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Accepted for/Published in: JMIRx Med

Date Submitted: May 31, 2021
Date Accepted: Sep 14, 2021
Date Submitted to PubMed: Sep 19, 2023

The final, peer-reviewed published version of this preprint can be found here:

Medical Brain Drain From Southeastern Europe: Using Digital Demography to Forecast Health Worker Emigration

Juric T

Medical Brain Drain From Southeastern Europe: Using Digital Demography to Forecast Health Worker Emigration

JMIRx Med 2021;2(4):e30831

DOI: 10.2196/30831

PMID: 37725553

PMCID: 10414368

Medical brain drain from South-Eastern Europe: using digital demography to forecast health worker emigration

  • Tado Juric

ABSTRACT

Background:

In this paper, we show that the tools of digital demography, such as the Google Trends (GT) can be very useful for determining, estimating, and predicting the migration of healthcare workers as well as for further predictions of the general interest in emigration.

Objective:

This paper analyses recent trends in the mobility of health workers in Europe and focuses specifically on the patterns of mobility among medical doctors and nurses from Western Balkans and Croatia to Germany and Austria. It identifies the drivers of this mobility and shows how to predict further migration of this stuff. In the last 10 years, every fourth nurse has emigrated from the Croatian health system - to Germany, while according to projections Croatia will lose as much as 1/3 of all doctors in the next five years.

Methods:

A special problem in the analysis of the emigration of healthcare workers from the Western Balkans and Croatia is the fact that there is no system for monitoring this process. Official data up to three years late, and exist only for persons who have deregistered from the state system. The basic methodological concept of our approach is to monitor the digital trace of language searches with the Google Trends analytical tool (trends.google.com). Initially, keywords were chosen by brainstorming possible words that we believed to be predictive, specific, and common enough for use in the forecasting of migration of healthcare professionals. To standardize the data, we requested the data for the period from Dec. 2015 to Dec. 2020 and divided the keyword frequency for each word giving us a search frequency index. Then we have compared searches with official statistics to prove the significations of results and correlations.

Results:

In Croatia search activities using GT for terms such as ‘‘Bewerbung” (job application), “Arbeit” (work), “Krankenschwester, Bewerbung” (nurses, job application) correlate strongly with officially Germans data for emigrants from Croatia. The data collected by this method correlate with official data, which allows reliable forecasts for the future. Austria will soon become one of the most desirable emigration destinations for Croats, especially for healthcare workers. Simultaneously, the emigration of Croatian citizens to Germany will continue.

Conclusions:

Understanding why health care personnel emigrate from Western Balkans and Croatia and which are the consequences of this process are key to enable state agencies and government to develop optimal intervention strategies to retain medical staff. The benefit of this method is reliable estimates that can enable state agencies and the government to prepare and better respond to a possible shortage of healthcare workers and to protect the functioning of the health system.


 Citation

Please cite as:

Juric T

Medical Brain Drain From Southeastern Europe: Using Digital Demography to Forecast Health Worker Emigration

JMIRx Med 2021;2(4):e30831

DOI: 10.2196/30831

PMID: 37725553

PMCID: 10414368

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