Risk Adjustment Under the Affordable Care Act: A Guide for Federal and State Regulators

Summarizes discussions from a conference about the consequences of the 2010 healthcare reform's risk adjustment provisions, design and implementation challenges, and the merits of various risk adjustment strategies. Recommends diagnostic risk measures

The Theory and Practice of Disclosing HMO Physician Incentives

Despite the widespread consensus that physician incentives under managed care should be disclosed, there is little agreement on the who, what, when, and how of disclosure, nor is there agreement on the primary purpose of disclosure. Three forms of market failure point to three distinct, but overlapping purposes of disclosure, each of which points toward different forms, sources and contents of disclosures

The Defensive Effect of Medical Practice Policies in Malpractice Litigation

The theoretical prospects for medical practice policies to reform malpractice law by giving conclusive defensive effect to medical custom were studied. A practice policy, however rigorous, is of no use if the nature of the claimed error is either incorrect performance of the treatment in question or failure to recognize the correct practice policy to employ by virtue of a falure in diagnosis

Connecticut: Baseline Report - State Level Field Network Study of the Implentation of the Affordable Care Act

This report is part of a series of 21 state and regional studies examining the rollout of the ACA. The national network -- with 36 states and 61 researchers -- is led by the Rockefeller Institute of Government, the public policy research arm of the State University of New York, the Brookings Institution, and the Fels Institute of Government at the University of Pennsylvania.Connecticut demonstrates how well even a smaller state can do in implementing health insurance reform through its own exchange. Broad political and industry support for a state-based exchange has resulted in one of the very best functioning exchanges in the country. Difficult or potentially contentious issues that Connecticut may face in coming years include: 1) high health care costs and the diminished level of price competition among hospitals; 2) whether additional insurers will enter the exchange and whether the new nonprofit insurance co-op will remain financially viable; 3) whether the SHOP exchange will achieve critical mass; and 4) the appropriate level of consumer representation on the exchange board

Selection of attributes for modelling Bach chorales by a genetic algorithm

A genetic algorithm selected combinations of attributes for a machine learning system. The algorithm used 90 Bach chorale melodies to train models and randomly selected sets of 10 chorales for evaluation. Compression of pitch was used as the fitness evaluation criterion. The best models were used to compress a different test set of chorales and their performance compared to human generate models. G.A. models outperformed the human models, improving compression by 10 percent

A Decision tree-based attribute weighting filter for naive Bayes

The naive Bayes classifier continues to be a popular learning algorithm for data mining applications due to its simplicity and linear run-time. Many enhancements to the basic algorithm have been proposed to help mitigate its primary weakness--the assumption that attributes are independent given the class. All of them improve the performance of naïve Bayes at the expense (to a greater or lesser degree) of execution time and/or simplicity of the final model. In this paper we present a simple filter method for setting attribute weights for use with naive Bayes. Experimental results show that naive Bayes with attribute weights rarely degrades the quality of the model compared to standard naive Bayes and, in many cases, improves it dramatically. The main advantages of this method compared to other approaches for improving naive Bayes is its run-time complexity and the fact that it maintains the simplicity of the final model

Feature subset selection: a correlation based filter approach

Recent work has shown that feature subset selection can have a position affect on the performance of machine learning algorithms. Some algorithms can be slowed or their performance adversely affected by too much data some of which may be irrelevant or redundant to the learning task. Feature subset selection, then, is a method of enhancing the performance of learning algorithms, reducing the hypothesis search space, and, in some cases, reducing the storage requirement. This paper describes a feature subset selector that uses a correlation based heuristic to determine the goodness of feature subsets, and evaluates its effectiveness with three common ML algorithms: a decision tree inducer (C4.5), a naive Bayes classifier, and an instance based learner(IBI). Experiments using a number of standard data sets drawn from real and artificial domains are presented. Feature subset selection gave significant improvement for all three algorithms; C4.5 generated smaller decision trees

Practical feature subset selection for machine learning

Machine learning algorithms automatically extract knowledge from machine readable information. Unfortunately, their success is usually dependant on the quality of the data that they operate on. If the data is inadequate, or contains extraneous and irrelevant information, machine learning algorithms may produce less accurate and less understandable results, or may fail to discover anything of use at all. Feature subset selection can result in enhanced performance, a reduced hypothesis search space, and, in some cases, reduced storage requirement. This paper describes a new feature selection algorithm that uses a correlation based heuristic to determine the “goodness” of feature subsets, and evaluates its effectiveness with three common machine learning algorithms. Experiments using a number of standard machine learning data sets are presented. Feature subset selection gave significant improvement for all three algorithm

Who Will Be Uninsured After Health Insurance Reform?

Projects state-by-state compositions of the uninsured after reforms take effect including those eligible for Medicaid or exchanges but not enrolled, those exempt from the individual mandate due to a lack of affordable options, and undocumented immigrants