Determining How Far an Adult Rare Disease Patient Needs to Travel for a Definitive Diagnosis: A Cross-Sectional Examination of the 2018 National Rare Disease Survey in China

Background: To investigate the multidimensional difficulties in accessing a definitive diagnosis of adult rare diseases and the associated impact factors in China. Methods: A total of 1010 adult rare disease patients from the 2018 China Rare Disease Survey were used for analysis. The Structural Equation Models examined the interrelationships among five accessibility indicators and the effects of three sets of impact factors. Results: (1) Accessibility: 72.97% of patients were misdiagnosed; they waited an average of 4.30 years and visited 2.97 hospitals before the definitive diagnosis; 67.13% were diagnosed outside the home city and traveled an average of 562 km. (2) Interrelationships among accessibility indicators: the experience of misdiagnosis significantly increased diagnosis delay and the number of hospitals visited, but had no significant effect on healthcare utilization across cities. (3) Impact factors: the rarity of disease only increased the number of hospitals visited and residence–hospital distance; high-quality healthcare distribution was key in determining accessibility; the older, disabled, poor, and less-educated individuals, and those in Central/West China were disadvantaged. Conclusion: The socioeconomic dimension of difficulties in accessing a definitive diagnosis of rare diseases should be attended, especially the uneven distribution of high-quality healthcare and those disadvantaged patients. More systematic rare disease surveys are needed in the future.

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Examining Trans-Provincial Diagnosis of Rare Diseases in China: The Importance of Healthcare Resource Distribution and Patient Mobility

Sustainability ◽

10.3390/su12135444 ◽

2020 ◽

Vol 12 (13) ◽

pp. 5444 ◽

Cited By ~ 1

Author(s):

Xiang Yan ◽

Dong Dong ◽

Shenjing He ◽

Chris Webster

Keyword(s):

Rare Disease ◽

Geographical Distribution ◽

Rare Diseases ◽

Accurate Diagnosis ◽

Long Distance ◽

High Quality ◽

Healthcare Resources ◽

Quality Healthcare ◽

Child Patient ◽

The Impact

(1) Background: Rare disease patients in China usually have to travel a long distance, typically across provinces, for an accurate diagnosis due to the uneven distribution of healthcare resources. This study investigated the impact factors of their trans-provincial diagnosis. (2) Methods: An analysis was made of 1531 cases (1032 adults and 499 children) garnered from the 2018 China Rare Disease Survey, representing a large patient community inflicted with 75 rare diseases from across 31 Chinese provinces. Logistic regression models were used for separate analysis of adult and child patient groups. (3) Results: Nearly half (47.2%) of patients obtained their accurate diagnosis outside their home provinces. The uneven geographical distribution of high-quality healthcare had a significant impact on variation in trans-province diagnosis. Adult patients with lower family income, rural hukou and severer physical disability were disadvantaged in accessing trans-provincial diagnosis. Families with a child patient tended to pour resources into obtaining the trans-provincial diagnosis. The rarity of the disease had only a minimal effect on healthcare utilization across the provinces. (4) Conclusions: In addition to medical care, more attention should be paid to the socioeconomic factors that prevent the timely diagnosis of a rare disease, especially the uneven geographical distribution of high-quality healthcare resources, the financial burden on the family and the differences between adult and child patients.

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Creating a global rare disease patient registry linked to a rare diseases biorepository database: Rare Disease-HUB (RD-HUB)

Contemporary Clinical Trials ◽

10.1016/j.cct.2010.06.007 ◽

2010 ◽

Vol 31 (5) ◽

pp. 394-404 ◽

Cited By ~ 57

Author(s):

Yaffa R. Rubinstein ◽

Stephen C. Groft ◽

Ronald Bartek ◽

Kyle Brown ◽

Ronald A. Christensen ◽

...

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Disease Patient ◽

Patient Registry ◽

Rare Disease Patient

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How to design a registry for undiagnosed patients in the framework of rare disease diagnosis – suggestions on software, data set and coding system

10.21203/rs.3.rs-122656/v2 ◽

2021 ◽

Author(s):

Alexandra Berger ◽

Anne-Kathrin Rustemeier ◽

Jens Göbel ◽

Dennis Kadioglu ◽

Vanessa Britz ◽

...

Keyword(s):

Open Source ◽

Rare Disease ◽

Rare Diseases ◽

Action Plan ◽

Correct Diagnosis ◽

Disease Patient ◽

Disease Diagnosis ◽

Clinical Findings ◽

Snomed Ct ◽

Data Set

Abstract Background: About 30 million people in the EU and USA, respectively, suffer from a rare disease. Driven by European legislative requirements, national strategies for the improvement of care in rare diseases are being developed. To improve timely and correct diagnosis for patients with rare diseases, the development of a registry for undiagnosed patients was recommended by the German National Action Plan. 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.Results: To develop a registry for undiagnosed patients, a software for data acquisition and storage, an appropriate data set and an applicable terminology/classification system for the data collected are needed. We have used the open-source software OSSE (Open-Source Registry System for Rare Diseases) to build the registry for undiagnosed patients. Our data set is based on the minimal data set for rare disease patient registries recommended by the European Rare Disease Registries Platform. We extended this Common Data Set to also include symptoms, clinical findings and other diagnoses. In order to ensure findability, comparability and statistical analysis, symptoms, clinical findings and diagnoses have to be encoded. We evaluated three medical ontologies (SNOMED CT, HPO and LOINC) for their usefulness. With exact matches of 98% of tested medical terms, a mean number of five deposited synonyms, SNOMED CT seemed to fit our needs best. HPO and LOINC provided 73% and 31% of exacts matches of clinical terms respectively. Allowing more generic codes for a defined symptom, with SNOMED CT 99%, with HPO 89% and with LOINC 39% of terms could be encoded.Conclusions: With the use of the OSSE software and a data set, which, in addition to the Common Data Set, focuses on symptoms and clinical findings, a functioning and meaningful registry for undiagnosed patients can be implemented. The next step is the implementation of the registry in centres for rare diseases. With the help of medical informatics and big data analysis, case similarity analyses could be realized and aid as a decision-support tool enabling diagnosis of some patients.

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How to design a registry for undiagnosed patients in the framework of rare disease diagnosis: suggestions on software, data set and coding system

Orphanet Journal of Rare Diseases ◽

10.1186/s13023-021-01831-3 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Alexandra Berger ◽

Anne-Kathrin Rustemeier ◽

Jens Göbel ◽

Dennis Kadioglu ◽

Vanessa Britz ◽

...

Keyword(s):

Open Source ◽

Rare Disease ◽

Rare Diseases ◽

Action Plan ◽

Correct Diagnosis ◽

Disease Patient ◽

Disease Diagnosis ◽

Clinical Findings ◽

Snomed Ct ◽

Data Set

Abstract Background About 30 million people in the EU and USA, respectively, suffer from a rare disease. Driven by European legislative requirements, national strategies for the improvement of care in rare diseases are being developed. To improve timely and correct diagnosis for patients with rare diseases, the development of a registry for undiagnosed patients was recommended by the German National Action Plan. 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. Results To develop a registry for undiagnosed patients, a software for data acquisition and storage, an appropriate data set and an applicable terminology/classification system for the data collected are needed. We have used the open-source software Open-Source Registry System for Rare Diseases (OSSE) to build the registry for undiagnosed patients. Our data set is based on the minimal data set for rare disease patient registries recommended by the European Rare Disease Registries Platform. We extended this Common Data Set to also include symptoms, clinical findings and other diagnoses. In order to ensure findability, comparability and statistical analysis, symptoms, clinical findings and diagnoses have to be encoded. We evaluated three medical ontologies (SNOMED CT, HPO and LOINC) for their usefulness. With exact matches of 98% of tested medical terms, a mean number of five deposited synonyms, SNOMED CT seemed to fit our needs best. HPO and LOINC provided 73% and 31% of exacts matches of clinical terms respectively. Allowing more generic codes for a defined symptom, with SNOMED CT 99%, with HPO 89% and with LOINC 39% of terms could be encoded. Conclusions With the use of the OSSE software and a data set, which, in addition to the Common Data Set, focuses on symptoms and clinical findings, a functioning and meaningful registry for undiagnosed patients can be implemented. The next step is the implementation of the registry in centres for rare diseases. With the help of medical informatics and big data analysis, case similarity analyses could be realized and aid as a decision-support tool enabling diagnosis of some undiagnosed patients.

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Patient Empowerment in Rare Diseases Slovak Rare Disease Alliance − Contribution to the Creation of the National Plan of Rare Diseases in Slovakia Eurordis – Benefits of Membership / Pacientske organizácie v oblasti zriedkavých chorôb – ich činnosť aj pri príprave národného plánu v SR slovenská aliancia zriedkavých chorôb Eurordis - európska aliancia zriedkavých chorôb – výhody členstva

Acta Facultatis Pharmaceuticae Universitatis Comenianae ◽

10.2478/afpuc-2013-0009 ◽

2013 ◽

Vol 60 (Supplementum-VIII) ◽

pp. 41-45

Author(s):

B. Ramljaková

Keyword(s):

Health Care ◽

Rare Disease ◽

Rare Diseases ◽

Disease Patient ◽

Insurance Company ◽

National Plan ◽

Patient Health ◽

The Creation ◽

Rare Disease Patient ◽

Care Development

After the endorsement of the National strategy of rare disease patient health care development for years 2012 - 2013 by the government of the SR on October 24, 2012, it is important for all participants in the process to get involved. (Who are all the participants? - doctors, pharmacists, scientist, national authorities, regulators, health insurance companies, social insurance company, health care and social workers, pharmaceutical industry, but also politicians, patients and patient organizations) Based on the experience and problems which are being solved by patients, it is necessary for POs to focus on areas important for the creation of NP RD in the SR. These are most of all: complex approach to patients based on a multidisciplinary team, inclusion of patients into decision making - an educated patient is a prerequisite for this; specialized services for RD patients and their families; integration of RD patients into existing health care and social system and help lines. Slovak Alliance of Rare Diseases (Alliance RD) was founded and registered at the Ministry of Interior of the SR on December 12, 2011. The reason for its foundation was the effort to solve problems in the area of RDs in a complex and systemic way, which is proved by its involvement in the creation of NP RD in the SR. It houses 12 POs working in the field of RD in Slovakia. The objective of the Alliance RD is to keep improving the health and social life conditions of rare disease patients and their families, to improve the quality of rare disease patients’ lives, and to support their social integration. In close cooperation with EURORDIS - Rare Disease Europe − it took part in EUROPLAN II (2012 - 2015), a project organized by the National conference for the support of the creation of National plan of rare disease patient health care development in Slovakia.

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How to Design a Registry for Undiagnosed Patients in the Framework of Rare Disease Diagnosis – Suggestions on Software, Data Set and Coding System

10.21203/rs.3.rs-122656/v1 ◽

2020 ◽

Author(s):

Alexandra Berger ◽

Anne-Kathrin Rustemeier ◽

Jens Göbel ◽

Dennis Kadioglu ◽

Vanessa Britz ◽

...

Keyword(s):

Open Source ◽

Rare Disease ◽

Rare Diseases ◽

Action Plan ◽

Correct Diagnosis ◽

Disease Patient ◽

Disease Diagnosis ◽

Clinical Findings ◽

Snomed Ct ◽

Data Set

Abstract Background: About 30 million people in the EU and USA, respectively, suffer from a rare disease. Driven by European legislative requirements, national strategies for the improvement of care in rare diseases are being developed. To improve timely and correct diagnosis for patients with rare diseases, the development of a registry for undiagnosed patients was recommended by the German National Action Plan. 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.Results: To develop a registry for undiagnosed patients, a software for data acquisition and storage, an appropriate data set and an applicable terminology/classification system for the data collected is needed. We used the open source software OSSE (Open Source Registry System for Rare Diseases) to build the registry for undiagnosed patients. Our data set is based on the minimal data set for rare disease patient registries recommended for European Rare Disease Registries Platform. We extended this Common Data Set to also include symptoms, clinical findings and other diagnoses. In order to ensure findability, comparability and statistical analysis, symptoms, clinical findings and diagnoses have to be encoded. We evaluated three medical ontologies (SNOMED – CT, HPO and LOINC) for their usefulness. With exact matches of 98% of tested medical terms, a mean number of five deposited synonyms, SNOMED CT seemed to fit our needs best. HPO and LOINC provided 73% and 31% of exacts matches of clinical terms respectively. Allowing more generic codes for a defined symptom, with SNOMED-CT 99%, with HPO 89% and with LOINC 39% of terms could be encoded.Conclusions: With the use of the OSSE software and a data set, which, in addition to the Common Data Set, focuses on symptoms and clinical findings, a functioning and meaningful registry for undiagnosed patients can be implemented. The next step is the implementation of the registry in centres for rare diseases. With the help of medical informatics and big data analysis, case similarity analyses could be realized and aid as a decision-support tool enabling diagnosis of some patients.

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Linked Registries: Connecting Rare Diseases Patient Registries through a Semantic Web Layer

BioMed Research International ◽

10.1155/2017/8327980 ◽

2017 ◽

Vol 2017 ◽

pp. 1-13 ◽

Cited By ~ 6

Author(s):

Pedro Sernadela ◽

Lorena González-Castro ◽

Claudio Carta ◽

Eelke van der Horst ◽

Pedro Lopes ◽

...

Keyword(s):

Semantic Web ◽

Rare Disease ◽

Rare Diseases ◽

Disease Patient ◽

Data Representation ◽

Patient Registries ◽

Holistic View ◽

Specific Patient ◽

Semantic Layer ◽

Rare Disease Patient

Patient registries are an essential tool to increase current knowledge regarding rare diseases. Understanding these data is a vital step to improve patient treatments and to create the most adequate tools for personalized medicine. However, the growing number of disease-specific patient registries brings also new technical challenges. Usually, these systems are developed as closed data silos, with independent formats and models, lacking comprehensive mechanisms to enable data sharing. To tackle these challenges, we developed a Semantic Web based solution that allows connecting distributed and heterogeneous registries, enabling the federation of knowledge between multiple independent environments. This semantic layer creates a holistic view over a set of anonymised registries, supporting semantic data representation, integrated access, and querying. The implemented system gave us the opportunity to answer challenging questions across disperse rare disease patient registries. The interconnection between those registries using Semantic Web technologies benefits our final solution in a way that we can query single or multiple instances according to our needs. The outcome is a unique semantic layer, connecting miscellaneous registries and delivering a lightweight holistic perspective over the wealth of knowledge stemming from linked rare disease patient registries.

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Results of a Patient Reported Experience Measure (PREM) to measure the rare disease patients and caregivers experience: a Spanish cross-sectional study

Orphanet Journal of Rare Diseases ◽

10.1186/s13023-021-01700-z ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Mercedes Guilabert ◽

Alba Martínez-García ◽

Marina Sala-González ◽

Olga Solas ◽

José Joaquín Mira

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Healthcare Services ◽

Paediatric Population ◽

Cross Sectional Study ◽

Sectional Study ◽

Optimal Care ◽

Cross Sectional ◽

Patient Reported ◽

Mean Time

Abstract Objective To measure the experience of the person having a rare disease in order to identify objectives for optimal care in the health care received by these patients. Methods. A cross-sectional study was conducted in Spain involving patients associated with the Spanish Rare Diseases Federation [Federación Española de Enfermedades Raras] (FEDER). A modified version of the PREM IEXPAC [Instrumento para evaluar la Experiencia del Paciente Crónico] instrument was used (IEXPAC-rare-diseases). Scores ranged between 0 (worst experience) and 10 (best experience). Results A total of 261 caregivers (in the case of paediatric population) and patients with rare diseases (response rate 54.4%) replied. 232 (88.9%) were adult patients and 29 (11.1%) caregivers of minor patients. Most males, 227 (87%), with an average age of 38 (SD 13.6) years. The mean time since confirmation of diagnosis was 7.8 (SD 8.0) years. The score in this PREM was 3.5 points out to 10 (95%CI 3.2–3.8, SD 2.0). Caregivers of paediatric patients scored higher, except for coordination of social and healthcare services. Conclusions There are wide and important areas for improvement in the care of patients with rare diseases. This study involves a first assesment of the experience of patients with rare diseases in Spain.

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Leveraging the UMLS As a Data Standard for Rare Disease Data Normalization and Harmonization

Methods of Information in Medicine ◽

10.1055/s-0040-1718940 ◽

2020 ◽

Author(s):

Qian Zhu ◽

Dac-Trung Nguyen ◽

Eric Sid ◽

Anne Pariser

Keyword(s):

Rare Disease ◽

Rare Diseases ◽

Mendelian Inheritance ◽

Data Normalization ◽

Community Settings ◽

Unified Medical Language System ◽

Data Standard ◽

Medical Language ◽

Disease Concepts ◽

High Level

Abstract Objective In this study, we aimed to evaluate the capability of the Unified Medical Language System (UMLS) as one data standard to support data normalization and harmonization of datasets that have been developed for rare diseases. Through analysis of data mappings between multiple rare disease resources and the UMLS, we propose suggested extensions of the UMLS that will enable its adoption as a global standard in rare disease. Methods We analyzed data mappings between the UMLS and existing datasets on over 7,000 rare diseases that were retrieved from four publicly accessible resources: Genetic And Rare Diseases Information Center (GARD), Orphanet, Online Mendelian Inheritance in Men (OMIM), and the Monarch Disease Ontology (MONDO). Two types of disease mappings were assessed, (1) curated mappings extracted from those four resources; and (2) established mappings generated by querying the rare disease-based integrative knowledge graph developed in the previous study. Results We found that 100% of OMIM concepts, and over 50% of concepts from GARD, MONDO, and Orphanet were normalized by the UMLS and accurately categorized into the appropriate UMLS semantic groups. We analyzed 58,636 UMLS mappings, which resulted in 3,876 UMLS concepts across these resources. Manual evaluation of a random set of 500 UMLS mappings demonstrated a high level of accuracy (99%) of developing those mappings, which consisted of 414 mappings of synonyms (82.8%), 76 are subtypes (15.2%), and five are siblings (1%). Conclusion The mapping results illustrated in this study that the UMLS was able to accurately represent rare disease concepts, and their associated information, such as genes and phenotypes, and can effectively be used to support data harmonization across existing resources developed on collecting rare disease data. We recommend the adoption of the UMLS as a data standard for rare disease to enable the existing rare disease datasets to support future applications in a clinical and community settings.

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Cooccurrence of Two Different Genetic Diseases: A Case of Valproic Acid Hepatotoxicity in Nicolaides–Baraitser Syndrome (SMARCA2 Mutation)—Due to a POLG1-Related Effect?

Neuropediatrics ◽

10.1055/s-0039-1694976 ◽

2019 ◽

Vol 51 (01) ◽

pp. 049-052

Author(s):

Benedikt Hofmeister ◽

Celina von Stülpnagel ◽

Steffen Berweck ◽

Angela Abicht ◽

Gerhard Kluger ◽

...

Keyword(s):

Valproic Acid ◽

Literature Review ◽

Rare Disease ◽

Clinical Features ◽

Rare Diseases ◽

Rare Complication ◽

Genetic Diseases ◽

Related Effect ◽

Higher Sensitivity ◽

Polg1 Mutation

AbstractNicolaides–Baraitser syndrome (NCBRS) is a rare disease caused by a mutation in the SMARCA2 gene. Clinical features include craniofacial dysmorphia and abnormalities of the limbs, as well as intellectual disorder and often epilepsy. Hepatotoxicity is a rare complication of the therapy with valproic acid (VPA) and a mutation of the polymerase γ (POLG) might lead to a higher sensitivity for liver hepatotoxicity. We present a patient with the coincidence of two rare diseases, the NCBRS and additionally a POLG1 mutation in combination with a liver hepatotoxicity. The co-occurrence in children for two different genetic diseases is discussed with the help of literature review.

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