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Using Health Factors Data for VA Health Services Research
Barnett PG, Chow A, Flores NE
Health Economics Resource Center #28, February 2014 | Download »
  • Data generated by clinical reminders software have been consolidated into a national health factors database. These data were standardized to identify current tobacco users, former users, and never users. Over the three fiscal years 2009-2011, the health factors database included tobacco use assessments of 5.0 million patients in 14.4 million encounters. Among 5.7 million users of VA care in fiscal year 2011, 4.0 million (70.3%) had a timely tobacco use status assessment in the health factors dataset. For persons with a tobacco use assessment in fiscal year 2009, a follow-up assessment was available within 24 months for 88% of those initially assessed as a current user and for 86% of those initially assessed as having quit within the last 7 years. The follow-up assessment found that 12.3% of those initially determined to be a tobacco user had quit and that relapse was more common among those who had quit for a shorter period. The health factors database is a useful source of information for long-term follow-up and epidemiologic studies.
Updating the HERC Average Cost Method: Use of 2009 Medicare Data and an Analysis of CABG Surgery
Wagner TH, Cowgill EH
Health Economics Resource Center #27, March 2012 | Download »
  • The HERC Average Cost dataset for inpatient medical/surgical care is created annually by combining Medicare relative value units (RVUs) to estimate U.S. Department of Veterans Affairs (VA) costs for every VA encounter. These methods have been described in detail elsewhere.1 In 2011, we updated the statistical model using Medicare data from 2009. This technical report describes the updated model and includes a more detailed examination of cardiac bypass surgery (CABG) average costs.
Use and Cost of Fee Basis Services in FY2007
Smith M, Chen S, Fan A
Health Economics Resource Center #26, December 2010 | Intranet only
  • The purpose of this brief report is to describe major patterns in the Fee Basis data. The HERC guidebook on Fee Basis data (Smith and Chow 2010) describes the contents of the eight annual Fee Basis files. It also notes the variety of ways to access Fee Basis data. This report is a companion that provides specific data on spending and counts of services. The next chapter describes outpatient services and costs. It presents a number of tables that show the most common categories of outpatient care by type and frequency. Chapter 3 discusses inpatient data and the overlap of Fee Basis data with other VA administrative datasets.
A Guide to Estimating Wages of VHA Employees - FY2008 Update
Smith MW, Cheng A
Health Economics Resource Center #25, January 2010 | Intranet only
  • Economic analyses of VA care often include estimation of the cost of VA staff time. This report describes how to estimate average annual and hourly wages (including benefits) and presents these averages for fiscal years 2005-2008. Two sets of figures are presented, one based on data from the Financial Management System (FMS) and one based on data from the Decision Support System (DSS) Account-Level Budgeter Cost Center (ALBCC) datasets. The report also provides sample programs for calculating wage figures from each source.

    To increase comparability with ALBCC, we limited the FMS data to cost centers pertaining to direct medical care at VA facilities. For budget object codes (job categories) in the 1100-1199 range, FMS and ALBCC data files report nearly identical total expenditures. The distribution of dollars and hours across job categories was quite similar for common job categories, such as registered nurses and full-time physicians. There was considerable variation across data sources, however, in categories pertaining to trainees, temporary employees, and administrative staff.

    Because the average wages derived from the FMS and ALBCC data files are very similar, we conclude that researchers may use either source with confidence for common clinical job categories. It is difficult to provide any recommendation with respect to administrative, temporary, or trainee positions. An advantage of ALBCC over FMS is the detail available within job categories on spending across DSS intermediate products. FMS will be the only option if data from FY1999 and earlier are needed.
A Guide to Estimating Wages of VHA Employees - Supplement
Smith MW, King SS
Health Economics Resource Center #25, January 2010 | Intranet only
Dialysis Treatment Use and Costs Reported in VA Administrative Databases, FY2007
Smith MW, Siroka A
Health Economics Resource Center #24, March 2009 | Intranet only
  • This report reviews FY2007 VA data on dialysis procedures. It updates HERC Technical Report #17 (Smith and Richardson, 2005), which analyzed similar data for FY2004. We describe several DSS extracts that record dialysis care and explain step by step how to access them. An appendix lists the procedure codes and other variables used to locate dialysis care in DSS utilization records. We show the frequency of dialysis procedures recorded in DSS and the implied average cost per hour or per encounter. We also report figures from alternative utilization and cost data sources, the Outpatient Care file (OPC) and the HERC Average Cost datasets. The report ends with recommendations for researchers and policymakers.
Comparison of DSS Encounter-Level National Data Extracts and the VA National Patient Care Database: FY2004
King SS, Phibbs CS, Yu W, Barnett PG
Health Economics Resource Center #23, November 2007 | Intranet only
  • This report presents the results of a comparison between the Decision Support System (DSS) National Data Extracts (NDEs) and files from the VA National Patient Care Database (NPCD) and Patient Treatment File (PTF) in FY 2003 and FY 2004.
Comparing Outpatient Cost Data in the DSS National Pharmacy Extract and the Pharmacy Benefits Management V3.0 Database
Smith MW, King SS
Health Economics Resource Center #22, November 2007 | Intranet only
  • This technical report presents results of an investigation into cost data in the DSS and PBM prescription-level outpatient data. Although the two sources do not share a consistent cost variable, each provides an approximate VA acquisition cost. Our primary goal was to investigate the similarity in cost between them. Based on the rules for creating DSS data, we expected similar costs across datasets for prescriptions filled through outpatient mail-order pharmacies (CMOPs) and a slightly poorer match in costs for pharmacy window fills. A secondary goal was to explore how observed cost differences vary by drug type and VA station.
Matching Prosthetics Order Records in the VA National Prosthetics Patient Database (NPPD) to Health Care Utilization Databases
Smith MW, Phibbs CS, Su P
Health Economics Resource Center #21, July 2007 | Intranet only
  • This report presents results of several comparisons between NPPD and three utilization databases. We first compared the count of prosthetics records in NPPD to the count of prosthetics-related procedures for the same individuals recorded in the utilization databases. We then attempted to match NPPD records to the utilization records by fiscal year, patient ID, prosthetic category, and date. We find moderate concordance in the number of non-supply items across data sources, and that only a minority of NPPD records can be matched to utilization records. The relatively low match rate most likely reflects the process by which prosthetics are ordered and received rather than missingness or data entry error. The report concludes with suggestions of other research uses for NPPD.
A Guide to Identifying Non-Veteran Records in the Inpatient and Outpatient Databases
King S, Shane A, Smith MW
Health Economics Resource Center #20, September 2006 | Intranet only
  • In this report, we provide a workable approach for identifying non-veteran records. Thus, researchers who need to identify, analyze or exclude non-veteran records in their studies may find our approach helpful. The identification of non-veteran records is especially important in studies of the healthcare use of female veterans.
Spending for VA Specialized Mental Health Care
Wagner TH
Health Economics Resource Center #19, October 2006 | Download »
Fee Basis Data: A Guide for Researchers
Smith MW, Chow A
Health Economics Resource Center #18, November 2007 | Intranet only
  • This guidebook is intended to help researchers understand and use national Fee Basis files. It describes the contents of the files, notes their limitations, and offers suggestions for their use in research. It also provides information on file access and documentation, and contact information for Fee Basis managers.
Dialysis Treatment Use and Costs Reported in VA Administrative Databases
Smith MW, Richardson SS
Health Economics Resource Center #17, March 2005 | Intranet only
  • In this report we review current VA data on dialysis procedures. We describe several DSS extracts that record dialysis care and explain step by step how to access them. An appendix lists the procedure codes and other variables used to locate dialysis care in DSS utilization records. We show the frequency of dialysis procedures recorded in DSS and the implied average cost per hour or per encounter. We also report figures from alternative utilization and cost data sources, the National Patient Care Database (NPCD) and the HERC Average Cost datasets. The report ends with recommendations for researchers and policymakers.
The Effects on Measured Workload and Costs of Limiting CPT Codes in the NPCD SE File
Phibbs CS, Su P, Barnett PG
Health Economics Resource Center #15, November 2004 | Intranet only
  • The current programming rules for the creation of the SAS SE extract of the National Patient Care Data (NPCD) outpatient encounters database allows no repetition of Common Procedural Terminology (CPT) codes and sets a maximum limit of 15 CPT codes per record. However, the source Oracle database in Austin, from which the SAS extracts are created, contains an array that has a maximum of 500 CPT occurrences and that imposes no restrictions on repetition of CPT codes.

    To address concerns about the data currently excluded from the NPCD SE SAS extract, a special 10% random sample of the NPCD outpatient encounters data was created that allowed repetition of CPT codes and up to 500 CPT codes per record. This file was used to examine the implications of the current limits and to recommend potential changes.
A Comparison of Outpatient Costs from the FY 2001 HERC and DSS National Data Extract Datasets
Phibbs CS, Schmitt SK
Health Economics Resource Center #14, April 2007 | Intranet only
  • The purpose of this report is to provide information to researchers about the differences between these two estimates of outpatient costs so that they can decide which cost data are the most appropriate for a particular research study. This report: Summarizes the key differences between the DSS and HERC outpatient cost estimates (not including outpatient pharmacy); Provides a comparison of FY 2001 DSS and HERC outpatient cost data by the HERC categories of outpatient care; Looks to identify any significant systematic differences between the DSS and HERC outpatient cost estimates.
Comparison Between DSS National Data Extracts and HERC Average Costs: Aggregate and Person-Level Costs, FY2001
Yu W, Berger M
Health Economics Resource Center #13, May 2004 | Intranet only
  • This report is one of three comparisons of the two VA cost datasets at HERC. In this report we look at person-level annual costs; the other two reports compare inpatient and outpatient costs at the encounter level, respectively. We define person-level annual cost as the total VA health care cost incurred by one person within fiscal year 2001 (FY2001, the period October 1, 2000 – September 30, 2001). In Section 2, we describe the structural differences between the two datasets and the effects of these differences on cost estimates at various levels of cost aggregation. Section 3 addresses the difference between person-level and encounter-level costs, Section 4 provides methods, Section 5 reports the results, and section 6 provides recommendations for data selection.
A guide to estimating wages of VHA employees
Smith MW, Velez J
Health Economics Resource Center #12, July 2004 | Intranet only
  • This report describes how to estimate average annual and hourly wages (including benefits) and presents these averages for fiscal years 2000-2003. Two sets of figures are presented, one based on data from the Financial Management System (FMS) and one based on data from the Decision Support System (DSS) Account-Level Budgeter Cost Center (ALBCC) datasets. The report also provides sample programs for calculating wage figures from each source.
A Guide to Estimating Wages of VHA Employees SUPPLEMENT
Smith MW, Velez J
Health Economics Resource Center #12, July 2009 | Intranet only
Evaluation of the VA Nursing Home Resident Assessment Instrument Minimum Data Set: Resource Utilization Group III in FY2001 and FY2002
Hill A, Yu W
Health Economics Resource Center #11, January 2004 | Intranet only
  • HERC staff earlier applied the Resource Utilization Group II (RUG II) system to the FY98-FY00 HERC Average Cost Data for nursing home care.1 Because of a change in the assessment instrument, VA data on nursing home care for FY01 and later were not available until recently. HERC obtained the new FY01 and FY02 RUG III assessment data in April, 2003. Unfortunately, we found problems in the RUG III data that cause us considerable concern. This report summarizes our findings.
A Comparison for Inpatient Costs from the HERC and DSS National Data Extract Datasets
Wagner TH, Velez J
Health Economics Resource Center #10, January 2004 | Intranet only
  • This study had two objectives: to assess the financial information from which the DSS and HERC data are created, and to compare using bivariate and multivariate techniques encounter-level inpatient costs from DSS and HERC for FY01 (fiscal year; October 1, 2000 – September 30, 2001).

    This report is organized as follows. Chapter 2 describes the HERC and DSS datasets in more detail, including the financial data from which these two datasets are built. We then conduct a statistical analysis of the HERC and DSS inpatient costs using 617,503 records. In chapter 3, we describe the methods for comparing the HERC and DSS inpatient data. Results are presented in chapter 4. Chapter 5 concludes.
Reconciliation of DSS Encounter-Level National Data Extracts and the VA National Patient Care Database: FY2001-FY2002
Yu W, Barnett PG
Health Economics Resource Center #9, December 2003 | Intranet only
  • This report presents results of reconciliation between the Decision Support System (DSS) National Data Extracts (NDEs) and files from the VA National Patient Care Database (NPCD) and Patient Treatment File (PTF) in fiscal year 2001 and 2002.
A Comparison of the National VA Outpatient Database to Electronic Medical Records
Ayyangar L, Trafton J, Barnett PG
Health Economics Resource Center #8, August 2003 | Download »
  • This technical report compares two sources of information on ambulatory care provided by the U.S. Department of Veterans Affairs (VA). We compared the VA electronic medical record to the VA national outpatient utilization database. We wished to validate data to be used in the economic component of the Multisite Opioid Substitution Treatment (MOST) study. The MOST study is evaluating the effect of adherence to clinical practice guidelines on the cost and outcomes of patients being treated for opiate dependence at seven sites.

    We looked at a random sample of ambulatory care data for a small sample of patients. We compared the VA medical record, VISTA to the outpatient events file, a SAS extract of the National Patient Care Database (NPCD).
Recommendations for a New Allocation System for 101 Funds
Wagner TH, Stunz A
Health Economics Resource Center #7, October 2002 | Download »
  • The VA Office of Research and Development (ORD) currently allocates approximately 7% of its budget to VA health care systems (VAHCS) to support their research administration activities. These allocations are known as “101 funds.” This system is thought to be too inflexible and inadequate for research programs that are expanding and that are facing increasing regulatory demands, is overly dependent on a Medical Center’s past performance, and is very difficult to update. We were asked by ORD to propose a new allocation method that addresses these limitations and is easy to calculate in terms of staff time and existing data sources.
Indirect Costs of Specialized VA Mental Health Treatment
Barnett PG, Berger MS
Health Economics Resource Center #6, January 2003 | Download »
  • This technical report describes the indirect cost of specialized inpatient mental health treatment programs of the U.S. Department of Veterans Affairs (VA).

    The technical report has three sections. The first section presents our calculation of the ratio of indirect to direct costs in VA specialty mental health inpatient programs. We separately identify research, education, benefits, and national and regional administration, all indirect costs that we excluded from our estimate. The goal of this effort is to find an indirect cost ratio, a factor than can be multiplied by observed direct costs to estimate indirect cost.

    The second section of this report presents our estimate of the average daily cost of VA dietary services. The third section of this report describes the average daily DSS cost of care of specialty inpatient mental health programs, including both direct and indirect cost. We calculated this so that we could compare our cost estimate to the estimates in DSS.
Cost of Positron Emission Tomography: Method for Determining Indirect Cost
Barnett PG, Berger MS
Health Economics Resource Center #5, May 2003 | Download »
  • This paper describes methods of determining the indirect cost associated with Positron Emission Tomography (PET) scans and the manufacture of 18-F-Fluorodeoxyglucose (FDG), the radioactive isotope used in PET scans.
Reconciliation of DSS Encounter-Level National Data Extracts with the VA National Patient Care Database FY2001
Yu W, Barnett P
Health Economics Resource Center #4, October 2002 | Intranet only
  • This report describes reconciliation of data from the two sources for FY2001. The reconciliation consists of three major parts: inpatient discharges, inpatient bedsections, and outpatient files. The inpatient discharge and treating specialty files in the DSS National Data Extracts (NDEs) were reconciled with the Patient Treatment Files (PTFs) in the NPCD database. The DSS Outpatient extract was reconciled with the NPCD Outpatient Event file (also called the SE file). For FY2001, the reconciliation method and results for inpatient care were very similar to that of FY2000. However, the reconciliation between the two outpatient databases was enhanced with more detailed investigation.

    In addition to the reconciliation between the DSS NDE and the NPCD files, we also reconciled the DSS NDE treating specialty with the DSS discharge files. Compared with the result in FY00, the FY01 showed improvement in internal consistency of the DSS NDE inpatient files.
The cost of operating institutional review boards (IRBs) in the VA
Wagner TH, Chadwick GL, Cruz AME
Health Economics Resource Center #3, October 2002 | Download »
  • Many claim that institutional review boards (IRBs) are under-funded, yet little is known about the costs of operating an IRB. With the growing number of IRB-related problems and the desire to increase support, this study estimated the costs of operating IRBs in the VA. We also estimated the optimal costs for IRBs and assessed whether there are economies of scale (i.e., whether cost is a function of the IRB size).
Human subjects compliance programs: optimal operating costs in the VA
Wagner TH, Barnett PG
Health Economics Resource Center #2, January 2000 | Download »
  • This report estimates the optimal costs for operating a human subjects compliance program. Specific aims include: 1) To determine the recommended staffing, support personnel and the number of Institutional Review Board (IRB) panel members needed to review the number of human subjects protocols considered by an average volume VA medical center. 2) To use the Research and Development Information System (RDIS) to compare VA medical centers by research revenues and types of studies. 3) To use information from Aims 1 and 2 to project IRB operating costs for a hypothetical optimally staffed large and medium volume VA medical center.
Determining the Cost of VA Care with the Average Cost Method for the 1993-1997 Fiscal Years
Barnett PG, Chen S, Wagner T
Health Economics Resource Center #1, October 2000 | Download »
  • This technical report deals with issues including the handling of facility mergers, the distribution of Indirect Cost CDAs, merging CDR cost data with utilization files, the need to aggregate reporting categories, how to handle matches that are difficult, and how to handle facilities without patient care. It also describes techniques for matching CDR cost data, which represent activities that occur in a particular fiscal year, with data on inpatient stays, which sometimes cross fiscal years.