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The Effect of Geographic Units of Analysis on Measuring Geographic Variation in Medical Services Utilization. More research is needed to better estimate the range of confounding due to geography across different types of observational comparative effectiveness studies and healthcare utilization outcomes.

Though the magnitude of the area-level geography effects were small in this case, they were still statistically significant and should therefore be examined as part of this observational CER study. Because geographic variation in health care delivery is ubiquitous, it could be a comparative effectiveness research (CER) best practice to test for possible geographic confounding in observational data. In the multilevel models for this antipsychotic case example, patient composition represented a stronger source of confounding than geographic context. ESDA indicated significant spatial variation in antipsychotic prescription patterns and moderate variation in hospitalization and ED visits thereby indicating possible confounding by geography. Likelihood of mental health-related outcomes were compared between patients starting PP (NГўв‚¬вЂ°=Гўв‚¬вЂ°295) and oral SGAs (NГўв‚¬вЂ°=Гўв‚¬вЂ°8,626) using multilevel logistic regression models adjusting for patient composition (demographic and clinical factors) and geographic region. ESDA techniques were used to examine spatial patterns of antipsychotic prescriptions and outcomes (hospitalization and emergency department (ED) visits). A new-start cohort study was conducted analyzing patient-level administrative claims data (-) from Missouri Medicaid. long-acting paliperiodone palmitate (PP). The case presented compares the effectiveness of two antipsychotic treatment strategies: oral second-generation antipsychotics (SGAs) vs.

#Using justin ivona voice in clownfish how to

This paper demonstrates how to use exploratory spatial data analysis (ESDA) and spatial statistical methods to investigate and control for these potential biases. Root, Elisabeth Dowling Thomas, Deborah S K Campagna, Elizabeth J Morrato, Elaine HДЄrea-level variation in treatment and outcomes may be a potential source of confounding bias in observational comparative effectiveness studies. PMID:19285103ДЄdjusting for geographic variation in observational comparative effectiveness studies: a case study of antipsychotics using state Medicaid data. The relationship between risk factor scores and mortality was stronger for CHD than stroke.

Conclusions Weak associations between CHD and stroke mortality and strong associations between CHD and stroke risk scores suggest geographic variation in risk factors may not underlie geographic variations in stroke and CHD mortality. There was a stronger (p < 0.0001) association between state-level FCRS and state-level CHD mortality (r = 0.28, p = 0.18), than between FSRS and stroke mortality (r = 0.12, p = 0.56). Results There was no relationship between CHD and stroke mortality rates (r = 0.04 p = 0.78), but there was between CHD and stroke risk scores at the individual (r = 0.68 p < 0.0001) and state (r = 0.64, p < 0.0001) level. In an ecologic analysis, the age-adjusted, race-sex weighted, average state-level risk factor levels were compared to state-level mortality rates. Vital statistics provided age-adjusted CHD and stroke mortality rates. Methods Framingham CHD Risk Score (FCRS) and Stroke Risk Score (FSRS) were calculated for 25,770 stroke-free and 22,247 CHD-free participants from the REasons for Geographic And Racial Differences in Stroke cohort. Purpose Geographic variation in risk factors may underlie geographic disparities in coronary heart disease (CHD) and stroke mortality. Howard, George Cushman, Mary Prineas, Ronald J.

Advancing the Hypothesis that Geographic Variations in Risk Factors Contribute Relatively Little to Observed Geographic Variations in Heart Disease and Stroke Mortality