Medios masivos

I took a number of steps to identify all incident cases of CRC in the study period. Firstly, I identified all patients with a code for CRC at any position in the HES record. Next, I identified all admissions to hospital for these patients, even if a given admission did not code for CRC. Finally, I removed patients that appeared to have the CRC code as co-morbidity and not as an incident case.

I showed that identifying cases that had a CRC code at any position, rather than just the primary diagnosis (or first position code) was a good way of capturing the maximum number of patients through the HES system. The advantage of this was especially apparent for emergency cases and patients that presented in extremis with a short survival from presentation. Identifying such patients was obviously important in attempting to understand the full spectrum of disease in England. Yet these cases could be missed if a presentation initially coded a symptom code such as rectal bleeding or obstruction at position

one, with CRC at a later coding position. In particular, patients presenting as an emergency are coded poorly, as are those who died during the presenting episode or shortly afterwards and did not have further elective admissions where the coding may have been more accurate. Therefore my methodological approach was likely to have made two significant adjustments not seen in traditional approaches; a) to identify a proportion of patients whose earliest contact with secondary care is with an emergency presentation that was not previously recognised because the CRC code was lacking and b) to include a group of patients not previously identified, those lacking a CRC code at position one. These patients will tend to have worse outcomes with a lower rate of surgery and higher one-year mortality rate than patients identified from primary diagnosis code alone. I believe this was one reason why the cohort study outcomes were slightly worse than similarly matched external reports (e.g. the NBOCAP report for 2006/7) - I was identifying some patients not picked up by other analyses of HES data and cancer registries. When considering the reverse possibility, that I had included patients with a CRC code as co-morbidity or coded incorrectly one needs to understand the steps taken to mitigate this risk. Identifying patients with the worst outcomes is important because they are the group with most to benefit from interventions. By reducing this variation in outcomes, the overall care of English patients with CRC will be improved.

By identifying all admissions for patients with one or more CRC codes, I maximised the information obtainable for each patient. Recording only episodes where CRC was coded would create a database of around 250,000 episodes, while my approach identified 360,000 episodes. This was especially important for identifying when the index admission was from an earlier relevant admission (see section 2.5.2.2). Without this analysis a day case admission for a diagnostic colonoscopy before the CRC1 admission would not have been identifiable as the ‘index admission’ despite its obvious relevance to the CRC pathway.

I also demonstrated methodological rigour by firstly searching for important codes at the episode level. This eliminated the possibility of missing a code only recorded in a finished consultant episode that was not recorded in the final episode for that admission.

Prevalent cases and cases incorrectly coded with CRC would initially have been captured by my approach. I needed refinement to remove these cases and to do so I made three adjustments to the cohort. Firstly, for any patient without a CRC code in the first two diagnostic positions at any admission I judged it unlikely that the case was active or new and these were excluded. Secondly, patients with a miscoding were removed; these were taken to be patients with more than one non-CRC gastrointestinal malignancy code and only a single CRC code. If there were two or more CRC codes then the patients was retained with the presumption this referred to synchronous cancers. Lastly, patients with a colorectal operation before the CRC1 were removed. Again the justifiable assumption was made that this was more likely to represent an operation for a cancer diagnosed before the start of the study period (i.e. a prevalent CRC case).

I incorporated other strategies to try and improve the study cohort’s accuracy. For example, I was aware that some hospitals have a policy of coding many more co-morbidities than others. This creates the ‘constant risk fallacy’ whereby patients of comparable health appear to have more co-morbidity in highly coding units. The effect of this is to imply these highly coding units have better outcomes for matched co-morbidity, compared to units that code less thoroughly. To mitigate against this, I restricted co-morbidity to three groups (0, 1 and more than 1) thus reducing the effect of case mixed adjustment caused by some units recording a much greater number of co-morbidities(244).