Comorbidity Networks From Population-Wide Health Data: Aggregated Data of 8.9M Hospital Patients (1997-2014)

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.