Analizing & Influencing
The Veterans Health Administration is an organization within the Department of Veterans Affairs (VA) that provides health care services to veterans. In 1997, the Veterans Health Administration established the Veterans' Equitable Allocation of Resources (VERA) System to improve the distribution of congressionally appropriated medical resources among the 21 Veterans Integrated Service Regional Networks (VISNs) that comprise the Veterans Health System.
However, in 2000, the Veterans Health Administration commissioned the RAND Corporation to conduct a study to determine whether VERA resources were underallocated in certain regions of the country and to certain veterans with special health care needs. Initially planned for only six months, the study evolved into a three-year, multi-phase project that provided the VA with the tools it needed to adjust its resource allocation in response to changing needs and policy considerations.
What is VERA actually?
The mission of the Department of Veterans Affairs is “to serve America's veterans …. and to be their primary advocate to ensure they receive health care.” All veterans who have been honorably discharged from active military service are entitled to VA benefits. Of the approximately 26 million veterans, nearly 7 million were covered by the Veterans Health Care System in 2002, and more than 4 million used the system's services that same year.
Dollars follow veterans
The VERA system was designed with several goals in mind: to distribute resources equitably among regional networks, to prioritize funding for veterans-those whose disability or illness was service-connected and those with special health care needs (such as blind veterans), and to make the distribution system simple and predictable.
Under VERA, the allocation of funds to each regional network is based on where veterans receive care. In other words, the following year's resources will be allocated based on the number of veterans served in that region in previous years. Resources are also adjusted for geographic differences in labor costs.
VERA also allocates resources based on the health status of patients in each region (their health status or “case mix”), because the sickest patients are the most expensive to treat. When RAND researchers began the assessment, VERA divided patients into three disease categories, with regional allocation based on the number of patients in each category. In 2002, these categories (and their per-patient allocations) were: primary care ($3,121), primary care ($197), and complex care ($41,667).
Primary care patients, representing about 95% of patients receiving IL health care services, were patients with relatively routine health care needs. Routine patients were those who had been hospitalized within the previous three years or who had undergone a comprehensive health examination at a VA facility; nonroutine patients, on the other hand, were occasional users of the VA system. Patients with complex care needs were those who required significant healthcare resources to manage long-term chronic or debilitating illnesses.
As originally designed, the VERA system has several important features.
First, the annual VA budget is a fixed amount. Thus, if the funds allocated to one region increase, each region's share, or at least some other regions' shares, will inevitably decrease. In this zero-sum system, the consequences of reallocating resources are much more severe than if an increase in the budget allocated to one or two regions did not affect the others.
It also creates incentives to minimize the cost of treating patients. Since the resources allocated to a region for a patient's treatment depend solely on the patient's disease category, there was a small chance that some regions would provide less optimal care to save resources for patients. In addition, because patient classification under VERA could be influenced by the patient's use of services (e.g., longer hospital stays), VERA-as originally designed-provided an incentive to game the system, i.e., to let a patient stay in the hospital longer than necessary or to use other means to classify a patient into a complex care category in order to maximize resources for that patient.
The objectives of the VERA study are defined in the Congressional mandate
In 2000, Congress enacted legislation requiring VA to study how the VERA set-asides addressed or resolved various problems identified in the legislation. In particular, Congress wanted to know whether the regional allocation formula took into account regional differences in the following areas:
- maintaining older, sometimes historic facilities.
- strengthening institutions and their management structures
- urban, peri-urban and rural areas
a case mix of patients with above-average morbidity.
- acting as a teaching hospital, i.e., having links with medical schools (which tend to receive the sickest patients and may require higher staff-to-patient ratios)
- extreme weather conditions in some areas.
What do the VERA VA leadership think?
What did VA Administrators say about VERA?
To help Congress get answers over a six-month period, the researchers based their analysis on site visits to VA facilities across the country, interviews with VA health care administrators, and a review of past studies and legislation related to these issues. Overall, VERA appeared to do a more equitable job of allocating funds than previous systems.
VERA's resource allocation was better than that of previous systems because it matched the geographic distribution of veterans. In addition, VA officials noted that VERA is simpler than previous allocation systems and has a better incentive structure. However, some VA health officials have noted that several factors beyond their control affect the cost of care. These include the age of facilities, physical condition, and historical significance of buildings:
Some administrators reported having to use buildings that were hundreds of years old, lacked adequate insulation and ventilation, or had to maintain buildings that could not even be used. Other factors influencing costs include medical school affiliation and, not surprisingly, the health status of patients. Interestingly, climate and location (urban or rural) were not among the cost drivers.
What really influences patient costs?
Based on input from VA leadership, Congress and VA asked RAND to determine how many different factors affect patient care costs and to develop an equation or set of equations (“model”) that would allow VA to calculate the impact of VA health care policy changes on patient costs.
Using actual patient data from VA and the Centers for Medicaid and Medicare Services, as well as county databases, the researchers created two models to predict the impact of various factors on costs: a patient model and a facility model. The patient model only accounted for patient-related factors such as socioeconomic status, age, gender, health status, other care options (e.g., Medicare or Medicaid), and the VA facility used by the patient. The facility model was created to examine facility-specific factors that affect costs, such as urban and rural location, health center accessibility, and infrastructure characteristics.
These models allowed researchers to predict patient costs under different scenarios, sum costs for all patients in a facility or region, and compare total costs to actual costs to predict the impact of changes (later, researchers combined the patient and facility models into a simple model).
What has quantitative analysis shown? First, and perhaps most importantly, it demonstrated that it is possible to create an equation that allows the VA to change regional allocations based on changes in a number of factors other than patients and facilities.
Second, the analysis showed that patient costs in a given region are affected by a number of patient-related factors, such as gender and average patient age: women tend to pay slightly more than men, and older patients have higher healthcare costs than younger patients, at least until age 85, when costs begin to decline. The researchers also found that a patient's length of stay, research costs, food costs, the number of beds in a facility, the size of the building, and differences in labor costs affect the regional cost of care.
Another important finding is that moving from the current classification of patient conditions into three categories to a more accurate measure of severity of illness-where patients are divided into more categories of illness-would result in a significant redistribution of resources among regions: regions with more sick patients would receive more resources, while regions with fewer sick patients would receive fewer resources. RAND recommended that VA modify its ad hoc adjustment system to better reflect the needs of different regions.
Another important factor affecting patient costs is reliance on Medicare: the higher the proportion of Medicare patients in a region, the lower the cost of care for VA patients in that region. On this basis, RAND recommended that VA consider relying on Medicare in its allocation decisions.
What has VA done in response to RAND's advice?
In response to RAND's findings, VA decided to apply a more precise adjustment for patient health status using ten disease categories (see table). Should they have adopted an even more sophisticated adjustment system? RAND concluded that the complexity of moving to such a system would have more than offset the potential benefits.
Although we do not yet know whether the allocation changes were accepted by regional directors, VA managers accepted the shift to case-by-case adjustments as an improvement in the fairness of allocation processes and decisions. RAND's detailed modeling convincingly demonstrated that the more detailed allocation based on ten disease categories captured most of the variation in patient costs and that other factors were simply not important enough to be included in the calculations.
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David W. Newton is a board certified pharmacist and also has been a board member for boards of examiners for the National Association of Boards of Pharmacy since 1983. His areas of expertise are primarily pharmaceuticals as well as cannabinoids. You can read an article about his expertise in CBD on the National Library of Medicine.