Large-scale data show promise to provide efficiency gains through individualized risk predictions in many business and policy settings. Yet, assessments of the degree of data-enabled efficiency improvements remain scarce. We quantify the value of the availability of a variety of data...

Personendaten aus der Verwaltung (Administrativdaten) haben sich in den letzten Jahrzehnten als wichtige Basis zur Evaluierung von Politikmaßnahmen erwiesen. Durch maschinelles Lernen können basierend auf diesen Daten auch Vorhersagen getroffen werden, die zur Lösung gesellschaftlicher...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...

Improving physicians’ prescription practices is a primary strategy for countering the rise in resistance to antibiotics. This would prevent physicians from incorrectly prescribing antibiotics, one of the main causes of antibiotic resistance. The increasing availability of medical data and...

Human decision-making differs due to variation in both incentives and available information. This generates substantial challenges for the evaluation of whether and how machine learning predictions can improve decision outcomes. We propose a framework that incorporates machine learning on...

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...

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...

Antibiotic resistance constitutes a major health threat. Predicting bacterial causes of infections is key to reducing antibiotic misuse, a leading driver of antibiotic resistance. We train a machine learning algorithm on administrative and microbiological laboratory data from Denmark to predict...