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

Adherence to Cardiovascular Disease Medications: Does Patient-Provider Race/Ethnicity and Language Concordance Matter?

BACKGROUND: Patient–physician race/ethnicity and language concordance may improve medication adherence and reduce disparities in cardiovascular disease (CVD) by fostering trust and improved patient–physician communication. OBJECTIVE: To examine the association of patient race/ethnicity and language and patient–physician race/ethnicity and language concordance on medication adherence rates for a large cohort of diabetes patients in an integrated delivery system. DESIGN: We studied 131,277 adult diabetes patients in Kaiser Permanente Northern California in 2005. Probit models assessed the effect of patient and physician race/ethnicity and language on adherence to CVD medications, after controlling for patient and physician characteristics. RESULTS: Ten percent of African American, 11 % of Hispanic, 63% of Asian, and 47% of white patients had same race/ethnicity physicians.24% of Spanish-speaking patients were linguistically concordant with their physicians. African American (46%), Hispanic (49%) and Asian (52%) patients were significantly less likely than white patients (58%) to be in good adherence to all of their CVD medications (p<0.001). Spanish-speaking patients were less likely than English speaking patients to be in good adherence (51%versus 57%, p<0.001). Race concordance for African American patients was associated with adherence to all their CVD medications (53% vs. 50%, p<0.05). Language concordance was associated with medication adherence for Spanish-speaking patients (51% vs. 45%, p<0.05). CONCLUSION: Increasing opportunities for patient– physician race/ethnicity and language concordance may improve medication adherence for African American and Spanish-speaking patients, though a similar effect was not observed for Asian patients or Englishproficient Hispanic patients

A survey of QoS-aware web service composition techniques

Web service composition can be briefly described as the process of aggregating services with disparate functionalities into a new composite service in order to meet increasingly complex needs of users. Service composition process has been accurate on dealing with services having disparate functionalities, however, over the years the number of web services in particular that exhibit similar functionalities and varying Quality of Service (QoS) has significantly increased. As such, the problem becomes how to select appropriate web services such that the QoS of the resulting composite service is maximized or, in some cases, minimized. This constitutes an NP-hard problem as it is complicated and difficult to solve. In this paper, a discussion of concepts of web service composition and a holistic review of current service composition techniques proposed in literature is presented. Our review spans several publications in the field that can serve as a road map for future research

Health Insurance Exchanges in Health Care Reform: Legal and Policy Issues

Examines the role of health insurance exchanges in a reformed healthcare system, reviews past experiences with exchanges, compares the House and Senate bills' approaches to the exchanges' design and function, and discusses the policy issues they raise

Learning in Strategic Alliances

{Excerpt} Strategic alliances that bring organizations together promise unique opportunities for partners. The reality is often otherwise. Successful strategic alliances manage the partnership, not just the agreement,for collaborative advantage. Above all, they also pay attentionto learning priorities in alliance evolution. The resource-based view of the firm that gained currency in the mid-1980s considered that the competitive advantage of an organization rests on the application of the strategic resources at its disposal. These days, orthodoxy recognizes the merits of the dynamic, knowledge-based capabilities underpinning the positions organizations occupy in a sector or market. Strategic alliances—meaning cooperative agreements between two or more organizations—are a means to enhance strategic resources: self-sufficiency is becoming increasingly difficult in a complex, uncertain, and discontinuous external environment that calls for focus and flexibility in equal measure. Everywhere, organizations are discovering that they cannot “go” it alone and must now often turn to others to survive

Rethinking Map Legends with Visualization

This design paper presents new guidance for creating map legends in a dynamic environment. Our contribution is a set of guidelines for legend design in a visualization context and a series of illustrative themes through which they may be expressed. These are demonstrated in an applications context through interactive software prototypes. The guidelines are derived from cartographic literature and in liaison with EDINA who provide digital mapping services for UK tertiary education. They enhance approaches to legend design that have evolved for static media with visualization by considering: selection, layout, symbols, position, dynamism and design and process. Broad visualization legend themes include: The Ground Truth Legend, The Legend as Statistical Graphic and The Map is the Legend. Together, these concepts enable us to augment legends with dynamic properties that address specific needs, rethink their nature and role and contribute to a wider re-evaluation of maps as artifacts of usage rather than statements of fact. EDINA has acquired funding to enhance their clients with visualization legends that use these concepts as a consequence of this work. The guidance applies to the design of a wide range of legends and keys used in cartography and information visualization

Controllability of Social Networks and the Strategic Use of Random Information

This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network, and considers two well-known strategies for influencing social contexts. One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad-hoc metrics defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills, supporting our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable

To what extent does severity of loneliness vary among different mental health diagnostic groups: A cross-sectional study.

Loneliness is a common and debilitating problem in individuals with mental health disorders. However, our knowledge on severity of loneliness in different mental health diagnostic groups and factors associated with loneliness is poor, thus limiting the ability to target and improve loneliness interventions. The current study investigated the association between diagnoses and loneliness and explored whether psychological and social factors were related to loneliness. This study employed a cross-sectional design using data from a completed study which developed a measure of social inclusion. It included 192 participants from secondary, specialist mental health services with a primary diagnosis of psychotic disorders (n = 106), common mental disorders (n = 49), or personality disorders (n = 37). The study explored differences in loneliness between these broad diagnostic groups, and the relationship to loneliness of: affective symptoms, social isolation, perceived discrimination, and internalized stigma. The study adhered to the STROBE checklist for observational research. People with common mental disorders (MD = 3.94, CI = 2.15 to 5.72, P < 0.001) and people with personality disorders (MD = 4.96, CI = 2.88 to 7.05, P < 0.001) reported higher levels of loneliness compared to people with psychosis. These differences remained significant after adjustment for all psychological and social variables. Perceived discrimination and internalized stigma were also independently associated with loneliness and substantially contributed to a final explanatory model. The severity of loneliness varies between different mental health diagnostic groups. Both people with common mental disorders and personality disorders reported higher levels of loneliness than people with psychosis. Addressing perceived mental health discrimination and stigma may help to reduce loneliness

Maintaining Coverage, Affordability, and Shared Responsibility When Income and Employment Change

Outlines the 2010 reform's provisions for adjusting premium and cost-sharing subsidies when incomes change, coordinating eligibility for programs, facilitating continuous coverage, and minimizing transitions between exchanges. Makes recommendations