We analyze how machine learning predictions may improve antibiotic prescribing in the context of the global health policy challenge of increasing antibiotic resistance. Estimating a binary antibiotic treatment choice model, we find variation in the skill to diagnose bacterial urinary tract...

The access and use of administrative health data in Germany is limited by several factors. Due to the large number and heterogeneity of data holders, data are usually only available in fragmented form, and access is often regulated in a non-transparent manner. Linkage of health data with other...

Die Stellungnahme der Arbeitsgruppe "Gesundheitsdaten" identifiziert aus gesundheitsökonomischer Perspektive eine deutliche Diskrepanz zwischen Forschungsbedarfen und den am Forschungsstandort Deutschland vorgefundenen Bedingungen des Datenzugangs. Ein ungenügender Datenzugang ist aber nicht...

In the fight against antibiotic resistance, reducing antibiotic consumption while preserving healthcare quality presents a critical health policy challenge. We investigate the role of practice styles in patients' antibiotic intake using exogenous variation in patient-physician assignment....

Inefficient human decisions are driven by biases and limited information. Health care is one leading example where machine learning is hoped to deliver efficiency gains. Antibiotic resistance constitutes a major challenge to health care systems due to human antibiotic overuse. We investigate how...