A hypermedia-based group decision support system to support collaborative medical decision-making

Abstract

The systematic evolution of a hypermedia-based group decision support system (GDSS) architecture to support collaborative medical decision-making (MDM) is presented in this paper. This GDSS is for subsequent use by designers and researchers in the GDSS/medical informatics arena who can use several or parts of the presented architecture for effecting collaborative MDM. The GDSS design also supports various levels of inference-based medical support ranging from the lower diagnostic levels to the higher clinical levels. The evolution of this architecture incorporated systematic research and investigation of the basic elements of the MDM process, associated procedures, tools and the potential impact of different characteristics of medical groups. This architecture incorporates clinical reasoning and problem-solving features identified through an analysis of the schools of MDM from a GDSS perspective. Identification of inadequacies from a collaborative MDM perspective of existing GDSS research frameworks and architectures has also influenced current architecture development. The inexact nature of cognitive processes that are inherent in MDM necessitated the incorporation of “cognitive-aid structures” and the “cognitive appropriation processes” architectural components. The MEDICALWARE™ 1 1 MEDICALWARE is a trademark of Quantum Enterprises, NJ. component, integrated with a GDSS is designed to provide problem-solving support, access to clinical algorithms and procedures, expert inference support and several MDM support tools with hypermedia functionality. Hypertext templates with semantic nodes and links provide group members the ability to modify templates for accommodating expected or unexpected variations in decision-making criterion in handling a clinical case. Group members can thus ascertain whether they have followed all required procedures and algorithms, and modify diagnostic procedures if necessary. Several facets of the GDSS architecture can be prototyped and field-tested, incorporating clinical algorithms and related diagnostic support tools. The GDSS architecture presented can also be used for empirical studies in collaborative MDM.