P G Barnett1. 1. Health Services Research and Development Field Program, US Department of Veterans Affairs, Menlo Park, CA, USA. pbarnett@odd.stanford.edu
Abstract
BACKGROUND: Estimates of health care cost are needed to conduct cost-effectiveness research at the facilities operated by the US Department of Veterans Affairs. METHODS: The medical literature was searched for VA studies to characterize different cost methods and identify their advantages and disadvantages. RESULTS: Different methods are appropriate for different studies. Analysts who wish to capture the effect of an intervention on resources used in a health care encounter may wish to create a detailed pseudo-bill by combining VA utilization data with unit costs from the non-VA sector. If a cost function can be estimated from non-VA data, VA costs may be determined more economically from a reduced list of utilization items. If the analysis involves a new intervention or a program that is unique to VA, direct measurement of staff time and supplies may be needed. It is often sufficient to estimate the average cost of similar encounters, for example, the average of all hospital stays with the same diagnosis and same length of stay. Such estimates may be made by combining VA cost and utilization data bases and by applying judicious assumptions. CONCLUSIONS: Assumptions used to estimate costs need to be documented and tested. VA cost-effectiveness research could be facilitated by the creation of a universal cost data base; however, it will not supplant the detailed estimates that are needed to determine the effect of clinical interventions on cost.
BACKGROUND: Estimates of health care cost are needed to conduct cost-effectiveness research at the facilities operated by the US Department of Veterans Affairs. METHODS: The medical literature was searched for VA studies to characterize different cost methods and identify their advantages and disadvantages. RESULTS: Different methods are appropriate for different studies. Analysts who wish to capture the effect of an intervention on resources used in a health care encounter may wish to create a detailed pseudo-bill by combining VA utilization data with unit costs from the non-VA sector. If a cost function can be estimated from non-VA data, VA costs may be determined more economically from a reduced list of utilization items. If the analysis involves a new intervention or a program that is unique to VA, direct measurement of staff time and supplies may be needed. It is often sufficient to estimate the average cost of similar encounters, for example, the average of all hospital stays with the same diagnosis and same length of stay. Such estimates may be made by combining VA cost and utilization data bases and by applying judicious assumptions. CONCLUSIONS: Assumptions used to estimate costs need to be documented and tested. VA cost-effectiveness research could be facilitated by the creation of a universal cost data base; however, it will not supplant the detailed estimates that are needed to determine the effect of clinical interventions on cost.
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