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Author ORCID Identifier



Open Access Dissertation

Document Type


Degree Name

Doctor of Philosophy (PhD)

Degree Program

Industrial Engineering & Operations Research

Year Degree Awarded


Month Degree Awarded


First Advisor

Jenna Marquard

Second Advisor

Elizabeth Henneman

Subject Categories

Health Information Technology | Industrial Engineering | Nursing | Systems Engineering | Technology and Innovation


Health information technology (IT) implementation can be costly, and remains a challenging problem with mixed outcomes on patient safety and quality of care. Systems engineering and IT management experts have advocated the use of sociotechnical models to understand the impact of health IT on user and organizational factors.

Sociotechnical models suggest the need for user-centered implementation approaches, such as user training and support, and focus on processes to mitigate the negative impact and facilitate optimal IT use during training. The training design and development should also follow systematic processes guided by instructional development models. It should take into account of users’ characteristics of learning, and employ scientific training theories to adopt validated methods that facilitate learning and health IT integration.

My study aimed to develop and evaluate a scientific model-guided and systematically developed health IT user training program that explicitly mitigate IT negative impact and facilitate optimal use. I used an electronic health record (EHR) as the health IT, and used medication reconciliation as the clinical task. I developed a sociotechnical model to guide analysis of users’ clinical tasks and their IT interaction, and utilized this model to analyze technical aspects of an EHR, and explicitly integrate the EHR into the workflow of a medication reconciliation task. I designed and developed the training program following existing models, and designed cognitive mapping based interventions to facilitate learning and health IT integration.

I implemented and evaluated the training program using a controlled experiment with nursing senior baccalaureate students. Evaluation of participants’ training performance showed that the developed training program was effective. The training program improved trainees’ system use competency by comparing trainees’ pre- and post- training performance, i.e., trainees were able to conduct clinical tasks using the EHR correctly and efficiently, and transfer the competency to use another EHR after training. The training also improved trainees’ clinical outcomes by comparing clinical outcomes between the two training conditions, i.e., trainees who learned cognitive mapping were more competent to identify medication discrepancies. This result implied the proposed methodology could be used as an approach to health IT training, and may be generalizable to other clinical tasks, environments, or role-types.