Alison H. Trainer

Key Points: We evaluated a hub and spoke mainstreaming model to enable nephrologists to order genomic tests independently in their clinic across the state of Victoria. Over 1000 tests were ordered, with the diagnostic yield remaining similar regardless of ordered by local nephrologists or tertiary genomics services. A mainstreaming model proved feasible, scalable, and clinically effective, offering a practical framework for integrating genomics to routine kidney care. Background: Genomic testing has substantial diagnostic and clinical value in nephrology, yet integrating testing into routine care requires service-level changes to ensure timely and equitable access. Methods: We conducted an observational cohort study at four tertiary centers, with a pragmatic, quasi-experimental design to evaluate evidence-informed, service-level interventions to make genomic testing more accessible and routinely embedded within nephrology practice. We implemented a hub and spoke model which provided nephrologists with training, practical resources, and regular case-based discussions, to support test ordering and interpretation within their own clinics. Laboratory audits (June 2021–July 2024) evaluated how public reimbursement and implementation interventions influenced testing patterns. Three periods were compared: prefunding, postfunding, and postintervention. Results: Across the study period, 1028 genomic tests were ordered (63% adults, 37% children; median age 32 years). Results were available for 1014 tests, with an overall diagnostic yield of 34%, which remained stable across all time points. The diagnostic yield was similar regardless of whether testing occurred at tertiary genomics services (249 of 772, 32%) or via local nephrologists (92 of 242, 38%). The number of unique providers ordering tests was higher (T1: 37, T2: 69, T3: 87). The proportion of testing in mainstream nephrology settings rose from 23% to 74%, while absolute testing numbers in multidisciplinary clinics remained consistent over the study period. Conclusion: Mainstreaming genomic testing in nephrology was feasible, scalable, and clinically effective. This model was associated with better access without compromising diagnostic yield and provides a practical framework for integrating genomic medicine into routine kidney care.

Introduction: This project will establish a nationally consistent and ethically defensible approach to embed genomic testing in Australian primary care. Many non-genetic health professionals (eg, general practitioners (GPs) and other specialists) have limited experience with such testing. Current tests—both subsidised and consumer-paid—target a range of genes and conditions, making appropriate selection challenging. A structured implementation approach is therefore crucial. We will develop, test, refine and evaluate internationally relevant tools to support GPs and consumers in using genomics effectively. Methods and analysis: Aims of the project are to (1) develop, implement and evaluate key supports for GPs offering tests through three interventions: primary health point-of-care resources, a practical guide to dealing with ethical issues affecting clinicians and established recommendations for a national approach for genetic counsellors to support GPs providing genetic testing; (2) develop and evaluate consumer resources and plan the implementation strategies; (3) evaluate real-world utilisation and equity of access to genetic testing in primary care using linked Medicare and population data. This project will focus on two genomic applications recently made available in Australia on the universal insurance scheme (Medicare): a reproductive genetic carrier screen (an example of the role of genetics in reproductive testing) and genetic testing for familial hypercholesterolaemia (an example of a condition-specific test). Both tests can be complex for GPs to understand and explain to consumers and have potential implications beyond the purpose of the test (eg, personal health implications for carriers and results are also relevant to genetic relatives). Developing a robust clinical pathway and process for these tests will prepare GPs for future more complex applications of clinical genomics. The study will take place from January 2024 to December 2026. Ethics and dissemination: Ethical approval for this work has been received from the Macquarie University Human Research Ethics Committee (Ref: 520241849560183) and the Royal Children’s Hospital Research Ethics and Governance (HREC/112451). Findings will be disseminated via publications, conferences and engagement with primary care networks and policymakers.

Background: Health interventions delivered by digital platforms are gaining popularity and are evolving to address the needs of patients with chronic diseases. The heterogeneity of chronic diseases requires that digital health platforms vary in their approaches to chronic disease management. Objective: This review aimed to explore the characteristics of digital health platforms and the corresponding digital interventions developed to support patients with chronic diseases. This includes those platforms’ design, development, and the metrics by which any incremental benefits they provide are assessed. Methods: We searched electronic databases including Scopus, Web of Science, PsycINFO, IEEE Xplore, MEDLINE, and Embase. Relevant articles published from January 2013 to November 2024 were extracted. Extracted data were then synthesized using qualitative content analysis and presented in narrative form with relevant tables. Results: In total, we identified 69 digital health platforms supporting the management of 20 chronic diseases. Most platforms were mobile apps (n=22) or a combination of web and mobile apps (n=15). Most of the platforms (n=44) were tailored to support self-management of chronic diseases. These platforms also provided a web-based portal where health care providers could review and manage the information recorded by patients. In 77% (53/69) of the studies, patients reported that the digital interventions delivered by the platform improved their quality of life, their health, and their ability to self-manage their chronic diseases. In addition, health care providers reported positive outcomes, including improved clinical utility and patient communication. While short-term health outcomes of the digital health interventions were largely positive, long-term health outcomes remain unknown. This was because most of the studies were short-term pilots and often formative in nature (n=42). Many had limited sample sizes, limited participant uptake of the digital platforms, and technical issues. In many cases, further personalization of platforms was required to meet patients’ self-management needs. Conclusions: Digital health interventions can be beneficial in the management of chronic disease. The adoption of digital interventions in combination with regular clinical care can improve health outcomes, support self-management, and enhance communication between patients and health care providers. However, long-term user engagement is the major barrier to their long-term success. High dropout rates, often resulting from a lack of motivation or technical issues, testify to the need for adaptive, low-burden interventions that function seamlessly in users’ daily lives. Adopting user-centered and co-design approaches that engage both clinicians and patients in designing digital health platforms may enhance the usability and uptake of such platforms.

Background: The effectiveness and cost-effectiveness of genetic testing for hereditary breast and ovarian cancer largely rely on the identification and clinical management of individuals with a pathogenic variant prior to developing cancer. Simulation modelling is commonly utilised to evaluate genetic testing strategies due to its ability to synthesise collections of data and extrapolate over long time periods and large populations. Existing genetic testing simulation models use simplifying assumptions for predictive genetic testing and risk management uptake, which could impact the reliability of their estimates. Our objective was to develop a microsimulation model that accurately reflects current genetic testing and subsequent care in Australia, directly incorporating the dynamic nature of predictive genetic testing within families and adherence to cancer risk management recommendations. Methods: The populatioN gEnEtic testing MOdel (NEEMO) is a population-level microsimulation that incorporates a detailed simulation of individuals linked within five-generation family units. The genetic component includes heritable high- and moderate-risk monogenic gene variants, as well as polygenic risk. Interventions include clinical genetic services, breast screening, and risk-reducing surgery. Model validation is described, and then to illustrate a practical application, NEEMO was used to compare clinical outcomes for four genetic testing scenarios in patients newly diagnosed with breast cancer (BC) and their relatives: (1) no genetic testing, (2) current practice, (3) optimised referral for genetic testing, and (4) genetic testing for all BC. Results: NEEMO accurately estimated genetic testing utilisation according to current practice and associated cancer incidence, pathology, and survival. Predictive testing uptake in first- and second-degree relatives was consistent with known prospective genetic testing data. Optimised genetic referral and expanded testing prevented up to 9.3% of BC and 4.1% of ovarian cancers in relatives of patients with BC. Expanding genetic testing eligibility to all BC patients did not lead to improvement in life-years saved in at-risk relatives compared to optimised referral of patients eligible for testing under current criteria. Conclusions: NEEMO is an adaptable and validated microsimulation model for evaluating genetic testing strategies. It captures the real-world uptake of clinical and predictive genetic testing and recommended cancer risk management, which are important considerations when considering real-world clinical and cost-effectiveness.

Introduction Individuals at an inherited high-risk of developing adult-onset disease, such as breast cancer, are rare in the population. These individuals require lifelong clinical, psychological and reproductive assistance. After a positive germline test result, clinical genetic services provide support and care coordination. However, ongoing systematic clinical follow-up programmes are uncommon. Digital health solutions offer efficient and sustainable ways to deliver affordable and equitable care. This paper outlines the codesign and development of a digital health platform to facilitate long-term clinical and psychological care, and foster self-efficacy in individuals with a genetic disease predisposition. Methods and analysis We adopt a mixed-methods approach for data gathering and analysis. Data collection is in two phases. In phase 1, 300 individuals with a high-risk genetic predisposition to adult disease will undertake an online survey to assess their use of digital health applications (apps). In phase 2, we will conduct focus groups with 40 individuals with a genetic predisposition to cardiac or cancer syndromes, and 30 clinicians from diverse specialities involved in their care. These focus groups will inform the platform’s content, functionality and user interface design, as well as identify the barriers and enablers to the adoption and retention of the platform by all endusers. The focus groups will be audiorecorded and transcribed, and thematic and content data analysis will be undertaken by adopting the Unified Theory of Acceptance and Use of Technology. Descriptive statistics will be calculated from the survey data. Phase 3 will identify the core skillsets for a novel digital health coordinator role. Outcomes from phases 1 and 2 will inform development of the digital platform, which will be user-tested and optimised in phase 4. Ethics and dissemination This study was approved by the Peter MacCallum Human Research Ethics Committee (HREC/88892/PMCC). Results will be disseminated in academic forums, peer-reviewed publications and used to optimise clinical care.

Background Research identifying and returning clinically actionable germline variants offer a new avenue of access to genetic information. The psychosocial and clinical outcomes for women who have received this ‘genome-first care’ delivering hereditary breast and ovarian cancer risk information outside of clinical genetics services are unknown. Methods: An exploratory sequential mixed-methods case-control study compared outcomes between women who did (cases; group 1) and did not (controls; group 2) receive clinically actionable genetic information from a research cohort in Victoria, Australia. Participants completed an online survey examining cancer risk perception and worry, and group 1 also completed distress and adaptation measures. Group 1 participants subsequently completed a semi structured interview. Results: Forty-five participants (group 1) and 96 (group 2) completed the online survey, and 31 group 1 participants were interviewed. There were no demographic differences between groups 1 and 2, although more of group 1 participants had children (p = 0.03). Group 1 reported significantly higher breast cancer risk perception (p < 0.001) compared to group 2, and higher cancer worry than group 2 (p < 0.001). Some group 1 participants described how receiving their genetic information heightened their cancer risk perception and exacerbated their cancer worry while waiting for risk-reducing surgery. Group 1 participants reported a MICRA mean score of 27.4 (SD 11.8, range 9–56; possible range 0–95), and an adaptation score of 2.9 (SD = 1.1). Conclusion: There were no adverse psychological outcomes amongst women who received clinically actionable germline information through a model of ‘genome-first’ care compared to those who did not. These findings support the return of clinically actionable research results to research participants.

Personal Breast Cancer (BC) Risk Assessments (PBCRA) have potential to stratify women into clinically-actionable BC risk categories. As this could involve population-wide genomic testing, women’s attitudes to PBCRA and views on acceptable implementation platforms must be considered to ensure optimal population participation. We explored these issues with 31 women with different BC risk profiles through semi-structured focus group discussions or interviews. Inductive thematic coding of transcripts was performed. Subsequently, women listed factors that would impact on their decision to participate. Participants’ attitudes to PBCRA were positive. Identified themes included that PBCRA acceptance hinges on result actionability. Women value the ability to inform decision-making. Participants reported anxiety, stress, and genetic discrimination as potential barriers. The age at which PBCRA was offered, ease of access, and how results are returned held importance. Most women value the opportunity for PBCRA to inform increased surveillance, while highlighting hesitance to accept reduced surveillance as they find reassurance in regular screening. Women with BRCA pathogenic variants value the potential for PBCRA to identify a lower cancer risk and potentially inform delayed prophylactic surgery. This study highlights complexities in adopting advances in BC early detection, especially for current users who value existing processes as a social good.

Purpose: The increasing popularity of direct-to-consumer genetic testing (DTCGT) is thought to be creating a burden on clinical genetic health services worldwide. However, no studies have collected recent evidence regarding the extent of this impact in Australia. Methods: We administered an online survey to Australian clinical genetics services, asking questions related to DTCGT-related referrals received and outcomes over the past 10 years. Results: Eleven publicly-funded clinical genetics services completed the survey, reporting over 100 DTCGT-related referrals. Most referrals (83%) were made by general practitioners seeking interpretation of DTCGT results. More than 30% of referrals related to imputed genetic risk estimates generated from third-party web-based software tools. Services reported low validation rates for DTCGT results (<10%). Procedures for managing DTCGT referrals and granting appointments were variable between services, with most services (8/11) lacking specific procedures. Conclusion: Our study helps quantify the impact of DTCGT on clinical genetics services, and highlights the impact of imputed genetic risk estimates generated from third-party software.