Rare diseases are defined by prevalence. In the European Union (EU), a disease is considered to be rare, if it affects less than 5 of 10,000 people. In the United States of America (USA) a rare disease is defined as affecting less than 200,000 inhabitants, translating to a prevalence of about 8–9 out of 10,000 people.(1) About 30 million people in both the EU and the USA are suffering from a disease that is considered a rare disease.(2, 3)
Orphanet is a 37-country network, aiming to increase knowledge of rare diseases. It was cofounded by the European Commission in 1997. As of 2020, classification and descriptions of 6,172 rare diseases are included in the Orphanet database; 71.9% being genetic and the onset of symptoms occuring in 69.9% during childhood. About 85% of rare diseases are ultra-rare with a prevalence of less than 1 per 1,000,000.(1)
Many rare diseases are severe chronic conditions with a complex clinical presentation and a negative impact on life expectancy and quality of life.(4) Prevention and cure as well as adequate therapies exist only for a minority of rare diseases.(5)
Implications for Patients
Patients with rare diseases face a multitude of disease-related problems. Starting with delayed diagnosis, multiple doctor’s visits before a diagnosis is made, misleading diagnosis, lack of comprehensive information provided at the time of diagnosis, insufficient coordination of care, inadequate transition from paediatric to adult care, and low or non-existent access to medication due to poor knowledge or lacking research and clinical trials. Patient organizations play a vital role in improving these circumstances.(6, 7)
Implications for Physicians
Due to the large number of rare diseases it is impossible for a single doctor to be familiar with all of them. Especially general practitioners, who are the first contact for many patients, feel insufficiently trained in detecting rare diseases and often lack close interdisciplinary collaboration.(8)
Implications for Researchers
For researchers, one of the main obstacles is to include an adequate number of patients in clinical trials. This is a problem with any rare disease but especially affects the ultra-rare diseases. To improve this situation, collaboration of multiple centres of expertise nationwide, in some cases internationally, is needed. Therefore, research networks have started to coordinate research projects and implement highly standardized structures of data collection and sharing.(2, 9, 10)
Implications for the Economy
Patients with rare diseases generate a lot of health care expenditures. Unnecessary costs occur especially during the time before a diagnosis is established: Multiple health care contacts over a period of up to 30 years have been documented.(7) Inadequate utilization of costly therapies due to incomplete diagnosis or false indication is another reason for waste of resources.
Actions for Rare Diseases
Initiated by patient organizations, rare diseases have gained attention in politics over the last decade. Driven by European legislative requirements, national strategies for the improvement of care in rare diseases had to be developed.(11) In Germany, the National Action Plan for People with Rare Diseases implemented 52 measures to improve health care for patients with rare diseases. Some examples are: Recommendations for the implementation of national centres of expertise, specific measures to accelerate time to diagnosis, research support, improvement of information management as well as suggestions on financing of these measures.(12)
Concerning research, the development of a registry toolbox for creating individual disease-specific registries was requested. This registry toolbox should make use of an open source software with a defined minimal data scheme and an emphasis on interoperability on a national and international level as well as metadata management.(12) This project was conducted collaboratively by the Institute of Medical Biometrics, Epidemiology and Informatics of the University Medical Center of the Johannes Gutenberg University Mainz and the University Hospital Frankfurt in 2013 as part of the German National Action Plan and yielded the “Open Source Registry System for Seltene Erkrankungen (OSSE)”. OSSE is an easily scalable and customizable template for developing disease specific rare disease registries automatically connected to a meta data repository and fulfilling FAIR criteria. Further development is since ongoing by the Medical Informatics Group (MIG) of the University Hospital Frankfurt.(12–15)
To improve timely and correct diagnosis for patients with rare diseases, the development of a ‘registry for undiagnosed patients’ was also recommended by the German National Action Plan, taking into account that a high percentage of these ‘undiagnosed patients’ eventually are diagnosed to have a rare disease.(12)
Similar National strategies have been developed in most member states of the European Union as well as Norway, Switzerland and the UK.(16) Some international examples are: The National Institutes of Health Undiagnosed Diseases Program, which started in 2008(17); the “Nan-Byo” (which translates as “difficult and illness”), which was established in 1972 in Japan and extended in 2015 as Japan’s Initiative on Rare and Undiagnosed Diseases(18); Just recently, in February 2020, the Australian government announced to provide funding for activities to implement the National Strategic Action Plan for Rare Diseases, which was developed by Rare Voices Australia.(19)
Registries for Rare Diseases
Registries in general and especially in the field of rare diseases can help to connect data from multiple health care providers (HCP), thus enlarging the data base for research questions, including epidemiology of rare diseases. However, disease-specific ICD-10 codes are not available for most rare diseases and Orpha-codes, OMIM-codes or alpha-IDs are not used in routine clinical care. Therefore, prevalence calculated from disease-specific registries have limited accuracy.(20, 21) And, of course, usually academia driven registries do not achieve sufficient representation of the whole disease population to allow calculation of prevalence.
Due to the fact that undiagnosed patients present with a wide variety of symptoms at different levels and specialities within the health care system, it is even more complicated to assess the number of undiagnosed patients. With a nationwide registry, the impact of undiagnosed patients on the health care system could be estimated. In addition, it could accompany patients on their way to diagnosis, pointing out structural problems in the health care system. As soon as a patient is diagnosed and agrees to data-sharing, the collected data set could be transferred to a disease-specific registry, if such a registry exists. This would help in gaining patients and data for disease-specific research questions as well as connecting different centres of expertise to work together more closely.
With the help of medical informatics and big data analysis, case similarity analysis could be realized and aid as a decision-support tool probably facilitating diagnosis for some patients.
As most medical registries focus on one specific disease or group of diseases, they contain disease-specific and disease-relevant data. Patients, who are not yet diagnosed do not fit into these registry schemes. Therefore, in this paper we focus on the question on how such a registry for undiagnosed patients can be built and which information it should contain.