Author ORCID Identifier


Defense Date


Document Type


Degree Name

Doctor of Philosophy


Health Related Sciences

First Advisor

Teresa S. Nadder, Ph.D.

Second Advisor

Lauretta A. Cathers, Ph.D

Third Advisor

Melissa Jamerson, Ph.D.

Fourth Advisor

William J. Korzun, Ph.D.


Communication errors in health services delivery significantly compromise quality in clinical decision making (CDM). Diagnostic information generated by clinical laboratories (CL) accounts for as much as 93% of objective data in the clinical record and therefore is foundational in CDM. This work describes the Diagnostics Consultation Model© (DCM©), a CL communications portal, which supports CDM within interprofessional teams, providers, and institutions. Specific aims were to develop and validate a workflow prediction index (the complexity index, CI) to assign resolution of consultation requests based on an algorithm comprised of characteristics available at the point of consultation initiation. The CI functions as the entry to a workflow process directing consultation requests, first, to medical laboratory professional (MLP) for investigation and then branching into processes for tracking medical history, clinical information, resolution logic, conclusions, and recommendations for all health professionals involved in consultation CDM and for documentation in the health record.

Data to develop the CI were collected during CL daily activities and describe consultation characteristics important in CDM and available at the point of consultation initiation. The CI was validated with consultation characteristics available after consultation completion.

The work describes DCM© methodology which documents, characterizes, and analyzes workflow and improves CDM for MLP and other health professionals throughout health systems.

Conclusion DCM© methodology provides capability to follow individuals’ medical histories longitudinally and, through regular consultations, to address issues of access, equity, and compliance for the purpose of development of an evidence based, individualized care plan for every patient/consumer.


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