Health Services and Outcomes Research Methodology This is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Are marginalized two-part models superior to non-marginalized two-part models for count data with excess zeroes? Estimation of marginal effects, model misspecification, and model selection
This article aims to answer these questions through a comprehensive investigation. We first summarize the existing non-marginalized and marginalized two-part models and then develop marginalized hurdle Poisson and negative binomial models for cross-sectional count data with abundant zero counts. Our interest in the investigation lies particularly in the (average) marginal effect and (average) incremental effect and the comparison of these effects. The estimators of these effects are presented, and variance estimators are derived by using delta methods and Taylor series approximations. Though the marginalized models attract...
Source: Health Services and Outcomes Research Methodology - September 1, 2018 Category: Statistics Source Type: research

Does the inter-unit reliability (IUR) measure reliability?
AbstractIn monitoring health care providers, various outcomes are used to assess the performance and quality of care given. We consider a measure that is normally distributed across the majority of providers with both a within and between component contributing to the overall variability of the measure. In such cases, the inter-unit reliability (IUR) is commonly used to assess the usefulness of a measure for identifying extreme providers. In this article, we define and discuss the IUR and note its role under various assumptions about the source of the between-provider variance. This variability may be due primarily to diff...
Source: Health Services and Outcomes Research Methodology - September 1, 2018 Category: Statistics Source Type: research

Statistical testing when the populations from which samples are drawn are uncertain
AbstractThe topic of this article is hypothesis testing when the populations from which the data are drawn are known only with a given probability distribution. Some important areas of application for which such a situation arises is reviewed briefly. The specific cases herein considered are testing a one-sided hypothesis involving two populations. An illustrative small data set, involving six observations, is used to demonstrate relevant approaches and calculations for such testing. Both a frequentist approach and a Bayesian approach are developed. In both of these approaches, use is made of all possible data configuratio...
Source: Health Services and Outcomes Research Methodology - September 1, 2018 Category: Statistics Source Type: research

Using Veterans Affairs Corporate Data Warehouse to identify 30-day hospital readmissions
We examined all VA bedded stays with an admission date in 2009. Non-acute portions of a stay were dropped. VA to VA transfers were merged when consecutive discharge and admission dates were within one calendar day. Finally, hospitalizations that occurred in a non-VA facility were merged. The 30-day readmission rate was calculated at each step of t he algorithm to demonstrate the impact. The total number of VA medical hospitalizations in 2009 with live discharges was 505,861. The 30-day readmission rate after adjusting for VA to VA transfers and incorporating non-VA care was 18.3% (95% confidence interval (CI): 18.2, 18.4%)...
Source: Health Services and Outcomes Research Methodology - September 1, 2018 Category: Statistics Source Type: research

Causal inference for multi-level treatments with machine-learned propensity scores
AbstractPropensity score-based methods have been widely developed to adjust for confounders in observational studies to estimate causal treatment effect for binary treatments. We generalize these causal inference methods to the multi-level treatment case. We review the generalized causal inference framework and several propensity score estimation methods. We conduct a comprehensive simulation study to evaluate the performance of multinomial logistic regression, generalized boosted models, random forest and data adaptive matching score for estimating propensity scores based on inverse probability of treatment weighting. Fro...
Source: Health Services and Outcomes Research Methodology - August 30, 2018 Category: Statistics Source Type: research

Accounting for study participants who are ineligible for linkage: a multiple imputation approach to analyzing the linked National Health and Nutrition Examination Survey and Centers for Medicare and Medicaid Services ’ Medicaid data
AbstractData from the National Health and Nutrition Examination Survey have been linked to the Center for Medicare and Medicaid Services ’ Medicaid Enrollment and Claims Files for the survey years 1999–2004. The linked data are produced by the National Center for Health Statistics’ (NCHS) Data Linkage Program and are available in the NCHS Research Data Center. This project compares the usefulness of multiple imputation to accou nt for data linkage ineligibility and other survey nonresponse with currently recommended weight adjustment procedures. Estimated differences in environmental smoke exposure across Medicaid/Ch...
Source: Health Services and Outcomes Research Methodology - August 16, 2018 Category: Statistics Source Type: research

Does the inter-unit reliability (IUR) measure reliability?
AbstractIn monitoring health care providers, various outcomes are used to assess the performance and quality of care given. We consider a measure that is normally distributed across the majority of providers with both a within and between component contributing to the overall variability of the measure. In such cases, the inter-unit reliability (IUR) is commonly used to assess the usefulness of a measure for identifying extreme providers. In this article, we define and discuss the IUR and note its role under various assumptions about the source of the between-provider variance. This variability may be due primarily to diff...
Source: Health Services and Outcomes Research Methodology - June 27, 2018 Category: Statistics Source Type: research

A shared parameter location scale mixed effect model for EMA data subject to informative missing
We present a shared parameter modeling approach that links the primary longitudinal outcome with potentially informative missingness by a common set of random effects that summarize a subjects ’ specific traits in terms of their mean (location) and variability (scale). The primary outcome, conditional on the random effects, are allowed to exhibit heterogeneity in terms of both the mean and within subject variance. Unlike previous methods which largely rely on numerical integration or ap proximation, we estimate the model by a full Bayesian approach using Markov Chain Monte Carlo. An adolescent mood study example is illus...
Source: Health Services and Outcomes Research Methodology - June 7, 2018 Category: Statistics Source Type: research

Are marginalized two-part models superior to non-marginalized two-part models for count data with excess zeroes? Estimation of marginal effects, model misspecification, and model selection
This article aims to answer these questions through a comprehensive investigation. We first summarize the existing non-marginalized and marginalized two-part models and then develop marginalized hurdle Poisson and negative binomial models for cross-sectional count data with abundant zero counts. Our interest in the investigation lies particularly in the (average) marginal effect and (average) incremental effect and the comparison of these effects. The estimators of these effects are presented, and variance estimators are derived by using delta methods and Taylor series approximations. Though the marginalized models attract...
Source: Health Services and Outcomes Research Methodology - June 5, 2018 Category: Statistics Source Type: research

A bivariate Bernoulli model for analyzing malnutrition data
AbstractMultivariate binary responses from the same subject are usually correlated. For example, malnutrition of children are usually measured using ‘stunting’ (low height-for-age) and ‘wasting’ (low weight-for-age) calculated from their height, weight and age, and hence the status of being stunted may depend on the status of being wasted and vice-versa. For analyzing such malnutrition data, one needs special statistical models allowing for dependence between the responses to avoid misleading inference. The problem of dependence in multivariate binary responses is generally addressed by using marginal models with g...
Source: Health Services and Outcomes Research Methodology - June 1, 2018 Category: Statistics Source Type: research

Consistent estimation of polychotomous treatment effects with selection-bias and unobserved heterogeneity using panel data correlated random coefficients model
AbstractWe estimate multiple treatment effects in presence of selection-bias and response heterogeneity, using panel data. A control function was added to a fixed-effects based correlated random coefficients model. Selection model to create the control function was contrasted between multinomial logit and multinomial probit. For the multinomial logit model, parametric and semi-parametric bias correction techniques, as proposed in Lee (Econometrica 51(2):507 –512,1983), Dubin and McFadden (Econometrica  52(2):345–362,1984) and Dahl (Econometrica 70(6):2367 –2420,2002) respectively, were implemented. We find that cont...
Source: Health Services and Outcomes Research Methodology - June 1, 2018 Category: Statistics Source Type: research

Comparing the spatial attractiveness of hospitals using zero-inflated spatial models
AbstractPolicy makers increasingly rely on hospital competition to incentivize patients to choose high-value care. Amongst all possible drivers, the travel distance without any doubt is one of the most important. In this paper we propose the use of a spatial Bayesian hierarchical model to assess the impact of distance on the number of patient admissions in hospitals, and thereby, compare hospital attractiveness. To this aim a MCMC sampler has been designed. We apply our methodology to patient admissions for asthma in four hospitals located in the H érault department of France. Results indicate that the most attractive...
Source: Health Services and Outcomes Research Methodology - June 1, 2018 Category: Statistics Source Type: research