An application of cmaps in the description of clinical information structure and logic in electronic health records

Abstract

The development and implementation of competent and cost-effective computerized medical records that profoundly improve physician productivity and knowledge management will require the development of a new paradigm for the representation and analysis of medical knowledge and logic. Medical knowledge is acquired inductively by observing, measuring, and eliciting information from patients in a process that is investigational rather than transactional. Most, if not all, current approaches to health information technology (HIT) rely on a logic and data structure that imposes significant limitations on the ability of physicians to thoroughly and efficiently document and access empiric patient data because the information is almost invariably organized in a way which presumes, rather than makes explicit, the relationships of concepts and their meaning. Cmapping provides a graphical method of capturing and displaying expert content knowledge that is simple to comprehend and modify and provides a foundation for a dynamic, inductive, and inclusive method of clinical documentation and research. The basis of medical decision analysis along with representative samples of medical knowledge modeling in the Cmap format is presented. The knowledge structures that are captured in Cmaps can be expressed directly in propositional logic, enabling the capability to convert Cmapped clinical expressions to be used to define a description logic for clinical evidence documentation and analysis that can in turn be mapped to multiple natural languages. The described description logic approach can be used to formulate digital messages and documents and to automate the process of converting description specifications formulated in propositional logic into operational electronic health record solutions for capture and reporting of clinical encounters. It has also been demonstrated that using Cmaps to elicit content knowledge from physicians to build point-of-care clinical documentation screens can significantly reduce the time and costs necessary to implement the physician's knowledge into operational systems and that using Cmaps eliminates the need for HIT expertise in the rules-encoding process.

Keywords: Cmaps; Health information technology; electronic health records; medical records; patient data.

Figures

Figure 1

Simple blood pressure description model.

Figure 2

Complex blood pressure description model.

Figure 3

Observation-Orientation-Decision-Action Loop.

Figure 4

Medical decision cycle.

Figure 5

Observation-Orientation-Decision-Action Loop—medical decision cycle.

Figure 6

Iris description model.

Figure 7

Macula lutea description model.

Figure 8

Iris clinical statement.

Figure 9

Vessels retina linked Cmap from Figure 7.

Figure 10

Location planar linked Cmap from Figures 6, 7, and 9.

Figure 11

Iris Cmap displayed using universally unique semantic identifier (uuSID)defined in Table 1.

Figure 12

Iris clinical statement.

Figure 13

Iris clinical statement in the existential form characteristic of a finding list.

Figure 14

MedTrak Systems, Inc, point-of-care EMR blood pressure template.

Figure 15

MedTrak Systems, Inc, point-of-care electronic medical record blood pressure template (Italian).