title: 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.
authors.affiliation: Johns Hopkins Bloomberg School of Public Health , Baltimore, MD , USA.
authors.forename: Karen
authors.initials: K
authors.lastname: Kinder
authors.forename: Luisa M
authors.initials: LM
authors.lastname: Pettigrew
mesh_terms: D057286:Electronic Health Records / Q000592:standards*; D019317:Evidence-Based Medicine; D006801:Humans; D011320:Primary Health Care / Q000639:trends*
keywords: Electronic health record; case-mix; multi-morbidity; predictive modelling; primary care