Biomedical subjects
Publications and source records attributed to W A Reinke.
Managed care creates a corporate environment in which competitiveness demands close attention to quality. Although the health care sector may benefit from solutions derived in other industries, it attaches unique importance to noneconomic, intangible factors. Adequate cost-utility analysis must take such factors into account instead of relying on artificial numerical values.
In carrying out surveys to estimate disease prevalence or health services coverage in a region, investigators are often interested in identifying communities or other subareas in which the problem of interest is especially severe. In view of the large number of subareas to be examined, the investigator seeks rapid methods of assessment that require minimum sampling in each. Lot quality assurance sampling, developed more than 60 years ago to meet industrial quality control needs, has been found to serve public health purposes as well. Curiously, other more recent and more powerful industrial techniques have not received the recognition they deserve. Several of them are discussed in this paper and likely applications are cited. They fall into two categories: 1) lot acceptance methods to depict static conditions in a population and 2) more dynamic process monitoring methods for continuous surveillance. Under the first category, techniques of double sampling and sequential sampling are described. Reduced and tightened scrutiny, control charts, and exponential smoothing are highlighted as especially promising approaches under the process control category.
The analysis reported here was the latest in a series of efforts to clarify the relative importance of the health system and of socioeconomic factors to a nation's general level of health. The study has also quantified national and regional deviations from the general pattern as a basis for selective investigation of the effects of planned interventions.The analysis was unusually comprehensive in that it included 131 WHO Member States. As in a number of other studies, socioeconomic factors were found to account for much of the national variation in life expectancy. Inclusion of health resource variables added a special lagged effect which ultimately accounted for 90% of life expectancy variation. Evidence was also obtained that socioeconomic factors may operate partially through the development of health resources. It appears, therefore, that though socioeconomic factors are necessarily linked to health improvement, they are not sufficient in the absence of corresponding development of a viable health services infrastructure.Residual deviations from the general pattern varied systematically by WHO region in 30% of the cases. Most notably, in the African Region the number of physicians is well below even the modest level expected on the basis of the socioeconomic situation in the region. There is, however, considerable variation within individual countries, and it was not possible to find any significant relationship between the WHO manpower development programme and the national health resource parameters. It is therefore concluded that statistical analysis is of limited applicability in this field.
Consideration of unmet need as well as effective demand for health services is desirable for planning but frequently ignored. This paper reports an analysis of the findings from a national health survey conducted in Chile to obtain information on both met and unmet demand. The joint analysis proved feasible and highly informative. Total felt need tended to be relatively constant among population groups in comparison with differences in actual services utilization. Moreover, exceptions to this general finding revealed patterns that should improve our insights for health planning.
Many more or less attractive techniques have been proposed for statistical analyses involving multiple sources of variation, for example in examing the possible contributors to differential patterns of health services utilization and expenditure. A large scale investigation of such patterns among 10,000 household in Chile provided a useful basis for comparison of alternative analytical approaches. The multiple regression, Automatic Interaction Detection, and Multisort techniques were applied to the survey data deparately and in combination and results were compared. The Multisort technique was found to be the single most useful and convenient approach, but the most meaningful results were obtained from the systematic application of the three approaches combined.
Projection of the probable demand for health services over time is one of the most important-and difficult-aspects of the health planning process. Not only must the planner contend with many variables external to the health sector, but also with the difficult to predict correlations between the supply of health, services and the resultant demand. This article briefly reviews some of the principal demand projection methods in use and then describes in detail the one adopted in the Chilean health manpower study. The demand portion of the study in Chile involved three main elements: 1) a sample survey which measured the met and unmet demand for medical, dental, and hospital services as a function of six population variables (age, sex, location, income, educational level, and medical insurance status); 2) a baseline demand projection which takes into account the probable effects of changes in these six variables over ten and 20 years on the utilization of services; and 3) an alternative projection which postulates the fulfillment of certain targets for the improvement of health care. The approach offers the planner a number of important analytical and programmatic advantages compared with other methods now available and are discussed along with their limitations.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.
Explore the source record for details and available documents.