Curso intensivo de regresion logistica

Núm al catàleg de Patrimoni: 3887 (institut Mental i Església)Bernader, J. O

A Computer Simulation of the EPI Survey Strategy

Lemeshow S (Division of Public Health, School of Health Sciences, University of Massachusetts, Amherst MA 01003, USA), Tserkovnyi A G, Tulloch J L, Dowd J E, Lwanga S K and Keja J. A computer simulation of the EPI survey strategy. Internationa Journal of Epidemiology 1985, 14: 473-481. A Monte Carlo simulation study was designed to evaluate the sample survey technique currently used by the Expanded Programme on Immunization(EPI) of the World Health Organization. Of particular interest was how the EPI strategy compared to a more traditional sampling strategy with respect to bias and variability of estimates. It was also of interest to investigate whether the estimates of population vaccination coverage were accurate to within 10 percentage points of the actual levels. It was found that within particular clusters, the EPI method was particularly sensitive to pocketing of vaccinated individuals, but the more traditional method gave more accurate and less variable results under a variety of conditions. However, the stated goal of the EPI, of being able to produce population estimates accurate to within 10 percentage points of the true levels in the population, was satisfied in the artificially created populations studie

Diagnosis-Specific Readmission Risk Prediction Using Electronic Health Data: a Retrospective Cohort Study

Background: Readmissions after hospital discharge are a common occurrence and are costly for both hospitals and patients. Previous attempts to create universal risk prediction models for readmission have not met with success. In this study we leveraged a comprehensive electronic health record to create readmission-risk models that were institution- and patient- specific in an attempt to improve our ability to predict readmission. Methods: This is a retrospective cohort study performed at a large midwestern tertiary care medical center. All patients with a primary discharge diagnosis of congestive heart failure, acute myocardial infarction or pneumonia over a two-year time period were included in the analysis. The main outcome was 30-day readmission. Demographic, comorbidity, laboratory, and medication data were collected on all patients from a comprehensive information warehouse. Using multivariable analysis with stepwise removal we created three risk disease-specific risk prediction models and a combined model. These models were then validated on separate cohorts. Results: 3572 patients were included in the derivation cohort. Overall there was a 16.2% readmission rate. The acute myocardial infarction and pneumonia readmission-risk models performed well on a random sample validation cohort (AUC range 0.73 to 0.76) but less well on a historical validation cohort (AUC 0.66 for both). The congestive heart failure model performed poorly on both validation cohorts (AUC 0.63 and 0.64). Conclusions: The readmission-risk models for acute myocardial infarction and pneumonia validated well on a contemporary cohort, but not as well on a historical cohort, suggesting that models such as these need to be continuously trained and adjusted to respond to local trends. The poor performance of the congestive heart failure model may suggest that for chronic disease conditions social and behavioral variables are of greater importance and improved documentation of these variables within the electronic health record should be encouraged

Choosing a Survey Sample When Data on the Population Are Limited: A Method Using Global Positioning Systems and Aerial and Satellite Photographs

Background Various methods have been proposed for sampling when data on the population are limited. However, these methods are often biased. We propose a new method to draw a population sample using Global Positioning Systems and aerial or satellite photographs. Results We randomly sampled Global Positioning System locations in designated areas. A circle was drawn around each location with radius representing 20 m. Buildings in the circle were identified from satellite photographs; one was randomly chosen. Interviewers selected one household from the building, and interviews were conducted with eligible household members. Conclusions Participants had known selection probabilities, allowing proper estimation of parameters of interest and their variances. The approach was made possible by recent technological developments and access to satellite photographs. &nbsp

Evaluation of the impact of 2 years of a dosing intervention on canine echinococcosis in the Alay Valley, Kyrgyzstan

Echinococcosis is a re-emerging zoonotic disease in Kyrgyzstan. In 2012, an echinococcosis control scheme was started that included dosing owned dogs in the Alay Valley, Kyrgyzstan with praziquantel. Control programmes require large investments of money and resources; as such it is important to evaluate how well these are meeting their targets. However, problems associated with echinococcosis control schemes include remoteness and semi-nomadic customs of affected communities, and lack of resources. These same problems apply to control scheme evaluations, and quick and easy assessment tools are highly desirable. Lot quality assurance sampling was used to assess the impact of approximately 2 years of echinococcosis control in the Alay valley. A pre-intervention coproELISA prevalence was established, and a 75% threshold for dosing compliance was set based on previous studies. Ten communities were visited in 2013 and 2014, with 18-21 dogs sampled per community, and questionnaires administered to dog owners. After 21 months of control efforts, 8/10 communities showed evidence of reaching the 75% praziquantel dosing target, although only 3/10 showed evidence of a reduction in coproELISA prevalence. This is understandable, since years of sustained control are required to effectively control echinococcosis, and efforts in the Alay valley should be and are being continued

Individual Risk

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/90540/1/j.1751-7176.2012.00592.x.pd