A nationwide adaptive prediction tool for coronary heart disease prevention.

Abstract

Standardised electronic recording of cardiovascular risk factor data collected during primary care delivery could be used to create a new strategy, using an adaptive prediction model, for targeting primary prevention interventions at high-risk individuals. In the short term, this should progressively improve data quality and allow risk modification to be monitored at the population level. In the long term, feedback of data on cardiovascular disease development might enable the model to tailor the recommended interventions more appropriately to the needs of the individual and to adapt to future changes in risk patterns. Ultimately, the inclusion of additional cardiovascular risk factors might enable a richer, more realistic picture of cardiovascular risk profiles to be uncovered. This model may have wider uses in both research and practice, and provides a further incentive for the standardisation of record keeping in primary care.