PhD Scientific Days 2026

Health Sciences 2.

Geospatial Distribution and Potential Economic Implications of Health Development Offices in Hungary

Előadó neve

Domján, Péter, MSc

Neptune code

GHW1EM

Előadó munkahelye

Semmelweis University, Doctoral College, Health Sciences Division Interdisciplinary Applied Health Sciences Program

Előadó telefonszáma

+36307271150

Előadó e-mail címe

domjan.peter@phd.semmelweis.hu

Az előadás címe

Geospatial Distribution and Potential Economic Implications of Health Development Offices in Hungary

Szerző(k) neve és munkahelye

MSc Domján Péter¹, Dr. Bertalan Ádám², Angyal Viola², Petrov Iván³, Dr. Vingender István⁴

1: Semmelweis University, Doctoral College, Health Sciences Division Interdisciplinary Applied Health Sciences Program
2: Semmelweis University, Doctoral College, Health Sciences Division Institute of Digital Health Sciences
3: Semmelweis University, Heart and Vascular Center, Department of Sports Medicine
4: Semmelweis University, Faculty of Health Sciences, Department of Social Sciences

Bemutatás módja

Szóbeli

Szekció

Health Sciences 2.

Language of the presentation

English

Preferred session

Health Sciences

Összefoglaló szövege

Introduction
Health Development Offices (HDOs) are key elements of preventive healthcare in Hungary. However, regional differences in their spatial distribution raise questions regarding equitable access to preventive services.

Aims
This study aims to describe the geospatial distribution of HDOs and to explore their potential economic implications using a model-based approach.

Methods
A county-level geospatial analysis was conducted using population data and the proportion of elderly residents to assess service coverage. National-level epidemiological rates for type 2 diabetes, cardiovascular diseases, and mental health service utilization (based on available data from 2019, 2021, and 2023) were used to estimate baseline disease burden. These rates were applied to county-level population data. A simplified budget impact framework was used to estimate potential changes in disease burden under conservative assumptions. Relative risk reductions (1–3%) and adherence rates (30–70%) were defined based on literature-informed ranges. Uncertainty was explored using Monte Carlo simulation.

Results
The geospatial analysis identified regional differences in HDO distribution, with relatively higher coverage in rural areas. Model-based estimates suggest that even small reductions in disease burden could be associated with measurable changes in healthcare utilization. Results remained stable across a wide range of parameter values.

Conclusion
Geospatial and model-based approaches can provide useful insights into the potential role of preventive services. However, results should be interpreted cautiously due to data limitations and the use of aggregated national-level inputs.

Funding
No external funding.

University

Semmelweis University

Supervisor

Dr. Vingender István

Publication of my abstract

I give consent to the publication of my abstract on the website of the congress.

phd.section.field

in doctoral studies after complex exam (PhD)

Kind

Szabad

Status

elfogadva

Accepted presentation method

szóbeli

Előadás fájl jóváhagyás

nem rendelkezett róla

Előadó

8043

Start

17:00

End

17:10