The management of bias and noise in public sector decision-making: experimental evidence from healthcare

Nicola Belle, Paola Cantarelli and Sophie Y. Wang

Public Management Review, 2024, vol. 26, issue 11, 3246-3269

Abstract: In six randomized online experiments with 2,647 medical doctors we test whether – depending on the choice architecture – physicians engaged in prescribing decisions in public organizations fall prey to systematic error (i.e. bias) and make significantly different choices when faced with the same clinical case (i.e. level noise). Results show that experts tend to make irrational choices that are influenced by outgroup bias, social comparison, past behaviour, confirmation bias, loss aversion, equivalence framing, and asymmetric dominance. We also find evidence of significant level noise, that is, between-prescriber variability, with the distribution of responses differing remarkably across experimental arms.

Date: 2024
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DOI: 10.1080/14719037.2024.2322159

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