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La Cartella Clinica Informatizzata: prospettive diagnostiche e di presa in carico integrata nel percorso assitenziale del Malato Raro
No full textLa Cartella Clinica Informatizzata nel percorso diagnostico-assistenziale del Malato Raro: sviluppo e implementazione di un sistema di raccolta e analisi dell'informazione clinica fenotipica e genotipica. Computerized Medical Record in the diagnostic-care of the Rare Diseases: development and implementation of a system for the collection and analysis of clinical phenotypic and genotypic data
Full text linkInternationally there is no single definition of a rare disease: in European countries and beyond is determined on the basis of different thresholds of prevalence, in accordance with regulatory requirements: in the European Union (EU), a disease is rare if it has a population prevalence of less than or equal to 1/2000 inhabitants (0.05 %). Rare diseases, from a clinical and epidemiological point of view-, are a very heterogeneous group, with about 5000-8000 entities, mostly with genetic origin, often severe, chronically debilitating, progressive and potentially fatal, representing a major public health problem; nevertheless, in the past, have received little scientific interest, are hardly included in international classifications and barely visible at the level of health information, for many of them also epidemiologic data are not yet available. The main reason seems to be the absence of a system of correct coding and traceability in health information systems: the existing classification systems for collecting phenotypic and genotypic data, are widely heterogeneous, lacking a standard terminology, slightly inter-operable, solely dedicated to the classification of the phenotype or supplied with database features of variants and related phenotypes profiles. Some of these databases are already operating, other developing, along with the implementation of NGS technologies, which guaranteed the medical scientific community, compared to traditional techniques, the study of a wide range of genetic diseases, with the collapse of cost and time of data analysis. Worldwide were established centers and research projects in highly specialized techniques of genome sequencing and development of databases of genomic variants, that have made available a large variety and quantity of new information, often difficult to manage and interpret. The commitment of the scientific community is therefore the systematic organization of that huge amount of data, potentially useful to the correct interpretation of the pathogenic significance of genomic variants in relation to the clinical phenotype. Based on emerging data from the literature, the records of patients and pathologies constitute interesting tools for the development of knowledge useful for the clinical and epidemiological aspect and in the field of rare diseases. Many existing registers must address issues of quality, accessibility and standardization of data, optimization of resources, and interoperability, related to fragmentation of coding systems of diseases. The situation on European and international scene seems to favor the establishment of global registers or common platforms for coordination of all existing and future registers, following a uniform approach, coordinated and of the highest quality. The implementation of this model is currently a strategic objective of the European community within the project EPIRARE and of the US community in the project on Global Rare Diseases Registry (GRDR). In the evolutionary path that supports the implementation of the public health service to improve the exercise of the right to healthcare of citizens, the current development of innovative information technologies, which make available comprehensive information, shared and able to guarantee citizens the best continuity of care, is critical. In Italy, the Electronic Health Record (FSE) is the computerized collection of data of the clinical history of an individual, designed as part of the National Health Service (SSN) according to the National Guidelines issued by the Ministry of Health in November 2010. The process is slow, but with the introduction of the SFE is to be hoped that in the near future, we witness a revolutionary change in the relationship between health infrastructure and citizen, so far characterized by communication barriers, rigid and cumbersome bureaucratic procedures and paperwork with improvement of the flow of data and the diagnostic process and healthcare. Also in the international context is documented the usefulness of the so-called "Electronic Health Record" (EHR) or "Personal Health Record" (PHR) to assist this process in healthcare, as well as for measuring and monitoring the quality of care and for translational research, but the construction and development of the FSE are still at a preliminary stage and the challenges of making the application infrastructure are numerous, especially for developing countries.
Another major challenge on many fronts to health systems in the field of rare diseases is that represented by the heterogeneous group of patients without diagnosis, individuals with known diseases incorrectly recognized, experiencing delays and diagnostic errors, or individuals with unknown diseases; these patients over-use inadequate diagnostic pathways and their care needs are not satisfied, with high human and social costs.
To date the problem of patients without diagnosis was universally recognized worldwide as central, to the planning of health care networks for patients with a rare disease, but its still unresolved: the attempts made in the USA with Undiagnosed Diseases Program (UDP) of National Institute of Health (NIH) clinical Center have shown promising results, but appeared poorly sustainable in clinical practice and still have limited epidemiological value.
Nationally some Accredited Centres for excellence in the diagnosis and treatment of specific rare diseases or groups of related rare diseases, have established projects targeted on finding solutions to methodological collection of clinical phenotype-genotype correspondence, supporting the diagnostic process of patients with rare diseases, with special attention to patients without a diagnosis or with a generic presumptive diagnosis: Region-University research Project "Next Generation Sequencing and Gene Therapy to diagnose and Cure rare Diseases in Emilia Romagna (rarer)" and Ministerial Project "A multicenter collaborative research network for the identification and study of rare undiagnosed patients: the impact on the rare disease National Health Service network (UnRareNet)".
In the broader context of these research projects present PhD project designed to create a unique collection of analytical data, describing phenotype and genotype features of patients with known or suspected diagnosis, between groups of selected rare diseases, based on a computerized platform, with implementation of the model of the Regional Registry for Rare Diseases, already used in the Veneto Region.
A further objective was the creation of a specific product useful for clinical management in the field of rare diseases, especially with respect to efficiency, speed and accuracy of diagnostic assessment, through the transfer of the instrument for collection of clinical phenotype-genotype data in patients with diseases or groups of selected rare diseases in the form of generalized Computerized Medical Record (CCI).
The form CCI should have features which cut across rare diseases registry and the hospital medical records, dedicated to a single episode of care, and should structur on the emerging pattern of computerized personal health record, such as in Italy, the "Fascicolo Sanitario Elettronico".
The added value is the integration of the relational database research potential with the clinical applications of CCI in the practical management and care of patients with rare diseases. It was also planned the networking of CCI as part of a shared use of clinical, genetic and healthcare data in real contexts of clinical excellence, such as those offered by the RARER and UnRareNet projects.
The project is structured in three different phases:
1. identification and sharing, within the common RARER protocol, of a suitable methodology for the construction of 8 different disease registries, with implementation of the clinical database and structuring a form of collection of genotypic data;
2. realization and network sharing of module CCI such as a sustainable product in a clinical setting, containing clinical information in a relational database;
3. implementation of the acquisition data system and module CCI, with the expansion of the patient population in the context of the project UnRareNet, data analysis, identifying the correlation between genotype and phenotype pictures, and design of an expert system able to manage complex procedures for data processing.
The research project proposed the implementation of a relational database with the collection through CCI of clinical data in patients with rare diseases with known or suspected diagnosis, in the context of some rare diseases of specific interest.
The clinical entities and major and minor entities, describing phenotype and genotype features are classified in the database according to a classificatory nodular and multihierarchical like a tree method, which integrates uni and multidimensional internationally recognized classification systems and, at the same timem respects the anatomical structure and function of the human organism.
The database includes 72,360 records, distributed between the main and secondary entities (signs, symptoms, comorbidity, impairments, diagnostic, attributes) and relationships between entities, 117 different clinical entities, 63 different genes and 1,186 total patients. The results obtained during the development and implementation of the system of collection of clinical information, with the implementation of the module CCI in the context of the project RARER, have proved the usability of the product in a preliminary context; the expansion of the clinical application in the context of the project UnRareNet, has produced promising results and the system showed a good performance in terms of similar and dissimilar phenotypes, managing fully clinical information regarding total number of different rare diseases and proving thus be generalized flexible and interoperable. The data are still limited at the time, but having analytical characteristics pre-coded, are immediately usable for future complex processing. The collection of genetic information and integration with clinical information appeared feasible with promising results, although the project UnRareNet this is still absolutely at a preliminary stage; patients without diagnosis is about 10% of the total, but more than half of them do not yet have genetic investigation, which proved to be useful to confirm the diagnosis in 53% of cases with known disease. On the total sample of patients, the use of NGS technologies seems to be limited at this stage, but the results highlight the potential of the modern techniques of genome sequencing in the implementation of the diagnostic process; expanding the population of patients enrolled and the targeted application of these new technologies could allow wider knowledge on the phenotypic and genotypic profile of the considered diseases. Having a broader patient population, the creation of the expert system, of which the foundations were laid in the context of this project, will be possible through the collection of theoretical frequencies of clinical and diagnostic findings of some groups of rare diseases related (metabolic, mitochondrial), arising from the international literature and to be included in the system for processing of clinical scenarios. The expert system will allow the validation of diagnoses simulated by collecting new cases with known diagnosis, and the formulation of new diagnoses of known diseases or identification of new clinical entities, even with use of neural networks or Kohonen networks and Fuzzy methods. The methodology for collecting phenotypic and genotypic information in patients with rare diseases, proposed in this PhD project, proved sufficient to satisfy the requirements of applicability and suggested a number of future applications, which aim the expansion of knowledge on genomic variability of rare diseases and to reduce the number of patients without a diagnosis
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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