Současný masivní rozvoj sekvenování lidských genomů či exomů v biomedicínském výzkumu je jednou z důležitých cest k personalizované medicíně. Čtení lidské genetické informace nicméně generuje potenciálně citlivá a zneužitelná data, což s sebou přináší etická, legislativní a bezpečnostní úskalí. Z tohoto důvodu je nutné při práci s těmito daty dodržovat řadu opatření, a to v průběhu jejich celého životního cyklu – při jejich získávání, úschově, zpracování, využití, sdílení, archivaci i opakovaném využití. Důležitost správné praxe při práci s genomickými daty je navíc umocněna aktuálními evropskými trendy směřujícími k otevřené vědě a digitalizaci. Proto byl vypracován následující soubor doporučení stanovujících zásady pro výzkumnou práci se sekvencemi lidského genomu nebo jeho částí. Doporučení se opírají o dva dokumenty vydané Světovou aliancí pro genomiku a zdraví (GA4GH) a zahraniční literaturu, čímž shrnují všechny klíčové recentní pokyny týkající se většiny relevantních aspektů pro práci s lidskými genomickými daty.
The current significant development of human genome/exome sequencing in biomedical research is one of the important paths leading to personalized medicine. However, sequencing of human genetic information generates potentially sensitive and exploitable data, which leads to ethical, legal, and security issues. For this reason, it is necessary to follow several measures when working with these data, applying to their entire life cycle – i.e., acquisition, storage, processing, usage, sharing, archiving, and reuse. In addition, importance of good practice during the whole data life cycle is emphasized by current European trends towards open science and digital transformation. Therefore, the following recommendations have been developed, establishing principles for work with the whole human genome sequences or parts of it in research context. The recommendations are based on two documents published by the Global Alliance for Genomics and Health (GA4GH) and on foreign literature, thus summarizing recent relevant guidance on most aspects of working with human genomic data.
- MeSH
- Codes of Ethics * MeSH
- Genomics * ethics MeSH
- Humans MeSH
- Information Dissemination ethics MeSH
- Check Tag
- Humans MeSH
- Publication type
- Practice Guideline MeSH
The paper shows the importance of e-health applications for electronic healthcare development. It describes several e-health applications for health data collecting and sharing that are running in the Czech Republic. These are IZIP system, electronic health record MUDR and K4CARE project applications. The e3-health concept is considered as a tool for judging e-health applications in different healthcare settings.
- MeSH
- Medical Record Linkage methods MeSH
- Electronic Health Records organization & administration MeSH
- Information Dissemination methods MeSH
- Case-Control Studies MeSH
- Information Storage and Retrieval methods MeSH
- Health Records, Personal * MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic MeSH
Lékařská doporučení jsou systematicky popisované poznatky, které by měly pomoci lékařům v rozhodování o vhodné péči o zdraví ve specifických podmínkách. Některé evropské projekty se již začaly zabývat otázkami, jak reprezentovat doporučení na počítači tak, aby bylo možné aplikovat algoritmy pro odvozování závěrů ze znalostí obsažených v lékařských doporučeních a z dat o pacientech zadaných lékařem nebo uložených v klinickém či nemocničním informačním systému. Jedním z cílů projektu MGT je ukázat, jak převádět lékařská doporučení, například WHO/ISH doporučení pro hypertenzi, do elektronické podoby pomocí jazyka OCML. OCML je především jazykem pro reprezentaci znalostí, ale svým propojením s programovacím jazykem Common Lisp, jehož je nadstavbou, nabývá výpočetní síly. Přístup této studie je v podstatě komplementární k článku autorů Svátek V., Kočka T. a Jiroušek R. (v tomto časopise), který je založen práve na „znalostních" konstruktech OCML a postupuje od obecného vymezení k definici konkrétních doporučení.
- MeSH
- Research Support as Topic MeSH
- Medical Informatics Computing MeSH
- Humans MeSH
- Decision Making, Computer-Assisted MeSH
- Research Design MeSH
- Check Tag
- Humans MeSH
- Publication type
- Practice Guideline MeSH
- Geographicals
- Europe MeSH
- MeSH
- Health Care Economics and Organizations MeSH
- Electronic Health Records * organization & administration MeSH
- Internet MeSH
- Medical Informatics MeSH
- Humans MeSH
- Programming Languages MeSH
- Reference Standards * MeSH
- Systems Integration * MeSH
- Medical Informatics Applications MeSH
- Check Tag
- Humans MeSH
- Publication type
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Colombia MeSH
BACKGROUND: The Big Multiple Sclerosis Data (BMSD) network ( https://bigmsdata.org ) was initiated in 2014 and includes the national multiple sclerosis (MS) registries of the Czech Republic, Denmark, France, Italy, and Sweden as well as the international MSBase registry. BMSD has addressed the ethical, legal, technical, and governance-related challenges for data sharing and so far, published three scientific papers on pooled datasets as proof of concept for its collaborative design. DATA COLLECTION: Although BMSD registries operate independently on different platforms, similarities in variables, definitions and data structure allow joint analysis of data. Certain coordinated modifications in how the registries collect adverse event data have been implemented after BMSD consensus decisions, showing the ability to develop together. DATA MANAGEMENT: Scientific projects can be proposed by external sponsors via the coordinating centre and each registry decides independently on participation, respecting its governance structure. Research datasets are established in a project-to-project fashion and a project-specific data model is developed, based on a unifying core data model. To overcome challenges in data sharing, BMSD has developed procedures for federated data analysis. FUTURE PERSPECTIVES: Presently, BMSD is seeking a qualification opinion from the European Medicines Agency (EMA) to conduct post-authorization safety studies (PASS) and aims to pursue a qualification opinion also for post-authorization effectiveness studies (PAES). BMSD aspires to promote the advancement of real-world evidence research in the MS field.
- MeSH
- Big Data MeSH
- Humans MeSH
- International Cooperation MeSH
- Registries * MeSH
- Multiple Sclerosis * epidemiology therapy MeSH
- Information Dissemination MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
Background: Developed countries are planning the creation of national EHR (Electronic Health Record) systems to modernize the healthcare field and improve its quality, security and efficiency. Objectives: To support clinical data sharing, it is important that an EHR is designed to be integrated within an appropriate architectural context aimed to satisfy the needs of all actors involved in this information management by adding and integrating new functionalities to existing solutions. Methods: SOA (Service Oriented Architecture) provides a good approach to promote the easy integration and alignment of a new and existing solution into a cohesive architecture. The HSSP (Healthcare Service Specification Program) was formed to adopt the SOA approach to guarantee interoperability between applications and distributed and heterogeneous devices, by providing a set of standards to design and develop specific services. Results: The authors present a landscape architecture to support the collaboration between actors involved in the treatment of chronic diseases. The core of this architecture consists of services compliant to HSSP standards. Among these, the authors developed: Health Record Management Services, Health Terminology Services and Health Identity Services. The proposed architecture and these services have already been adopted in different systems: a telemonitoring system to support the continuity of care of CHF (Congestive Heart Failure) patients, two systems to share clinical data to manage clinical trials in both infectivology and ophthalmology. Conclusions: The main advantage of the proposed architecture is its flexibility that allows it to be adapted over time and to be adopted in all health care scenarios.
Today, applications for Grids emerge in various scientific fields, each with specific requirements. We present concept and architecture which enables biomedical experts to collaborate and share resources by encapsulating their knowledge and expertise as grid services, with (semi-)formally described semantics. Grid Services allow machine processing of the encapsulated knowledge, while their semantic description provides means for their automated discovery and interaction. This brings new possibilities of building biomedical systems offering machine-driven assistance to the biomedical experts.
Qualitative research plays a pivotal role in health psychology, offering insights into the intricacies of health-related issues. However, the specificity of qualitative methodology presents challenges in adhering to standard open science principles, including data sharing. The guidelines to address these issues are limited. Drawing from the author's experience in conducting in-depth interviews with middle-aged and older adults regarding their sexuality, this article discusses various challenges in implementing data sharing requirements. It emphasizes factors like participants' reasonable reluctance to share in specific populations, the depth of personal information gleaned from comprehensive interviews, concerns surrounding potential data misuse both within and outside academic circles, and the complex issue of obtaining informed consent. A universal approach to data sharing in qualitative research proves impractical, emphasizing the necessity for adaptable, context-specific guidelines that acknowledge the methodology's nuances. Striking a balance between transparency and ethical responsibility requires tailored strategies and thoughtful consideration.
- MeSH
- Behavioral Medicine MeSH
- Informed Consent MeSH
- Qualitative Research * MeSH
- Middle Aged MeSH
- Humans MeSH
- Interviews as Topic MeSH
- Aged MeSH
- Sexuality psychology MeSH
- Information Dissemination * MeSH
- Check Tag
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
In this paper, we propose a health data sharing infrastructure which aims to empower a democratic health data sharing ecosystem. Our project, named Health Democratization (HD), aims at enabling seamless mobility of health data across trust boundaries through addressing structural and functional challenges of its underlying infrastructure with the core concept of data democratization. A programmatic design of an HD platform was elaborated, followed by an introduction of one of our critical designs-a "reverse onus" mechanism that aims to incentivize creditable data accessing behaviors. This scheme shows a promising prospect of enabling a democratic health data-sharing platform.
- Publication type
- Journal Article MeSH
The International Committee of Medical Journal Editors (ICMJE) provides recommendations to improve the editorial standards and scientific quality of biomedical journals. These recommendations range from uniform technical requirements to more complex and elusive editorial issues including ethical aspects of the scientific process. Recently, registration of clinical trials, conflicts of interest disclosure, and new criteria for authorship - emphasizing the importance of responsibility and accountability -, have been proposed. Last year, a new editorial initiative to foster sharing of clinical trial data was launched. This review discusses this novel initiative with the aim of increasing awareness among readers, investigators, authors and editors belonging to the Editors' Network of the European Society of Cardiology.
