Improving primary care through information. A Wonca keynote paper

Abstract

Information from health care encounters across the entire health care spectrum, when consistently collected, analysed and applied can provide a clearer picture of patients’ history as well as current and future needs through a better understanding of their morbidity burden and health care experiences. It can facilitate clinical activity to target limited resources to those patients most in need through risk adjustment mechanisms that consider the morbidity burden of populations, and it can help target quality improvement and cost saving activities in the right places. It can also open the door to a new chapter of evidence-based medicine around multi-morbidity. In summary, it can support a better integrated health system where primary care can provide continuous, coordinated, and comprehensive person-centred care to those who could benefit most. This paper explores the potential uses of information collected in electronic health records (EHRs) to inform case-mix and predictive modelling, as well as the associated challenges, with a particular focus on their application to primary care.

Keywords::

• Electronic health record
• multi-morbidity
• primary care
• case-mix
• predictive modelling

Acknowledgements

The content of this paper reflects that of the keynote Barbara Starfield Memorial Lecture given during the 20th World Organization of Family Doctors’ (Wonca) World Conference in June 2013 by Karen Kinder. The authors should like to acknowledge Normalie Barton for her assistance in preparing the manuscript.

Declaration of interest: The authors alone are responsible for the content and writing of the paper.

The Johns Hopkins University has copyrighted software based on the ACG System that is one of the tools available to help analyse health care data as described in this article. Royalties are paid to the university when this software is licensed. The corresponding author is a faculty member of the Johns Hopkins University.