PubMed Health⌕ Search

Biomedical subjects

P Diehr

Publications and source records attributed to P Diehr.

At least 19 recordsLinked to original sources
PubMed1992

Assessing response bias in random-digit dialling surveys: the telephone-prefix method.

Knowledge of the characteristics of survey non-respondents is important to determine generalizability to the population of interest. In a recent random-digit dialling survey of health behaviours only 73 per cent of the households contacted provided any information about household composition, and only 74 per cent of those actually completed the extended interview, for an overall response rate of 54 per cent. To identify possible biases we grouped all attempted phone numbers by their prefix, and looked for the association between the response rate for that prefix and other summary variables known about the prefix. A simulation study showed that the method can identify non-response biases if certain assumptions are correct. The analysis suggested that our survey data under-represent older people and those with a college education. We found no significant biases in health behaviours, possibly because the basic assumptions did not hold. This method may assist in identification of non-response bias in other studies.

Adult↗
PubMed1992

Multi-level analysis in epidemiologic research on health behaviors and outcomes.

Individual-level health behaviors and outcomes have multi-level determinants (individual and environmental). Multi-level analysis seeks to explain individual outcomes in terms of both individual and environmental or aggregate variables. Ecologic fallacy (improper inference about individual-level associations based on associations measured only at the aggregate level) can result from confusion about the level of inference that is of ultimate interest. The perspective of multi-level analysis acknowledges the importance of both individual and environmental variables in determining health behaviors and outcomes at the level of the indivisible unit--the individual. The authors review concepts and methods of multi-level analysis and their application to epidemiologic research on health behavior and health outcomes.

Chronic Disease↗
PubMed1992

Can small-area analysis detect variation in surgery rates? The power of small-area variation analysis.

A variety of statistical methods can be used in small-area analysis to test whether there is more variation than would be expected by chance alone. However, the power of these methods to detect existing variation has never been studied. The authors used data regarding back surgery in Washington State to suggest several types of variation that might exist (alternative hypotheses), and then used computer simulation to determine the power, or the probability of detecting this variation. The chi-square test had the highest power of all methods considered against most alternative hypotheses. Power is higher if there are no multiple admissions, rates are higher, and counties have larger or similar population size. Problems of accounting for multiple admissions, adjustment for age and sex, choosing the optimum size of small areas, and detection of outliers also are discussed.

Age Factors↗
PubMed1992

Small area analysis of surgery for low-back pain.

Rates of spine surgery (discectomy, laminectomy, fusion) vary several-fold among "small areas" such as counties or hospital market areas. To ascertain why this is so, an analysis was conducted of variability in rates among counties in the State of Washington (N = 39). Since, unlike previous published reports, this study excluded patients with cancer, major trauma, and infection, as well as those with cervical and thoracic procedures, rates in this study pertain specifically to the problem of low-back pain. Six classes of variables to explain variability among county rates were defined: I) percentage of the labor force in heavy labor and transportation occupations; II) socioeconomic conditions; III) neurologic and orthopedic surgeon density; IV) occupancy rate of back surgery hospitals; V) primary payer and VI) health care availability. In all, the effect of 28 explanatory variables was tested. In doing so, the authors took into account the possibility of spurious correlation. The rate of surgery for low-back pain varied nearly 15-fold among counties. The explanatory variables that were tested, however, accounted for only a minor part of the variability. The hypothesis that "physician practice style factor" accounts for the major part is explored; potential properties of practice style factor are specified for further testing.

Back Pain↗
PubMed1992

Restricted activity days among older adults.

OBJECTIVES: The number of restricted activity days experienced by an individual in the course of a year is an important measure of functional well-being, particularly for older adults. We sought to determine multivariate associations between restricted activity days and various health conditions. METHODS: We used data from the 1984 Supplement on Aging of the National Health Interview Survey to estimate the relationship between restricted activity days and age, gender, and the presence or absence of selected chronic conditions and falls for all noninstitutionalized people aged 65 years and over. Chronic conditions and falls accounted for most of the variance in the model. RESULTS: Of an annual average of 31 restricted activity days, 6 days were associated with falls; 4 days with heart disease; 4 days with arthritis and rheumatism; 2 days each with high blood pressure, cerebrovascular disease, and visual impairment; and 1 day each with atherosclerosis, diabetes, major malignancies, and osteoporosis. CONCLUSIONS: These results can be used in estimating the potential impact of health promotion programs on the health status of noninstitutionalized older adults.

Accidental Falls↗
PubMed1992

Testing the null hypothesis in small area analysis.

The goal of small area analysis is often to demonstrate that hospital admission rates or procedure rates vary greatly among regions, suggesting the occurrence of unnecessary admissions or procedures in some regions. Recent articles have shown that such variation may be largely due to chance, even if no underlying differences exist among the small areas; thus, it is important to test if the observed variation is larger than expected by chance. In this article we discuss how the appropriate method for testing the null hypothesis depends on the distribution of the number of admissions at the person level. If it is not possible for an individual to have more than one admission for a given procedure, the appropriate test is a simple chi-square test. If multiple admissions are possible, a modified chi-square test can be used to account for the excess variability due to multiple admissions. Failure to make the correct modification to the chi-square test in this latter case can result in spurious results. This underscores the importance of collecting data on multiple admissions in order to estimate the distribution of the number of admissions at the individual-patient level.

Analysis of Variance↗
PubMed1991

Sampling elderly in the community: a comparison of commercial telemarketing lists and random digit dialing techniques for assessing health behaviors and health status.

A study of health behaviors in four communities in the western United States in 1988 provided the opportunity to compare two methods of sampling elderly respondents for a telephone interview. The Polk telemarketing lists were used to identify 1,407 respondents aged 65 years and older in four communities, where 253 respondents in the same age group were also identified by the method of random digit dialing. Individuals identified from the Polk lists received a letter prior to the initial telephone contact. The overall response rate was 49.3% for random digit dialing and 57.3% for the Polk lists. On the average, the identification of one elderly respondent using the Polk lists required about 20-25% as much interviewer time per subject identified as was required by the random digit dialing method. The elderly identified by the Polk lists were significantly older than those identified by random digit dialing, and the proportions of the Polk sample who were married, white, or had an income of greater than $10,000 were slightly higher than those of the random digit dialing sample. Among 40 variables measuring various health behaviors, indicators of health status, and participation in health-related programs and classes, only three differed significantly between the two samples. The authors conclude that sampling from commercial telemarketing lists was an efficient method of identifying elderly respondents and that in these four communities, the estimates of health behaviors and health status were comparable with those obtained by random digit dialing techniques.

Aged↗
PubMed1991

Community-level comparisons between the grocery store environment and individual dietary practices.

BACKGROUND: This article examines the relationship at the community level between individual dietary practice and the grocery store environment. METHODS: Individual dietary practice was measured in 12 communities using a telephone survey to obtain self-reported diet. A protocol was developed to measure two aspects of the grocery store environment in these same 12 communities: the relative availability of healthful (low-fat and high-fiber) products, and the amount of health-education information provided. Comparisons were made between individual and store-level measures at two levels of geographic aggregation: community (typically a county) and zip code within community (n = 34). RESULTS: We found positive and statistically significant correlations at both the community and the zip code level between the availability of healthful products in stores and the reported healthfulness of individual diets. Positive correlations were also found between measures of the amount of health-education material provided by stores and the healthfulness of individual diets, but these correlations did not reach statistical significance. CONCLUSIONS: The results provide support for including measures of the grocery store environment as part of a community-level assessment of dietary behavior.

Adult↗
PubMed1991

Reproducibility and responsiveness of health status measures. Statistics and strategies for evaluation.

Before being introduced to wide use, health status instruments should be evaluated for reliability and validity. Increasingly, they are also tested for responsiveness to important clinical changes. Although standards exist for assessing these properties, confusion and inconsistency arise because multiple statistics are used for the same property; controversy exists over how to measure responsiveness; many statistics are unavailable on common software programs; strategies for measuring these properties vary; and it is often unclear how to define a clinically important change in patient status. Using data from a clinical trial of therapy for back pain, we demonstrate the calculation of several statistics for measuring reproducibility and responsiveness, and demonstrate relationships among them. Simple computational guides for several statistics are provided. We conclude that reproducibility should generally be quantified with the intraclass correlation coefficient rather than the more common Pearson r. Assessing reproducibility by retest at one-to-two week intervals (rather than a shorter interval) may result in more realistic estimates of the variability to be observed among control subjects in a longitudinal study. Instrument responsiveness should be quantified using indicators of effect size, a modified effect size statistic proposed by Guyatt, or the use of receiver operating characteristic (ROC) curves to describe how well various score changes can distinguish improved from unimproved patients.

Analysis of Variance↗
PubMed1991

Participation of higher users in a randomized trial of Medicare reimbursement for preventive services.

In a study of older enrollees in an HMO, we found that seniors who are higher users of health care services are willing to participate in health promotion programs. Although people aged 85 or older and those with chronic diseases are slightly more reluctant to participate, they are willing to make additional visits for health promotion purposes. Close proximity to the clinic and support from their family physician are important correlates of participation.

Age Factors↗
PubMed1991

Estimating county percentages of people without health insurance.

County data on the percentage of people without health insurance are seldom available, although state program planning requires such information. As part of an evaluation of Washington's Basic Health Plan (BHP), we conducted a telephone survey in nine Washington counties to estimate the percentage of people under the age of 65 who were uninsured. We used regression analysis to estimate the percentage uninsured in a county as a function of the percentage unemployed. Two validation approaches yielded very good results, suggesting that the equation could be used to estimate the percentage uninsured in unsurveyed counties. The variation ranged from 15% to 23% uninsured in the 9 surveyed counties, and was estimated to range from 9% to 35% among the state's 39 counties. With proper caution, estimates based on this equation can probably be used in other states if better data are unavailable.

Data Collection↗
PubMed1990

Use of a preferred provider plan by employees of the City of Seattle.

Little is known about the use of services in a preferred provider organization (PPO). We studied a preferred provider arrangement between Pacific Medical Center and employees of the City of Seattle. In the second 12 months of this program 8,529 subjects submitted at least one claim; of these, only 420 (4.9%) ever used the preferred provider. Those who used the PPO at least once differed significantly from those who never used it on age, sex, employee/dependent status, and utilization in the previous year. Outpatient and total charges were higher for PPO users than for nonusers before and after control for those characteristics. Those who used the PPO exclusively were similar to those who never used it. People who used both the PPO and other providers were at higher risk for use of services, and had much higher overall utilization, with or without control for other variables. No differences were found between people who obtained only a small proportion of their services at the PPO and those who had most (but not all) of their use at the PPO. Many of these findings can be explained by a self-selection model. It is important for research on PPOs to have an independent manner of assessing who is a PPO user.

Adolescent↗
PubMed1990

A small area simulation approach to determining excess variation in dental procedure rates.

All small area analyses need to compare the observed variability in rates to that expected by chance alone, but the expected variability is usually not known. This paper uses patient-level data for five dental procedures to simulate the distributions of the summary statistics that are usually generated in such studies. These statistics are found to vary greatly even under the "null hypothesis" that all dentists are using procedures at the same rates. The simulated dentist rates are compared to observed rates obtained in a different study. These findings illustrate problems that can occur in small area analysis studies, and emphasize the importance of using statistical techniques that are appropriate for the data that are to be analyzed. Investigators should make every effort to obtain patient-level data, or at least to understand the underlying distribution of the number of procedures per patient, to avoid mistaking significant deviations from an incorrect model as evidence for significant variation among small areas.

Analysis of Variance↗
PubMed1990

Evaluating community-based nutrition programs: assessing the reliability of a survey of grocery store product displays.

A pilot test of a survey of grocery store product displays was conducted to measure the amount of health-education information provided and the proportion of the display devoted to "healthier" products. Inter-rater reliability ranged between 0.73 and 0.78 for the healthiness indices and between 0.30 and 0.67 for the health education measures. Test-retest reliability ranged from 0.44 to 1.0.

Food Labeling↗
PubMed1990

Early detection and control of cancer in clinical practice.

As part of the Community Cancer Care Evaluation, a random-sample survey of practicing physicians in 12 geographic areas was conducted in 1985 to provide information about physician practice patterns with reference to cancer detection, control, and treatment. All respondents were asked whether they routinely performed comprehensive physical examinations, breast palpations, mammography, rectal examinations, chest roentgenography, and stool guaiac examinations on normal healthy patients older than 50 years. Responses were examined in terms of American Cancer Society and National Cancer Institute (Bethesda, Md) recommendations. Conformity with recommendations was dependent on the geographic area, the specific procedure, and the specialty of the physician. Across all procedures, frequency of performance varied with years since graduation from medical school, with more recent graduates more likely to conform to recommended standards.

Adult↗
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↗