Modeling end-users' acceptance of a knowledge authoring tool.

OBJECTIVES: Knowledge bases comprise a vital component in the classic medical expert system model, yet the knowledge acquisition process by which they are created has been characterized as highly iterative and labor-intensive. The difficulty of this process underscores the importance of knowledge authoring tools that satisfy the demands of end-users. The authors hypothesize that the acceptability of a knowledge authoring tool for the creation of medical knowledge base content can be predicted by an accepted model in the information technology (IT) field, specifically the Technology Acceptance Model (TAM). METHODS: An online survey was conducted amongst knowledge base authors who had previously established experience with the authoring tool software. The Likert-based questions in the survey were patterned directly after accepted TAM constructs with minor modifications to particularize them to the software being used. The results were analyzed using structural equation modeling. RESULTS: The TAM performed well in predicting endusers' behavioral intentions to use the knowledge authoring tool. Five out of seven goodness-of-fit statistics indicate that the model represents the behavioral intentions of the authors well. All but one of the hypothesized relationships specified by the TAM were significant with p values less than 0.05. CONCLUSIONS: The TAM provides an adequate means by which development teams can anticipate and better understand what aspects of a knowledge authoring tool are most important to their target audience. Further research involving other behavioral models and an expanded user base will be necessary to better understand the scope of issues that factor into acceptability.

The knowledge authoring tool: an XML-based knowledge acquisition environment.

As part of an enterprise effort to develop new clinical information systems at Intermountain Health Care, we are developing a Knowledge Authoring Tool that facilitates the development of medical knowledge. At present, users of the application can compose order sets and other clinical knowledge documents based upon XML schemas. The flexible nature of the application allows for the authoring of new types of documents once an XML schema and accompanying web form have been developed and stored in a shared repository. The need for a knowledge acquisition tool stems largely from the desire for medical practitioners to be able to write their own content for clinical use. We hypothesize that knowledge content for clinical use can be successfully implemented around XML-based document frameworks containing structured and coded knowledge.