The value of data for prediction policy problems: Evidence from antibiotic prescribing
DIW Discussion Paper, Nr. 1939 (with Hannes Ullrich and Michael Ribers)
AbstractLarge-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 combinations for tackling the policy problem of curbing antibiotic resistance, where the reduction of inefficient antibiotic use requires improved diagnostic prediction. Focusing on antibiotic prescribing for suspected urinary tract infections in primary care in Denmark, we link individual-level administrative data with microbiological laboratory test outcomes to train a machine learning algorithm predicting bacterial test results. For various data combinations, we assess out of sample prediction quality and efficiency improvements due to prediction-based prescription policies. The largest gains in prediction quality can be achieved using simple characteristics such as patient age and gender or patients' health care data. However, additional patient background data lead to further incremental policy improvements even though gains in prediction quality are small. Our findings suggest that evaluating prediction quality against the ground truth only may not be sufficient to quantify the potential for policy improvements.
Physician effects in antibiotic prescribing: Evidence from physician exits
Draft available on request (with Hannes Ullrich)
AbstractHuman antibiotic consumption is considered the main driver of antibiotic resistance. Reducing human antibiotic consumption without compromising health care quality poses one of the most important global health policy challenges. A crucial condition for effective policies is to identify who drives antibiotic treatment decisions. We investigate to what extent physician practice style, as opposed to patient-specific factors, determines general practice antibiotic intake and health outcomes. Using linked administrative data from Denmark, a low-prescribing country, we first document that prescriptions in general practice drive large variation in antibiotic consumption. To identify the causal effect of physician practice style on variation in antibiotic prescribing, we exploit quasi-experimental variation in patient-physician relations due to physician exits from clinics in general practice. We estimate that physician practice style accounts for 53 to 56 percent of the cross-practice variation in all antibiotic consumption, and for 74 to 81 percent in broad-spectrum antibiotic consumption. We find little evidence that low prescribing styles adversely affect health outcomes measured as preventable hospitalizations due to infections. Our findings suggest that policies to curb antibiotic resistance are most effective when aimed at improving physician decision-making. We document that high prescribing practice styles are positively associated with physician age and negatively with staff size and the availability of diagnostic tools, suggesting that improvements in the quality of diagnostic information could be an important path to improved decisions.
The effect of a ban on gender-based pricing on risk selection in the German health insurance market
Health Economics, Vol. 29(1), pp. 3-17, 2020 (with Martin Salm)