Título: Helping Clinicians Identify the Clinical Utility of Genetic Tests
Autores: Gu, Yulong; University of Auckland
Warren, Jim; University of Auckland
Day, Karen; University of Auckland
Fecha: 2011-07-19
Publicador: Electronic journal of health informatics
Fuente:
Tipo: info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion

Tema: Decision Support Systems, Clinical; Genetic Services; Genetic Testing; Information Technology
Descripción: Objective: Medical genetics presents great potential for improving healthcare outcomes, but faces challenges for managing the test results. This paper focuses on the gaps in clinician knowledge regarding genetic testing and asks what health information technologies (IT) can help non-specialists (e.g., General Practitioners) to identify the utility of an available genetic test. Methods: This is part of a grounded theory study in the context of New Zealand genetic services to identify core issues in genetic information management. 48 genetic service stakeholders were interviewed and their comments triangulated with our notes and organizational documents or guiding policies in the domain. Results: Little information is available to clinicians regarding 1) clear evidence for test utilities, 2) protocols for choosing among service models, and 3) clinical guidelines for patient management based on test results. It appears that these uncertainties are related to the ambiguity in clinician attitudes towards referring a patient for a test and in acting on the test results. Discussion: The heavy dependence on clinician knowledge presents opportunities for health IT innovators to assist clinicians in key tasks, such as assessing disease risks, identifying the benefits and availability of genetic tests, streamlining referral processes, and managing patients according to test results. Conclusion: The gaps in clinician knowledge regarding genetic testing, especially regarding its clinical utility, are a barrier for involving healthcare providers in genetic services delivery. Decision support systems and electronic referral systems may empower healthcare professionals with knowledge and tools to improve utilization of genetic information for better healthcare outcomes.
Idioma: Inglés

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