Short-term outcomes of a COVID-adapted triage pathway for colorectal cancer detection.

AIM: The dramatic curtailment of endoscopy and CT colonography capacity during the coronavirus pandemic has adversely impacted timely diagnosis of colorectal cancer (CRC). We describe a rapidly implemented COVID-adapted diagnostic pathway to mitigate risk and maximize cancer diagnosis in patients referred with symptoms of suspected CRC. METHOD: The 'COVID-adapted pathway' integrated multiple quantitative faecal immunochemical tests (qFIT) to enrich for significant colorectal disease with judicious use of CT with oral contrast to detect gross pathology. Patients reporting 'high-risk' symptoms were triaged to qFIT+CT and the remainder underwent an initial qFIT to inform subsequent investigation. Demographic and clinical data were prospectively collected. Outcomes comprised cancer detection frequency. RESULTS: Overall, 422 patients (median age 64 years, 220 women) were triaged using this pathway. Most (84.6%) were referred as 'urgent suspicious of cancer'. Of the 422 patients, 202 (47.9%) were triaged to CT and qFIT, 211 (50.0%) to qFIT only, eight (1.9%) to outpatient clinic and one to colonoscopy. Fifteen (3.6%) declined investigation and seven (1.7%) were deemed unfit. We detected 13 cancers (3.1%), similar to the mean cancer detection rate from all referrals in 2017-2019 (3.3%). Compared with the period 1 April-31 May in 2017-2019, we observed a 43% reduction in all primary care referrals (1071 referrals expected reducing to 609). CONCLUSION: This COVID-adapted pathway mitigated the adverse effects on diagnostic capacity and detected cancer at the expected rate within those referred. However, the overall reduction in the number of referrals was substantial. The described risk-mitigating measures could be a useful adjunct whilst standard diagnostic services remain constrained due to the ongoing pandemic.

Development of a customised data management system for a COVID-19-adapted colorectal cancer pathway.

OBJECTIVES: A customised data management system was required for a rapidly implemented COVID-19-adapted colorectal cancer pathway in order to mitigate the risks of delayed and missed diagnoses during the pandemic. We assessed its performance and robustness. METHODS: A system was developed using Microsoft Excel (2007) to retain the spreadsheets' intuitiveness of direct data entry. Visual Basic for Applications (VBA) was used to construct a user-friendly interface to enhance efficiency of data entry and segregate the data for operational tasks. RESULTS: Large data segregation was possible using VBA macros. Data validation and conditional formatting minimised data entry errors. Computation by the COUNT function facilitated live data monitoring. CONCLUSION: It is possible to rapidly implement a makeshift database system with clinicians' regular input. Large-volume data management using a spreadsheet system is possible with appropriate data definition and VBA-programmed data segregation. The described concept is applicable to any data management system construction requiring speed and flexibility in a resource-limited situation.