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The Global Multidimensional Poverty Index (MPI) was developed in 2010 by the Oxford Poverty & Human Development Initiative (OPHI) and the United Nations Development Programme [4] and uses health, education and standard of living indicators to determine the incidence and intensity of poverty experienced by a population.
A notable criticism is that although the Social Progress Index can be seen as a superset of indicators used by earlier econometric models such as Gross National Well-being Index 2005, Bhutan Gross National Happiness Index of 2012, and World Happiness Report of 2012, unlike them, it ignores measures of subjective life satisfaction and ...
The Multidimensional Poverty Index (MPI): The 2010 Report featured a new multidimensional poverty measure that complements income-based poverty assessments by looking at multiple factors at the household level, from basic living standards to access to schooling, clean water and health care. About 1.7 billion people—fully a third of the ...
In 2007, the US Institute for Healthcare Improvement proposed “whole system measures” that address structure, process, and outcomes of care. [10] These indicators supply health care leaders with data to evaluate the organization’s performance in order to design strategic QI planning.
The Mazziotta–Pareto index (MPI) is a composite index [1] (OECD, 2008 [2]) for summarizing a set of individual indicators that are assumed to be not fully substitutable. [3] It is based on a non-linear function which, starting from the arithmetic mean of the normalized indicators, introduces a penalty for the units with unbalanced values of the indicators (De Muro et al., 2011 [4]).
Long-term unemployment (12 months or more, % of labour force), 2005. Varies from 0.4% for the United States to 5.0% for Germany. This indicator has by far the greatest variation, with a value as high as 9.3% at HDI position 37. Population below 50% of median adjusted household disposable income (%), 1994–2002. Varies from 5.4% for Finland to ...
In computing, an enterprise[-wide] master patient index is a form of customer data integration (CDI) specific to the healthcare industry.Healthcare organizations and groups use EMPI to identify, match, merge, de-duplicate, and cleanse patient records to create a master index that may be used to obtain a complete and single view of a patient.
SRI 2 is a framework and a process. The framework consists of a set of reflective statements centred on ten recovery indicators. These recovery indicators are based on research about what works in recovery e.g. ‘service is strengths based’ and ‘goals are identified and addressed’.