Improving the diagnostic stage of the suspected colorectal cancer pathway: A quality improvement project

Healthc (Amst). 2016 Sep;4(3):225-34. doi: 10.1016/j.hjdsi.2015.09.004. Epub 2015 Sep 28.

Abstract

We aimed to improve the lead-time and the patient experience of the diagnostic stage of the suspected colorectal cancer pathway. This project worked within the constraints of limited resources and an austere environment. The core team included a project manager trained in quality improvement methodologies. Senior and Fleming's planned change model was used as the overall framework. Baseline data supported the case for change and highlighted targets for improvement. A stakeholder workshop employed social movement theory, lean thinking, experience-based design and patient stories to engage influential leaders and secure support and commitment. Solutions that arose from the workshop were then researched. A "Genchi Genbutsu" ethos took the team to Northumbria to learn about another unit's pathway innovations. Subsequently, our new pathway employed solutions aimed at increasing the proportion of patients who went straight-to-test. Consensus on the design was achieved using Schein's process consultation theory. Implementation of the new pathway resulted in a significant reduction in the median time from referral to endoscopy from 26 days to 14 days (P<0.001), and a significant increase in the proportion going straight-to-test from 6% to 43%. Changes to improve patient experience were also implemented, however data to evidence this has not yet been collected. Going forward, further standardisation is required and issues around sustainability need to be tackled. This project exemplified, amongst others, the value of working from data from the beginning and a comprehensive early stakeholder engagement.

Keywords: Colorectal cancer; Experience based design; Lean; PDSA; Process consultation; Quality improvement.

MeSH terms

  • Case Management*
  • Colorectal Neoplasms / diagnosis*
  • Critical Pathways*
  • Endoscopy / statistics & numerical data
  • Female
  • Humans
  • Leadership
  • Male
  • Program Evaluation
  • Quality Assurance, Health Care / methods*
  • Quality Improvement / organization & administration
  • Referral and Consultation / statistics & numerical data*
  • Time-to-Treatment
  • United Kingdom