Introduction:Long-term lung cancer survival in England has improved little in recent years and is worse than many countries. The Department of Health funded a campaign to raise public awareness of persistent cough as a lung cancer symptom and encourage people with the symptom to visit their GP. This was piloted regionally within England before a nationwide rollout.Methods:To evaluate the campaign's impact, data were analysed for various metrics covering public awareness of symptoms and process measures, through to diagnosis, staging, treatment and 1-year survival (available for regional pilot only).Results:Compared with the same time in the previous year, there were significant increases in metrics including: public awareness of persistent cough as a lung cancer symptom; urgent GP referrals for suspected lung cancer; and lung cancers diagnosed. Most encouragingly, there was a 3.1 percentage point increase (P<0.001) in proportion of non-small cell lung cancer diagnosed at stage I and a 2.3 percentage point increase (P<0.001) in resections for patients seen during the national campaign, with no evidence these proportions changed during the control period (P=0.404, 0.425).Conclusions:To our knowledge, the data are the first to suggest a shift in stage distribution following an awareness campaign for lung cancer. It is possible a sustained increase in resections may lead to improved long-term survival.

ObjectivesTo link the Diagnostic Imaging Dataset (DID) to Hospital Episode Statistics (HES) to explore the association between patient imaging and hospital based care and outcomes for cancer patients in English NHS hospitals. This is the first time this linkage has taken place. The analysis also aims to look at how each patient first presented in HES (A&E, emergency admission, elective care, regular attendance), when and by what route relevant tests were requested and geographic variation in access to imaging ApproachPatient imaging records from the DID were linked to HES databases containing details of all inpatient, outpatient and A&E admissions at NHS hospitals in England in 2012/13 and 2013/14. Match rank criteria were developed to ensure that patients in HES were accurately linked to patients in DID by NHS number, date of birth and other unique identifiers. We used HES to identify patients with a lung cancer diagnosis and investigate their use of imaging and the temporal nature of tests to evaluate whether patients were following recommended pathways (e.g. having chest x-rays followed by CT scans before their lung cancer diagnosis) and the time between these events. Lung cancer patients were identified by developing an algorithm to search through diagnostic fields for clinical codes within HES databases. Where there was a lung cancer code the record was flagged and subsequently extracted. ResultsThe combined HES and DID datasets consisted of more than 340 million records. Within this large dataset we identified 49,888 patients with a lung cancer code in one of their HES diagnosis fields to a DID diagnostic image record for inpatient records alone. A high proportion (97%) of records were matched in one of the top 3 rank levels, suggesting the linkage was successful. The results illustrate the relationship between the imaging referral pathway and hospital episodes (e.g. surgical resection, emergency presentation). ConclusionsInvestigating how people engage with imaging services and hospital care will increase our understanding of the pathways associated with lung cancer diagnosis.The results from this analysis will contribute new knowledge about how lung cancer patients interact with hospitals and imaging services.

ObjectivesTo link the Diagnostic Imaging Dataset (DID) to cancer registration records to allow investigation of imaging performed in patients diagnosed with cancer and its relation to patient pathways and outcomes for lung and ovarian cancer patients diagnosed in England in 2013. ApproachAll available DID data from April 2012 until July 2015 were joined with registry data for all patients diagnosed with lung cancer in 2013, extracted from Public Health England's tumourlevel cancer records. Records were joined on NHS number and date of birth for individuals aged 15-99, with a non-provisional tumour record and with only one lung cancer diagnosis.One tumour can be linked to many imaging records. Because DID data are not limited to cancer-associated imaging, variables were created to flag imaging records that are likely to be related to the lung cancer diagnosis.Lists of imaging procedure (SNOMED) codes considered to be related to the cancer diagnosis were created in consultation with clinicians. Imaging records that took place in the 3 months prior to diagnosis and were on the list of relevant procedure codes were flagged as relevant records.The same method was replicated for ovarian cancer. The resulting linkage has highlighted issues with potential missing imaging data and this is being explored and will be reported upon. ConclusionThis is the first time linkage of DID and cancer registration data has taken place. The newly linked dataset will enable researchers to explore the imaging dataset further, with the potential to deepen understanding of issues such as imaging usage and intervals in imaging delivery.