Setting up the Benchmark

The Primary Care Foundation developed a completely new approach that is driven by data extracts supplied by out of hours providers for four separate weeks over a six month period.  This is supplemented by web based questionnaires for both  commissioners and providers, ensuring that we derive the information we need from the people best placed to provide it, as well as requiring both parties to validate and ‘sign off’ each others’ submissions.

There were extensive pilots during 2008 allowing us to improve and refine the benchmark, including processes for collecting and validating data, the key performance measures, as well as how we support members to reflect on the findings and focus on the priorities for service improvement.  We shared the developing findings at conferences, SHA-wide networks and through articles (e.g. Health Service Journal, 11 September 2008, pp. 23-24.).  Although the benchmark had to have the support of out of hours providers (and was actively supported by the NHS Alliance, the main representative body within this sector), we were clear that it needed to be owned and paid for by the commissioners, so it was important to promote the initiative with PCTs.  Important decisions about the scope of the benchmark and setting a price were made with a national advisory group involving leaders from PCTs, providers, the Department of Health and the Audit Commission.  We also decided that to further enhance the benchmark a separate, authoritative measure of patient experience was needed and this has been added by working in partnership with CFEP UK Surveys, a leading provider of patient surveys in primary care and out of hours services.

After each round of the benchmark, a report is sent to each commissioner and service provider identifying their performance, but providers currently retain their anonymity, although after a major consultation, this is set to change for the fourth round. We also run a series of half-day workshops with both commissioners and providers to help them understand the different measures and how they can be used to improve performance locally.  These include an analysis of a number of possible explanatory factors allowing PCTs and services to compare themselves with others with similar population density or deprivation.