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Head and Neck Data

Head and Neck Data. Hannah Marder, Cancer Manager Prof Steve Thomas, Consultant Surgeon With thanks to Hannah Osguthorpe and Amelia Lowe for their assistance in producing the data. Dataset.

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Head and Neck Data

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  1. Head and Neck Data Hannah Marder, Cancer Manager Prof Steve Thomas, Consultant Surgeon With thanks to Hannah Osguthorpe and Amelia Lowe for their assistance in producing the data

  2. Dataset • Patients diagnosed between 01/06/2018 and 31/05/2019 inclusive and entered on the Bristol Cancer Register • Diagnosed with head and neck cancer, primary or recurrence, or with other cancers discussed at head and neck MDT (e.g. skin, CUP) • Data as at audit point – no work done to enter missing data • Manual grouping required post extraction (done by non-clinician with advice)

  3. Table 1a – Head and Neck cancers diagnosed by site and pathology - primary

  4. Table 1b – Head and Neck cancers diagnosed by site and pathology - recurrences

  5. Table 2 – Head and Neck primary cancers by treatment type AM = Active monitoring

  6. Table 3 – Head and Neck cancers (primary) with multiple surgeries (not including for separate recurrence)

  7. Table 4 – Head and Neck cancers (primary and recurrence) with mortality within 30 days of diagnosis 5/6 were for palliative treatment only due to advanced disease, cormorbidities or both. 1 patient had early stage disease and curative intent. Received radioiodine. Cause of death not recorded. Aged <50, had previous lymphoma as well as thyroid cancer. Note – mortality data (vital status and date of death if relevant) can be obtained, therefore longer term mortality than 30 days could be provided in future

  8. Table 5 – Head and Neck cancers by numbers of recorded CNS contacts NB: Will not include Bath CNS contacts

  9. Table 6 – Head and Neck cancers by TNM grouping

  10. Data requested by not currently routinely collected: • ACE 27 comorbidity (present on 0% records) • PEG dependence (present on 0% records) • Care plan intent and modality (present on 7% records) • Performance status (present on 3% records) • NB: Bath data e.g. CNS contacts will not be recorded on Bristol register

  11. Observations • Not all patients have started/completed all treatments – may need to look at more historic data to have better idea about full treatment packages • What counts as a ‘treatment’ under Cancer Waiting Time rules may not count as a treatment in the eyes of the clinical team. For example, a debulking would count as a treatment under waiting time rules but may not be considered part of the treatment package by the clinicians. These data use waiting times information.

  12. Observations (2) • Stage grouping is very difficult to ascertain, especially for non-clinical staff • Data completeness is an issue in several areas – the information can often be found in free text, but entry into specific boxes is needed to be useful for analysis. Collection live in MDT is possible, but needs sufficient time to do. There is insufficient resource to enter all the data retrospectively into the boxes.

  13. Next steps • Select one or two key audit questions and agree to collect data on these for next six months • Present the results at the next meeting • Discuss resource to complete the missing fields more fully – collection live in MDT is most efficient and can be easily done but needs sufficient time per discussion

  14. PATHOS audit • All potentially eligible patients diagnosed with head and neck cancer from trial start to census date (31/05/19) checked (includes RUH patients, where trial entry information may not be avialable) • 7 eligible and entered • 6 eligible and offered but not entered • 23 apparently eligible and apparently not offered

  15. PATHOS audit (2) • Next steps – clinical check of the 23 patients to identify if they really were eligible, and if so, were they offered the trial, and if not, why not • Identify any actions to improve recruitment based on the reasons not offered (if any rectifiable reasons exist) • Observation – the trial was mentioned regularly in clinic letters early in the trial, less often in more recent letters

  16. Clinical trials and data • (Some) clinical trials now stop the waiting time clock which means there is a performance benefit in participating – useful to mention if applying to start trials! • If the right data are collected in reportable fields, automated tools to check potential eligibility could be developed

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