Learning from new colorectal cancers: a qualitative synthesis of significant event reports

Cooper-Moss, Nicola orcid iconORCID: 0000-0003-0527-6287, Achint, Bajpai, Smith, Neil, Merriel, S W D and Chauhan, Umesh orcid iconORCID: 0000-0002-0747-591X (2023) Learning from new colorectal cancers: a qualitative synthesis of significant event reports. British Journal of General Practice (BJGP) Open .

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Official URL: https://doi.org/10.3399/BJGPO.2023.0088

Abstract

Background Colorectal cancer is the second leading cause of cancer-related mortality in the United Kingdom and a significant contributor to morbidity and mortality worldwide. Early diagnosis provides opportunities for intervention and improved survival. Significant Event Analysis (SEA) is a well-established quality improvement method for learning from new cancer diagnoses.

Aim This study aimed to provide additional insights into diagnostic processes for colorectal cancer and to identify areas for improvement in patient care pathways.

Design & setting 53 general practices across Pennine Lancashire, England, submitted one or more SEA reports as part of an incentivised scheme.

Method A standardised data collection form was used to collate learning points and recommendations for improvements. 161 reports were analysed using an inductive framework analysis approach.

Results There was an overarching theme of building vigilance and collaboration between and within general practices and secondary care. Four main sub-themes were also identified including education, individualised and flexible care, ownership and continuity, and communication.

Conclusion These findings provide additional insights into colorectal cancer pathways from a primary care perspective. Practices should be supported in developing protocols for assessment and follow-up of patients with varying presentations. Screening and access to investigations are paramount for improving early diagnosis, however, a flexible diagnostic approach is required according to the individual circumstances of each patient.


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