Data pipeline quality: development and validation of a quality assessment tool for data-driven algorithms and artificial intelligence in healthcare

BMJ Health & Care Informatics 2026 Open access

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Authors: Eris van Twist, Brian van Winden, Rogier de Jonge, H Rob Taal, Matthijs de Hoog, Alfred C. Schouten, David M. J. Tax, Jan Willem Kuiper
DOI: 10.1136/bmjhci-2025-101608
Cited by: 1
References: 71

Abstract

OBJECTIVES: To develop and validate a tool for standardised quality assessment of data-driven algorithms in healthcare, focusing on the underlying data pipeline. METHODS: Data Assessment Tool for Algorithm Critical Appraisal and Robust Evidence (DATA-CARE) was iteratively developed from the established Quality In Prognosis Studies framework, selected after reviewing 10 existing quality assessment tools for observational and artificial intelligence studies. DATA-CARE evaluates five quality domains of the data pipeline: study population, data, algorithm, outcome and report transparency. Each domain comprises three to five quality criteria. With a total score of 75 points, study quality is categorised as low (

Fields of Study & Subjects

Sepsis Diagnosis and Treatment Artificial Intelligence in Healthcare and Education Healthcare Technology and Patient Monitoring

Publication details

Journal / source
BMJ Health & Care Informatics
Publisher
BMJ
Volume
33
Issue
1
Pages
e101608–e101608
Publication date
1 February 2026
Language
EN