Code Sharing in Healthcare Research: A Practical Guide and Recommendations for Good Practice

TL;DR

This paper provides practical recommendations and guidelines for sharing analytical code in healthcare research to enhance reproducibility, transparency, and adherence to open science principles.

Contribution

It offers a comprehensive, actionable framework aligned with FAIR principles to improve code sharing practices in healthcare research.

Findings

Addresses common barriers to code sharing

Provides clear guidance for making code reusable and robust

Supports compliance with publishing and funding standards

Abstract

As computational analysis becomes increasingly more complex in health research, transparent sharing of analytical code is vital for reproducibility and trust. This practical guide, aligned to open science practices, outlines actionable recommendations for code sharing in healthcare research. Emphasising the FAIR (Findable, Accessible, Interoperable, Reusable) principles, the authors address common barriers and provide clear guidance to help make code more robust, reusable, and scrutinised as part of the scientific record. This supports better science and more reliable evidence for computationally-driven practice and helps to adhere to new standards and guidelines of codesharing mandated by publishers and funding bodies.