WHERE DOES RESPONSIBILITY LIE? ANALYSING LEGAL AND REGULATORY RESPONSES TO FLAWED CLINICAL DECISION SUPPORT SYSTEMS WHEN PATIENTS SUFFER HARM. (20th July 2022)

• Record Type: Journal Article
• Authors: Prictor, Megan
• Is Part Of: Medical law review. Volume 31:Number 1(2023)
• Page Start: 1
• Page End: 24
• Publication Date: 2022-07-20
• Subjects: Clinical decision support systems -- Consumer law -- Contract -- Harm -- Negligence -- Regulation; Medical laws and legislation -- Great Britain -- Periodicals; Medical jurisprudence -- Periodicals; Jurisprudence -- Periodicals; Legislation, Medical -- Periodicals; Medical jurisprudence; Medical laws and legislation; Great Britain; 344.41041
• DOI: 10.1093/medlaw/fwac022
• Languages: English
• ISSNs: 0967-0742

Abstract

Abstract: Clinical decision support systems (CDSSs) are digital healthcare information systems that apply algorithms to patient data to generate tailored recommendations. They are designed to support, but neither dictate nor execute, clinical decisions. CDSSs can introduce new risks, both by design features that heighten clinician burden and by outright errors that generate faulty recommendations for care. In the latter instance, if such unintercepted recommendations were to result in harm to the patient, novel legal questions emerge. Does legal responsibility for this harm lie with the clinician, the software developer or both? What is the clearest path to a remedy? Further, how does the Australian regulatory framework provide for oversight and redress? This article analyses the potential forms of legal redress in negligence, contract and under statutory consumer law, for the patient and the clinician. It also examines the Australian regulatory framework, specifically in relation to the Australian Competition and Consumer Commission and the Therapeutic Goods Administration, and reflects on the framework's adequacy to protect patients and clinicians. It finds that the regulatory approach and the contour of legal risk still centre upon the clinician's duty to exercise decisional autonomy and to intercept flawed recommendations generated by algorithmic errors within CDSSs.