Typically, the first major burden for those affected is getting the correct diagnosis. Unfortunately, this is often a lengthy and complex process accompanied by a range of corresponding challenges.
For example, in a survey conducted by EURORDIS of 12,000 patients with rare disease, over 40% of patients are initially misdiagnosed (fig 1). Moreover, results from the survey show that patients visit an average of 7.3 physicians before an accurate diagnosis is given, with an average time to diagnosis between 7.6 to 5.6 years in the US and UK, respectively.
Adapted from EURORDIS-Voice of 12,000 patients
A multitude of medical informatic solutions exist to help health care providers identify and confirm rare disease diagnoses, particularly for rare diseases arising on a genetic basis, which account for an estimated 80% of cases.
Freely available, searchable, comprehensive online databases of genetic disease phenotypes and human genes are available through resources, such as the Online Mendelian Inheritance in Man (OMIM) database, accessible through the NCBI database portal.
Together with newer AI-based searchable database applications, including FindZebra , Phenomizer, and image based genetic syndrome identification tools, such as Face2Gene,healthcare providers are bolstered in reducing diagnostic odysseys by an ever-increasing armamentarium of resources to construct a rare disease differential diagnosis.
Once a most likely diagnosis is identified, healthcare providers can utilise existing additional bioinformatic repositories to identify potential genetic testing laboratories, such as the Genetic Testing Registry (GTR). This a searchable centralised database of genetic tests, also accessible through the NCBI database portal, facilitates molecular confirmation of clinical suspicion.
Once a diagnosis has been reached, innovative software solutions can support the search for the right but often also rare experts. Here, comprehensive databases, such as se-atlas or Orphanet, can provide support, as well as the American College of Medical Genetics and Genomics (ACMG) “Find a Genetic Clinic” searchable database.
Medical informatics is also facilitating connections between clinicians, researchers, and patients. For example, resources such as the Matchmaker Exchange use a network of application programming interface-connected genomic and phenotypic data to match individuals with a shared interest or experience in similar rare genetic disorders and genetic variations. Another avenue for creating connections is social media. However, while social channels do offer opportunities, they also harbour risk.
In the case of rare diseases, there is a need to collect data tailored to the respective disease. Disease-related patient registries are particularly well-suited for this purpose. Due to their specificity, the quality-assured data these registries collect is much more suitable than the pure analysis of health care data. However, integrating analysis of such register data with health care data analysis can be advantageous.
Two aspects are challenging here. On the one hand, the usually small stakeholders of a particular rare disease often only have access to limited resources and possibilities to build up a register that fits the data models of state-of-the-art systems.
On the other hand, researchers who could derive great benefit from such data sources have little chance of finding these data treasures in the first place. The experts are often widely distributed, which makes cooperation difficult.
A similar barrier is also found in data collection. In most cases, different data sets are not coordinated, and as a result they are only compatible with each other to a limited extent. Difficulties at the organisational and legal levels can further complicate the issue of data management.
One important goal of initiatives like the European Joint Programme on Rare Diseases (EJP-RD) is to support researchers to find available resources for rare disease research activities, such as data sets or biomaterial.
To achieve this, different sources are identified, brought together, and made searchable via a metasearch functionality. That cooperation, which is that important in the research of rare diseases, is directly supported by technical solutions.
When addressing those mentioned challenges, medical informatics approaches offer good opportunities to improve the situation. For example, through IT support of the so-called FAIR (Findable, Accessible, Interoperable, Reusable) criteria.
FAIR criteria acts a guide for data producers and publishers as the landscape for medical informatics matures. With greater volumes of data being shared and distributed online, it is important to develop functional infrastructure that prioritises accessibility.
With a foundation of easy-to-access information, healthcare providers and life sciences companies can dedicate more time to developing new therapeutics and treatment options for patients.
Joanne M. Hackett is the Head of Genomic and Precision Medicine at IQVIA and previously was the Chief Commercial Officer at Genomics England.
Dr Hackett is a clinical academic, entrepreneur, investor, and a strategic, creative visionair with global experience spanning successful start-ups to Fortune 500 companies. Aside from her curious passion for life and positivity, Joanne is known for building innovation, driving personalised medicine and leading through fast paced, complex changing ecosystems and integrations. Joanne’s goal is to contribute in bringing the world novel, cost effective and simple health care solutions, and she is particularly keen on building the case for prevention, open science and citizen genomics. She has extensive global experience across academic, business and clinical institutions, and enjoys sharing her experiences with the Boards she sits on as well as companies she provides strategic advice to.
Joanne has been publicly recognised for her relentless pursuit of revolutionising healthcare and has been named one of the top six Influential Leaders in Healthcare by CIO Look, the Accenture Life Science Leader of the year, Freshfields Top 100 Most Influential Women, One HealthTech Top 70 Women in the NHS, Pharmaceutical Market Europe’s 30 women leaders in UK healthcare and BioBeat Top 50 Women in Biotech Award. Joanne believes in human courage and perseverance against the odds, and demonstrates that positive change, whether in a company or in one’s personal life, can be carved out from even the greatest of trials. As a believer of ‘health = wealth’, Joanne is an internationally known yoga instructor.
Dr David Tegay, is the senior medical director for IQVIA’s Pediatric and Rare Disease Center of Excellence, where he provides medical strategy to paediatric and rare disease programmes across the company.
Tegay has more than 20 years of experience as a practicing clinical geneticist across the spectrum of rare genetic disorders, with expertise in adult and paediatric genetic disease, neurogenetics, cardiogenetics, newborn screening and inherited metabolic disorders.
Prior to joining IQVIA, he served in multiple leadership roles at tertiary care academic medical centres.
Holger Storf heads the Data Integration Centre (DIC) at the University Hospital Frankfurt and leads the Medical Informatics Group (MIG) since November 2015. The DIC focuses on the exploitation, integration and provision of clinical routine and research data for different purposes. The MIG is focussed on designing and developing innovative software solutions close to application, especially in the field of rare diseases. Additionally, he is the CO-PI for Frankfurt of the MIRACUM-Consortium, funded in the German Medical Informatics Initiative and project leader of different national and EU-wide Rare Disease Registry-Projects and Dr. Storf continues coordinating the technical activities of the OSSE-project (Open Source Registry System for Rare Diseases). Holger Storf graduated from the Heidelberg University in 2007 with a diploma in Medical Informatics and finished his PhD in 2013. Before establishing the MIG he worked at the Institute for Medical Biometry, Epidemiology and Informatics (IMBEI) in Mainz for two years. Previously he worked for six years at the Fraunhofer Institute for Experimental Software Engineering (IESE) as a member of the Data Management & Ambient Technologies department in applied national and international research projects.
Dennis Kadioglu, M.Sc. is the deputy head of both the Medical Informatics Group (MIG) and the Data Integration Center (DIC) at the University Hospital Frankfurt in Frankfurt am Main. He graduated with a Master’s in Medical Informatics from the Fachhochschule Dortmund – University of Applied Sciences and Arts. His research focuses on the development of methods for improving the exploitation and integration of medical routine and research data for answering subordinate questions. He is known for the ongoing development and application of the software solution Data Element Hub (DEHub), which as a Metadata Repository holds reusable specifications about the data elements of a data set. In this field he contributes to various research projects like MIRACUM (funded in the German Medical Informatics Initiative by the German Ministry of Education and Research) and EJP-RD (funded in Horizon 2020 by the European Union) focusing on the development of adequate IT support to foster collaboration in medical research. This also includes the continuous development of the OSSE registry framework, which was developed specifically for the field of rare diseases.
IQVIA is a leading global provider of advanced analytics, technology solutions and clinical research services to the life sciences industry. IQVIA creates intelligent connections to deliver powerful insights with speed and agility — enabling customers to accelerate the clinical development and commercialization of innovative medical treatments that improve healthcare outcomes for patients. With approximately 77,000 employees, IQVIA conducts operations in more than 100 countries. Learn more at www.iqvia.com