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VIReC Cyber Seminar Series 2006
VA Databases and MethodsVA Databases and Methods
Assessing VA Outpatient Healthcare Use
Presented byDenise M. Hynes, Ph.D., R.N.
Director, VA Information Resource CenterResearch Health Scientist, MCHSPR COE
2
Session Objectives
Why Measuring Outpatient Use is Not Always as Simple as it Seems
Key Data Source Review: Medical SAS Outpatient Databases & DSS Outpatient
Measurement Strategies for Evaluating Outpatient Care Use
Where To Go For More Help
3
Session Objectives
Why Measuring Outpatient Use is Not Always as Simple as it Seems
Key Data Source Review: Medical SAS Outpatient Databases
Measurement Strategies for Evaluating Outpatient Use
Where To Go For More Help
4
Outpatient Use Measurement Issues
Frequency of outpatient visits– Recent year? Longer historical view?
Specific types of outpatient visits by provider type– Separate nurse visits from physician visits
Specific types of clinical settings or clinics– Dialysis care? CBOCs versus VAMC Outpatient?
Outpatient procedures– Can a CABG really be done in an outpatient setting?
When outpatient care overlaps with inpatient care– Which is it?
Assessing comorbidity with outpatient care data– Inpatient diagnoses versus outpatient diagnoses
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Session Objectives
Why Measuring Outpatient Use is Not Always as Simple as it Seems
Key Data Source Review: Medical SAS Outpatient Databases & DSS Outpatient
Measurement Strategies for Evaluating Outpatient Use
Where To Go For More Help
6
VA Outpatient Medical SAS Datasets
AKA as OPC (Outpatient Clinic File) or National Patient Care Database (NPCD) Outpatient SAS files
Records generated for each ambulatory care encounter recorded in VISTA
Outpatient events coded by CPT code, whereas Inpatient Datasets coded by ICD9
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VA Outpatient Data Flow to the Med SAS Datasets
Data Flow from the VHA Medical Centers to the Austin Automation Center (AAC)
to the Medical SAS Outpatient Datasets
VHA Medical Centers Tables at AAC (local VISTA system) (relational database)
Medical SAS Outpatient Datasets
Visit Dataset – Clinic stop codes and patient demographics for all encounters
Event Dataset – Procedure codes, diagnosis codes and patient demographics for one encounter at one clinic
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VA Medical SAS Outpatient Datasets
File Reference Dates
Visit SF 1980 - present
Event SE 1998 – present
Diagnosis SG 1997 – 2001
Procedure SC 1990 - 2001
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Data Elements Common In Outpatient Med SAS Datasets
Patient identifier (SCRSSN)
Patient demographics (Age, date of birth, race, marital status)
Patient Zip Code, County, & State of Residence
Date of encounter
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Common Data Elements
Means Test Indicator (MEANS)
Patient eligibility code (ELIG)– ELIG < 11 identifies a veteran
Agent Orange exposure claimed (AOIND/AGOLOC)
Radiation exposure claimed (RAD)– Visit: 4 categories– Event: exposed vs. not exposed
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Outpatient Visit Dataset (SF)
Record = One day’s encounters for a patient at a clinic
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Outpatient Visit (SF) DatasetSelected Data Elements
One record per visit
Up to 15 clinic stops per visit
No diagnosis or procedure information
Race:– RACE– RACE1 – RACE7 from FY2004
Insurance and religious preference only in Visit file
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Outpatient Event (SE) Dataset
Record = Ambulatory encounter– Coded as Primary Clinic Stop, which is officially
referred to as DSS Identifier
No limit on number of encounters per day
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Outpatient Event (SE) DatasetSelected Data Elements
Record = Ambulatory encounter or clinic stopNo limit on number of clinic stops per dayUp to 10 diagnoses in ICD-9 codes (DXLSF, DXF2 – DXF10) per recordUntil FY2003: Up to 15 procedures in CPT4 codes (CPT1 – CPT15), no repeats allowedSince FY2004: Up to 20 CPT4 codes with repetition allowedEncounter ID to link the Event dataset with HERC Outpatient Average Cost Dataset since FY2003Appointment type only in Event Dataset
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VA Outpatient Med SAS DatasetsDatasets in AAC are named MDPPRD.MDP.SAS.(XXyy) where XX = the two letter code below and yy = two digit FY
Outpatient Care– SE – Outpatient Event File
• Information about each encounter (clinic stop) during a day’s outpatient care
• Combines diagnostic and procedural info in one dataset– SF – Outpatient Visit File (expanded in FY97 to include demographics
previously in SC)• Information about a day’s outpatient care encounters
Outpatient Care – discontinued datasets– SC – Outpatient Procedure File (not generated after FY2001)
• Contains CPT-4 outpatient procedure information• Now folded into SE
– SG – Outpatient Diagnosis File (not generated after FY2001)• Contains outpatient ICD-9-CM diagnosis information• Now folded into SE
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Strengths of VA Outpatient Med SAS Datasets
Centralized data source
Large groups of patients
Unique identifier (SCRSSN: Scrambled Social Security Number) allows linking records across files/years
Given good coding, datasets are reflective of general clinical status
Historical data available back to 1970’s
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Limitations of VA Outpatient Med SAS Datasets
Does not include all outpatient care dimensions– Does not include VA home care or telehealth
events– Fee basis care, contract care, and Medicare
outpatient use available in separate national datasets
– Non-VA non-Medicare outpatient care use not included
18
Another Data Source: DSS National Data Extract (NDE)
Outpatient (OPAT) File Available since FY99
Has one record for each unique clinic stop visit
Seven indicator variables (flags) to identify different types of data sources in outpatient clinic records
Linkable with other VA data
Due to large file size, data are grouped by VISNs and divided into Clinic Stop 160 (Pharmacy) and all other stops
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DSS NDE OPAT Dataset
Includes costs fields
Some discrepancies with NPCD/OPC exist
HERC Report #9 on Reconciliation of DSS Encounter-level National Data Extracts with the VA National Patient Care Database, FY2001-FY 2002
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Session Objectives
Why Measuring Outpatient Use is Not Always as Simple as it Seems
Key Data Source Review: Medical SAS Outpatient Databases & DSS Outpatient
Measurement Strategies for Evaluating Outpatient Use
Where To Go For More Help
21
Measurement Strategies in Evaluating Outpatient Use: Outpatient Procedures
Outpatient Outpatient Event (SE) File has information about each encounter– Appointment type only in Outpatient Event File– Encounter = “clinic stop”– Primary Clinic Stop (CL): The first three characters of the 6-character
Decision Support System (DSS) Identifier used to identify the production units or the revenue centers for outpatient care.
– Secondary Clinic Stop (CLC): The last three characters of the DSS Identifier
– No limit on number of encounters/clinic stops per day; no priority order– Since FY2004: Up to 20 CPT4 codes with repetition allowed; before, up to
15 procedures with no repeats allowed; no priority order– Note: You may want to exclude emergency room visits (CL = 101, 102)
Outpatient Visit (SF) File has information about a day’s encounters– One record per visit– Up to 15 clinic stops per visit– No procedure information
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Measurement Strategies in Evaluating Outpatient Use: Outpatient Surgeries
Look by CPT code in Outpatient Event (SE) File
Look by Clinic Stop (variables: CL, CLC) in Outpatient Event (SE) File– Sampling of clinic stop codes: General Surgery (CL = 401), Cardiac
Surgery (CL = 402), Neurosurgery (CL = 406). For complete list of clinic stop codes, refer to: http://www.virec.research.va.gov/References/RUG/RUG-Outpatient04.pdf
Outpatient Surgeries could be included in Inpatient Workload– If interested in a particular type of surgery, also refer to Inpatient Med SAS
Surgery and Procedure files – different facilities record procedures differently depending upon whether the procedure was done as an outpatient/inpatient or in the OR suite/outpatient surgery.
Check the VA’s Fee Basis files for information on surgeries that are typically done on a fee basis: http://www.herc.research.med.va.gov/data/fb.asp
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Measurement Strategies in Evaluating Outpatient Care: Including Outpatient Surgeries
Example from Morrison, et al CSP#385
Angina With Extremely Serious Operative Mortality Evaluation (AWESOME) trial CSP #385, PI: Douglass Morrison MD, PhD)
This RCT compared Percutaneous Coronary Interventions (PCI, previously known as angioplasty) to Coronary Artery Bypass Grafts (CABG) for the urgent revascularization of medically refractory, high-risk myocardial ischemia patients– Compared survival and survival free of angina for men with medically
refractory myocardial ischemia at high-risk for adverse outcomes– Also conducted a cost-effectiveness analysis of PCI vs. CABG in these
patients – cost-effectiveness analysis funded by NIH R03 HL70287, PI: Kevin Stroupe, PhD
Concluded that the PCI-assigned patients had lower medical costs and better survival, suggesting that PCI is the “economically dominant strategy” in high-risk patients
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Measurement Strategies in Evaluating Outpatient Use: Including Outpatient Surgeries
Example from Morrison, et al CSP#385
The original AWESOME trial ran from Feb. 1995 – Feb. 2000. Using data from administrative databases we extended follow-up through Sep. 2003 Data on hospital stays and outpatient visits in VA were from the VA National Patient Care Database 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)– To identify PCI or CABG procedures, used procedure codes in
inpatient and outpatient procedure (SC) files, and surgery ICD9CM codes in surgery files and used CPT codes in outpatient event (SE) file.
Non-VA care paid for by VA was from the Fee Basis FilesMedicare claims data for the 296 (67%) Medicare-eligible patients (i.e., 65 years of age or older) at enrollment
25
Outpatient Event (SE) Dataset includes up to 10 diagnoses in ICD-9 codes (DXLSF, DXF2 – DXF10) per record
• DXLSF = Primary Diagnosis for this encounter• DXF2 – DXF10 = Patient problems beyond the principal
reason for the encounter--only 15% of records in FY99 contained a DXF2
• Not available prior to FY97
Agent orange and radiation exposure claimed is a common data element in all outpatient datasets
Outpatient Visit (SF) Dataset does *not* contain any diagnosis information
What if you were interested in diagnosis linked outpatient care prior to FY97??
Measurement Strategies in Evaluating Outpatient Use: Outpatient Diagnoses
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No outpatient data element with physician specialty
Proxy: Area of care associated with the visit– Outpatient Event dataset includes CMS category of
provider (variable: PROV1–PROV10)– http://www.virec.research.va.gov/References/RUG/RUG-O
utpatient04.pdf– Appendix A:– 1100XX series physicians/osteopath
• eg,110400 anesthesiology; 110600 cardiology; 110700 dermatology, etc.
Measurement Strategies in Evaluating Outpatient Use: Outpatient Provider Specialty
27
Can link Inpatient and Outpatient databases via SCRSSN (Scrambled Social Security Number; patient unique identifier)Identify inpatient event and dates of stay– All inpatient datasets include data on admission and discharge
date and time– Use inpatient bedsection datasets to determine acute length of
stay
Identify all outpatient procedures conducted during LOS– All outpatient datasets include date of encounter as a common
data element (VIZDAY)– Outpatient Event File has information about each encounter’s
procedures
To see if a patient has been discharged to outpatient treatment, refer to the “OPT” variable (outpatient treatment) in the Inpatient Main dataset (1 = Yes, 2 = Due to service-connected disability, patient is automatically eligible for outpatient care)
Measurement Strategies in Evaluating Outpatient Use: Outpatient Care Concomitant w/Inpatient Care
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Measurement Strategies in Evaluating Outpatient Use: Intensity of Outpatient Care
Example from Ashton et al., Am J Managed Care 2003
Retrospective cohort study conducted by secondary analysis of Medical SAS Inpatient and Outpatient datasets
Describe comorbid conditions and patterns of inpatient and outpatient service use by veterans with diabetes mellitus (DM)
Utilization rates computed for 1997
Measured intensity of care using Inpatient and Outpatient datasets– Inpatient: bed-day rates (cumulative # of days in hospital)
– Outpatient: Rates of primary care visits, including ancillary services, consults, urgent care visits
Results: In VA, beneficiaries with DM have a heavy burden of comorbidities, face a significant risk of dying, and are heavy users of inpatient and outpatient services.
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Measurement Strategies in Evaluating Outpatient Use: Outpatient Care Over Time
Example from Maciejewski and Maynard, Diabetes Care 2004
Retrospective cohort study conducted by secondary analysis of Medical SAS Inpatient and Outpatient datasetsDescribe patterns of inpatient and outpatient care by veterans with diabetes mellitus (DM), stratified by age and racial groupInpatient utilization for years 1994-1998; outpatient utilization for years 1997-1998Used VA Medical SAS Inpatient to measure:– Length of stay– Number of hospital discharges– Rate of hospital discharge
Used VA Medical SAS Outpatient Datasets to measure:– Number of outpatient visits
Results: Between 1994-1998, hospitalization rates decreased and outpatient visits increased
30
From: Maciejewski ML and Maynard CM. Diabetes-Related Utilization and Costs for Inpatient and Outpatient Services in the Veterans Administration. Diabetes. 2004: 27(suppl 2):B69-B73.
OPC-SE OPC-SE
OPC SC since FY90OPC SC since FY90OPC DX started in 1997OPC DX started in 1997
OPC-SF-back to 1980OPC-SF-back to 1980
But no DX field to identify the DM casesBut no DX field to identify the DM cases
Outpatient Care Over TimeExample from Maciejewski and Maynard, 2004
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Session Objectives
Why Measuring Outpatient Use is Not Always as Simple as it Seems
Key Data Source Review: Medical SAS Outpatient Databases
Measurement Strategies for Evaluating Outpatient Care Use
Where To Go For More Help
32
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
33
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– [email protected] – (708) 202-2413
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Selected Recent References on Measurement of VA Outpatient Use
Murphy PA, Cowper DC, Seppala G, Stroupe KT, Hynes DM. Veterans Health Administration inpatient and outpatient care data: a rich resource of research data. Effective Clinical Practice. 2002: 5:e4.
Available at http://www.acponline.org/journals/ecp.
Fortney JC, Borowsky SJ, Hedeen AN, Maciejewski ML, Chapko MK. VA community-based outpatient clinics: access and utilization performance measures. Medical Care. 2002: Jul;40(7): 561-9.
Fuller MA, Shermock KM, Secic M, Laich JS, Durkin MB. Service use and costs among VA patients with schizophrenia taking risperidone or olanzapine. Psychiatry Serv. 2002: 53(7):855-60.
Ashton CM, Septimus J, Petersen NJ, Souchek J, Menke TJ, Collings TC, Wray NP. Healthcare use by veterans treated for diabetes mellitus in the Veterans Affairs medical care system. American Journal of Managed Care. 2003: 9(2):145-150.
Maciejewski ML and Maynard CM. Diabetes-Related Utilization and Costs for Inpatient and Outpatient Services in the Veterans Administration. Diabetes. 2004: 27(suppl 2):B69-B73.
35
Selected Recent References on Measurement of VA Outpatient Use
(CONTINUE)
Weaver FM, Hatzakis M, Evans CT, Smith B, LaVela SL, Wallace C, Legro MW, Goldstein B. A comparison of multiple data sources to identify vaccinations for veterans with spinal cord injuries and disorders. J Am Med Inform Assoc. 2004: 11(5):377-9. Epub 2004 Jun 7.
Washington DL, Villa V, Brown A, Damron-Rodriguez J, Harada N. Racial/ethnic variations in veterans' ambulatory care use. Am J Public Health. 2005: 95(12):2231-7. Epub 2005 Oct 27.
Payne SM, Lee A, Clark JA, Rogers WH, Miller DR, Skinner KM, Ren XS, Kazis LE. Utilization of medical services by Veterans Health Study (VHS) respondents. J Ambul Care Manage. 2005: Apr-Jun;28(2):125-40.
Weeks WB, Bott DM, Lamkin RP, Wright SM. 2005. Veterans Health Administration and Medicare outpatient health care utilization by older rural and urban New England veterans. J Rural Health. 2005 Spring;21(2):167-71.
Luther SL, French DD, Powell-Cope G, Rubenstein LZ, Campbell R. 2005. Using administrative data to track fall-related ambulatory care services in the Veterans Administration Healthcare system. Aging Clin Exp Res. 2005 Oct;17(5):412-8.
Fortney JC, Steffick DE, Burgess JF Jr, Maciejewski ML, Petersen LA. Are primary care services a substitute or complement for specialty and inpatient services? Health Serv Res. 2005: Oct;40(5 Pt 1):1422-42.
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Suggested other resources Medical SAS Datasets:
Data Quality InformationQuality assessments performed by the Office of Inspector General, the Medical Care Cost Recovery program, and special workgroups
Data Quality, Information Assurance, Office of Information (Please refer to the set slides from this presentation on the VIReC Intranet website for the link to this office).
VHA Coding Council (Please refer to the set slides from this presentation on the VIReC Intranet website for the link to this office).
HSRData e-mail listserv
37
Audience Question
Question:– Do you have information about the Inpatient
Encounter Files?
Answer:– The Austin Automation Center “Inpatient Encounters” files are
relatively new. Patients in this file were seen in one of the VHA outpatient clinics while they had an inpatient status, where “inpatient status” is defined as patients in acute care, extended care, observation care, or non-VA care status. The Outpatient Encounters files exclude services that are included in the Inpatient Encounters files. The file uses CPT codes because the services are provided at the outpatient stops. The AAC file is “MDPPRD.MDP.SAS.IEyy” where “yy” refers to the two-digit year. The file is sorted by SCRSSN, VIZDAY, and STA6A. Data are available beginning in fy2005.
* See the National Patient Care Database Data Dictionary on the Intranet for further details.