Public Service Agreement - Health Sector Progress Report - October 2011

Public Service Agreement – Health Sector Progress Report – October 2011 Click here to download PDF 7.66MB

Non-Commercial State Agencies - Public Service Agreement Progress Report - October 2011

Non-Commercial State Agencies – Public Service Agreement Progress Report – October 2011 Click here to download PDF 35KB

Machine learning algorithms for spatial data. Case studies: Environmental pollution, natural hazards, renewable resources

This paper presents general problems and approaches for the spatial data analysis using machine learning algorithms. Machine learning is a very powerful approach to adaptive data analysis, modelling and visualisation. The key feature of the machine learning algorithms is that they learn from empirical data and can be used in cases when the modelled environmental phenomena are hidden, nonlinear, noisy and highly variable in space and in time. Most of the machines learning algorithms are universal and adaptive modelling tools developed to solve basic problems of learning from data: classification/pattern recognition, regression/mapping and probability density modelling. In the present report some of the widely used machine learning algorithms, namely artificial neural networks (ANN) of different architectures and Support Vector Machines (SVM), are adapted to the problems of the analysis and modelling of geo-spatial data. Machine learning algorithms have an important advantage over traditional models of spatial statistics when problems are considered in a high dimensional geo-feature spaces, when the dimension of space exceeds 5. Such features are usually generated, for example, from digital elevation models, remote sensing images, etc. An important extension of models concerns considering of real space constrains like geomorphology, networks, and other natural structures. Recent developments in semi-supervised learning can improve modelling of environmental phenomena taking into account on geo-manifolds. An important part of the study deals with the analysis of relevant variables and models' inputs. This problem is approached by using different feature selection/feature extraction nonlinear tools. To demonstrate the application of machine learning algorithms several interesting case studies are considered: digital soil mapping using SVM, automatic mapping of soil and water system pollution using ANN; natural hazards risk analysis (avalanches, landslides), assessments of renewable resources (wind fields) with SVM and ANN models, etc. The dimensionality of spaces considered varies from 2 to more than 30. Figures 1, 2, 3 demonstrate some results of the studies and their outputs. Finally, the results of environmental mapping are discussed and compared with traditional models of geostatistics.

Public Service Agreement 2010-2014 - Health Sector Action Plan 2012

This revised Action Plan is designed to support the delivery of the HSEâ?Ts 2012 National Service Plan by facilitating the fast-tracking of measures required to deliver essential health and personal social services across the country within the context of further reductions in funding and staff numbers. The implementation of the National Service Plan, approved by the Minister for Health on 13 January 2012, represents a major challenge to the health services and comes at a time of major reform of the public health system.   Click here to download PDF 161kb

Public Service Agreement 2010-2014 (Croke Park Agreement) Integrated Departmental and Agencies Action Plan 2012

Public Service Agreement 2010-2014 (Croke Park Agreement) Integrated Departmental and Agencies Action Plan 2012 Integrated Departmental and Agencies Action Plan (Jan 2012) PDF 54kb Integrated Departmental and Agencies Action Plan (Oct 2012) PDF 194kb  

Public Service Agreement 2010-2014 (Croke Park Agreement) - Second Annual Progress, Savings and Productivity Reports for the Department and its Agencies

Public Service Agreement 2010-2014 (Croke Park Agreement) – Second Annual Progress, Savings and Productivity Reports for the Department and its Agencies Integrated Annual Progress Report for the Department and its Agencies PDF 327kb Annual Savings Report for the Department’s Agencies PDF 205kb Productivity Report for the Department and its Agencies PDF 205kb

Public Service Agreement - Revised Health Sector Action Plan - December 2012

The health service has been at the forefront in delivering significant change under the PSA. The substantial contribution already made by health service staff, especially during the period of concentrated retirements up to February 2012, is acknowledged and much appreciated by management. These changes are being achieved in what is a complex working environment with increasing demands, (500,000 increase in medical card holders between 2007 and 2012) and a growing and ageing population, within a public health service which is undergoing unprecedented organisational change and reform, accompanied by a reducing workforce. Public Service Agreement – Revised Health Sector Action Plan- December 2012 savings report Click here to download PDF 51kb

Public Service Agreement - Health Sector second annual progress and savings report

Department cover letters PDF 839kb Main health sector progress report PDF 11.1mb Traffic light document PDF 39kb Savings template PDF 268kb

Public Service Agreement Health Sector 3rd Annual Progress Report 1st April to 31st December 2012

Public Service Agreement Health Sector 3rd Annual Progress Report 1st April to 31st December 2012 Click here to download PDF 1MB

Public Service Agreement 2010-2014 (Croke Park Agreement) - Third Annual Progress and Savings Report for the Department and its Agencies

Public Service Agreement 2010-2014 (Croke Park Agreement) – Third Annual Progress and Savings Report for the Department and its Agencies   Click here to download Integrated Progress Report on Action Plan for the Department and its Agencies PDF 242KB Click here to download Annual Savings Report for the Department’s Agencies PDF 155KB

Framework Agreement between the Minister for Health and the Irish Medical Organisation in respect of a process for engagement concerning the GMS/GP Contract

Minister of State with responsibility for Primary Care, Alex White TD, today (4 June 2014) concluded a series of meetings with the Irish Medical Organisation (IMO) with the signing of the Framework Agreement between the Minister of Health, the HSE and the Irish Medical Organisation (IMO) setting out a process for engagement concerning the GMS/GP contract and other publicly funded contracts involving General Practitioners (GPs). Download document here

Department of Health and Children Consolidated Salary Scales - Clause 2.31 of the Haddington Road Agreement

CONSOLIDATED SALARY SCALES IN ACCORDANCE WITH CLAUSE 2.31 OF THE HADDINGTON ROAD AGREEMENT These scales must be read in conjunction with Department of Health Circular 3/2014 With reference to Clause 2.31 of the Haddington Road Agreement (HRA) which addresses the remuneration of new entrant grades who entered the Public Service on or after 1 January 2011 and were subject to Department of Health Circular 2/2011 dated 24 March 2011.   New entrants to health sector recruitment grades, who were subject to the 2011 reduced pay rates will be assimilated to the revised/merged incremental payscale as and from 1 November 2013. Download the document here

Prevalence of the metabolic syndrome in the Seychelles according to different definitions, contribution of components, and agreement between different definitions

Background: The metabolic syndrome (MS) represents a cluster of metabolic disorders that predicts diabetes and cardiovascular disease. Several definitions exist and further descriptive and prospective data are needed to compare these definitions and their significance in different populations. Objective: We examined, in a country of the African region, i) the prevalence of MS according to three major definitions (ATP, IDF, WHO); ii) the contribution of individual MS components; and iii) the agreement between the three considered definitions. We also examined the prevalence among diabetics and non-diabetics. Methods: We conducted an examination survey in a sample representative of the general population aged 25-64 of the Seychelles (Indian Ocean, African region), attended by 1255 persons (participation rate of 80.2%). Results: The prevalence of MS was similar with either definition of MS in men (24%-25%) but differed in women (WHO: 25%, ATP: 32%; IDF: 35%). Upon exclusion of diabetic persons, the prevalence was 5-10% lower for all three MS definitions: most diabetic persons had MS although a substantial proportion of diabetic men aged 45-64 did not have MS. The following components were found most often among persons with MS: 90% had high blood pressure (HBP) and 78% had obesity (ATP); 95% had obesity and 84% had HBP (WHO), and 89% had HBP and 75% had impaired glucose regulation (IDF) -not considering impaired glucose regulation and obesity that are compulsory components of the WHO and IDF definitions, respectively. Among persons with MS based on either of the three definitions (37% of total population), less than 80% met both ATP and IDF criteria, 67% both WHO and IDF criteria, 54% both WHO and ATP criteria and only 37% met all three definitions. Conclusions. We found a fairly high prevalence of MS in an African population. However, because there was only poor agreement between the 3 MS definitions, the fairly similar proportions of MS based on ATP, IDF or WHO definitions identified, to a substantial extent, different subjects as having MS.

Adult Learning Services

Evidence Review 4 - Adult learning services Briefing 4 - Adult learning services This pair of documents, commissioned by Public Health England, and written by the UCL Institute of Health Equity, address the role of participation in learning as an adult in improving health. There is evidence that involvement in adult learning has both direct and indirect links with health, for example because it increases employability. There is some evidence that those who are lower down the social gradient benefit most, in health terms, from adult learning. However, there is a gradient both in participation in adult learning and skill level, whereby the more someone would benefit from adult learning, the less likely they are to participate, and the lower their literacy and numeracy skills are likely to be. This is due to a range of barriers, including prohibitively high costs, lack of personal confidence, or lack of availability and access. These papers also show that there are a number of actions local authorities can take to increase access to adult learning, improve quality of provision and increase the extent to which it is delivered and targeted proportionate to need. The full evidence review and a shorter summary briefing are available to download above. This document is part of a series. An overview document which provides an introduction to this and other documents in the series, and links to the other topic areas, is available on the ‘Local Action on health inequalities’ project page. A video of Michael Marmot introducing the work is also available on our videos page.