TY - JOUR T1 - Rationalising data use for general practice: a missed opportunity? JF - British Journal of General Practice JO - Br J Gen Pract SP - e603 LP - e605 DO - 10.3399/bjgp16X686485 VL - 66 IS - 649 AU - Louis S Levene AU - Nicola Walker AU - Richard Baker AU - Andrew Wilson AU - Catherine Honeyford Y1 - 2016/08/01 UR - http://bjgp.org/content/66/649/e603.abstract N2 - Practices and practitioners are required to produce bespoke reports using data for an ever-increasing range of purposes, including, among others, appraisals, contractual monitoring, quality assurance, and performance management by several bodies, without regard to unnecessary duplication of effort. Examples include producing numerous individual patient care plans for clinical commissioning groups (CCGs), a minimum of one completed audit cycle every 5 years for each GP as part of General Medical Council revalidation, and responses to the 130 questions of a Care Quality Commission (CQC) inspection. This huge non-clinical workload adds stress to practices and may be contributing to the current GP recruitment and retention crisis.The priorities of data use cannot solely be monitoring and performance management; to improve population outcomes (for example, premature mortality, morbidity, hospital admissions, time lost from work), we argue that general practice must also use data to strengthen its essential public health role. Local populations’ characteristics should be examined to better understand both health needs and the effect of interventions on outcomes, beyond the limited scope of the Quality and Outcomes Framework (QOF).1 This requires: the availability of timely, accurate information on practice populations’ characteristics and outcomes, to enable practices (individually or as groups) to define local healthcare needs;addressing needs so that the development of effective practice policies target all patients who might benefit, including early interventions to prevent or delay morbidity;2 andmonitoring the implementation and effect of these policies, using process, intermediate, and final-outcome data.Although this article considers mainly data extraction, interpretation, and presentation, a distinction needs to be made between these processes and the processes of data collection and entry. The designers of information systems need to support users … ER -