Recognizing and reporting child physical abuse: a cross sectional survey of primary health care professionals

Objectives: To assess primary health care professionalsâ?? ability to recognise child physical abuse within their everyday practice. Design: Cross-sectional survey Participants: A stratified random sample of 979 nurses, doctors, and dentists working in primary care in NI. Results: Four hundred and thirty one primary health care professionals responded [44% response rate]. Thirty two per cent were doctors, 35% were dentists and 33% were nurse professionals. The mean age was 41.63 years. Fifty-nine percent (251) stated that they had seen a suspicious case of child physical abuse and 47% (201) said they had reported it. Seventy-two per cent (310) of participants were aware of the mechanisms for reporting child physical abuse. Ability and willingness to recognise and report abuse discriminated the three professions. Conclusions: The findings suggest a professional reluctance to engage in recognising and reporting abuse. Barriers could be reduced by providing training and professional support for the primary care professionals.

The Open Method of Coordination on Health Care After the Lisbon Strategy II: Towards a Neoliberal Framing?

This paper undertakes a content analysis of the discourse on the Open Method of Coordination on Health Care (OMC/HC) in order to show how equity and solidarity are increasingly linked to optimisation and, as such, how neoliberalism increasingly frames health care. Some of the side-effects of this reframing for politics are highlighted: legitimating and extending EU governance, reducing the space for oppositional formations and limited citizenship. The analysis begins by interrogating the broader context of the Lisbon Strategy II, after which the techniques of the OMC/HC and its substantive outputs are analysed.

Modelling Patient Duration of Stay to Facilitate Resource Management of Geriatric Hospitals

A fundamental aspect of health care management is the effective allocation of resources. This is of particular importance in geriatric hospitals where elderly patients tend to have more complex needs. Hospital managers would benefit immensely if they had advance knowledge of patient duration of stay in hospital. Managers could assess the costs of patient care and make allowances for these in their budget. In this paper, we tackle this important problem via a model which predicts the duration of stay distribution of patients in hospital. The approach uses phase-type distributions conditioned on a Bayesian belief network.