E Kilsdonk1, L W Peute2, R J Riezebos3, L C Kremer4, M W M Jaspers5. 1. Centre for Human Factors Engineering of interactive Health Information Technology (HIT-lab), Department of Medical Informatics, Academic Medical Center, University of Amsterdam, The Netherlands. Electronic address: e.kilsdonk@amc.uva.nl. 2. Centre for Human Factors Engineering of interactive Health Information Technology (HIT-lab), Department of Medical Informatics, Academic Medical Center, University of Amsterdam, The Netherlands. Electronic address: l.w.peute@amc.uva.nl. 3. Centre for Human Factors Engineering of interactive Health Information Technology (HIT-lab), Department of Medical Informatics, Academic Medical Center, University of Amsterdam, The Netherlands. Electronic address: rinkeriezebos@gmail.com. 4. Department of Pediatric Oncology, Emma Children's Hospital/Academic Medical Center, University of Amsterdam, The Netherlands. Electronic address: l.c.kremer@amc.uva.nl. 5. Centre for Human Factors Engineering of interactive Health Information Technology (HIT-lab), Department of Medical Informatics, Academic Medical Center, University of Amsterdam, The Netherlands. Electronic address: m.w.jaspers@amc.uva.nl.
Abstract
OBJECTIVE: To investigate whether the use of the think-aloud method with propositional analysis could be helpful in the design of a Clinical Decision Support System (CDSS) providing guideline recommendations about long-term follow-up of childhood cancer survivors. MATERIALS AND METHODS: The think-aloud method was used to gain insight into healthcare professionals' information processing while reviewing a paper-based guideline. A total of 13 healthcare professionals (6 physicians and 7 physician assistants) prepared 2 fictitious patient consults using the paper-based guideline. Propositional analysis was used to analyze verbal protocols of the think-aloud sessions. A prototype CDSS was developed and a usability study was performed, again with the think-aloud method. RESULTS: The analysis revealed that the paper-based guideline did not support healthcare practitioners in finding patient-specific recommendations. An information processing model for retrieving recommendations was developed and used as input for the design of a CDSS prototype user interface. Usability analysis of the prototype CDSS showed that the navigational structure of the system fitted well with healthcare practitioners' daily practices. CONCLUSIONS: The think-aloud method combined with propositional analysis of healthcare practitioners' verbal utterances while they processed a paper-based guideline was useful in the design of a usable CDSS providing patient-specific guideline recommendations.
OBJECTIVE: To investigate whether the use of the think-aloud method with propositional analysis could be helpful in the design of a Clinical Decision Support System (CDSS) providing guideline recommendations about long-term follow-up of childhood cancer survivors. MATERIALS AND METHODS: The think-aloud method was used to gain insight into healthcare professionals' information processing while reviewing a paper-based guideline. A total of 13 healthcare professionals (6 physicians and 7 physician assistants) prepared 2 fictitious patient consults using the paper-based guideline. Propositional analysis was used to analyze verbal protocols of the think-aloud sessions. A prototype CDSS was developed and a usability study was performed, again with the think-aloud method. RESULTS: The analysis revealed that the paper-based guideline did not support healthcare practitioners in finding patient-specific recommendations. An information processing model for retrieving recommendations was developed and used as input for the design of a CDSS prototype user interface. Usability analysis of the prototype CDSS showed that the navigational structure of the system fitted well with healthcare practitioners' daily practices. CONCLUSIONS: The think-aloud method combined with propositional analysis of healthcare practitioners' verbal utterances while they processed a paper-based guideline was useful in the design of a usable CDSS providing patient-specific guideline recommendations.
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