Towards a flexible, process-oriented IT architecture for an integrated healthcare network
Proceedings of the 2004 ACM symposium on Applied computing
Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
Statistical and Inductive Inference by Minimum Message Length (Information Science and Statistics)
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This paper presents a rationale, created from first principles, for the design criteria for the architecture of clinical information systems. The criteria are developed according to the heuristic axiom of Ockham's Razor, presented here for the first time and operationalised in the form of three principles; Generalization, Minimalization and Coverage. The minimal set of characteristics of the application is defined as -- the context, roles of physician, the nature of the data, the business processes, the change management program, and the criteria for success. This set of characteristics is developed to demonstrate how they define the details of a proposed architecture, which can be used to create not a clinical information system (CIS) but a generator of clinical information systems. The generator creates CISs that have the characteristics of complete user control of the design of all input and output presentations and workflow with real-time adaptability, ad hoc analytics with natural language processing of all free-text, all information automatically coded in a lingua franca terminology(s) of clinical choice, and native level interoperability between CISs An example of a CIS generated for the Trauma Service of an Australian hospital is described. The "generative" model is presented as a superset of the strategies for building best-of-breed and enterprise systems and thereby representing a new paradigm in Clinical Information System development. The parsimonious model is demonstrated by creating CISs requiring only 11 objects for designing the users interfaces along with their business logic.