VIReC CyberSeminar Series 2006 VA Databases and Methods

1. VIReC CyberSeminar Series 2006VA Databases and Methods Assessing Healthcare Use Using VA Inpatient Data Presented by Kevin Stroupe, PhD Research Health Scientist, MCHSPR COE Research Assistant Professor, Feinberg School of Medicine, Northwestern University

2. Session Objectives • How has healthcare utilization been measured in VA studies? • Overview of Medical SAS inpatient databases • Finding information in the Inpatient Medical SAS databases • Example of VA study that measured VA healthcare utilization • Where to go for more help

3. Session Objectives • How has healthcare utilization been measured in VA studies? • Overview of Medical SAS inpatient databases • Finding information in the Inpatient Medical SAS databases • Example of VA study that measured VA healthcare utilization • Where to go for more help

4. Assessing Healthcare Use: Data Sources • How has healthcare utilization been measured in VA studies? • Patient surveys (primary data collection) • Payne et al, J Ambul Care Manage, 2005 • Washington et al, Am J Public Health, 2005 • VA Office of Quality and Performance (OQP)* • External Peer Review Program (EPRP) • medical record abstraction on several performance measures • will only include information on services that are tracked by VHA performance measures • data available from OQP through data use agreement • See Weaver et al, J Am Med Inform Assoc, 2004 * See: http://vaww.oqp.med.va.gov/oqp_services/performance_measurement/tech_man.asp

5. Assessing Healthcare Use: Data Sources • How has healthcare utilization been measured in VA studies? (cont’d) • 2001 National Survey of Veterans* • Conducted by VA Office of Policy, Planning, and Preparedness • Veteran survey, including information on health care use • Does not have identifiers that can be linked to other VA data • See Final Report and Methodology** • VistA*** • Local patient healthcare utilization information • Permission to access obtained locally • Data element may have a different meanings between different sites • See Fuller et al, Psychiatr Serv, 2002 * See http://www.virec.research.va.gov/DataSourcesName/NationalSurveyVeterans/2001NationalSurveyofVeterans.htm ** See http://www1.va.gov/vetdata/page.cfm?pg=5 *** See: http://www.virec.research.va.gov/DataSourcesName/VISTA/VistA.htm

6. Assessing Healthcare Use: Data Sources • How has healthcare utilization been measured in VA studies? (cont’d) • Medical SAS Inpatient and Outpatient Datasets* • Most important database for VA healthcare utilization information • National VHA health care delivery data • SAS datasets housed on mainframe computer at Austin Automation Center (AAC) • Divided into inpatient and outpatient datasets • Datasets available on a quarterly basis • In general, researchers are advised to use the annual, closed-out datasets • Common element: patient identifier (scrambled SSN) • Focus of this session * See: http://www.virec.research.va.gov/DataSourcesName/Medical-SAS-Datasets/SAS.htm

7. Session Objectives • How has healthcare utilization been measured in VA studies? • Overview of Medical SAS inpatient databases • Finding information in the Inpatient Medical SAS databases • Example of VA study that measured VA healthcare utilization • Where to go for more help

8. Strengths of Medical SAS Datasets • Centralized data source • Large groups of patients • Given good coding, reflective of general clinical status • Unique identifier (SCRSSN: Scrambled Social Security Number) allows linking records across files/years • Quality assessments are conducted on datasets

9. Limitations of Medical SAS Datasets • Not all care dimensions • Nursing home utilization is not available at a national level • VA databases contain limited information on the use of non-VA services • Incentives for coding • Some conditions may be under-reported in administrative data compared with medical records (coding errors)

10. Inpatient Data Flow

11. Inpatient Datasets • Inpatient datasets cover four main categories of inpatient care: • Acute: Inpatient stays for acute care (generally referred to as “the Inpatient Data”, “the inpatient utilization data”) • Extended: Inpatient stays paid for by the VA that occur in domiciliaries, VA nursing homes, or community nursing homes • Observation: Hospital stays (generally less than 24 hours) for monitoring, evaluation, or assessment prior to inpatient admission or assignment to care in another setting • Non-VA: Data on care funded by the VA and provided in non-VA hospitals • Within each category of care, cover four datasets: • Main File:A patient's inpatient stay (episode of care) • Bed Section File:A patient's inpatient stay under a specified physician treating specialty service • Procedure File:One day's procedure during an inpatient stay • Surgery File:One day's surgeries during an inpatient stay (not available for Observation Care)

12. Inpatient Datasets • Datasets in AAC are named: MDPPRD.MDP.SAS.(XXyy) where XX = the two letter code below and yy = two digit FY • Inpatient: • PM – Acute Care Main File • PB – Acute Care Bed Section File • PP – Acute Care Procedure File • PS – Acute Care Surgery File • Long Term/Extended Care: • XM – Extended Care Main File • XB – Extended Care Bed Section File • XP – Extended Care Procedure File • XS – Extended Care Surgery File • Observation Care: • PMO – Observation Care Main File • PBO – Observation Care Bed Section File • PPO – Observation Care Procedure File • No surgery file • Contract Care: • NM – Non – VA Care Main File • NB – Non – VA Care Bed Section File • NP – Non – VA Care Procedure File • NS – Non – VA Care Surgery File

13. Session Objectives • How has healthcare utilization been measured in VA studies? • Overview of Medical SAS inpatient databases • Finding information in the Inpatient Medical SAS databases • Example of VA study that measured VA healthcare utilization • Where to go for more help

14. Assessing Inpatient Healthcare Use:Finding info in Inpatient Medical SAS Datasets • Question: • Where do I find information about admissions? • Answer: • All inpatient datasets include data on admission, discharge date and time, and discharge type (e.g., Regular, Death-Autopsy, Non-bed Care) • VA Inpatient Main includes information on care characteristics, i.e., DRG and discharge disposition • VA Inpatient Bed Section includes information on bed section DRG

15. Assessing Inpatient Healthcare Use:Finding info in Inpatient Medical SAS Datasets • Question: • Where can I find information on a patient’s diagnosis upon admission? • Answer: • All inpatient datasets include principal diagnosis (DXPRIME) for admission (condition determined to be chiefly responsible for the admission) • Inpatient Main datasets includes diagnostic codes in ICD-9 • Primary Diagnosis: DXPRIME = diagnosis chiefly responsible for the admission • DXLSF = Diagnosis responsible for the majorpartofthefullstay • Secondary Diagnoses: DXF2 – DXF10 = ICD-9 codes that represent patient problems beyond the principal reason for the encounter. • Bed Section Datasets include bed section diagnosis (max 5) • No reliable date of diagnosis in claims or administrative data • Cohort includes a mix of Incident cases + Prevalent cases

16. Assessing Inpatient Healthcare Use:Finding info in Inpatient Medical SAS Datasets • Question: • Where do I find information about inpatient procedures? • Answer: • Inpatient procedure datasets contain information on: • Procedure, coded in ICD-9-CM (vs. CPT for outpatient procedures) • Dialysis type & number of dialysis treatments • Inpatient surgery datasets also include procedure information, including surgery or procedure day • Note: Surgery = Procedure performed in main or specialized operating room. “Procedure” in Facility A may = “Surgery” in Facility B. Look at both datasets.

17. Assessing Inpatient Healthcare Use:Finding info in Inpatient Medical SAS Datasets • Question: • How do I identify the specialty of the physician providing inpatient care? • Answer: • Inpatient procedure datasets include information on physician’s specialty (bed section) • Inpatient bed section datasets include information on physician specialty • Bed section is *not* the physical location of care. Physical Location Code = PLBED • Each record in the inpatient bed section dataset = One bed section stay • Maximum of 25 bed section records per inpatient stay

18. Assessing Inpatient Healthcare Use:Finding info in Inpatient Medical SAS Datasets • Question: • How do I identify care for a defined period of time? • Answer: • Records for the inpatient databases are created at discharge for the full stay, even if the admission was in a prior year • Exception: Claims for Non-VA Care are included in the dataset for the fiscal year they were submitted, not the year for which care was provided • All inpatient datasets include data on admission and discharge date and time • In the VA, there is a distinction between acute stays and non-acute stays. See subsequent slides for how to calculate acute length of stay (ALOS)

19. Assessing Inpatient Healthcare Use:Finding info in Inpatient Medical SAS Datasets • Question: • How do I compute acute length of stay (LS)? • Answer: • Inpatient Main dataset includes information on care characteristics, including LOS, which may include extended care stay • Use bed section data in Inpatient dataset • Date & time of transfer into & out of bed section (BSINDAY & BSOUTDAY) to compute acute care LOS • HERC inpatient Average Cost Datasets documentation has details (pp. 29 - 32)

20. Session Objectives • How has healthcare utilization been measured in VA studies? • Overview of Medical SAS inpatient and outpatient databases • Finding information in the Inpatient Medical SAS databases • Example of VA study that measured VA healthcare utilization • Where to go for more help

21. Research Example • Cooperative Studies Program conducted a randomized controlled trial (RCT) • the Angina With Extremely Serious Operative Mortality Evaluation (AWESOME) trial • CSP #385, PI: D. Morrison MD, PhD • This RCT compared Percutaneous Coronary Intervention (PCI) to Coronary Artery By-Pass Grafts (CABG) for • the urgent revascularization of medically refractory, • high-risk • myocardial ischemia patients • These patients, at high risk for major complications or death from surgery, have largely been excluded from other RCTs

22. Research Example • The AWESOME RCT • Enrolled patients over a 5-year period from February 1995 through February 2000 • Compared survival and survival free of angina for men with medically refractory myocardial ischemia at high-risk for adverse outcomes • 16 VA medical centers

23. Research Example • We conducted a cost-effectiveness analysis of the AWESOME trial (NIH R03 HL70287, PI: K. Stroupe, PhD) • To compare costs of initial revascularization procedures for patients randomized to PCI or CABG • To compare utilization and costs of follow-up care between patients randomized to PCI or CABG • To compare the total direct healthcare costs for patients randomized to receive either PCI or CABG • To examine the cost-effectiveness of PCI vs CABG in these patients – effectiveness measured in years of survival

24. Research Example • Of the clinically eligible patients, 454 consented to be randomized - 232 CABG and 222 PCI patients • Insufficient information was available to identify 9 patients in the VA databases • 445 patients have been included in the cost-effectiveness analysis • 227 CABG patients • 218 PCI patients

25. Research Example:Methods:Data Sources - Utilization • The original AWESOME trial ran from Feb. 1995 – Feb. 2000. Using data from national VA and Medicare databases we extended follow-up through Sep. 2004 • Data on hospital stays and outpatient visits in VA were from the VA Medical SAS Datasets • Outpatient files: Outpatient Visit File; Outpatient Event File; Outpatient Procedure File • Inpatient files: Acute Inpatient Files (PM, PB, PP, PS); Extended Care Files (XM, XB, XP, XS); Observation Files (PMO, PBO, PPO) • Non-VA care paid for by VA was from the Fee Basis Files • Non-VA hospitalizations for Medicare-enrolled patients came from Medicare claims data

26. Research Example:Methods:Data Sources - Utilization • To identify PCI or CABG, we used • Procedure codes (ICD-9) in inpatient procedure files (PP, XP, PPO) and • Surgery codes (ICD-9) in inpatient surgery files (PS, XS) • CPT codes in outpatient event file and outpatient procedure files • ICD-9 surgery codes and CPT codes in Fee basis • ICD-9 surgery codes in Medicare data

27. Research Example:Results: Healthcare Utilization

28. Research Example:Results: Healthcare Utilization

29. Research Example • Cost Effectiveness Analysis concluded that the PCI-assigned patients had lower medical costs and survival was at least as good at 5 years, suggesting that PCI is the “economically dominant strategy” in high-risk patient

30. Session Objectives • How has healthcare utilization been measured in VA studies? • Overview of Medical SAS inpatient and outpatient databases • Finding information in the Inpatient Medical SAS databases • Example of VA study that measured VA healthcare utilization • Where to go for more help

31. VIReC Help • VIReC Webpage http://www.virec.research.va.gov • Information on VA data sources and how to access data • Documentation on some VA datasets, i.e., Medical SAS datasets: • http://www.virec.research.va.gov/DataSourcesName/Medical-SAS-Datasets/SASdocumentation.htm • Includes lists of variables and their dataset locations • Descriptions of each of the variables • Values for selected variables

32. VIReC Help (cont’d) • HSRData Listserv • Join at VIReC Web site • Discussion among > 200 data stewards, managers, and users • Past messages in archive (on intranet) • VIReC Help Desk • VIReC staff will answer your question and/or direct you to available resources on topics • VIReC@va.gov • (708) 202-2413

33. Bibliography • Fuller MA, Shermock KM, Secic M, Laich JS, Durkin MB. 2002. Service use and costs among VA patients with schizophrenia taking risperidone or olanzapine. Psychiatr Serv. 53(7):855-60. • Payne SM, Lee A, Clark JA, Rogers WH, Miller DR, Skinner KM, Ren XS, Kazis LE. 2005. Utilization of medical services by Veterans Health Study (VHS) respondents. J Ambul Care Manage. Apr-Jun;28(2):125-40. • Washington DL, Villa V, Brown A, Damron-Rodriguez J, Harada N. 2005. Racial/ethnic variations in veterans' ambulatory care use. Am J Public Health. 95(12):2231-7. Epub 2005 Oct 27. • Weaver FM, Hatzakis M, Evans CT, Smith B, LaVela SL, Wallace C, Legro MW, Goldstein B. 2004. A comparison of multiple data sources to identify vaccinations for veterans with spinal cord injuries and disorders. J Am Med Inform Assoc. 11(5):377-9. Epub 2004 Jun 7.

34. Suggested other resources: Medical SAS Datasets:Data Quality Information • Quality assessments performed by the Office of Inspector General, the Medical Care Cost Recovery program, and special workgroups • Data Quality, Information Assurance, Office of Information (http://vaww.vhaco.va.gov/dataquality/ default.htm). • VHA Coding Council (http://vaww1.va.gov/health/him/VHACC/VA_HIM_P/coding_council1.htm) - VHA Coding Handbook • HSRData e-mail listserv

35. Suggested other resources: • Murphy PA, Cowper DC, Seppala G, Stroupe KT, Hynes DM. 2002. Veterans Health Administration inpatient and outpatient care data: a rich resource of research data. Effective Clinical Practice. 5:e4. Available at http://www.acponline.org/journals/ecp.