Translation of personalized decision support into routine diabetes care

J Diabetes Sci Technol. 2010 Nov 1;4(6):1532-9. doi: 10.1177/193229681000400631.

Abstract

Objective: The aim of this study was to evaluate the impact of personalized decision support (PDS) on metabolic control in people with diabetes and cardiovascular disease.

Research design and methods: The German health insurance fund BKK TAUNUS offers to its insured people with diabetes and cardiovascular disease the possibility to participate in the Diabetiva® program, which includes PDS. Personalized decision support is generated by the expert system KADIS® using self-control data and continuous glucose monitoring (CGM) as its data source. The physician of the participating person receives the PDS once a year, decides about use or nonuse, and reports his/her decision in a questionnaire. Metabolic control of participants treated by use or nonuse of PDS for one year and receiving CGM twice was analyzed in a retrospective observational study. The primary outcome was hemoglobin A1c (HbA1c); secondary outcomes were mean sensor glucose (MSG), glucose variability, and hypoglycemia.

Results: A total of 323 subjects received CGM twice, 289 had complete data sets, 97% (280/289) were type 2 diabetes patients, and 74% (214/289) were treated using PDS, resulting in a decrease in HbA1c [7.10±1.06 to 6.73±0.82%; p<.01; change in HbA1ct0-t12 months -0.37 (95% confidence interval -0.46 to -0.28)] and MSG (7.7±1.6 versus 7.4±1.2 mmol/liter; p=.003) within one year. Glucose variability was also reduced, as indicated by lower high blood glucose index (p=.001), Glycemic Risk Assessment Diabetes Equation (p=.009), and time of hyper-glycemia (p=.003). Low blood glucose index and time spent in hypoglycemia were not affected. In contrast, nonuse of PDS (75/289) resulted in increased HbA1c (p<.001). Diabetiva outcome was strongly related to baseline HbA1c (HbA1ct0; p<.01) and use of PDS (p<.01). Acceptance of PDS was dependent on HbA1ct0 (p=.049).

Conclusions: Personalized decision support has potential to improve metabolic outcome in routine diabetes care.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aged
  • Attitude of Health Personnel
  • Biomarkers / blood
  • Blood Glucose / drug effects
  • Blood Glucose / metabolism
  • Cardiovascular Diseases / complications
  • Cardiovascular Diseases / therapy*
  • Chi-Square Distribution
  • Decision Support Systems, Clinical*
  • Diabetes Mellitus, Type 1 / blood
  • Diabetes Mellitus, Type 1 / complications
  • Diabetes Mellitus, Type 1 / drug therapy*
  • Diabetes Mellitus, Type 2 / blood
  • Diabetes Mellitus, Type 2 / complications
  • Diabetes Mellitus, Type 2 / drug therapy*
  • Female
  • Germany
  • Glycated Hemoglobin / metabolism
  • Health Knowledge, Attitudes, Practice
  • Humans
  • Hypoglycemia / chemically induced
  • Hypoglycemic Agents / adverse effects
  • Hypoglycemic Agents / therapeutic use*
  • Logistic Models
  • Male
  • Middle Aged
  • Monitoring, Ambulatory*
  • National Health Programs
  • Program Evaluation
  • Retrospective Studies
  • Surveys and Questionnaires
  • Time Factors
  • Treatment Outcome

Substances

  • Biomarkers
  • Blood Glucose
  • Glycated Hemoglobin A
  • Hypoglycemic Agents
  • hemoglobin A1c protein, human