Health and Health Coverage in the South: A Data Update

With its recent adoption of the Affordable Care Act (ACA) Medicaid expansion to adults, Louisiana became the 32nd state to move forward with the expansion, and the 7th of the 17 states that make up the American South to expand. However, within the South, which has high rates of chronic disease and poor health outcomes, the majority of states still have not adopted the Medicaid expansion. The ACA and its Medicaid expansion offer important opportunities to expand access to health coverage, particularly in the South, where Medicaid and CHIP eligibility levels across groups have lagged behind other regions for many years.1 While many factors contribute to chronic disease and poor health outcomes, expanding health coverage can provide an important step in improving health by supporting individuals' ability to access preventive and primary care and ongoing treatment of health conditions. This brief provides key data on the South and the current status of health and health coverage in the South to provide greater insight into the health needs in the region and the potential coverage gains that may be achieved through the ACA. State specific data for the indicators presented in the brief are available in Tables 1 through 6

Computer program documentation D1FLTD to drive SINDA boundary nodes: User's guide

The thermal model correlation process begins when measured thermocouple data is available from the orbital flight tests of the shuttle. For this effort, it is necessary to convert some of the system improved numerical differencing analyzer (SINDA) diffusion or arithmetic nodes to boundary nodes and then drive these boundary nodes to the temperature profile of a flight measurement. An efficient way to provide this capability within the SINDA and OFT software systems is to provide a new SINDA routine, D1FLTD, for use in VARIABLES 1 of SINDA, to access the processed (word-addressable) orbital data reduction center flight data and store the appropriate measurement temperature in the desired SINDA temperature location. The ODRC flight data that is to be used for driving the boundary nodes must be assigned a logical unit number and must reside on a word-addressable file. The user must also provide two SINDA constants for the word positions of the first and last words of the temperature record for each measurement identifier (MID), i.e. each call to D1FLTD, used in the model. D1FLTD is then called from the VARIABLES 1 block to obtain the SINDA boundary node temperature for any MID on the file at any time point

Addition of a demand plotting capability to SINDA

The use of the DISSPLA plotting package to write a routine to be added to SINDA is described. This routine, DISPX1, allows the data within a SINDA execution to be plotted in the demand mode

Computer program documentation: ODRC demand plotting program user's guide

The Orbital Data Reduction Center (ODRC) Demand Plotting Program provides the user with three main options, each of which provides the additional option of generating a numerical summary and/or plots for the Measurement ID's (MID) on the Measurement Node Correlation (MNC) list. Option one reads MID data from word addressable ODRC files, stores the data on a temporary file, and uses it to build the numerical summary and/or plots, according to user input instructions. Options two and three read MID data from a word addressable ODRC file and component node data from a word addressable HSTFLO or HISTRY file. The component node data is used to calculate a predicted MID. Then, for option two, the MID and predicted MID data is used to generate a numerical summary and/or plots. For option three, the component node data itself is used in generating the numerical summary and/or plots. The numerical summary is sent to the BRKPT file, RELOCOK, and can be viewed after the execution of the program using the edit mode to find the desired section of the summary

Architectural Layer Recovery for Software System Understanding and Evolution

This paper presents an approach to identify software layers for the understanding and evolution of software systems implemented with any object-oriented programming language. The approach first identifies relations between the classes of a software system and then uses a link analysis algorithm (i.e. the Kleinberg algorithm) to group them into layers. Additionally to assess the approach and the underlying techniques, the paper also presents a prototype of a supporting tool and the results from a case study

Revisiting 'Skin in the Game' Among Medicare Beneficiaries: An Updated Analysis of the Increasing Financial Burden of Health Care Spending From 1997 to 2005

Presents data on the out-of-pocket expenses of Medicare beneficiaries as a share of income, analyzed by insurance status, region, and various demographics, as well as spending percentile. Breaks down out-of-pocket spending into eight categories

Medicare Spending and Use of Medical Services for Beneficiaries in Nursing Homes and Other Long-Term Care Facilities

Analyzes Medicare spending on and utilization by beneficiaries in long-term care facilities for hospitalizations, emergency room visits, and skilled nursing facilities. Explores ways to reduce hospitalizations, save costs, and improve the quality of care

Reaching for the Stars: Quality Ratings of Medicare Advantage Plans, 2011

Outlines the Centers for Medicare and Medicaid Services' quality ratings of Medicare Advantage plans, including locations and types of highly rated plans, and a proposed demonstration to modify the quality-based payments authorized by the reform law

Medicare Advantage Plan Star Ratings and Bonus Payments in 2012

Estimates total Medicare spending on and distribution of quality ratings-based bonus payments for Medicare Advantage plans in 2012 by company, tax status, state and county and in relation to cuts in plan payments under federal health reform

Quality Ratings of Medicare Advantage Plans: Key Changes in the Health Reform Law and 2010 Enrollment Data

Examines performance measures used to set plans' quality ratings, 2010 healthcare reform provisions for bonus payments to plans with high ratings, plan enrollment by rating, and ratings by plan type, analyzed by state and county. Considers implications