Performance Evaluation Clinical Task Ontology(PECTO): An approach for building simulation-based evaluation of new technologies and their effect on health worker performance

Jose F. Florez-Arango, Santiago Patiño-Giraldo, M. Sriram Iyengar, Jack W. Smith

Research output: Contribution to journalConference articlepeer-review


This poster presents a proposed Clinical Tasks Ontology (PECTO) designed to evaluate effects of technologies on human performance under controlled conditions, such as clinical simulation scenarios (CSS), across multiple clinical domains including prehospital care. In recent years there has been an explosion of technologies, including Information and Communications Technologies (ICTs) that are designed to assist health workers and improve their performance across a spectrum of clinical activities from pre-hospital care to post-surgical care. However, each new technology introduces its own requirements on the health worker and has the potential to either increase or decrease the perceived workload on the health-worker. Since perceived workload can have significant effects on health worker performance [4], it is important to carefully measure work-load changes and relate these to health worker performance measures such as task errors, and procedure compliance. Clinical Simulation Scenarios are often used to perform controlled experiments in which health workers' performance on clinical conditions, simulated by various means, including Human Patient Simulators, is observed and measured with and without the technology being studied[5]. The Clinical Tasks Ontology (PECTO) was developed, among other applications, to help design such evaluation experiments. A major objective of such studies is to evaluate the performance of health workers as they perform specific clinical tasks. In this context, the PECTO presents a novel approach for task classification and analysis since previous approaches [6]-[8] do not account for sources of workload, and measurement of human performance in terms of errors and protocol compliance. An ontological approach was selected to build the classification system enabling tasks to have multiple properties that can be related to dependent variables. Previous work in task analysis and task classification include an ontological approach to plans and processes[6], some modeling of event evaluation [7], and a clinical task model of care plans[8], as well as comprehensive approaches to model human factors and workload.

Original languageEnglish (US)
JournalCEUR Workshop Proceedings
StatePublished - 2016
Externally publishedYes
Event2016 Joint International Conference on Biological Ontology and BioCreative - Food, Nutrition, Health and Environment for the 9 Billion, ICBO-BioCreative 2016 - Corvallis, United States
Duration: Aug 1 2016Aug 4 2016

ASJC Scopus subject areas

  • Computer Science(all)


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