Value of diagnosis

How the value of a diagnosis can be an end in itself – even where there is no change in outcomes or management

Patients and families with rare genetic diseases often face a lengthy odyssey in their quest for diagnosis; a quest that can span many years (7 years on average) and frequently involves dozens of specialists and tests. As the world embraces a call to end the diagnostic odyssey for patients with rare diseases, the question of the value of a diagnosis gains importance.

Sharing the data

In Canada, the Care for Rare research consortium increasingly relies on multinational federated data sharing platforms such as Matchmaker exchange (MME) to facilitate the matching of cases with similar profiles based on their observable characteristics and genes to identify unsolved cases of rare disease.

A federated data system is a type of meta-database that interconnects multiple databases while maintaining security and privacy. The federated data system can be queried by multiple parties to enable solutions to diagnosis, treatment for patients with rare disease and offer recruitment to relevant trials. The success of MME is illustrative of the potential value of larger scale data-sharing platforms in increasing diagnosis rates, reducing unnecessary testing and shortening the lengthy diagnostic odyssey.

Value of diagnosis when there is no cure

Sometimes diagnostic testing provides an answer that enables appropriate treatment or changes in management which improves health outcomes and reduces unnecessary testing and treatments. One of the challenges is understanding the value of a diagnosis even in the absence of these changes in treatment or management – that is the intrinsic value of the information itself. Another challenge is capturing the value of a negative result that rules out a disorder and the reassurance to someone of this type of finding. These are challenges in diagnostic testing in general, and particularly salient to rare diseases.

Patient-preference research methods

“Patient-preference research methods” can help explain and quantify these values. These methods have been used in health and healthcare, including a few studies in valuing genetic testing for rare diseases.

Patient-preference research methods, are a rigorous quantitative approach to eliciting and assessing the relative desirability of a health intervention or service such as genetic testing. Patient preferences reflect how much something matters to a patient (i.e. how much they value something) and what benefit and risk tradeoffs patients are willing to make. These methods provide a theory-based experimental approach to eliciting and analysing patient-reported preferences.

Knowledge provides relief

The following examples illustrate how patient preference methods can be used to address some of the challenges of understanding the value of a diagnosis. One study found that Canadian parents of children with rare diseases were willing to pay:

In another study looking at a representative sample of American adults, 62% were interested in basic genomic test results and were willing to pay on average $299. In contrast, 45% of respondents were interested in additional test results for which medical treatment is currently unclear and were willing to pay on average $180 for this information. These findings show that additional information is of substantial value over and above the basic testing even when it had no direct or immediate implications.

Expansion of federated genomic sharing networks and collaboration on larger scale health and economic studies to assess the value of such systems, including assessing the value of a diagnosis and of diagnostic testing is urgently required. These multinational collaborations will be critical to supporting the global challenge to end the diagnostic odyssey for rare-disease patients.

Deborah Marshall, Professor, Department of Community Health Sciences and Medicine, Arthur J.E. Child Chair Rheumatology Outcomes Research, Alberta Children’s Hospital Research Institute, McCaig Institute for Bone and Joint Health, O’Brien Institute for Public Health, Cumming School of Medicine, University of Calgary

Francois Bernier MD, Head and Professor, Department of Medical Genetics, Section Head, Clinical Genetics, Department of Paediatrics, Alberta Children’s Hospital Research Institute, Cumming School of Medicine, University of Calgary.

Gillian R. Currie, Adjunct Associate Professor, Departments of Paediatrics and Community Health Sciences, Alberta Children’s Hospital Research Institute, O’Brien Institute for Public Health, Cumming School of Medicine, University of Calgary

Karen V. MacDonald MPH, Department of Community Health Sciences, Cumming School of Medicine, University of Calgary