Development of a tailored, computerized, breast cancer risk assessment and decision support tool: What do clinicians want?

Background:End user input into the design of decision support tools is critical to enhance integration and future routine use in clinical practice. As part of the development of an evidence-based, tailored, computerised breast cancer (BC) risk assessment and management tool, we examined clinicians' requirements. Methods:Australian breast surgeons (BSs) and primary care clinicians (PCCs) were recruited through local professional networks. Facilitated focus group discussions about current practice of assessing and managing BC risk and perceptions of the proposed tool were audiotaped, transcribed and managed using QSR NVivo. A coding framework was developed based on the transcripts. Data were coded and analysed to identify key themes. Results:Four focus groups, involving 12 BSs and 17 PCCs (12 doctors, 5 practice nurses) were conducted. 55% were male, mean age 45 years (range 25–67), mean of 14 years in practice. Clinicians reported difficulties assessing and managing BC risk and lack of available tools to standardise their current approach to risk assessment and management. Most considered themselves confident in identifying potentially high risk women (women with multiple affected relatives and therefore potentially carrying high-risk mutations), but not in identifying women at moderately increased risk. They thought a tool would help reassure anxious women at lower risk and so avoid unnecessary referral or investigations. They thought desirable tool features would include: evidence-based, accessible (web-based), visual, simple data entry process, displays of absolute risk (not relative) and risk estimates in multiple formats (words, pictographs, graphs) to improve comprehension. Clinicians considered that women would be able to input risk factors before the clinic visit but that joint user and clinician data entry was preferable. Conclusions:Development of tools for BC risk assessment and management could benefit from addressing these needs of clinicians in order to optimise translation of current and future knowledge into clinical practice.