A method is presented to plan the required sample size when estimating regression-based reference limits

BACKGROUND AND OBJECTIVE: Reference limits are widely used in anthropometry, the behavioral sciences, medicine, and clinical chemistry. They describe the distribution of a quantitative variable in a healthy population, and are often a smooth function of age or another determinant. Thus, instead of estimating reference limits separately for several age groups, it is more economical and parsimonious to use regression methods to estimate reference limits as a function of age. Although the variability of regression-based reference limits has been addressed previously, the available methods to determine the sample sizes needed to estimate them are neither transparent nor user-friendly. METHODS: We propose a simple and intuitive formula using margins of error, to project the sample sizes required to achieve a given degree of precision, for different sampling strategies. RESULTS: We present two examples for the calculation of the sample size required to estimate a specific reference limit using various age distributions. CONCLUSION: We provide a simple formula to calculate the sample size needed to estimate a specific reference limit to a specified degree of precision. The structure of the formula can easily accommodate different age-sampling strategies.     

An efficient test for the analysis of dichotomized variables when the reliability is known

A difference in an outcome variable between the treatment groups in a trial does not necessarily mean that there is a difference in the number of patients who experience relevant improvement on that variable. When the relevant improvement corresponds with an outcome or change in outcome that exceeds a certain threshold, the outcome variable can be dichotomized. A responder is a patient whose outcome exceeds the threshold. Comparisons can be made between the number of responders in the two treatment groups using logistic regression, or some other method to evaluate binary outcomes. An important disadvantage of this approach is the loss of power. In general, it is more efficient to test the difference between the mean values.We developed a statistical test that compares response rates for a dichotomized variable. It requires that an estimate of the reliability of the outcome variable is available. Simulations showed that the test was valid and robust over a wide range of distributions and sample sizes. The power was greater than the power of a chi(2) test, which would enable substantial reduction in the sample size.     

Access to non-funded health services (the legal implications)

The challenge to a healthcare system committed to providir universal access is how best to allocate the resources available. Resource allocation in the delivery of healthcare gives rise to the fundamental issue as to whether there is a right to healthcare recognized in law.     

职业化是卫生管理队伍建设的必由之路

卫生管理队伍是最重要的卫生资源，职业化是卫生管理人员发挥关键作用的必备条件。卫生管理队伍职业化的基本要求有：思想革命化，要求具有较高的思想觉悟，献身敬业的精神和公正廉洁的品质；知识现代化，要求具有较高的文化水平和广博的科学知识；能力专业化，要求具有较强的卫生管理专业的管理工作能力；工作专职化，要求全身心地投入到卫生管理工作中去。卫生管理队伍职业化的主要措施有：发展卫生管理学历教育，卫生管理专业毕业生应是卫生管理人员的主要来源；发展卫生管理专业继续教育开展岗位培训，进行上岗、在岗和转岗培训。     

Methods for estimating the AIDS incubation time distribution when date of seroconversion is censored

In most cohort studies on HIV infection and AIDS, data on time from seroconversion to AIDS or death are doubly censored, both at the time origin and at the endpoint of interest. In epidemiological research, the most frequently adopted approach is to restrict the analysis to persons with narrow seroconversion intervals and to impute the midpoint of this interval as date of seroconversion. For many cohort studies, the consequence is that a substantial proportion of the data is not used. We consider four methods that are expected to be less biased when all cohort data are used: two imputation methods, conditional mean and multiple imputation, and two likelihood maximization methods. We derive the likelihood structure of the cohort data and clarify its dependence on study design. All methods are applied to data from the Amsterdam cohort study among injection drug users. In a simulation study the data generation process of this cohort study is imitated. The performance of midpoint, conditional mean and multiple imputation are compared. With midpoint imputation, both an analysis using the full data set, as well as one restricted to the cases with small seroconversion intervals, is performed. Conditional mean imputation comes out as the preferred method. It gives best results with respect to mean squared error. Moreover, when confidence intervals are computed through standard methods that ignore the uncertainty in the imputed date of seroconversion, coverage probabilities are almost correct.     

Public assessment of health services provided to the population of the Moscow region

The articles deals with the results of a sociological pool of 2262 citizens of the Moscow Region for the purpose of studying the public assessment of rendering the medial care to population. The instruments related with shaping the public opinion about health care are discussed.     

A spreadsheet-based method for estimating the skin disposition of volatile compounds: application to N,N-diethyl-m-toluamide (DEET)

The disposition of N,N-diethyl-3-methylbenzamide (DEET) applied to split-thickness human cadaver skin was measured in modified Franz cells maintained at 32 degrees C and fitted with a vapor trap. Ethanolic solutions of DEET (1% w/w) spiked with (14)C radiolabel were applied to skin at a dose of 10 microL per cell, corresponding to a DEET dose of 127 microg/cm(2). Room air was drawn over the skin at velocities ranging from 10-100 mL/min. Evaporation of radiolabel from the skin surface and absorption into the receptor solution were monitored for 24 hr post-dose. The percentage of radioactivity collected in the vapor trap after 24 hr increased with airflow, ranging from 16 +/- 4% at 10 mL/min to 59 +/- 7% at 70 mL/min. The percentage of radioactivity absorbed through the skin after 24 hours decreased with increasing airflow, ranging from 69 +/- 7% at 10 mL/min to 20 +/- 1% at 80 mL/min. Tissue retention after 24 hr was 6-14% of the radioactive dose with no clear correlation to airflow. This data as well as DEET absorption data from two previous in vitro studies in which dose and location (fume hood or bench top) was varied were analyzed in terms of a recently developed diffusion/evaporation model for skin implemented on an Excel spreadsheet. A priori model calculations based on independently estimated transport parameters (Model 1) were compared with calculations based on fitted parameters (Models 2 and 3). The analysis of the combined dataset (n = 272 observations) showed that the Model 1 estimates matched the cumulative disposition profiles to within a root mean square error of 12.4% of the applied dose (r(2) = 0.65), whereas the Model 2 and Model 3 fits matched to within 9.4% (r(2) = 0.80) and 6.5% (r(2) = 0.91), respectively. The Model 3 fits were obtained using a concentration-dependent diffusivity of DEET in the stratum corneum, the value of which increased 3.4-fold between low concentrations and saturation. This result was consistent with the mild skin penetration enhancement effect for DEET reported elsewhere. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resource: a word document containing tables and figures including more information on the spreadsheet skin absorption model.]     

Sales force can lead to dollars for OH (occupational health) services

As hospitals enter the 1990s, one of the challenges they will face is finding additional sources of revenue. Occupational Health (OH) programs offer an opportunity for increased dollars--but only for hospitals willing to use sales tactics common to corporate America. In the following article, the author tells how an institution can sell OH services.     

The case for developing publicly-accessible datasets for health services research in the Middle East and North Africa (MENA) region

Background  

The existence of publicly-accessible datasets comprised a significant opportunity for health services research to evolve into a science that supports health policy making and evaluation, proper inter- and intra-organizational decisions and optimal clinical interventions. This paper investigated the role of publicly-accessible datasets in the enhancement of health care systems in the developed world and highlighted the importance of their wide existence and use in the Middle East and North Africa (MENA) region.     

A sampling and analytical method for airborne m-phenylenediamine (MPDA) and 4,4'-methylenedianiline (MDA)

A method has been developed and validated for monitoring worker exposure to airborne m-phenylenediamine (MPDA) and 4,4'-methylenedianiline (MDA) in an epoxy resin manufacturing operation. Aerosol and vapor MPDA and MDA are collected on an acid-coated, glass-fiber filter to stabilize them as their amine salts. The amines are extracted from the filter with a mixture of acetonitrile in aqueous base and then treated with acetic anhydride to form the diacetamide derivatives. Studies were performed on the acetylation reaction to establish sample work-up conditions. The derivatives are analyzed by high performance liquid chromatography with UV detection. The method was tested for precision and accuracy using the National Institute for Occupational Safety and Health (NIOSH) criteria for a valid industrial hygiene method. The method may be used with confidence to measure from 0.90 to 755 micrograms of MPDA and/or 0.36 to 55 micrograms of MDA in a total air volume of 200 to 630 L, sampling at a rate of 1.5 to 2.0 L/min. Collected samples remain stable on filters for at least 1 week before analysis. The method will not suffer from interference from high relative humidity or other process volatiles, including diglycidyl ether of bisphenyl A and bis(2,3-epoxycyclopentyl) ether. Test atmospheres of the process materials were prepared in the laboratory for validation of the overall sampling and analytical method. This method can be applied to most aromatic amines and is recommended for monitoring both ambient and workplace air.     

The distillation method: A novel approach for analyzing randomized trials when exposure to the intervention is diluted

ObjectiveTo introduce a novel analytical approach for randomized controlled trials that are underpowered because of low participant enrollment or engagement.Data SourcesReanalysis of data for 805 patients randomized as part of a pilot complex care intervention in 2015–2016 in a large delivery system. In the pilot randomized trial, only 64.6% of patients assigned to the intervention group participated.Study DesignA case study and simulation. The “Distillation Method” capitalizes on the frequently observed correlation between the probability of subjects'' participation or engagement in the intervention and the magnitude of benefit they experience. The novel method involves three stages: first, it uses baseline covariates to generate predicted probabilities of participation. Next, these are used to produce nested subsamples of the randomized intervention and control groups that are more concentrated with subjects who were likely to participate/engage. Finally, for the outcomes of interest, standard statistical methods are used to re‐evaluate intervention effectiveness in these concentrated subsets.Data Extraction MethodsWe assembled secondary data on patients who were randomized to the pilot intervention for one year prior to randomization and two follow‐up years. Data included program enrollment status, membership data, demographics, utilization, costs, and clinical data.Principal FindingsUsing baseline covariates only, Generalized Boosted Regression Models predicting program enrollment performed well (AUC 0.884). We then distilled the full randomized sample to increasing levels of concentration and reanalyzed program outcomes. We found statistically significant differences in outpatient utilization and emergency department utilization (both follow‐up years), and in total costs (follow‐up year two only) at select levels of population concentration.ConclusionsBy offering an internally valid analytic framework, the Distillation Method can increase the power to detect effects by redefining the estimand to subpopulations with higher enrollment probabilities and stronger average treatment effects while maintaining the original randomization.     

A regression approach for estimating multiday adverse health effects of PM10 when daily PM10 data are unavailable

The authors propose a regression-based approach for obtaining multiday estimates of the adverse health effects of ambient particulate matter less than 10 microm in diameter (PM(10)) when daily PM(10) time-series data are unavailable. This situation is common in the United States, because most US cities take PM(10) measurements every 6 days. Current evidence suggests that adverse effects of PM(10) are not concentrated on a single day but rather are spread out over multiple days, so the unavailability of daily PM(10) data presents a problem for the estimation of these effects. The proposed model estimates weights that are used to construct a linear combination of single-lag PM(10) effect estimates obtained from the available PM(10) data. It is shown that this new approach provides estimates of the effect of PM(10) on mortality that have less bias and mean squared error than currently available methods. Application of this method to the US cities contained in the National Morbidity, Mortality, and Air Pollution Study database produces an estimated national average effect of PM(10) on nonaccidental mortality in persons over age 65 years, corresponding to a 0.32% increase per 10-microg/m(3) increment in PM(10). The estimated effects for cardiorespiratory mortality and other mortality are 0.34% and 0.22%, respectively.     

Getting closer to the truth: overcoming research challenges when estimating the financial impact of worksite health promotion programs

The authors describe the most important methodological challenges often encountered in conducting research and evaluation on the financial impact of health promotion. These include selection bias, skewed data, small sample size, metrics. They discuss when these problems can and cannot be overcome and suggest how some of these problems can be overcome through a creating an appropriate framework for the study, and using state of the art statistical methods.     

A statistical method (cross-validation) for bone loss region detection after spaceflight

Astronauts experience bone loss after the long spaceflight missions. Identifying specific regions that undergo the greatest losses (e.g. the proximal femur) could reveal information about the processes of bone loss in disuse and disease. Methods for detecting such regions, however, remains an open problem. This paper focuses on statistical methods to detect such regions. We perform statistical parametric mapping to get t-maps of changes in images, and propose a new cross-validation method to select an optimum suprathreshold for forming clusters of pixels. Once these candidate clusters are formed, we use permutation testing of longitudinal labels to derive significant changes.