Alan Gittelsohn

Small Area Variations in Health Care Delivery: A population-based health information system can guide planning and regulatory decision-making

Health information about total populations is a prerequisite for sound decision-making and planning in the health care field. Experience with a population-based health data system in Vermont reveals that there are wide variations in resource input, utilization of services, and expenditures among neighboring communities. Results show prima facie inequalities in the input of resources that are associated with income transfer from areas of lower expenditure to areas of higher expenditure. Variations in utilization indicate that there is considerable uncertainty about the effectiveness of different levels of aggregate, as well as specific kinds of, health services. Informed choices in the public regulation of the health care sector require knowledge of the relation between medical care systems and the population groups being served, and they should take into account the effect of regulation on equality and effectiveness. When population-based data on small areas are available, decisions to expand hospitals, currently based on institutional pressures, can take into account a communitys regional ranking in regard to bed input and utilization rates. Proposals by hospitals for unit price increases and the regulation of the actuarial rate of insurance programs can be evaluated in terms of per capita expenditures and income transfer between geographically defined populations. The PSROs can evaluate the wide variations in level of services among residents of different communities. Coordinated exercise of the authority vested in these regulatory programs may lead to explicit strategies to deal directly with inequality and uncertainty concerning the effectiveness of health care delivery. Population-based health information systems, because they can provide information on the performance of health care systems and regulatory agencies, are an important step in the development of rational public policy for health.

Increased risk of cancer in the Peutz-Jeghers syndrome

The Peutz-Jeghers syndrome is an autosomal dominant hereditary disease characterized by hamartomatous polyps of the gastrointestinal tract and by mucocutaneous melanin deposits. The frequency of cancer in this syndrome has not been studied extensively. Therefore, we investigated 31 patients with the Peutz-Jeghers syndrome who were followed from 1973 to 1985. All cases of cancer were verified by histopathological review. Cancer developed in 15 of the 31 patients (48 percent)--gastrointestinal carcinomas in 4, nongastrointestinal carcinomas in 10, and multiple myeloma in 1. In addition, adenomatous polyps of the stomach and colon occurred in three other patients. The cancers were diagnosed when the patients were relatively young, but after the Peutz-Jeghers syndrome had been diagnosed (interval between diagnoses, 25 +/- 20 years; range, 1 to 64). According to relative-risk analysis, the observed development of cancer in the patients with the syndrome was 18 times greater than expected in the general population (P less than 0.0001). Our results suggest that patients with the Peutz-Jeghers syndrome have an increased risk for the development of cancer at gastrointestinal and nongastrointestinal sites.

On the risk of organ loss.

Abstract A method for projecting surgical incidence rates to organ loss rates is described. When applied to surgical incidence derived from the Vermont health data system, major variations in organ loss rates are noted between geographically distinct communities served principally by different groups of physicians. The pattern of variation and contrasting observations from other regions suggest that differences in the incidence of surgery are related to varying medical opinion concerning the efficacy of specific therapeutic approaches.

APPLICATIONS OF LIFE TABLE ANALYSIS AND AUTOMATIC COMPUTER SELECTION OF POPULATION SUBGROUPINGS FOR CARDIOVASCULAR EPIDEMIOLOGIC STUDIES

Epidemiologic studies are directed a t measurement of disease risk in defined population subgroups and identification of subgroups at high or low risk of developing the disease. In the first case, subgroups are selected on an a priori basis while in the second, they are identified by their disease experience. Operationally, one is approached by specification of given data configurations while the other is a matter of applying a posteriori statistical classification techniques. The present objective is to describe a method for measuring risk within subsets automatically selected by computer, the selection procedure being based on a coding and processing methodology which has general applicability to many types of epidemiologic studies. For the sake of concreteness data are presented from the findings of the Albany Cardiovascular Health Center project (CVHC) , I a long-term prospective study of degenerative cardiovascular disease in a cohort of 1849 disease-free male civil-service workers. Initially brought under observation in 1953-54, the subjects were classified by a battery of procedures. They have been reexamined a t regular intervals and followed for the development of manifestations of coronary heart disease. An observation for a given subject is, thus, a sequence of disease states and measured variables together with fixed attributes and multichotomies.