Sclerosis multiplex a közép-magyarországi régióban: a helyi adatbázisfejlesztés tapasztalatai és jövőbeli lehetőségei

Author:

Iljicsov Anna1,Simó Magdolna1,Tegze Nárcisz1,Szócska Miklós2,Mátyus Péter2,Bereczki Dániel1

Affiliation:

1. Neurológiai Klinika, Semmelweis Egyetem, Általános Orvostudományi Kar Budapest, Balassa u. 6., 1083

2. Digitális Egészségtudományi Intézet, Semmelweis Egyetem, Egészségügyi Közszolgálati Kar Budapest

Abstract

Abstract: Introduction: Data during routine patient care are created in multiple digital and paper-based hardcopy systems, therefore their retrieval is cumbersome in the follow-up of patients. Multiple sclerosis is the most prevalent neurological disorder in the young age, with major consequences on health and socio-economic status. Aim: We set forth to create a user-friendly, detailed local database where it is easy to access, register and analyze data. Based on our experiences during building this registry, we develop the model of a modern type of database. Method: First we established a local registry in Excel, then data were transferred to the worldwide used iMed system. Separate pages were used to register basic data, follow-up visits, relapses, accompanying diseases, results of neuroimaging, cerebrospinal fluid, evoked response and other tests, pharmacological and non-pharmacological treatments. Results: The database currently contains data of 316 patients. MRI was performed in 96%, cerebrospinal fluid examination in 45% of the patients. The rate of primary progressive disease at disease onset is 9%. Disease modifying treatments were applied in 82% of the patients. Conclusion: The traditional manual data entry and data export in PDF format is obsolete and time-consuming. The development of local disease-specific databases appropriate for clinical and research purposes requires continuous and mostly automatic data entry. In future local registries the establishment of uniform documentational language and structure, and automatic transfer of information among different digital systems are required. We present the model of such a registry, which is based on a healthcare data lake. Orv Hetil. 2019; 160(4): 131–137.

Publisher

Akademiai Kiado Zrt.

Subject

General Medicine

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