Presentation on theme: "Which kind of knowledge is suitable for redesigning hospital logistic processes? Laura Măruşter and René J. Jorna Faculty of Management and Organization,"— Presentation transcript:
Which kind of knowledge is suitable for redesigning hospital logistic processes? Laura Măruşter and René J. Jorna Faculty of Management and Organization, University of Groningen, The Netherlands AIME’ 05, Aberdeen, Scotland
The problem The number of “multi-disciplinary” patients is growing: aging population, an increased specialization of doctors special centers have emerged, comprising different specialisms - we need knowledge expressed in explicit models to create multi-disciplinary units: different specialisms coordinate the treatment of specific groups of patients How to redesign the hospital logistic processes?
Our proposed approach We propose a knowledge management perspective for business process modelling –Knowledge content: analysing, modelling and reorganizing processes –Knowledge types: sensory, coded and theoretical knowledge [Boisot (1995), Jorna&vanHeusden (2000)] Sensory knowledge: based on sensory experience; it is very difficult to code. Coded knowledge: based on a conventional relation between the representation and that which is being referred to: texts, drawings, or mathematical formulas. Theoretical knowledge: why certain pieces of knowledge belong together; it is often used to identify causal relations (i.e. if-then-relations)
The knowledge management perspective for process modeling A. Knowledge creation: 1. Row Data → Coded Knowledge (RD →CK), 2. Coded Knowledge → Theoretical Knowledge (CK →TK) B. Knowledge use and transfer: - used for analyzing, diagnosing and reorganizing the logistic hospital process - easily transferred to other people, or parts of the organization.
I. Knowledge creation Result1: Developing Logistic Patient Groups 1.Operationalizing logistic complexity (6 logistic variables): RD → CK 2.Clustering logistic variables: CK → TK => two clusters: “moderately complex patients”, “complex patients” 3.Characterizing the clusters, via a rule- based model : CK → TK
I. Knowledge creation (cnt.) Result2: Constructing process models: CK → TK a). Petri net process models –Process mining: deriving process models from data, recorded at runtime in a process log. b). Instance graph process models - a graph where each node represents one log entry of a specific instance
The Petri net process model for “moderately complex patients” The Petri net process model for “complex patients” 3. CK → TK
The instance graph for five patients in the ``moderately complex'' cluster, with diagnosis “d440” – atherosclerosis. 4. CK → TK
Knowledge use and transfer Knowledge use: two new multi-disciplinary units can be created: 1. “moderately complex”: CHR, CRD, INT, NRL, NEUR 2. “complex”: CHR, CRD, INT, NRL, NEUR, OGH, LNG,ADI Knowledge transfer: the knowledge should be transparent, understandable and easy to be checked by all involved parties; our approach provides robust theoretical knowledge of a highly abstract kind of the logistic hospital process.
So, which kind of knowledge is suitable for redesigning hospital logistic processes?