[Databases in neurological diseases: overview of international examples in multiple sclerosis].

Abstract:

:Vast amounts of data are created during routine patient care which are stored in unstructured digital and hardcopy formats in healthcare institutions. Analysis of large databases help to define the healthcare needs of the population and to organize healthcare services for specific diseases. As a model, we selected multiple sclerosis (MS), a disease with well-defined diagnostic criteria, a usually inpatient initial diagnosis, and a need for regular outpatient check-up. Using multiple sclerosis as an example, we set forth to screen and analyze international and Hungarian databases. In the framework of the initiation of the data lake system of Semmelweis University, we aim to define features of the data system needed for disease-specific databases for future applications. To determine essential data-entry criteria for such a database, we review the most important multiple sclerosis registries. We evaluate the type of registered data, structure of database, privacy issues, the availability and ways of application of the databases. Initially, the MS databases were created locally, aiming for better care of patients. As a further step, data were collected for scientific research by national and international co-operations. Disease-specific databases have become of high priority for national healthcare providers, and long-term information on a population ("real-world" data) is extremely important to assess the effectivity and safety of a treatment at the population level. Our analysis contributes to a project which focuses on the aspects of developing a data lake at a service provider level including clinical, diagnostic and digital healthcare departments of Semmelweis University, Budapest, Hungary. Orv Hetil. 2019; 160(4): 123-130. :Absztrakt: A rutin-betegellátás során hatalmas adattömeg keletkezik, amelyet jelenleg elszórva, többféle informatikai és papíralapú rendszerben tárolnak az egészségügyi intézményekben. A nagy adatbázisok elemzése egy adott betegség vonatkozásában segít egy populáció egészségügyi szükségleteinek meghatározásában és egészségügyi ellátásuk megszervezésében. Modellként a sclerosis multiplexet (SM) választottuk, melynek jól meghatározott diagnosztikus kritériumai vannak; a kezdeti diagnózis általában fekvőbeteg-ellátó intézményben történik, és a betegek gondozása és követése a járóbeteg-ellátásban zajlik. A sclerosis multiplex példáján célunk a nemzetközi és hazai adatbázisok feltérképezése és elemzése. A Semmelweis Egyetemen induló adattófejlesztés elemeként célnak tűztük ki a betegségspecifikus adatbázisok szükséges jellemzőinek meghatározását. A lényeges adatbeviteli kritériumok meghatározása céljából áttekintjük a legfontosabb nemzetközi SM-adatbázisokat. Vizsgáljuk a rögzített adatokat, az adatbázisok struktúráját, kitérünk az adatvédelmi szempontokra, az egyes adatbázisok hozzáférhetőségére és alkalmazási lehetőségeire. A SM helyi adatbázisok kezdetben elsősorban a betegek hatékonyabb gondozását célozták. Következő lépésként helyi és nemzetközi tudományos kutatásokhoz is szükség volt a betegek adataira. A betegségspecifikus adatbázisok létrehozása nagy jelentőségű volt a finanszírozók számára is, és a nagy betegpopulációról szerzett hosszú távú információk (úgynevezett „real-world” adatok) rendkívül fontosak a készítmények hatékonyságának és mellékhatásainak pontosabb megítélésére a populáció szintjén. Elemzésünk hozzájárul egy egészségügyi intézményi „adattó” létrehozásának szempontjaira fókuszáló projekthez, melyben a Semmelweis Egyetem egyes klinikái és diagnosztikus egységei mellett a Digitális Egészségtudományi Intézet is részt vesz. Orv Hetil. 2019; 160(4): 123–130.

journal_name

Orv Hetil

journal_title

Orvosi hetilap

authors

Iljicsov A,Simó M,Tegze N,Szócska M,Mátyus P,Bereczki D

doi

10.1556/650.2019.31273

subject

Has Abstract

pub_date

2019-01-01 00:00:00

pages

123-130

issue

4

eissn

0030-6002

issn

1788-6120

journal_volume

160

pub_type

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