The 33 cases audited were collected in Professor Tilyard’s survey retrospectively on the selective basis of a perceived missed or delayed diagnosis of bowel cancer. The review was to recommend actions regarding: Colonoscopy Capacity and Provision, Referral Process, and Timely Access to Colonoscopy.

Additional information:

Have_(encrypted)_NHI Yes
Personally identifiable (e.g. linked to NHI numbers) and longitudinal or aggregated (e.g. for planning, clinical research etc.)? NHI
Volume of data (e.g. how many records) Since when? 33 cases
Scope Regional
Does the data contain diagnoses and clinical outcomes? Does the data contain procedures, device information and medication for therapy? Does this data set have cost / price data? Yes - Dx
Indication of data quality (e.g. missing values, duplications, inconsistencies etc.). Q: Audits? How do you ensure the data is valid and correct? Quality control was built into the data collection process. Following the review of the five initial cases, the information collated in the data collection tool and the additional narrative information collated in the Word document, were sent to the two independent clinical advisors for assessment regarding the quality of the data capture prior to more data being collated. Midway through the process this procedure was repeated to ensure that ongoing data capture was robust.
Brief info about the systems and processes used to collect/manage data. Q: Where the data is collected, in what form, and accessibility? The audit reviewed the process from referral to receipt or not of colonoscopy. The data sources for this audit included the following documentation: • Hospital records; hard and electronic copy • GP letters of referral • Colonoscopy Review Panel Summary List
Data format, e.g., data structure, data types, and storage form (relational database, Excel, csv, etc.). three types of data: dichotomous variables, dates and free text.