Approaches to population health care : the emerging context!

This paper provides a review of recent developments in population-based approaches to community health and explores the origins of the population health concept and its implications for the operation of health service management. There is a growing perception among health professionals that the key to improving health outcomes will be the implementation of integrated and preventive population-based resource management rather than investment in systems that respond to crises and health problems at the acute end of the service provision spectrum only. That is, we will need increasingly to skew our community health and welfare investments towards preventive care, education, lifestyle change, self-management and environmental improvement if we are to reduce the rate of growth in the incidence of chronic disease and mitigate the impact of these diseases upon the acute health care system. While resources will still need to be devoted to the treatment and management of physical trauma, infectious diseases, inherited illness and chronic conditions, it is suggested we could reduce the rate at which demand for these services is increasing at present by managing our environment and communities better, and through the implementation of more effective early intervention programs across particular population groups. Such approaches are known generally as population health management, as opposed to individual or illness - based health management' or even public health - and suggest that health systems might productively focus in the future on population level causation and not just upon disease-specific problems or illness management after the fact. Population health approaches attempt to broaden our understanding of causation and manage health through an emphasis on the health of whole populations and by building healthy communities rather than seeing "health care" as predominantly about illness management or responses to health crises. The concept also presupposes the existence of cleaner and healthier environments, clean water and food, and the existence of vibrant social contexts in which individuals are able to work for the overall good of communities and, ultimately, of each other.

Bioconcentration of selected personal care products in Ruditapes philippinarum (Manila clam)

The Bioconcentration Factor (BCF) is the principal source of information used to assess and regulate the potential hazard and risk for a chemical that has the potential to bioaccumulate in the marine environment, according to the Marine Strategy Framework Directive (MSFD). The main objective of this thesis was to estimate the BCFs of two different emerging contaminants in Ruditapes philippinarum (Manila clam) under controlled laboratory conditions: the UV filter 4-methylbenzylidene camphor (4-MBC) commonly used in skincare products, and the artificial sweetener Acesulfame potassium (ACE-K) used as a food additive. Ruditapes philippinarum organisms were exposed directly to 4-MBC and ACE-K nominal concentration of 1, 10 and 100 μg L-1 during 10 days. Bioconcentration factors (BCFs) were estimated according to 3 different models for both compounds. The 4-MBC estimated BCFs fall in range of 61553 - 539143 L Kg-1, showing that this compound is very bioaccumulative and could also undergo biomagnification in the marine food chain. On the contrary, estimated ACE-K BCF is consistently lower, in order of 7 L Kg-1 for the nominal exposure concentration of 100 μg L-1. The low ACE-K BCF could be explained by its high solubility in water and thus a rapid metabolization by clams during the experiments. In summary, future research focusing on the marine environment is needed on these two emerging compounds.

Smoothing a Discrete Hazard Function for the Number of Patients Colonized with Methicillin-Resistance Staphylococcus Aureus in an Intensive Care Unit

A new method for estimating the time to colonization of Methicillin-resistant Staphylococcus Aureus (MRSA) patients is developed in this paper. The time to colonization of MRSA is modelled using a Bayesian smoothing approach for the hazard function. There are two prior models discussed in this paper: the first difference prior and the second difference prior. The second difference prior model gives smoother estimates of the hazard functions and, when applied to data from an intensive care unit (ICU), clearly shows increasing hazard up to day 13, then a decreasing hazard. The results clearly demonstrate that the hazard is not constant and provide a useful quantification of the effect of length of stay on the risk of MRSA colonization which provides useful insight.