Using process elicitation and validation to understand and improve chemotherapy ordering and delivery

Tufts University School of Medicine, Boston, USA.
Joint Commission journal on quality and patient safety / Joint Commission Resources 11/2012; 38(11):497-505.
Source: PubMed


Chemotherapy ordering and administration, in which errors have potentially severe consequences, was quantitatively and qualitatively evaluated by employing process formalism (or formal process definition), a technique derived from software engineering, to elicit and rigorously describe the process, after which validation techniques were applied to confirm the accuracy of the described process.
The chemotherapy ordering and administration process, including exceptional situations and individuals' recognition of and responses to those situations, was elicited through informal, unstructured interviews with members of an interdisciplinary team. The process description (or process definition), written in a notation developed for software quality assessment purposes, guided process validation (which consisted of direct observations and semistructured interviews to confirm the elicited details for the treatment plan portion of the process).
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 declined significantly during and after the project, which was conducted from October 2007 through August 2008.
Each elicitation method and the subsequent validation discussions contributed uniquely to understanding the chemotherapy treatment plan review process, supporting rapid adoption of changes, improved communication regarding the process, and ensuing error reduction.

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Available from: Jenna L Marquard, Jan 10, 2014
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    ABSTRACT: Human errors are a major concern in many medical processes. To help address this problem, we are investigating an approach for automatically detecting when performers of a medical process deviate from the acceptable ways of performing that process as specified by a detailed process model. Such deviations could represent errors and, thus, detecting and reporting deviations as they occur could help catch errors before harm is done. In this paper, we identify important issues related to the feasibility of the proposed approach and empirically evaluate the approach for two medical procedures, chemotherapy and blood transfusion. For the evaluation, we use the process models to generate sample process executions that we then seed with synthetic errors. The process models describe the coordination of activities of different process performers in normal, as well as in exceptional situations. The evaluation results suggest that the proposed approach could be applied in clinical settings to help catch errors before harm is done.
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