Factors associated with home health care costs

Characteristics of Medicare-certified home health agencies in Texas and the contributions of selected agency characteristics on home health care costs were examined. Cost models were developed and estimated for both nursing and total visit costs using multiple regression procedures. The models included home health agency size, profit status, control, hospital-based affiliation, contract-cost ratio, service provision, competition, urban-rural input-price differences, and selected measures of patient case-mix. The study population comprised 314 home health agencies in Texas that had been certified at least one year on July, 1, 1986. Data for the analysis were obtained from Medicare Cost Reports for fiscal year ending between July 1, 1985 to June 30, 1986.^ Home health agency size, as measured by the logs of nursing and total visits, has a statistically significant negative linear relationship with nursing visit and total visit costs. Nursing and total visit costs decrease at a declining rate as size increases. The size-cost relationship is not altered when controlling for any other agency characteristic. The number of visits per patient per year, a measure of patient case-mix, is also negatively related to costs, suggesting that costs decline with care of chronic patients. Hospital-based affiliation and urban location are positively associated with costs. Together, the four characteristics explain 19 percent of the variance in nursing visit costs and 24 percent of the variance in total visit costs.^ Profit status and control, although correlated with other agency characteristics, exhibit no observable effect on costs. Although no relationship was found between costs and competition, contract cost ratio, or the provision on non-reimburseable services, no conclusions can be made due to problems with measurement of these variables. ^

HEALTH STATUS - HEALTH SERVICE RESOURCES - ECONOSOCIOCULTURAL DEVELOPMENT: IMPLICATIONS FOR HEALTH CARE POLICY IN AFRICA

Rational health services planning requires an examination of the effects of various factors on the health status of a population within a given set of socioeconomic circumstances. The commonly accepted explanations for improved health in the less developed countries (LDCs) are: Health Service Resources available to a population, Environmental and Life conditions, and the Econosociocultural Characteristics of the population.^ In the context of the low economic base from which many LDCs initiate development activities, a strong imperative exists for identifying in which of these major areas public health policy would be most effective in terms of improving health. A new conceptual model is proposed that would be used for future policy analyses to assess what changes in health status of populations in LDCs can be expected as direct functions of increased health service resources, and of improved environmental and econosociocultural conditions.^ While direct policy analysis is ill-advised at this time due to data inadequacy, the model is illustrated using data presently available for twenty-five relatively homogeneous Sub-Sahara African countries. Within the limitations of available data, study findings indicate that while econosociocultural conditions were the most important explanatory factors of the three major independent variables in 1970, health service resources became the most important in 1975. Study findings are inconclusive at this time with regards to the relative contributions of physicians and medical assistants in explaining variances in mortality in these countries.^ Because of the deficient nature of available data, study findings should be interpreted very cautiously. Tests of statistical significance of study findings were by-passed because of their situational technical inappropriateness. This study is significant in being the first of its kind and scope to focus on the Sub-Sahara African region of the World Health Organization, using the Wroclaw Taxonomic Method in conjunction with a stepwise regression technique. It is desirable, therefore, to examine the observed magnitude and directional consistency of all hypothesized relationships, even if evidence is inconclusive. ^

HEALTH CARE COST INCREASES IN METROPOLITAN AREAS

The research project is an extension of the economic theory to the health care field and health care research projects evaluating the influence of demand and supply variables upon medical care inflation. The research tests a model linking the demographic and socioeconomic characteristics of the population, its community case mix, and technology, the prices of goods and services other than medical care, the way its medical services are delivered and the health care resources available to its population to different utilization patterns which, consequently, lead to variations in health care prices among metropolitan areas. The research considers the relationship of changes in community characteristics and resources and medical care inflation.^ The rapidly increasing costs of medical care have been of great concern to the general public, medical profession, and political bodies. Research and analysis of the main factors responsible for the rate of increase of medical care prices is necessary in order to devise appropriate solutions to cope with the problem. An understanding of the community characteristics and resources-medical care costs relationships in the metropolitan areas potentially offers guidance in individual plan and national policy development.^ The research considers 145 factors measuring community milieu (demographic, social, educational, economic, illness level, prices of goods and services other than medical care, hospital supply, physicians resources and techological factors). Through bivariate correlation analysis, the number of variables was reduced to a set of 1 to 4 variables for each cost equation. Two approaches were identified to track inflation in the health care industry. One approach measures costs of production which accounts for price and volume increases. The other approach measures price increases. One general and four specific measures were developed to represent each of the major approaches. The general measure considers the increase on medical care prices as a whole and the specific measures deal with hospital costs and physician's fees. The relationships among changes in community characteristics and resources and health care inflation were analyzed using bivariate correlation and regression analysis methods. It has been concluded that changes in community characteristics and resources are predictive of hospital costs and physician's fees inflation, but are not predictive of increases in medical care prices. These findings provide guidance in the formulation of public policy which could alter the trend of medical care inflation and in the allocation of limited Federal funds.^