Combining statistical, rule-based, and physiologic model-based methods to assist in the management of diabetes mellitus.
Self-monitoring of capillary blood glucose is used by most patients with insulin-dependent diabetes mellitus as a means of assessing metabolic control. Therapeutic interventions are based on retrospective analysis of glycemic response to various factors, with insulin and diet playing the key roles. We describe a computer system being developed for intelligent automated analysis and interpretation of data relevant to glycemic control. CADMO (Computer-Assisted Diabetes Monitor) is intended to assist health care professionals with the management of patients with insulin-dependent diabetes. It takes as input glucose values and insulin doses collected via a memory meter by the patient over a period of several weeks. Rule-based logic, statistical methods, and a physiologic model of insulin pharmacokinetics and glucose dynamics are used to help detect meaningful patterns and trends in glucose and insulin data and to suggest approaches for optimizing insulin regimens.
Medical Informatics Program, Yale University School of Medicine, New Haven, Connecticut 06510.
M P
MP
Berger
R A
RA
Gelfand
P L
PL
Miller
D001786:Blood Glucose / Q000378:metabolism; D003627:Data Interpretation, Statistical; D003922:Diabetes Mellitus, Type 1 / Q000188:drug therapy* / Q000378:metabolism; D004334:Drug Administration Schedule; D004360:Drug Therapy, Computer-Assisted; D005103:Expert Systems; D006801:Humans; D007328:Insulin / Q000008:administration & dosage; D008838:Microcomputers; D008991:Monitoring, Physiologic; D012107:Research Design; D012651:Self Medication; D012984:Software; D013813:Therapy, Computer-Assisted
D001786:Blood Glucose; D007328:Insulin