PATSy: Patient database for research and training

Cox, Richard, Kilgour, J and Lum, C (2008) PATSy: Patient database for research and training. [Dataset]

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Abstract

PATSy (www.patsy.ac.uk) is an established (since 1998) on-line learning resource. It is a web-based generic shell designed to accept data from any discipline that has cases. The domains represented on PATSy currently include developmental reading disorders, neuropsychology, neurology/medical rehabilitation and speech and language pathologies. At the time of writing, sixty-one data-rich and extensively described cases of adults and children with disorders can be accessed under 4 domain headings - speech and language, dyslexia, medical rehabilitation and neuropsychology. The system is used by more than 30 university departments including 80% of UK Speech and Language science departments. It is part of the DfES/Becta `National Grid for Learning' (NGfL) and is indexed in numerous refereed online resource databases including BIOME, SOSIG, LESTER, LTSN Psychology and LTSN Medicine. Student feedback and focus group evaluations have generally been positive (www.patsy.ac.uk/speech/reports.html) & (www.patsy.ac.uk/neuropsychology/report.html). PATSy is designed for use in conjunction with more traditional methods of clinical training, professional education and academic teaching about disorders. This multimedia database (video, audio, pictures) serves as an electronic archive for case-based research as it contains rich collections of test data on research participants. It offers health science students an opportunity to practice diagnostic reasoning on `virtual patients'. Students access real patient data in the form of videos, assessments, and medical histories. PATSy's virtual patients can have psychometric and cognitive assessment tests `administered' to them by learners. Typically, PATSy is used in blended learning contexts. Students attend clinical placements and tutors integrate online PATSy sessions with lecture content. PATSy complements taught content and clinical placements in important ways though. First, tutors are provided with a way of exposing a class of students to the same cases (clinical placements don't always expose students to a wide range of cases and student experiences on placements can vary widely). PATSy also contains published and rare cases that can bring the journal literature alive for students. PATSy cases are mostly research grade, which means that each case has been assessed in-depth compared to most clinical assessments. Different disciplines (speech & language therapy, neuropsychology, medical rehabilitation) can use PATSy cases inter-professionally. The PATSy system can be extensively configured to the particular needs of user-departments. To ensure wide uptake, the system has been deliberately designed to be agnostic with respect to clinical teaching models (eg. information processing models versus traditional diagnostic models). Lecturers can `hold back' PATSy cases. Students can then be assessed dynamically and authentically as they diagnose a previously-unseen case using PATSy in its exam mode. Clinical reasoning is difficult to teach via direct instruction. It is difficult to give students a set of rules that they may universally apply (Williams, 1993; Jonassen, 1996). For this reason clinical science education (like law and other professions) is tending to adopt case-based teaching methods. Knowledge of the subject is represented in the form of many example cases (eg. Irby, 1994; Whitworth, Franklin & Dodd, 2004). PATSy is particularly well-suited to case-based teaching and for use in problem-based learning contexts. PATSy supports several types of use - researchers and clinicians canaccess the cases and see test data summaries, information about the patientfrom the case contributor, and access a list of research publications relating to the patient. In contrast, student access can be set up so that students are not presented with test data summaries but are, instead, required to work through and interpret test results.

Item Type: Dataset
Schools and Departments: School of Engineering and Informatics > Informatics
Depositing User: Richard Cox
Date Deposited: 06 Feb 2012 19:18
Last Modified: 06 Feb 2012 21:39
URI: http://sro.sussex.ac.uk/id/eprint/20026
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