/qtr | CY91-CY02 |
| Hospital Service Area File | $200/y | CY92-CY02 |
| Physician/Supplier Procedure Summary Master File (formerly Part B Procedure File) | $250/y | CY92-CY02 |
| Medicaid Drug Utilization by state | $535/qtr | CY91-- |
| Unique Physician ID Number (UPIN) | $100-330 | current |
| Cost Reports | $100/y | 1999 medpar & cost report |

## Research and Demonstration Grants at the CMS

- Purpose:  “develop, test, and implement new health care financing and payment policies ... evaluate the impact of CMS programs on beneficiaries, providers, States, ...”
- Generally funded through contracts rather than grants, but award grants and cooperative agreements under focused programs
- Annual grant programs
- 	-	Historically Black Colleges & Universities Grant Program
- 	-	Hispanic Health Services Research Grant Program
- 	-	Other Grant Opportunities
- http://www.cms.hhs.gov/researchers/priorities/grants.asp

## Medicaid (1)

- Each state administers its own Medicaid program
- eligibility standards
- type and amount of services
- Implications for research
- variations in eligibility criteria by state and over time
- cycling of enrollment/disenrollment

## Medicaid (2)

- Claims for
- Inpatient and outpatient hospital services
- Nursing facility services
- Physician and dentist services
- Lab, X-ray
- Optional services
- Prescription drugs
- Mental heath services
- Intermediate care services

## SEERSurveillance, Epidemiology, and End-Results Program

- Jessica Davila

## SEERSurveillance, Epidemiology, and End-Results Program

- Division of Cancer Control and Population Sciences
- National Cancer Institute

## SEERBackground

- Established in response to the National Cancer Act in 1971
- Public law 92-218
- “ The director of the national cancer institute shall....collect, analyze, and disseminate all data useful in the prevention, diagnosis, and treatment of cancer.....”

## SEERData Collection

- NCI contracts with universities and state health departments to collect cancer-related information
- Contractors have authority to register all cancer cases in a defined geographic area

## SEERData Collection

- From 1973-1991 – 9 registries:
- Atlanta, Connecticut, Detroit, Hawaii, Iowa, New Mexico, San Francisco/Oakland, Seattle/Puget Sound, Utah
- In 1992, 3 registries added:
- San Jose/Monterey
- Los Angeles
- Alaska Natives

## SEERObjectives

- Provide basis for estimating cancer incidence and mortality in the US
- Monitor trends in cancer rates, including incidence, survival, and mortality
- Monitor treatment trends for selected types of cancers (Patterns of Care study)
-  Identify subgroups of the population that are at high risk of being diagnosed with or developing cancer
- Serve as a research resource

## SEERData Items

- Case ID
- Reporting source (hospital, laboratory, private MD, nursing home, autopsy, death certificate)
- Demographic information (age, race, gender, county of residence)

## SEERData Items

- Description of neoplasm (Month and year of cancer diagnosis, type of cancer, histology, stage)
- Therapy (First course of therapy)
- Mortality (Vital status, date of death (if any), underlying cause of death)

## Example of HCQCUS Study Using SEER Data

- Geographic variation within the United States in the incidence of hepatocellular carcinoma (HCC)
- 	Jessica Davila, PhD; Nancy Petersen, PhD; Harlan A. Nelson, MS; Hashem B. El-Serag, MD, MPH
- To determine whether geographic variation exists in the incidence of HCC and to examine potential factors that might affect the distribution of HCC.
- 	Journal of Clinical Epidemiology 56(2003) 487-493.

## SEERResources

- SEER Website
- http//:seer.cancer.gov
- Publications, manuals, cancer statistics
- SEER-Stat
- Also available at http//:seer.cancer.gov
- CD-Rom with SEER-database
- Calculate your own statistics (frequencies, rate, survival)

## SEER-Medicare Data

## Linkage of SEER-Medicare data – Why?

- SEER and Medicare are both large, population based sources of data
- SEER program collects detailed clinical, demographic, and cause of death information for persons with cancer
- Medicare data are longitudinal, with claims from time of eligibility to time of death (with some exceptions)

## SEER-MedicareSpectrum of Analyses I

- Screening and detection
- Colonoscopy, mammography, PSA
- Diagnosis and treatment
- Receipt of appropriate treatment
- Treatment disparities
- Costs of diagnosis and treatment
- Post-treatment
- Long-term effects of therapy
- Surveillance

## SEER-MedicareSpectrum of Analyses II

- Recurrence
- Rates of recurrence
- Relationship of recurrence and initial treatment
- Relationship of recurrence and surveillance
- Terminal care
- Utilization of hospice services
- Costs associated with assisted living/nursing care
- Survival

## SEER-MedicareData Linkage

- Linkage is performed by NCI
- Personal identifiers for people in the SEER database are matched against CMS master enrollment file.  These people are assigned their HIC number from Medicare.
- HIC is used to extract Medicare claims for persons in SEER found to be Medicare beneficiaries

## SEER-MedicareData Availability

- SEER data are available for the entire time a registry has participated in the SEER-Medicare program
- Medicare claims files are available from 1991-2000 (except for MEDPAR which is available back to 1986)
- Linked data is currently available through 2000 (and is currently being updated)

## SEER-MedicareAdditional data

- Enrollment information (Part A and Part B entitlement, state-buy in, HMO enrollment) is available from Medicare
- Census variables at the zip-code level (median household income, education levels, population density)
- 5% random sample of persons residing in the SEER areas who have not been diagnosed with cancer (useful as non-cancer controls)

## SEER-MedicareLimitations

- Excludes non-covered services (prescription drugs)
- Under 65 population includes only the disabled and ESRD
- Reasons for tests are unknown (screening vs. diagnostic)
- Results of tests are unknown
- No information about risk factors

## Example of HCQCUS Study Using SEER-Medicare Data

- Hepatitis C and the rising incidence of hepatocellular carcinoma: a population-based study
- 	Jessica Davila, PhD; Robert O. Morgan, PhD; Yasser Shain, MD, MPH; Katherine A. McGlynn, PhD; Hashem B. El-Serag, MD, MPH
- To examine the temporal trends of risk factors (HCV, HBV, alcoholic liver disease, non-specific hepatitis and non-specific cirrhosis) in patients age 65 and older with HCC
- 	(Under review)

## SEER-MedicareResources

- SEER-Medicare website:
- _[http://appliedresearch.cancer.gov/](http://appliedresearch.cancer.gov/seermedicare)__[seermedicare](http://appliedresearch.cancer.gov/seermedicare)_
- RESDAC:
- _[http://www.resdac.umn.edu/](http://www.resdac.umn.edu/)_

## SEER-MedicareResources

- SEER-Medicare website:
- _[http://appliedresearch.cancer.gov/](http://appliedresearch.cancer.gov/seermedicare)__[seermedicare](http://appliedresearch.cancer.gov/seermedicare)_
- RESDAC:
- _[http://www.resdac.umn.edu/](http://www.resdac.umn.edu/)_