TOWARD CASE‐BASED REASONING FOR DIABETES MANAGEMENT: A PRELIMINARY CLINICAL STUDY AND DECISION SUPPORT SYSTEM PROTOTYPE

This paper presents a case‐based decision support system prototype to assist patients with Type 1 diabetes on insulin pump therapy. These patients must vigilantly maintain blood glucose levels within prescribed target ranges to prevent serious disease complications, including blindness, neuropathy, and heart failure. Case‐based reasoning (CBR) was selected for this domain because (a) existing guidelines for managing diabetes are general and must be tailored to individual patient needs; (b) physical and lifestyle factors combine to influence blood glucose levels; and (c) CBR has been successfully applied to the management of other long‐term medical conditions. An institutional review board (IRB) approved preliminary clinical study, involving 20 patients, was conducted to assess the feasibility of providing case‐based decision support for these patients. Fifty cases were compiled in a case library, situation assessment routines were encoded to detect common problems in blood glucose control, and retrieval metrics were developed to find the most relevant past cases for solving current problems. Preliminary results encourage continued research and work toward development of a practical tool for patients.

[1]  Luigi Portinale,et al.  Cased-Based Reasoning for medical knowledge-based systems , 2001, Int. J. Medical Informatics.

[2]  Enrique J. Gómez,et al.  Telemedicine as a tool for intensive management of diabetes: the DIABTel experience , 2002, Comput. Methods Programs Biomed..

[3]  Carl van Walraven,et al.  Clinical inertia in response to inadequate glycemic control: do specialists differ from primary care physicians? , 2005, Diabetes care.

[4]  Francisco del Pozo,et al.  New trends in diabetes management: mobile telemedicine closed-loop system. , 2004, Studies in health technology and informatics.

[5]  Riccardo Bellazzi,et al.  Supporting decisions in medical applications: the knowledge management perspective , 2002, Int. J. Medical Informatics.

[6]  Abdul V. Roudsari,et al.  Integrating model-based decision support in a multi-modal reasoning system for managing type 1 diabetic patients , 2003, Artif. Intell. Medicine.

[7]  Isabelle Bichindaritz,et al.  Case-Based Reasoning in CARE-PARTNER: Gathering Evidence for Evidence-Based Medical Practice , 1998, EWCBR.

[8]  S. Genuth,et al.  The effect of intensive treatment of diabetes on the development and progression of long-term complications in insulin-dependent diabetes mellitus. , 1993, The New England journal of medicine.

[9]  Isabelle Bichindaritz,et al.  Case-based reasoning in the health sciences: What's next? , 2006, Artif. Intell. Medicine.

[10]  Enrique J. Gómez,et al.  A telemedicine support for diabetes management: the T-IDDM project , 2002, Comput. Methods Programs Biomed..

[11]  Cynthia R. Marling,et al.  Case-Based Reasoning in the Care of Alzheimer's Disease Patients , 2001, ICCBR.

[12]  Richard W Grant,et al.  Quality of diabetes care in U.S. academic medical centers: low rates of medical regimen change. , 2005, Diabetes care.

[13]  Markus Nilsson,et al.  Advancements and Trends in Medical Case-Based Reasoning: An Overview of Systems and System Development , 2004, FLAIRS.

[14]  Christian Popow,et al.  VIE-DIAB: A Support Program for Telemedical Glycaemic Control , 2003, AIME.

[15]  Janet L. Kolodner,et al.  Case-Based Reasoning , 1989, IJCAI 1989.

[16]  Janet L. Kolodner,et al.  Improving Human Decision Making through Case-Based Decision Aiding , 1991, AI Mag..

[17]  L Gierl,et al.  Case-based reasoning for medical knowledge-based systems. , 2000, Studies in health technology and informatics.