HERC's Technical Reports answer specific research questions or document methods for creating datasets or conducting analyses. They answer a question at a specific moment in time and are not updated. Before using a Technical Report, we encourage readers to review all available updates to data and/or methods.
Technical Report 41: Implementation Costs of the Cooperative Pain Education and Self-Management (COPES) Intervention to Deliver In-Home Self-Management Support to Veterans with Chronic PainHealth Economics Resource Center, #41, May 2023 | View »
Cooperative Pain Education and Self-management (COPES) uses scalable, automated messaging to deliver in-home self-management support for Veterans with chronic pain. In this study, we estimated the total cost of the COPES intervention. We also estimated the cost of adding COPES to additional VA medical centers as well as the cost of replicating the intervention at a non-VA site.
Technical Report 40: Device-Collected Physiologic Data in VA ResearchHealth Economics Resource Center, #40, October 2022 | View »
Device-collected data from patient monitors are available and interpreted by healthcare staff but are rarely included in VA research studies because they are not available in a national data repository. Their omission could introduce information bias to research results. Thus, the goals of this technical report are to quantify differences between device-collected physiologic data and data obtained from the CDW Vital Signs domain for a cohort of surgical patients and discuss the potential impact of these “missing” data on analyses using physiologic data.
Technical Report 39: Understanding the impact of COVID-19 on hospitalization costs in DoD and VAHealth Economics Resource Center, #39, March 2022 | View »
US hospital systems lost over $50.7 billion per month over the course of the four-month period from March 1, 2020 to June 30, 2020 due to COVID-19 hospitalizations. This is due to factors such as cancelled services, additional costs associated with purchasing personal protective equipment, and additional labor costs. We aim to compare costs in the Department of Veterans Affairs (VA) and the Department of Defense (DoD) using COVID-19 hospitalizations as the driving example.
Technical Report 38: Encounters after Appointments Cancelled Due to COVID-19 in the Veterans Affairs Health Care SystemHealth Economics Resource Center, #38, November 2021 | View »
The COVID-19 pandemic caused an unprecedented interruption in healthcare delivery. This technical report presents data from the Veterans Health Administration on encounters after the initial wave of cancellations in March 2020.
Technical Report 37: The Effect of the COVID-19 Pandemic on VA Cost and Utilization DataHealth Economics Resource Center, #37, June 2021 | View »
In this technical report, we compare VA inpatient cost and utilization data in Fiscal Year (FY) 2019 to FY 2020 to understand the effect of the COVID-19 pandemic on VA inpatient data.
Technical Report 36: Indirect Costs of VA Cardio-Pulmonary Rehabilitation ProgramsHealth Economics Resource Center, #36, August 2019 | View »
In this technical report, we describe how we estimated the indirect costs of Cardio-Pulmonary Rehabilitation programs of the U.S. Department of Veterans Affairs (VA) from the national extracts of the VA Managerial Cost Accounting Office (MCA). We used data for federal fiscal year (FY18).
Technical Report 35: Procedure Codes in VHA: Use of Inpatient ICD Procedure vs Outpatient CPT CodesHealth Economics Resource Center, #35, July 2018 | View »
When coding outpatient procedures, the VHA uses only CPT codes. Inpatient care is primarily coded using International Classification of Diseases (ICD) procedure codes, but some inpatient procedures are captured using Current Procedural Terminology (CPT) codes. The VHA is not unique in its coding practices. CPT codes are used throughout the U.S. for coding in outpatient settings and for professional services provided in inpatient settings. The VHA adopted the national coding rules around 2000 for outpatient coding; national standards for coding inpatient care were implemented earlier.
Technical Report 34: Updating the HERC Average Cost Method: Updated Coefficients from 2015 Medicare DataHealth Economics Resource Center, #34, July 2018 | View »
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. In 2018, we updated the statistical model using Medicare data from 2015. This technical report describes the updated model.
Technical Report 33: Comparing the Measurement of Chronic Conditions in ICD-9-CM and ICD-10-CM in VA Patients, FY2014-FY2016Health Economics Resource Center, #33, December 2016 | View »
We developed ICD-9-CM and ICD-10-CM definitions for 34 different chronic conditions, and we compared the prevalence rates of these chronic conditions from federal fiscal year (FY) 2014 to FY2016 in a large sample of VA patients in order to measure the changes before and after transition to ICD-10-CM.
Technical Report 32: Costing Methods Used in VA Research, 1980-2012Health Economics Resource Center, #32, October 2016 | View »
The Health Economics Resource Center (HERC) of the U.S. Department of Veterans Affairs (VA) reviewed peer-reviewed publications to determine the methods and data sources used in studies of VA health care costs between 1980 and 2012. The review identified the number of published papers that used four principal methods of costing available to VA researchers and examined how practices differed in the last five years of the research that was reviewed. The review generated a bibliography of publications that used each of the four methods. The goal of this review was to identify priorities for HERC strategic planning.
Technical Report 31: Updating the Psychiatric Case Mix System (PsyCMS) Mental Health and Substance Use Grouper for ICD-10-CMHealth Economics Resource Center, #31, August 2016 | View »
PsyCMS was designed using the International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) codes from all Veterans who used VA healthcare services during the federal fiscal year 1999 (FY99). On October 1, 2015, all United States healthcare systems were required to begin using the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM). This report describes the methods HERC used to update PsyCMS with ICD-10-CM codes.
Risk Adjustment: Guide to the V21 and Nosos Risk Score ProgramsHealth Economics Resource Center, #30, January 2015 | View »
This document provides directions for creating the HCC V21 Risk Scores and Nosos scores from the MedSAS and CDW data.
Instrumental Variables with VA DataHealth Economics Resource Center, #29, April 2014 | Download »
Understanding causal relationships is critical for researchers. Although data from randomized controlled trials is preferred for understanding causal relationships, randomization is not always ethical or feasible, due to the high monetary and time costs. Unfortunately results from observational analyses are prone to bias, especially when the primary right-hand-side variable (i.e., the treatment) is correlated with other factors not included in the analysis; this is often referred to as endogeneity. Why is endogeneity a problem? Regression models assume that all right-hand-side variables are exogenous, hence the right-hand-side variables are often referred to as independent variables. When a variable is endogenous (correlated with unobserved variables), it violates an underlying assumption in the statistical model, resulting in a biased regression coefficient. Instrumental variables (IVs) is a statistical modeling technique to correct for endogeneity. This report describes the use of IVs in VA data. Section 2 provides background on IVs and how to use them, section 3 reviews common examples of IVs in VA data and their pitfalls, and the final section summarizes our discussion.
Using Health Factors Data for VA Health Services ResearchHealth 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 SurgeryHealth 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 FY2007Health 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 UpdateHealth 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 - SupplementHealth Economics Resource Center, #25, January 2010 | Intranet only
Dialysis Treatment Use and Costs Reported in VA Administrative Databases, FY2007Health 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: FY2004Health 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 DatabaseHealth 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.
Fee Basis Data: A Guide for ResearchersHealth 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.
Matching Prosthetics Order Records in the VA National Prosthetics Patient Database (NPPD) to Health Care Utilization DatabasesHealth 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 Comparison of Outpatient Costs from the FY 2001 HERC and DSS National Data Extract DatasetsHealth 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.
Spending for VA Specialized Mental Health CareHealth Economics Resource Center, #19, October 2006 | Download »
A Guide to Identifying Non-Veteran Records in the Inpatient and Outpatient DatabasesHealth 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.
Dialysis Treatment Use and Costs Reported in VA Administrative DatabasesHealth 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 FileHealth 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 guide to estimating wages of VHA employeesHealth 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.
Comparison Between DSS National Data Extracts and HERC Average Costs: Aggregate and Person-Level Costs, FY2001Health 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.
Evaluation of the VA Nursing Home Resident Assessment Instrument Minimum Data Set: Resource Utilization Group III in FY2001 and FY2002Health 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 DatasetsHealth 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-FY2002Health 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 RecordsHealth 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).
Cost of Positron Emission Tomography: Method for Determining Indirect CostHealth 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.
Indirect Costs of Specialized VA Mental Health TreatmentHealth 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.
Recommendations for a New Allocation System for 101 FundsHealth 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.
Reconciliation of DSS Encounter-Level National Data Extracts with the VA National Patient Care Database FY2001Health 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 VAHealth 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).
Determining the Cost of VA Care with the Average Cost Method for the 1993-1997 Fiscal YearsHealth 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.
Human subjects compliance programs: optimal operating costs in the VAHealth 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.