Several studies within and outside the US show that delays in cancer diagnosis are common. While studies of patients with newly diagnosed colorectal cancer have shown that 34%-65% had missed opportunities for earlier diagnosis and among patients with lung cancer, 38% had missed opportunities for earlier diagnosis, this area has not been subjected to measurement for quality improvement in the US. This is a key opportunity because late initiation of cancer treatment has been associated with higher mortality and causes of delayed diagnosis are multifactorial. The diagnosis of colorectal cancer (CRC) and lung cancer requires recognition of certain signs or symptoms and/or abnormal cancer screening tests (red-flags). Once these red-flags are recognized, patients should be referred for further diagnostic work-up. Research by our team and others suggests that doctor recognition of or action on these red-flags is not fail-safe.
Further, failures in communication and follow-up of abnormal test results suspicious for cancer (e.g., a chest x-ray with a nodule) are also common, possibly also reflecting system factors. Health systems need improved tools and strategies for comprehensive measurement and feedback related to preventable cancer delays. Although EHRs have collected enormous amounts of electronic data, these data must lead to actionable information to improve patient care through meaningful, reliable, and transparent metrics.
- Project Lead: Prof Hardeep Singh
- Senior CanTest Lead: Prof Hardeep Singh
- Others involved: Prof Yoryos Lyratzopolous (UCL), Dr Gary Abel (University of Exeter), Dr Andrew Zimolzak (IQuESt), Dr Daniel Murphy (IQuESt), Dr Divvy Upadhyay (Geisinger), Lisa Zubkoff (Dartmouth)
Aims & Objectives
Aim: To create e-measures to reduce preventable delays in lung and colorectal cancer diagnosis by identifying missed opportunities for diagnosis.
We will develop e-measure algorithms to find instances of missed opportunities for diagnosis in the electronic health record. In particular, we will examine “red flags” (e.g. a previous abnormal test result possibly indicating the presence of cancer without appropriate follow up), emergency presentations of cancer, and diagnosis of cancer at an advanced stage.
For measure development and application, we will build on our prior experience developing trigger tools. We will use the Safer Dx e-Trigger Tool Development framework, previously developed by our team for e-trigger development. This framework divides development into steps, including operationalization, data identification, testing, and assessment, that we are adapting to develop e-measures for this project.
Outputs & Impacts
Once the project is complete, there will be three validated measures for use in further research and quality improvement.
We envision that measurement can be automated in the future. We have experience working with institutions to operationalize e-triggers [https://www.ncbi.nlm.nih.gov/pubmed/30291180] and because of the emphasis on less manual effort, these e-measures could be similarly exportable.
- Singh H, Thomas EJ, Khan MM, Petersen LA. Identifying diagnostic errors in primary care using an electronic screening algorithm. Arch Intern Med, 2007. doi: 10.1001/archinte.167.3.302
- Murphy DR, Laxmisan A, Reis BA, Thomas EJ, Esquivel A, Forjuoh SN, Parikh R, Khan MM, Singh H. Electronic health record-based triggers to detect potential delays in cancer diagnosis. BMJ Quality & Safety, 2014. doi: 10.1136/bmjqs-2013-001874