Abstract
Turkey hosts one of the world’s largest refugee populations, including more than 3.6 million Syrians and hundreds of thousands of Afghans. Despite this scale, refugee status is often not recorded as a discrete field in electronic medical records. This omission is not unique to Turkey. Health and insurance databases rarely include a refugee status variable, making refugee-specific outcomes difficult to track without slow, manual review.
In Turkey, this data gap reflects a two-tiered system of access. Syrians under temporary protection receive free primary care through roughly 190 government-run Migrant Health Centers. Undocumented Afghans face a more restrictive reality and remain excluded from public health insurance. Together, these differences in legal status, registration, and access shape how refugees appear or disappear within health data systems.
This research argues that statistical underrepresentation among refugees is not incidental but is produced by classification choices embedded within electronic medical record systems. These choices influence which populations become visible to policymakers, how resources are distributed, and how health needs are measured. The project proceeds in three phases. First, a literature review traces Turkey’s transition from camp-based logbooks to the digitized Migrant Health Center network. Second, a computational analysis of aggregated Ministry of Health, WHO, UNHCR, and SIHHAT data examines where legal status, province of registration, and language of consultation are absent, inconsistently recorded, or lost across datasets. Third, published testimony from refugee health researchers and journalists, alongside comparative material from New York-based organizations, provides insight into practical interventions. The project ultimately identifies the metadata and classification fields that contribute to the statistical invisibility of displaced populations and considers how electronic health record systems could be redesigned to better capture refugee health outcomes.
Keywords: Refugee health systems, Electronic medical records, Health data invisibility, Syrian and Afghan refugees, Migrant Health Centers
I am currently a junior at Barnard College of Columbia University studying Computational Biology with a minor in Economics. Through my coursework and research experiences, I have developed a strong foundation in data analysis, quantitative modeling, and computational approaches to complex biological and social systems. My background in economics has further shaped how I think about resource allocation, structural inequality, and policy impacts at scale.
I am particularly interested in applying data science and computational methods to questions in public health, migration, environmental justice, and global health systems. Much of my work focuses on how large-scale systems, whether healthcare infrastructure, environmental conditions, or social policy, shape health outcomes for marginalized populations. I am especially drawn to research involving spatial analysis, longitudinal datasets, and health data infrastructure, as well as projects that bridge technical analysis with real-world policy and community impact.
