Year: 2026
Type: article
Study design: Systematic Review
Abstract: Purpose Professional prescribing decisions significantly influence healthcare outcomes, including client safety, cost efficiency and adherence to guidelines. This study aims to analyze the academic literature to understand the behavioral factors – either external interventions or internal mechanisms – behind prescribing decisions, which is a crucial aspect for healthcare management. Design/methodology/approach With a midpoint position on the miner–prospector continuum, we employed a systematic review methodology to identify and synthesize the behavioral mechanisms influencing the prescription behaviors of healthcare professionals, highlighting gaps in current research and their managerial and policy implications. The comprehensive search was conducted using the Scopus database, focusing on peer-reviewed studies published between 2019 and 2025. Findings The systematic review included 359 primary studies and identified a diverse set of factors, including training, social influences, cognitive biases and adherence to guidelines, with training and multi-factor approaches being the most frequently studied. Some factors are more compatible with elements of rational decision-making, such as adherence to guidelines or training. Other factors are more compatible with the idea that the rationality of decision-makers, even when they are experts, is bounded. Those include social influences, cognitive biases and decision noise. Originality/value This study provides a synthesis of management strategies for healthcare organizations interested in enhancing performance by leveraging micro-level prescribing behaviors. Evidence-based practical implications and a forward-looking research agenda are derived.
Source: Management Decision
Institutions: Scuola Superiore Sant'Anna, University of Florence
Language: English
Subfield: Family Practice
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Funder: European Commission
Awards: G1060098436, G972786147
OpenAlex ID: W7134125730