Health Equity: 03/23/10

Tuesday, March 23, 2010

[EQ] Innovation in Healthcare Delivery Systems: Conceptual Framework

Innovation in Healthcare Delivery Systems: Conceptual Framework

Vincent K. Omachonu Department of Industrial Engineering University of Miami

Norman G. Einspruch Department of Electrical and Computer Engineering, University of Miami

The Innovation Journal: The Public Sector Innovation Journal, Volume 15(1), 2010, Article 2.

Available online at: http://www.innovation.cc/scholarly-style/omachonu_healthcare_3innovate2.pdf

“……The healthcare industry has experienced a proliferation of innovations aimed at enhancing life expectancy, quality of life, diagnostic and treatment options, as well as the efficiency and cost effectiveness of the healthcare system.

Information technology has played a vital role in the innovation of healthcare systems. Despite the surge in innovation, theoretical research on the art and science of healthcare innovation has been limited. One of the driving forces in research is a conceptual framework that provides researchers with the foundation upon which their studies are built.

This paper begins with a definition of healthcare innovation and an understanding of how innovation occurs in healthcare. A conceptual framework is then developed which articulates the intervening variables that drive innovation in healthcare.

Based on the proposed definition of healthcare innovation, the dimensions of healthcare innovation, the process of healthcare innovation and the conceptual framework, this paper opens the door for researchers to address several questions regarding innovation in healthcare.

If the concept of healthcare innovation can be clarified, then it may become easier for health policymakers and practitioners to evaluate, adopt and procure services in ways that realistically recognize, encourage and give priority to truly valuable healthcare innovations. Lastly, this paper presents 10 research questions that are pertinent to the field of healthcare innovation. It is believed that the answers to these and other such questions will hold the key to future advances in healthcare innovation research…..”

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[EQ] Progress on Sanitation and Drinking-water: 2010 Update

Progress on Sanitation and Drinking-water: 2010 Update.

WHO/UNICEF Joint Monitoring Programme for Water Supply and Sanitation (JMP)
ISBN 978 92 4 156395 6 (NLM classification: WA 670)

The report confirms that advances continue to be made towards greater access to safe drinking-water.

Available online [60p.] at: http://www.unwater.org/downloads/JMP_report_2010.pdf

“……Progress in relation to access to basic sanitation is however insufficient to achieve the Millennium Development Goal (MDG) target to halve, by 2015, the proportion of people without sustainable access to safe drinking-water and basic sanitation.

Purpose and scope of this report This report describes the status and trends with respect to the use of safe drinking-water and basic sanitation, and progress made towards the MDG drinking-water and sanitation target.

As the world approaches 2015, it becomes increasingly important to identify who are being left behind and to focus on the challenges of addressing their needs.

This report presents some striking disparities: the gap between progress in providing access to drinking-water versus sanitation; the divide between urban and rural populations in terms of the services provided; differences in the way different regions are performing, bearing in mind that they started from different baselines; and disparities between different socioeconomic strata in society….”

Content:

Introduction

Status and progress towards the MDG target

Billions without improved sanitation

Millions without improved sources of drinking-water

Sanitation: world off track for MDG target

Sanitation ladder: global and regional trends

Drinking-water ladder: global and regional trends

Urban-rural disparities

Sanitation: urban-rural disparities

Drinking-water: urban-rural disparities

A closer look at the ladders

Open defecation

Shared and unimproved sanitation facilities

Piped water on premises and other improved sources of drinking-water

Additional perspectives

Time to collect drinking-water

Collection of drinking-water: gender disparities

Socioeconomic disparities: Sub-Saharan Africa

JMP method Joint Monitoring Programme

Statistical table

Progress on sanitation and drinking-water: country, regional and global estimates for 1990, 2000 and 2008

Annexes

Annex A Millennium Development Goals: regional groupings

Annex B Global and regional sanitation ladders: urban and rural

Annex C Global and regional drinking-water ladders: urban and rural

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[EQ] The Promise of Prevention: The Effects of Four Preventable Risk Factors on National Life Expectancy and Life Expectancy Disparities

The Promise of Prevention: The Effects of Four Preventable Risk Factors on National Life Expectancy and

Life Expectancy Disparities by Race and County in the United States

Goodarz Danaei1,2, Eric B. Rimm1,3, Shefali Oza2, Sandeep C. Kulkarni4, Christopher J. L. Murray5, Majid Ezzati1,2

1 Harvard School of Public Health, Boston, Massachusetts, United States of America, 2 Initiative for Global Health, Harvard University, Cambridge, Massachusetts, United

States of America, 3 Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, United States of America, 4 University of California, San

Francisco, California, United States of America, 5 Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington, United States of America

PLoS Medicine | www.plosmedicine.org - March 2010 | Volume 7 | Issue 3 | e1000248

Available online at: http://www.plosmedicine.org/article/info%3Adoi%2F10.1371%2Fjournal.pmed.1000248

“….There has been substantial research on psychosocial and health care determinants of health disparities in the United States (US) but less on the role of modifiable risk factors.
We estimated the effects of smoking, high blood pressure, elevated blood glucose, and adiposity on national life expectancy and on disparities in life expectancy and disease-specific mortality among eight subgroups of the US population (the ‘‘Eight Americas’’) defined on the basis of race and the location and socioeconomic characteristics of county of residence…..

Methods and Findings:

We combined data from the National Health and Nutrition Examination Survey and the Behavioral Risk Factor Surveillance System to estimate unbiased risk factor levels for the Eight Americas. We used data from the National Center for Health Statistics to estimate age–sex–disease-specific number of deaths in 2005.

We used systematic reviews and meta-analyses of epidemiologic studies to obtain risk factor effect sizes for disease-specific mortality. We used epidemiologic methods for multiple risk factors to estimate the effects of current exposure to these risk factors on death rates, and life table methods to estimate effects on life expectancy. Asians had the lowest mean body mass index, fasting plasma glucose, and smoking; whites had the lowest systolic blood pressure (SBP). SBP

The other three risk factors were highest in Western Native Americans, Southern low-income rural blacks, and/or low-income whites in Appalachia and the Mississippi Valley. Nationally, these four risk factors reduced life expectancy at birth in 2005 by an estimated 4.9 y in men and 4.1 y in women.

Life expectancy effects were smallest in Asians (M, 4.1 y; F, 3.6 y) and largest in Southern rural blacks (M, 6.7 y; F, 5.7 y). Standard deviation of life expectancies in the Eight Americas would decline by 0.50 y (18%) in men and 0.45 y (21%) in women if these risks had been reduced to optimal levels.

Disparities in the probabilities of dying from cardiovascular diseases and diabetes at different ages would decline by 69%–80%; the corresponding reduction for probabilities of dying from cancers would be 29%–50%. Individually, smoking and high blood pressure had the largest effect on life expectancy disparities.

Conclusions:
Disparities in smoking, blood pressure, blood glucose, and adiposity explain a significant proportion of disparities in mortality from cardiovascular diseases and cancers, and some of the life expectancy disparities in the US.

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