'As well as supporting QOF payments, the QMAS provides the NHS with a database of public health information on the prevalence of chronic and long-term illnesses.'

The quality and outcomes framework rewards general practices for providing evidence-based, high-quality care to patients with a specific set of chronic conditions. And its data can be used to improve other processes.

Clinical achievement is extracted automatically from practices' computer systems into the national quality management analysis system (QMAS). As well as supporting QOF payments, QMAS provides the NHS with a database of public health information on the prevalence of chronic and long-term illnesses.

The Information Centre for health and social care receives monthly extracts from QMAS and produces an annual online publication of all the information from the QOF. For the first time, disease prevalence information is available for all practices in England from a standard national dataset.

QOF is a new data source and analysis and interpretation is still evolving. Sometimes, lower prevalence reflects lower detection rates. Also, the raw data does not reflect differing population age structures or the complexities in areas of high standardised mortality ratios, where people die young and therefore do not have time to develop the morbidities of chronic disease.

It can, however, provide valuable base information for a variety of processes:

  • Acquiring and distributing resources: prevalence information reflects the way GPs and other clinicians record morbidity for clinical and QOF purposes. This represents a good proxy for the burden that falls on primary care nationally, and may inform NHS resource allocation to primary care trusts, GP budget-setting and service enhancements to address health needs.
  • Identifying need and unmet need: the dataset can help shape the detail of services. One primary care trust has used the diabetes prevalence data to identify the number of patients who have not had retinal screening. This was done by matching potential need against delivery using individual patient data.
  • Equally, QOF data can be used directly to develop appropriate health and well-being interventions for the population. It is possible, for example, to compare QOF prevalence figures at a local level with prevalence forecasts based on socio-demographic details. Large differences between the two could reflect unmet need or, at the very least, highlight areas for further investigation.
  • The potential of practice-based commissioning should be harnessed to improve quality in delivery. Commissioning clusters should be encouraged to consider the quality of care across the whole health economy, not just secondary care. As practice-based commissioning matures, outcomes indicators could be developed for primary medical care contractors that cover the whole health economy, drawing on QOF data as well as secondary care's hospital episode statistics.
  • Performance management and accreditation: among other things, the Our Health, Our Care, Our Saywhite paper looked at issues around provider accreditation. QOF is a rich dataset that could form part of a suite of measures PCTs might expect their constituent practices to deliver. Although QOF is a voluntary scheme, NHS patients have a reasonable right to expect such information as part of the choice agenda.

The introduction of QOF and the collection of practice-level data raises the possibility of links to other datasets. Triangulating with prescribing and hospital episode statistics data not only allows us to link primary and secondary care but will also open up the possibility of a set of indicators that begin to compare and measure the appropriateness of care.

Dave Roberts is manager of the prescribing support unit at the Information Centre for health and social care