Can a Conceptual Model Describe the Relationships between Health Determinants, Healthcare and Health Outcomes from a Population Perspective?

Talk Code: 
Richard Baker, John Bankart, Nicola Walker, Andrew Wilson
Author institutions: 
Department of Health Sciences, University of Leicester


If one of the priorities of a healthcare system is to optimise health outcomes in whole populations, then, to achieve this, a potentially large number of factors have to be considered or addressed. Those who plan, implement or research the provision of healthcare need to have an accurate understanding of these factors and of how they might interact. A good model aims to abstract and organise the key features from what is being modelled in order to examine its relationship to reality.


We searched the literature for relevant models, and reviewed the evidence about which main factors predict health outcomes in populations. After critiquing the strengths and limitations of previous models, we identified the need for a new conceptual model to describe the wide range of factors relevant to population health and their possible inter-relationships.


Our model, focused on primary care, is based upon the postulation of a network of variables representing entities that interact. A variety of disease- and person-related determinants give rise to health needs, which, in turn, result in health-related outcomes. Healthcare and other interventions may affect this progression, either by reducing the effects of disease-related and/or person-related factors in generating health needs (primary prevention), or by reducing the risk of adverse health outcomes (secondary prevention and/or management of health needs). Our model not only organises and describes variables, but also recognises the complexity and variability of the inter-relationships between the variables.


Our model could help:1. researchers to generate productive research questions about population health determinants and outcomes, and to explain their findings, and2. services responsible for delivering care to design and to evaluate feasible evidence-based interventions that can address population health needs.

Submitted by: 
Louis Levene
Funding acknowledgement: 
No dedicated funding