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- Title
Learning from new colorectal cancers: a qualitative synthesis of significant event reports.
- Authors
Cooper-Moss, Nicola; Bajpai, Achint; Smith, Neil; David Merriel, Samuel William; Chauhan, Umesh
- Abstract
Background: Colorectal cancer is the second leading cause of cancer-related mortality in the UK 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: To provide additional insights into diagnostic processes for colorectal cancer and to identify areas for improvement in patient care pathways. Design & setting: Fifty-three 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. In total, 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. The following four main sub-themes were also identified: 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.
- Subjects
MEDICAL protocols; QUALITATIVE research; INTERPROFESSIONAL relations; RESEARCH funding; PRIMARY health care; EARLY detection of cancer; COLORECTAL cancer; DESCRIPTIVE statistics; THEMATIC analysis; COMMUNICATION; QUALITY assurance; DATA analysis software; DISEASE complications
- Publication
BJGP Open, 2024, Vol 8, Issue 2, p1
- ISSN
2398-3795
- Publication type
Article
- DOI
10.3399/BJGPO.2023.0088