Biomedical subjects

E Volinn

Publications and source records attributed to E Volinn.

20 records · Page 2Linked to original sources

PubMed1991

Theories of back pain and health care utilization.

Because most people in the United States have occasional back pain, demand for the treatment of back pain is widespread. Yet, few treatments have proven to be more effective than placebo therapy. We examine patterns of treatment that have emerged in the absence of definitive treatment. We concentrate on high-cost users of back pain treatment (i.e., chronic pain patients) and high-cost treatments (i.e., surgical and non-surgical hospitalization for low back pain). The small minority of back pain patients whose disability persists into chronicity (90 days or more) accounts for a disproportionate amount of all back pain costs. Interventions have been developed to prevent back pain but, once back pain has already occurred, little is done to prevent it from becoming chronic. Drug therapy may be used to treat the symptom of chronic pain, the cause of which may not be thereby affected. Regarding high-cost treatments, surgical and nonsurgical hospitalizations for low back pain are common practices in the United States. Pain specialists for the past 15 years have advocated a conservative approach to back pain, but the rate of surgery for low back pain increased during this time. Average lengths of stay for surgical and nonsurgical low back pain hospitalizations decreased. We explore why, in the instance of low back pain surgery, change was resisted, whereas, in the instance of average lengths of stay, change was accepted. In view of why change may be resisted or accepted, we discuss interventions designed to change physicians' practice style.

Back Pain↗

PubMed1990

What is too much variation? The null hypothesis in small-area analysis.

A small-area analysis (SAA) in health services research often calculates surgery rates for several small areas, compares the largest rate to the smallest, notes that the difference is large, and attempts to explain this discrepancy as a function of service availability, physician practice styles, or other factors. SAAs are often difficult to interpret because there is little theoretical basis for determining how much variation would be expected under the null hypothesis that all of the small areas have similar underlying surgery rates and that the observed variation is due to chance. We developed a computer program to simulate the distribution of several commonly used descriptive statistics under the null hypothesis, and used it to examine the variability in rates among the counties of the state of Washington. The expected variability when the null hypothesis is true is surprisingly large, and becomes worse for procedures with low incidence, for smaller populations, when there is variability among the populations of the counties, and when readmissions are possible. The characteristics of four descriptive statistics were studied and compared. None was uniformly good, but the chi-square statistic had better performance than the others. When we reanalyzed five journal articles that presented sufficient data, the results were usually statistically significant. Since SAA research today is tending to deal with low-incidence events, smaller populations, and measures where readmissions are possible, more research is needed on the distribution of small-area statistics under the null hypothesis. New standards are proposed for the presentation of SAA results.

Age Factors↗