C8
Development and evaluation of a patient-centred tool to measure diagnostic delays (DELAYS2)
Richard Neal, Dianna Paterfield, Maggie Hendry, Sadia Chughtai, Mike Robling, Matthew Makin, Nick Stuart, Clare Wilkinson, Simon Gollins
Cardiff University, UK
Background
The duration between first symptom and a cancer diagnosis is important because, if shortened, it may lead to earlier stage diagnosis and better outcomes. There is no standard tool to measure this. Measurement is difficult because whilst hard symptoms (e.g. breast lumps) are often either present or absent, soft symptoms (e.g. tiredness) often have a more gradual onset. We aimed to develop a valid and robust tool to measure time from onset of symptoms to diagnosis.
Method
Phase 1:
We undertook further development and evaluation of our tool (Neal et al 2008). Ten patients were recruited following diagnosis, and completed questionnaires comprising demographic information and duration of symptoms. Some questions were cancer site specific, others generic. Response options for onset were either a date when symptoms were first noticed, or a free text estimate of duration. To facilitate recall we used a landmarking technique by including a calendar. Subsequently cognitive debrief interviews were conducted and the questionnaire circulated to patient/public groups. Participants helped clarify language used and made valuable suggestions to improve questionnaire design, wording and lessen anxiety. As landmarking was not liked, the calendar was removed.
Phase 2:
We are conducting a randomised trial in 3 hospitals across North Wales comparing self-complete with research nurse administered questionnaires, and are determining validity by comparison to general practice records. Eligible patients for 11 cancer sites are identified by research nurses in consultation with clinical teams. Invitation letters are sent, with reminders at 2 and 4 weeks.
Results
Preliminary results relating to validity of the responses and the completion rate by different modes of administration will be reported.
Conclusion
We anticipate that we will have a tool that can be used in descriptive and epidemiological studies of cancer delays, providing a valid and robust measure of time from first symptom to diagnosis.
