Resource utilization in home health care: results of a prospective study.

Resource utilization in home health care has become an issue of concern due to rising costs and recent initiatives to develop prospective payment systems for home health care. A number of issues remain unresolved for the development of prospective reimbursement in this sector, including the types of variables to be included as payment variables and appropriate measures of resource use. This study supplements previous work on home health case-mix by analyzing the factors affecting one aspect of resource use for skilled nursing visits--visit length--and explores the usefulness of several specially collected variables which are not routinely available in administrative records. A data collection instrument was developed with a focus group of skilled nurses, identifying a range of variables hypothesized to affect visit length. Five categories of variables were studied using multiple regression analysis: provider-related; patient's socio-economic status; patient's clinical status; patient's support services; and visit-specific. The final regression model identifies 9 variables which significantly affect visit time. Five of the 9 are visit-specific variables, a significant finding since these are not routinely collected. Case-mix systems which include visit time as a measure of resource use will need to investigate visit-specific variables, as this study indicates they could have the largest influence on visit time. Two other types of resources used in home health care, supplies and security drivers, were also investigated in less detail.

Radiology work-load measurements reflecting variables specific to hospital, patient, and examination: results of a collaborative study.

The authors coordinated the efforts of 44 hospitals in the United States to develop average times required for technologists to perform each of 19 radiologic examinations. When applicable, the overall average times were compared with extant Canadian work-load statistics. In six of the 14 examinations for which Canadian standards exist, the average times differed by 25% or more. The data were further analyzed to adjust time estimates for the effects of different hospital characteristics (e.g., number of beds, teaching status), patient characteristics (e.g., ambulation, outpatient status), and examination characteristics (e.g., number of views, resident involvement). The key factors and the magnitude of their effects varied from examination to examination, but the effects were generally large enough to have managerial significance. The factors can be evaluated by individual hospitals to produce customized estimates of average examination times. The data presented in this report can be used in management control systems by radiology departments in hospitals of varying sizes and teaching characteristics.

A cost analysis and management reporting system in occupational therapy.

Productivity management through cost analysis is fundamental in today's health care. A description of a cost analysis and management reporting system based on relative value units is presented in this article along with a practical method of identifying variable, fixed, and total costs for occupational therapy. Occupational therapy management participation in the cost analysis process is also discussed.

The chemistry laboratory. Development of average, fixed, and variable costs for incorporation into a management control system.

In order to estimate real cost savings achievable from reductions in laboratory test volume and in order to provide a management tool to help achieve such savings, we developed a management system for our chemistry laboratory. The system estimates the fixed costs (i.e., equipment, direct overhead, and indirect overhead costs), the variable costs (i.e., labor and supplies), and the total costs for each of the 81 tests performed in our hospital's chemistry laboratory. A monthly management report compares predicted changes in total variable costs (based on test volume) to actual variable cost changes. One useful insight from the system is that substantial savings may be realized from reducing low-volume, high-variable cost tests that are not normally the target of test-reducing strategies. The savings per test not ordered was estimated to be $5.24 for the low-volume, high-variable cost tests but only $0.45 for the high-volume, low-variable cost tests, nearly a 12-fold difference. A 10% volume reduction of the former (a reduction of only 6,400 tests annually) would achieve 63% of the savings from a 10% volume reduction of the latter (a reduction of 120,000 tests annually). An effective management reporting system, which tracks actual cost savings, is probably necessary to achieve these savings.