HERC: Non-VA
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Non-VA

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Looking for VA Community Care Data?

Overview

When Veterans use non-VA health services, much of this data can be obtained from existing databases, namely Medicare and Medicaid. More details on these datasets are below.

There are other databases, but those that are publicly available do not include patient identifiers. A good example is HCUPnet, which provides statistics from the Healthcare Cost and Utilization Project.  Among other non-VA files available to researchers are Medicare Cost Reports, American Hospital Association Survey, ZIP Code Files, and state hospital discharge reports.  If you are only interested in obtaining charges for a certain inpatient procedure or diagnosis, a good resource is the Healthcare Utilization and Cost Project (HCUP) webpage. HCUP is one of the databases developed by the Agency for Healthcare Quality and Research. They have an interactive web page that allows one to enter criteria and see average facility charges; note that HCUP does not include physician payments.  HCUP reports cost-adjusted charges; see Adjusting Charges from Private Hospital Data.

Researchers sometimes purchase claims data through companies, such as Optum and Truven (now IBM).  Those data are not available in VA.


Medicaid/Medicare Data

The Centers for Medicare & Medicaid Services (CMS) is responsible for administering Medicare. It also works with states to administer Medicaid (in California, Medicaid is referred to as Medi-Cal).

If you are a VA researcher interested in obtaining Medicare data for Veterans, please contact VIREC.

As the administering agency, CMS makes some utilization datasets available for researchers. These datasets are not specific to Veterans and they come in two flavors: Public Use Files (PUFs) and Beneficiary Encrypted Files (BEFs). As it suggests, the PUFs are at an aggregated level and have no information that can be used to link files to patients. On the other hand, BEFs provide encounter level data, but the social security number is scrambled. If you need to identify the Medicare beneficiaries, then the researcher must obtain special permission to access the research identifiable files (RIFs). Obtaining a RIF is very complicated and Health Care Finance Association (HCFA) will only release RIFs to certain researchers for specific projects; obtaining RIFs and BEFs is more complicated than getting a PUF.

The PUFs are free (see the CMS web site); RIFs and BEFs cost money and require human subjects approval to use the data.

There are many inpatient and outpatient files available for Medicare and Medicaid. For more information, contact the Research Data Assistance Center (ResDAC). They have a CMS contract to provide technical assistance. They can answer questions about access to data. They also provide limited technical assistance to help researchers identify questions that can be answered with the data.


Adjusting Charges from Private Hospital Data

Often we want to analyze charge data from utilization databases, like the Healthcare Cost and Utilization Project (HCUP). Yet, it is generally known that in health and medicine, charges rarely equal costs. In most cases, charges are greater than costs. However, the degree to which charges exceed costs is not easily determined. Hospitals and medical centers are somewhat idiosyncratic in how they generate bills.

Hence, we want to adjust the charges for two reasons:

  • to deflate charges so that they more closely reflect costs, and
  • to remove hospital-specific idiosyncracies.

The cost to charge ratio (CCR) is one way of making this adjustment. You can compute the CCR manually using the Medicare cost reports. Luckily, there is an easier way. CMS releases an Impact file each year. The Impact file is a hospital-level dataset that provides a lot of information, including the CCR.

Different departments or units within a hospital will often have different cost to charge ratios. We strongly recommend against using department-specific CCRs; these department-specific CCRs are subject to considerable interpretation and error within a hospital.


Estimating Medicare Payments for an Inpatient Short-Stay Acute Hospitalization

The cost of providing medical/surgical care in a hospital includes both a facility and a physician component. Medicare pays or reimburses hospitals based on the Diagnosis Related Group (DRG) and hospital-specific adjustments to this amount. With the DRG and the hospital Medicare identifier number, you can determine what Medicare would have paid for a given hospital stay.

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For an inpatient stay, Medicare calculates (1) hospital operating costs and (2) capital costs. For both (1) and (2), Medicare payments start with a standardized amount; hospitals in urban areas with more than 1 million persons face one set of standardized payment amounts, while all other hospitals face another set of standardized payment amounts.

The standardized amount is first adjusted to account for labor costs using the wage index. The standardized amount is then adjusted by the diagnostic related group (DRG) weight to reflect the patient’s case mix. In addition to the adjusted base amount, hospitals receive additional payments to reflect their share of low-income patients (known as disproportionate share) and their indirect medical education.

In addition to receiving Medicare reimbursement for hospital operating costs and capital costs, hospitals can request outlier payments and additional reimbursement based on their direct medical education. The outlier payment is for those patients who are much sicker and who stay much longer than average, and the Centers for Medicare and Medicaid Services have a description of outlier payments on their web site.

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With some simplifying assumptions regarding the wage index, disproportionate share and indirect medical education, a researcher can calculate a “national average” reimbursement for a particular DRG. In fact, this would result in two averages: one for large urban hospitals and one for all other hospitals. These averages would not include any outlier payments and they would not reflect direct medical education. Approximately 28% of all US hospitals in FY04 were teaching hospitals. For teaching hospitals, DME can represent an additional 10-20%.

Researchers should also recall that these estimated Medicare payment are for the facility and exclude professional fees (i.e., the physician’s reimbursement).

The Centers for Medicare & Medicaid Services (CMS) distribute a PC program called the Prospective Payment System (PPS) PC PRICER. If you enter the hospital identifier (PPS number), the DRG, the admission and discharge date, and the billed amount (charges), and whether the stay involved a transfer, the program tells you the Medicare reimbursement. The program calculates teaching payments, disproportionate share payments, geographic adjustments, and capital payments for that hospital. Since these change each year, there is a different version of the program for each year.

Unless the stay is unusually long (an outlier), the billed amount does not affect the reimbursement. Thus, it is possible to estimate a reimbursement without knowing the charges. Also, the length of stay does not usually affect reimbursement, so it is not critical to know the admission or discharge dates either. It is important to indicate if the stay involved a transfer to or from the hospital.

The program requires the hospital identification number. This six-digit identifiers consists of two digits for the state and four digits for the hospital. View the "Impact File" for one source of provider identifiers.

The Pricer software yields the cost of the hospital stay from Medicare's perspective. It may not be the “economic cost,” for example, if the stay is more expensive than expected for that DRG, Medicare pays the flat (DRG based) payment, and the hospital loses money on the stay.


Self-Report

Information on non-VA services use may be obtained directly from the participant. Below are some points to keep in mind.

Categories of care

Self-report questions should focus on categories of care for which costs are different and for which patients cognitively keep them separate. For example, it is common to ask about nights of inpatient care and then number of outpatient visits. However, it is probably not a good idea to ask about nights of intensive care unit (ICU) hospitalizations. Patients may recall being in an ICU, but are unlikely to be able to separate these categories accurately.

Validation

If the analyst uses the VA utilization databases and uses self-report for non-VA care, it is highly recommended that one set of questions specifically pertain to VA care and a second set of questions pertain to non-VA care. This permits validating the accuracy of self-reporting using patient responses for VA care for the study sample.

Cost

In almost every case, patients are not reliable sources of cost information because they rarely see the bill(s); bills can be confusing to say the least and recall of these data is not accurate. Therefore, the analyst must multiply the self-report data on units with estimated unit costs.

Researchers at the Health Economics Resource Center (HERC) have been involved in a number of clinical trials where there is an interest in understanding how the intervention affects veterans' use of care, including veterans' use of non-VA care. HERC researchers have developed a standard set of questions on self-reported non-VA utilization. These questions are often tailored or augmented for a particular study.

It is important to keep in mind that self-report involves cognitively complex questions. The patient is being asked to go back in time to remember events. The accuracy of the recall can be confounded if the events occurred a long time ago or if the patient used a lot of care. There is also inherent tension between asking precise questions and making the questions more cognitively complex to the point where the respondent is confused and the data are less accurate. For example, a visit to the emergency department (ED) where the patient stayed in the hospital overnight is unambiguously an ED visit but it is unclear whether it was also an inpatient stay. Adding qualifiers, such as "admitted to the hospital," may add precision at the risk of reducing accuracy.

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Last updated:  April 3, 2020