dVP_FAM-development and evaluation of a transsectoral digital care platform for individuals with familial cancer risks: study protocol for a multi-centre, cluster-randomised, mixed-methods study

Abstract

Background: Individuals with a family history of cancer face an increased risk of developing breast and ovarian cancer. Up to 30% of the 70,000 annual breast cancer cases in Germany are associated with a familial cancer burden. Early identification of these risks is crucial as personalised measures can enable early detection or prevention of cancer. Primary care gynaecologists are uniquely suited to assess family histories and facilitate referrals to hereditary cancer centres. However, solutions on how to support early referral are still lacking. This study evaluates the impact of the digital care platform dVP_FAM as a potential remedy compared to standard care. The primary hypothesis is that the platform will increase the proportion of care-seeking women with a familial cancer risk who have not yet developed cancer. Secondary outcomes include improvements in care efficiency, patient empowerment, and health-related quality of life.

Methods: The study is a multi-centre, cluster-randomised, mixed-method trial involving 44 gynaecological centres and 800 participants recruited through hereditary breast and ovarian cancer centres. All participants receive standard guideline-based care, while the intervention group also uses the dVP_FAM platform. The primary endpoint measures the proportion of participants with a familial cancer history who are cancer-free when seeking specialist counselling. Secondary outcomes are assessed using validated tools like the SF-12 and custom measures. Data collection employs a convergent mixed-methods approach, integrating quantitative and qualitative evidence.

Discussion: The dVP_FAM platform represents an innovative approach to digitising cancer prevention in Germany, enhancing early detection and care coordination. If successful, dVP_FAM could serve as a scalable model for digital health innovations, improving efficiency and modernising the delivery of personalised care across health systems.

Trial registration: German Clinical Trials Register, DRKS00030371 . Registered on 02 October 2023.

Keywords: Cancer prevention; Digital health; Early detection; Familial cancer risk; Genetic counselling; Healthcare efficiency; Hereditary breast and ovarian cancer; Patient empowerment; Primary care gynaecologists; Quality of life.