Health Services and Outcomes Research Methodology 
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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.Implications of family risk pooling for individual health insurance markets
AbstractWhile family purchase of health insurance may benefit insurance markets by pooling individual risk into family groups, the correlation across illness types in families could exacerbate adverse selection. We analyze the impact of family pooling on risk for health insurers to inform policy about family-level insurance plans. Using data on 8,927,918 enrollees in fee-for-service commercial health plans in the 2013 Truven MarketScan database, we compare the distribution of annual individual health spending across four pooling scenarios: (1) “Individual” where there is no pooling into families; (2) “real families...
Source: Health Services and Outcomes Research Methodology - December 1, 2017 Category: Statistics Source Type: research
Two parts are better than one: modeling marginal means of semicontinuous data
AbstractIn health services research, it is common to encounter semicontinuous data characterized by a point mass at zero followed by a continuous distribution with positive support. These are often analyzed using two-part mixtures that separately model the probability of use to account for the portion of the sample with zero values. Commonly, but not always, the second component models the continuous values conditional on them being positive. Prior work examining whether such two-part models are needed to appropriately draw inference from semicontinuous data compared to standard one-part regression models has found mixed r...
Source: Health Services and Outcomes Research Methodology - December 1, 2017 Category: Statistics Source Type: research
Using entropy balancing to strengthen an observational cohort study design: lessons learned from an evaluation of a complex multi-state federal demonstration
AbstractWe conducted an evaluation of a patient-centered medical home demonstration sponsored by the Centers for Medicare& Medicaid Services. We implemented a quasi-experimental pre-post with a comparison group design. Traditional propensity score weighting failed to achieve balance (exchangeability) between the two groups on several critical characteristics. In response, we incorporated a relatively new alternative known as entropy balancing. Our objective is to share lessons learned from using entropy balancing in a quasi-experimental study design. We document the advantages and challenges with using entropy balancin...
Source: Health Services and Outcomes Research Methodology - November 29, 2017 Category: Statistics Source Type: research
On the use of summary comorbidity measures for prognosis and survival treatment effect estimation
AbstractPrognostic scores have been proposed as outcome based confounder adjustment scores akin to propensity scores. However, prognostic scores have not been widely used in the substantive literature. Instead, comorbidity scores, which are limited versions of prognostic scores, have been used extensively by clinical and health services researchers. A comorbidity is an existing disease an individual has in addition to a primary condition of interest, such as cancer. Comorbidity scores are used to reduce the dimension of a vector of comorbidity variables into a single scalar variable. Such scores are often added to regressi...
Source: Health Services and Outcomes Research Methodology - June 21, 2017 Category: Statistics Source Type: research
Multivariate outlier detection in medicare claims payments applying probabilistic programming methods
AbstractThe rising elderly population continues to demand more cost-effective healthcare programs. In particular, Medicare is a vital program serving the needs of the elderly in the United States. The growing number of people enrolled in healthcare programs such as Medicare, along with the enormous volume of money in the healthcare industry, increases the appeal for, and risk of, fraudulent activities. Out of the many possible factors for the rising cost of healthcare, fraud is a major contributor, but its impacts can be lessened through the use of fraud detection methods. In this paper, we assess possible illegitimate act...
Source: Health Services and Outcomes Research Methodology - June 20, 2017 Category: Statistics Source Type: research
Implications of family risk pooling for individual health insurance markets
AbstractWhile family purchase of health insurance may benefit insurance markets by pooling individual risk into family groups, the correlation across illness types in families could exacerbate adverse selection. We analyze the impact of family pooling on risk for health insurers to inform policy about family-level insurance plans. Using data on 8,927,918 enrollees in fee-for-service commercial health plans in the 2013 Truven MarketScan database, we compare the distribution of annual individual health spending across four pooling scenarios: (1) “Individual” where there is no pooling into families; (2) “real families...
Source: Health Services and Outcomes Research Methodology - May 26, 2017 Category: Statistics Source Type: research
Two parts are better than one: modeling marginal means of semicontinuous data
AbstractIn health services research, it is common to encounter semicontinuous data characterized by a point mass at zero followed by a continuous distribution with positive support. These are often analyzed using two-part mixtures that separately model the probability of use to account for the portion of the sample with zero values. Commonly, but not always, the second component models the continuous values conditional on them being positive. Prior work examining whether such two-part models are needed to appropriately draw inference from semicontinuous data compared to standard one-part regression models has found mixed r...
Source: Health Services and Outcomes Research Methodology - March 29, 2017 Category: Statistics Source Type: research
Optimizing variance-bias trade-off in the TWANG package for estimation of propensity scores
In this study, we closely examine approaches to fine-tune one machine learning technique [generalized boosted models (GBM)] to select propensity scores that seek to optimize the variance-bias trade-off that is inherent in most propensity score analyses. Specifically, we propose and evaluate three approaches for selecting the optimal number of trees for the GBM in thetwang package in R. Normally, thetwang package in R iteratively selects the optimal number of trees as that which maximizes balance between the treatment groups being considered. Because the selected number of trees may lead to highly variable propensity score ...
Source: Health Services and Outcomes Research Methodology - December 25, 2016 Category: Statistics Source Type: research
Variation in mental illness and provision of public mental health services
AbstractBy providing affordable healthcare to many Americans for the first time, the Affordable Care Act increases demand for public mental health services. It is, however, unclear if states ’ provision standards for supply of mental health services will be able to accommodate this demand increase. Both the demand and supply of public mental health services vary within states; it is necessary to measure both locally. In this paper, we estimate the prevalence of mental illness within 3 0 geographical regions in the state of Virginia, a representative example of how many states organize their public mental health systems a...
Source: Health Services and Outcomes Research Methodology - December 23, 2016 Category: Statistics Source Type: research
Combining patient preferences with expected treatment outcomes to inform decision-making
AbstractPatient-centered care involves patients in decision-making about their medical care. Effective shared decision-making requires relevant evidence on the expected health outcomes of treatment, assessment of patient preferences for possible health outcomes, and a method to synthesize this information. Few tools exist to help clinicians and patients synthesize clinical evidence and personal preferences. We develop a statistical framework that combines multiple data sources on expected treatment outcomes with individual preferences to produce a personalized preference-weighted outcome score (PWOS). The PWOS can be calcu...
Source: Health Services and Outcomes Research Methodology - November 21, 2016 Category: Statistics Source Type: research
Statistical science at the forefront of health policy research: two ICHPS 2015 special issues
AbstractThe 11th International Conference on Health Policy Statistics (ICHPS) conference was successfully held from October 7 to 9, 2015, in Providence, Rhode Island, espousing the theme “Statistical Science at the Forefront of Health Policy Research”. Authors of research presented at ICHPS 2015, in both posters and talks, were invited to submit their completed papers in two special issues of Health Services and Outcomes Research Methodology. In addition, the issues feature inte rviews with the winners of the American Statistical Association’s Health Policy Statistics Section of the Long-Term Excellence and Mid-caree...
Source: Health Services and Outcomes Research Methodology - October 27, 2016 Category: Statistics Source Type: research
The well-being valuation model: a method for monetizing the nonmarket good of individual well-being
The objective of this research is to advance the evaluation and monetization of well-being improvement programs, offered by population health management companies, by presenting a novel method that robustly monetizes the entirety of well-being improvement within a population. This was achieved by utilizing two employers ’ well-being assessments with medical and pharmacy administrative claims (2010–2011) across a large national employer (n = 50,647) and regional employer (n = 6170) data sets. This retrospective study sought to monetize both direct and indirect value of well-being improvement across a population whos...
Source: Health Services and Outcomes Research Methodology - October 24, 2016 Category: Statistics Source Type: research
An interview with Constantine Gatsonis
(Source: Health Services and Outcomes Research Methodology)
Source: Health Services and Outcomes Research Methodology - October 20, 2016 Category: Statistics Source Type: research
Erratum to: A comparison of care management delivery models on the trajectories of medical costs among patients with chronic diseases: 4-year follow-up results
(Source: Health Services and Outcomes Research Methodology)
Source: Health Services and Outcomes Research Methodology - October 3, 2016 Category: Statistics Source Type: research
Privacy protection and aggregate health data: a review of tabular cell suppression methods (not) employed in public health data systems
AbstractPublic health research often relies on individuals ’ confidential medical data. Therefore, data collecting entities, such as states, seek to disseminate this medical data as widely as possible while still maintaining the privacy of the individual for legal and ethical reasons. One common way in which this medical data is released is through the us e of Web-based Data Query Systems (WDQS). In this article, we examined WDQS listed in the National Association for Public Health Statistics and Information Systems (NAPHSIS) specifically reviewing them for how they prevent statistical disclosure in queries that produce ...
Source: Health Services and Outcomes Research Methodology - September 28, 2016 Category: Statistics Source Type: research
