Recommendations for designing genetic test reports to be understood by patients and non-specialists

Abstract

Patients and non-specialist healthcare professionals are increasingly expected to understand and interpret the results of genetic or genomic testing. These results are currently reported using a variety of templates, containing different amounts, levels, and layouts of information. We set out to establish a set of recommendations for communicating genetic test results to non-expert readers. We employed a qualitative-descriptive study design with user-centred design principles, including a mixture of in-person semi-structured interviews and online questionnaires with patients, healthcare professionals and the general public. The resulting recommendations and example template include providing at-a-glance comprehension of what the test results mean for the patient; suggested next steps; and details of further information and support. Separation and inclusion of technical methodological details enhances non-specialists' understanding, while retaining important information for specialists and the patients' records. The recommendations address the high-level needs of patients and their nonspecialist clinicians when receiving genetic test results. These recommendations provide a solid foundation for the major content and structure of reports, and we recommend further engagement with patients and clinicians to tailor reports to specific types of test and results.

Clinical validation, implementation, and reporting of polygenic risk scores for common diseases

“…[47][48][49][50][51] Another laboratory could use the methods we describe to produce measures of continuous risk or of categorical risk at different thresholds thought to be clinically meaningful, which will likely vary between diseases. Modeling the prevailing scenario in clinical medicine in which a treating clinician orders a laboratory test for a patient and then receives the results, the content and format of the PRS report mirror those of a more traditional molecular diagnostic report, [64][65][66][67] written for clinicians and not explicitly for patients.…”

“…Based on the above validation, we produced a PRS report consistent in format and content with other clinical genetic test reports (Supplemental File 2). [64][65][66][67] That is, it includes a description of the test performed and a prominently displayed summary of important ndings and their interpretations, including any monogenic disease variants identi ed and any PRS indicating increased polygenic disease risk. A graphic highlights in red the disease(s) for which the patient has increased polygenic disease risk.…”

Design and user experience testing of a polygenic score report: a qualitative study of prospective users

“…Therefore, they cannot be summarized using Human Genome Variation Society (HGVS) nomenclature and classified by pathogenicity as is recommended for monogenic reports by the American College of Medical Genetics (ACMG), European Society of Human Genetics, and the Association for Clinical Genetic Science [13][14][15][16]. Further, Farmer et al, recommends the use of a neutral statement of fact to summarize genetic results on a report, such as 'a change in gene XYZ was found' [17]. However, since a polygenic score can only be calculated on the basis of genome-wide variation and interpreted in the context of comparison to a population, a parallel statement does not exist.…”

“…Recommendations for designing genetic test reports for both patients and non-genetics providers published by Farmer and colleagues provide a foundation for the creation of genetic test reports that expand beyond diagnosis of a monogenic disease [17]. However, the authors concluded that additional research is needed to tailor these reporting recommendations for polygenic scores.…”

Making prognostic algorithms useful in shared decision-making: Patients and clinicians’ requirements for the Predict:Breast Cancer interface

“…The user-centred design process is widely used in industry and considered best practice when designing interactive systems. The use of UCD in a medical context is less common but increasingly recognised as important [14][15][16]. We outline how we applied the UCD process to the Predict:Breast Cancer interface, and highlight insights that may help others ensure prognostic models maximise their potential to help with shared decision-making.…”