JMIR Publications

ABSTRACT

Background:

Delays in diagnosing cancer in primary care occur when an opportunity to make a timely diagnosis is missed. Tools that minimise prolonged diagnostic intervals and reduce missed opportunities to investigate patients for cancer are therefore a priority.

Objective:

Explore the usefulness and feasibility of a novel quality improvement (QI) tool, in which algorithms flag abnormal results that may be indicative of an undiagnosed cancer. This study allows for optimisation of the cancer recommendations before testing the efficacy in a RCT.

Methods:

Qualitative study using individual interviews (n=17) and focus groups (n=18) with general practice and consumers. Participants were purposively sampled as part of a pilot and feasibility study. The Clinical Performance Feedback Intervention Theory was applied to the analysis using a thematic approach.

Results:

The key facilitators to use were alignment with workflow; recognized need; the perceived importance of the clinical topic; and the GPs’ perception that the recommendations were within their control. The key barriers to use were patient communication; usability and complexity of the recommendations; and knowledge of the clinical topic.

Conclusions:

There was a recognized need for the QI tool to support the diagnosis of cancer in primary care, but barriers were identified that hindered the usability and actionability of the recommendations in practice. In response, the tool has been refined and is currently being evaluated as part of a RCT. Successful and effective implementation of this QI tool could support the detection of patients at risk of an undiagnosed cancer in primary care and assist in preventing unnecessary delays.