Comorbidity networks have become a valuable tool to support data-driven biomedical research. Yet, studies often are severely hindered by the availability of the necessary comprehensive data, often due to the sensitivity of health care information.

This study presents a population-wide comorbidity network dataset derived from 45 million hospital stays of 8.9 million patients over 17 years in Austria.

We present co-occurrence networks of hospital diagnoses, stratified by age, sex, and observation period in a total of 96 different subgroups. For each of these groups we report a range of association measures (e.g., count data, and odds ratios) for all pairs of diagnoses.

The dataset provides the possibility to researchers to create their own, tailor-made comorbidity networks from real patient data that can be used as a starting point in quantitative and machine learning methods.

This data platform is intended to lead to deeper insights into a wide range of epidemiological, public health, and biomedical research questions.

E. Dervic, K. Ledebur, S. Thurner, P. Klimek, Comorbidity Networks From Population-Wide Health Data: Aggregated Data of 8.9M Hospital Patients (1997–2014), Scientific Data 12 (2025) 215.