Managing risks or generating uncertainties? Ambiguous ontologies of testing in Australian healthcare

• Published in: Health (London, England : 1997) Vol. 25; no. 6; pp. 669 - 687
• Main Authors: Pienaar, Kiran, Petersen, Alan, Bowman, Diana M
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01-11-2021; Sage Publications Ltd
• Subjects: Genetic testing; Health problems; Health risks; Health services; Medical decision making; Medical personnel; Medical screening; Medicine; Ontology; Policy making; Risk assessment; Science and technology; uncertainty work; diagnosis; medical testing; science and technology studies; evidence; health professionals’ views
• ISSN: 1363-4593; 1461-7196
• DOI: 10.1177/1363459320912830

Medical testing promises to establish certainty by providing a definitive assessment of risk or diagnosis. But can those who rely on tests to offer advice or make clinical decisions be assured of this certainty? This article examines how Australian health professionals, namely clinicians, microbiologists, specialist physicians and health policymakers, delineate the boundary between certainty and uncertainty in their accounts of medical testing. Applying concepts from science and technology studies, and drawing on qualitative data from a sociological study of testing in Australian healthcare, we consider how professionals ascribe meaning to testing and test results. As we argue, for these health professionals, the ‘evidence’ that testing generates has ambiguous ontological significance: while it promises to provide diagnostic certainty and clear direction for advice or treatment, it also generates uncertainties that may lead to yet further tests. Our analysis leads us to question a key premise of testing, namely that it is possible to establish certainty in medical practice via the measurement of individual health risks and disease markers. Against this dominant view, the responses of the health professionals in our study suggest that uncertainty is intrinsic to testing due to the constantly changing, unstable character of ‘evidence’. We conclude by considering the implications of our analysis in light of healthcare’s increasing reliance on sophisticated technologies of ‘personalised’ testing using genetic information and data analytics.