Knowledge Management to Support Performance-based Medicine

Summary

Objectives: To discuss research issues for medical informatics in order to support the further development of health information systems, exploiting knowledge management and information and communication technology to increase the performance of Health Care Organizations (HCOs).

Methods: Analyze the potential of exploiting knowledge management technology in medicine.

Results and conclusions: The increasing pressure on HCOs to ensure efficiency and cost-effectiveness, balance the quality of care, and contain costs will drive them towards more effective management of medical knowledge derived from biomedical research. Knowledge management technology may provide effective methods and tools in speeding up the diffusion of innovative medical procedures. Reviews of the effectiveness of various methods of best practice dissemination show that the greatest impact is achieved when such knowledge is made accessible through the health information system at the moment it is required by care providers at their work sites. There is a need to take a more clinical process view of health care delivery and to identify the appropriate organizational and information infrastructures to support medical work. Thus, the great challenge for medical informatics is represented by the effective exploitation of the astonishing capabilities of new technologies to assure the conditions of knowledge management and organizational learning within HCOs.

Keywords

Health care organization - evidence based medicine - patient care process - knowledge management - careflow management

• References

• 1 Felch WC, Scanlon DM. Bridging the gap between research and practice. JAMA 2001; 2 (Suppl. 277) 155-6.
• 2 Millenson ML. Demanding Medical Excellence. 2nd ed. Chicago, USA: The University Chicago Press; 1999
• 3 Brook RH, McGlynn EA, Cleary PD. Measuring quality of care. N Engl J Med 1996; 335: 966-70.
• 4 Tanenbaum SJ. What physicians know. N Engl J Med 1993; 329: 1268-71.
• 5 Feder G, Eccles M, Grol R, Griffiths C, Grimshaw J. Using clinical guidelines. BMJ 1999; 318: 728-30.
• 6 Smith RG, Farquhar A. The road ahead for knowledge management. AI Magazine 2000; Winter 2000: 17-40.
• 7 Stefanelli M. The socio-organizational age of artificial intelligence in medicine. Artif Intell Med 2001; 23: 25-47.
• 8 Wenger E. Communities of Practice. New York, NY: Cambridge University Press; 1998
• 9 Polanyi M. The Tacit Dimension. London, UK: Routledge & Kegan Paul; 1966
• 10 Nonaka I, Takeuchi H. The Knowledge-Creating Company. Oxford, UK: University Press; 1995
• 11 Schreiber ATh, Akkermans JM, de Hoog R, Shadbolt NR, Van de Velde W, Wielinga BJ. Knowledge Engineering and Management. The CommonKADS Methodology. Cambridge, MA: The MIT Press; 2000
• 12 Abidi SSR. Knowledge management in health-care: towards ’knowledge-driven’ decision-support services. Int J Med Inf 2001; 63 1-2 5-18.
• 13 Von Krogh G, Ichijo K, Nonaka I. Enabling Knowledge Creation. New York, USA: Oxford University Press; 2001
• 14 Kuhn KA, Giuse D. From hospital information systems to health information systems – problems, challenges, pespectives. Methods Inf Med 2001; 40 (Suppl. 04) 275-87.
• 15 Fischer L. The Workflow Paradigm. 2nd ed. Lighthouse Point, USA: Future Strategies Inc., Book Division; 1995
• 16 Workflow Management Coalition.. aiim.org/wfmc/mainframe.htm
• 17 van der Aalst WMP. Three good reasons for using a Petri-net-based Workflow Management System. In: Information and Process Integration in Enterprises: Rethinking Documents. Wakayama T, Kannapan T, Khoong CM, Navathe S, Yates J. editors. Boston, MA: Kluwer Academic Publishers; 1998: 161-82.
• 18 Modeling and analyzing inter-organisational workflows.. Fukushima. Japan: IEEE Computer Society Press; 1998
• 19 Coiera E. When communication is better than computation. J Am Med Inform Assoc 2000; 7: 277-86.
• 20 Flores F. Management and Communication in the Office of the Future. Department of Philosophy University of California; at Berkeley: 1979
• 21 Boland RJ, Tenkasi RV. Perspective making and perspective taking in communities of knowing. Organization Science 1995; 6 (Suppl. 04) 350-72.
• 22 Dewey J. Logic: The Theory of Inquiry. New York, NY: Holt, Rinehart and Winston; 1938
• 23 Fox MS, Gruninger M. Enterprise modeling. AI Magazine 2000; Fall 1998: 109-21.
• 24 Falasconi S, Dazzi L, Lanzola G, Quaglini S, Saracco R, Stefanelli M. Towards cooperative patient management through organizational and medical ontologies. Methods Inf Med 1998; 37: 564-75.
• 25 Argyris C, Schön DA. Organizational Learning II. London, UK: Addison Wesley; 1996
• 26 NHS Executive.. Quality and Performance in the NHS. Performance Indicators: July 2000. 2000 Ref Type: Report
• 27 Heathfield H, Pitty D, Hanka R. Evaluating information technology in health care: barriers and challenges. BMJ 1998; 316: 1959-61.
• 28 Barley V, Neale G, Burns-Cox C, Savage P, Machin S, El Sobky A. et al. Reducing error, improving safety. BMJ 2000; 321 7259 505-14.
• 29 Reason J. Human error: models and management. BMJ 2000; 320: 768-70.
• 30 Adams HP, Brott TG, Crowell RM, Furln AJ, Gomez CR, Grotta J. et al. Guidelines for the management of patients with acute ischemic stroke. Stroke 1994; 25 (Suppl. 09) 1901-11.
• 31 Micieli G, Cavallini A, Anzola GP, Frattola L, Mamoli A, Stefanelli M. et al. Guideline compliance improves stroke survival. Proceedings of the 4th World Stroke Congress. Melbourne; Australia: 2000
• 32 Quaglini S, Rognoni C, Cavallini A, Micieli G. Evaluating the impact of a clinical practice guideline on stroke outcomes. In: Quaglini S, Barahona P, Andreassen S. editors. 8th Conference on Artificial Intelligence in Medicine in Europe, AIME 2001. Cascais, Portugal: Springer; 2001: 442-52.