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. 2025 Jun 11;54(4):dyaf118.
doi: 10.1093/ije/dyaf118.

Data Resource Profile: The Lithuanian health data reuse pathway

Julius Juodakis  1   2   3 , Simona Zubavičiūtė  2 , Austėja Dapkutė  4 , Saulė Greičienė  2 , Rytis Masiliūnas  4 , Indrė Narkevičienė  2 , Justas Trinkūnas  3   5 , Julija Žemaitytė  2 , Gita Literskė  2
Affiliations

Data Resource Profile: The Lithuanian health data reuse pathway

Julius Juodakis et al. Int J Epidemiol. .
No abstract available

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Figures

Figure 1.
Figure 1.
Age and sex distribution of outpatients in the ESPBI IS (national electronic health record system) and the general population of Lithuania for the year 2024. The bars represent the number of unique outpatients in each age group at the time of diagnosis. The black dots indicate the corresponding number of individuals in the general resident population of Lithuania. Infants may receive health records before getting a stable personal code and therefore may appear overrepresented. F: female; M: male.
Figure 2.
Figure 2.
The percentage of forest land in Lithuania’s municipalities for the year 2024 (bottom). The incidence of tick-borne encephalitis (TBE) per capita in Lithuania’s municipalities for the year 2024 (top). A person is considered a TBE case if they received three or more A84.X (where X—any number) entries in the ESPBI IS (national electronic health record system) over 2024. The patient’s residential address at the time of first TBE diagnosis in 2024 was used to calculate the TBE incidence per capita in Lithuania’s municipalities. Analysis was performed in Palantir Foundry platform.
See this image and copyright information in PMC

References

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    1. Population with Tertiary Education (Indicator). https://www.oecd.org/en/data/indicators/population-with-tertiary-educati..., 2017. (11 August 2024, date last accessed).
    1. Income Inequality (Indicator). https://www.oecd.org/en/data/indicators/income-inequality.html, 2017. (11 August 2024, date last accessed).