Abstract
89 Background: Chemotherapy order/administration consists of complex, interrelated processes where errors have potentially severe consequences. We report a study that quantitatively and qualitatively evaluated chemotherapy delivery employing a formal process definition language to elicit and describe rigorously the process, then applied mathematical validation techniques to confirm the description, analogously to how computer software development and other industries use accurate, precise process definitions to assure soundness through redundancy and correct event sequencing. Methods: The process, including exceptional situations and individuals’ recognition of and responses to these, was elicited through informal, unstructured interviews with members of an interdisciplinary team. The resulting process description (or process definition), written in a notation developed for software development process assessment, guided chemotherapy process validation consisting of rigorous process definition analysis, direct observations, and semi-structured interviews to confirm the elicited details for the treatment plan sub-process. Results: The overall process definition yielded 467 steps; 207 steps (44%) were dedicated to handling 59 exceptional situations. Validation yielded 82 unique process events (35 new expected but not yet described steps, 16 new exceptional situations, and 31 new steps in response to exceptional situations). Process participants actively altered the process as ambiguities and conflicts were discovered by the elicitation and validation components of the study. Chemotherapy error rates (evaluated by our safety reporting system) declined during and after the project (p <.001). Conclusions: The initial elicitation methods and subsequent validation discussions supported rapid adoption of changes, improved communication regarding the process, and yielded error reduction. A combination of rigorous elicitation and validation methods creates increasingly accurate descriptions of complex but repetitive medical processes, leading to identification and removal of existing process defects while avoiding the creation of new defects as processes evolve.
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