Algorithm-Based Online Software for Patients' Self-Referral to Breast Clinic as an Alternative to General...

Introduction The study aimed to assess the accuracy of online software in the use of self-referral to breast surgery clinics for patients with new signs and symptoms. The study also evaluated the appropriateness of GP referrals to breast clinics and evaluated patients' perceptions of an online self-referral portal to the breast clinic for the assessment of breast signs and symptoms.  Design and methods The pilot study was divided into two phases. In the first phase, prospective questionnaire-based data was collected from patients who were referred by a GP and presented to the regional breast unit with new signs and symptoms for breast conditions, Princess Alexandra Hospital NHS Trust (May - October 2018). The questionnaire assessed the time at each stage required by the patient to have a visit at the breast unit. It also asked the patient's opinion about an online self-referral portal to the surgical clinic. They were given hypothetical scenarios to evaluate their understanding of breast conditions. In the second phase, the patients presenting to symptomatic breast clinics were provided with the iPad to fill in their medical information in the online software. The data was collected between July and October 2019. The software algorithm was based on the National Institute of Clinical Health and Excellence (NICE) guidelines for breast conditions (2015). Breast surgeons' recommendations acted as a standard to evaluate the accuracy of GPs' referrals and software outcome for each patient.  Results There were 80 patients (mean age 49.1 [SD: 17.7], all females) included in the first phase of the study. The most common clinical presentation was a breast lump (47.6%), followed by breast pain (26.9%) and nipple changes (7.9%). Breast surgeons considered appropriate 75.6% of the referrals made by the GP. Seventy-two percent of the patients got an urgent appointment to see their GP, and 94.8% of the patients were urgently referred by their GP to see the breast surgeon. Only 37.8% of the urgent referrals were correctly referred as urgent. Having a direct online referral system for breast conditions will be beneficial for patients was agreed by 78.4%. The majority (98.1%) of the participants answered correctly for the hypothetical questions requiring breast surgeon review. In the second phase, there were a total of 86 patients with a mean age of 43.9 (SD: 13.3). The most common presentation was breast lump (n=68, 79.1%) and other presentations included breast pain, nipple changes, and discharge. The GPs' accuracy of correct referral was 69.1%. One third (30.9%) of the referrals could have been managed in the community or as a routine review by the breast surgeon. In comparison, the online software's accuracy was 85.1% accurate (p=0.001). The accuracy for detecting patients who needed urgent breast clinic review was 100% for online software.  Conclusion A large proportion of referrals could have been dealt with in the community or referred routinely. Patients would prefer a direct online referral system to the breast clinic. They understand red flag signs and symptoms. Online software has the potential to streamline patients for symptomatic breast clinics. It can reduce the burden on the GPs who are constantly under pressure to diagnose patients accurately and refer to the correct specialty appropriately within a short time.