The complexity of diagnosing rare disease: An organizing framework for outcomes research and health economics based on real-world evidence

Robin Z Hayeems; Christine Michaels-Igbokwe; Viji Venkataramanan; Taila Hartley; Meryl Acker; Meredith Gillespie; Wendy J Ungar; Roberto Mendoza-Londona; Francois P Bernier; Kym M Boycott; Deborah A Marshall

doi:10.1016/j.gim.2021.11.005

The complexity of diagnosing rare disease: An organizing framework for outcomes research and health economics based on real-world evidence

Genet Med. 2022 Mar;24(3):694-702. doi: 10.1016/j.gim.2021.11.005. Epub 2021 Dec 3.

Affiliations

¹ Child Health Evaluative Sciences, The Hospital for Sick Children (SickKids), Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, The University of Toronto, Toronto, Ontario, Canada. Electronic address: robin.hayeems@sickkids.ca.
² Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada.
³ Child Health Evaluative Sciences, The Hospital for Sick Children (SickKids), Toronto, Ontario, Canada.
⁴ Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada.
⁵ Child Health Evaluative Sciences, The Hospital for Sick Children (SickKids), Toronto, Ontario, Canada; Institute of Health Policy, Management and Evaluation, Dalla Lana School of Public Health, The University of Toronto, Toronto, Ontario, Canada.
⁶ Division of Clinical and Metabolic Genetics, The Hospital for Sick Children (SickKids), Toronto, Ontario, Canada; Department of Pediatrics, Temetry Faculty of Medicine, The University of Toronto, Toronto, Ontario, Canada.
⁷ Department of Medical Genetics, Alberta Children's Hospital, Calgary, Alberta, Canada; Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Alberta, Canada.
⁸ Department of Genetics, Children's Hospital of Eastern Ontario, Ottawa, Ontario, Canada; Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada.
⁹ Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada; O'Brien Institute for Public Health, University of Calgary, Calgary, Alberta, Canada.

PMID: 34906497
DOI: 10.1016/j.gim.2021.11.005

Abstract

Purpose: To facilitate robust economic analyses of clinical exome and genome sequencing, this study was taken up with the objective of establishing a framework for organizing diagnostic testing trajectories for patients with rare disease.

Methods: We collected diagnostic investigations-related data before exome sequencing from the medical records of 228 cases. Medical geneticist experts participated in a consensus building process to develop the SOLVE Framework for organizing the complex range of observed tests. Experts categorized tests as indicator or nonindicator tests on the basis of their specificity for diagnosing rare diseases. Face validity was assessed using case vignettes.

Results: Most cases had symptom onset at birth (42.5%) or during childhood (43.4%) and had intellectual disability (73.3%). On average, the time spent seeking a diagnosis before sequencing was 1989 days (SD = 2137) and included 16 tests (SD = 14). Agreement across experts on test categories ranged from 83% to 96%. The SOLVE Framework comprised observed tests, including 186 indicator and 39 nonindicator tests across cytogenetic/molecular, biochemical, imaging, electrical, and pathology test categories.

Conclusion: Real-world diagnostic testing data can be ascertained and organized to reflect the complexity of the journey of the patients with rare diseases. SOLVE Framework will improve the accuracy and certainty associated with value-based assessments of genomic sequencing.

Keywords: Economic evaluation; Organizing framework; Outcomes research; Rare disease diagnosis; Real world evidence.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Exome Sequencing
Humans
Infant, Newborn
Outcome Assessment, Health Care*
Rare Diseases* / diagnosis
Rare Diseases* / genetics

Grants and funding

CIHR/Canada