The Performance Improvement Imperative: Utilizing a Coordinated, Community-Based Approach to Enhance Care and Lower Costs for Chronically Ill Patients

Proposes principles for federal leadership and a community-level strategy for improving healthcare performance for high-cost patients as a way to curb health spending. Lists programmatic priorities and design considerations for intervention initiatives

Process Improvement for Maximized Therapeutic Innovation Outcome.

Deconvoluting key biological mechanisms forms the framework for therapeutic discovery. Strategies that enable effective translation of those insights along the development and regulatory path ultimately drive validated clinical application in patients and populations. Accordingly, parity in What vs. How we transform novel mechanistic insights into therapeutic paradigms is essential in achieving success. Aligning molecular discovery with innovations in structures and processes along the discovery-development-regulation-utilization continuum maximizes the return on public and private investments for next-generation solutions in managing health and disease

Developing an Intervention Toolbox for the Common Health Problems in the Workplace

Development of the Health ↔ Work Toolbox is described. The toolbox aims to reduce the workplace impact of common health problems (musculoskeletal, mental health, and stress complaints) by focusing on tackling work-relevant symptoms. Based on biopsychosocial principles this toolbox supplements current approaches by occupying the zone between primary prevention and healthcare. It provides a set of evidence-informed principles and processes (knowledge + tools) for tackling work-relevant common health problems. The toolbox comprises a proactive element aimed at empowering line managers to create good jobs, and a ‘just in time’ responsive element for supporting individuals struggling with a work-relevant health problem. The key intention is helping people with common health problems to maintain work participation. The extensive conceptual and practical development process, including a comprehensive evidence review, produced a functional prototype toolbox that is evidence based and flexible in its use. End-user feedback was mostly positive. Moving the prototype to a fully-fledged internet resource requires specialist design expertise. The Health ↔ Work Toolbox appears to have potential to contribute to the goal of augmenting existing primary prevention strategies and healthcare delivery by providing a more comprehensive workplace approach to constraining sickness absence

The MVGC multivariate Granger causality toolbox: a new approach to Granger-causal inference

Background: Wiener-Granger causality (“G-causality”) is a statistical notion of causality applicable to time series data, whereby cause precedes, and helps predict, effect. It is defined in both time and frequency domains, and allows for the conditioning out of common causal influences. Originally developed in the context of econometric theory, it has since achieved broad application in the neurosciences and beyond. Prediction in the G-causality formalism is based on VAR (Vector AutoRegressive) modelling. New Method: The MVGC Matlab c Toolbox approach to G-causal inference is based on multiple equivalent representations of a VAR model by (i) regression parameters, (ii) the autocovariance sequence and (iii) the cross-power spectral density of the underlying process. It features a variety of algorithms for moving between these representations, enabling selection of the most suitable algorithms with regard to computational efficiency and numerical accuracy. Results: In this paper we explain the theoretical basis, computational strategy and application to empirical G-causal inference of the MVGC Toolbox. We also show via numerical simulations the advantages of our Toolbox over previous methods in terms of computational accuracy and statistical inference. Comparison with Existing Method(s): The standard method of computing G-causality involves estimation of parameters for both a full and a nested (reduced) VAR model. The MVGC approach, by contrast, avoids explicit estimation of the reduced model, thus eliminating a source of estimation error and improving statistical power, and in addition facilitates fast and accurate estimation of the computationally awkward case of conditional G-causality in the frequency domain. Conclusions: The MVGC Toolbox implements a flexible, powerful and efficient approach to G-causal inference. Keywords: Granger causality, vector autoregressive modelling, time series analysi

No equity, no triple aim: strategic proposals to advance health equity in a volatile policy environment

Health professionals, including social workers, community health workers, public health workers, and licensed health care providers, share common interests and responsibilities in promoting health equity and improving social determinants of health—the conditions in which we live, work, play, and learn. This article summarizes underlying causes of health inequity and comparatively poor health outcomes in the U.S. It describes barriers to realizing the hope embedded in the 2010 Patient Protection and Affordable Care Act that moving away from fee-for-service payments will naturally drive care upstream as providers respond to greater financial risk for the health of their patients by undertaking greater prevention efforts. The article asserts that health equity should serve as the guiding framework for achieving the Triple Aim of health care reform. It outlines practical opportunities for improving care and for promoting stronger efforts to address social determinants of health. These proposals include developing a dashboard of measures to assist providers committed to health equity and community-based prevention and to promote institutional accountability for addressing socio-economic factors that influence health

Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients.

In December 2017, the National Academy of Neuropsychology convened an interorganizational Summit on Population Health Solutions for Assessing Cognitive Impairment in Geriatric Patients in Denver, Colorado. The Summit brought together representatives of a broad range of stakeholders invested in the care of older adults to focus on the topic of cognitive health and aging. Summit participants specifically examined questions of who should be screened for cognitive impairment and how they should be screened in medical settings. This is important in the context of an acute illness given that the presence of cognitive impairment can have significant implications for care and for the management of concomitant diseases as well as pose a major risk factor for dementia. Participants arrived at general principles to guide future screening approaches in medical populations and identified knowledge gaps to direct future research. Key learning points of the summit included: recognizing the importance of educating patients and healthcare providers about the value of assessing current and baseline cognition;emphasizing that any screening tool must be appropriately normalized and validated in the population in which it is used to obtain accurate information, including considerations of language, cultural factors, and education; andrecognizing the great potential, with appropriate caveats, of electronic health records to augment cognitive screening and tracking of changes in cognitive health over time