Translation of personalized decision support into routine diabetes care.
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.


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.
Institute of Diabetes Gerhardt Katsch Karlsburg, Karlsburg, Germany.
Petra
P
Augstein
Lutz
L
Vogt
Klaus-Dieter
KD
Kohnert
Peter
P
Heinke
Eckhard
E
Salzsieder
D000368:Aged; D001291:Attitude of Health Personnel; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000187:drug effects / Q000378:metabolism; D002318:Cardiovascular Diseases / Q000150:complications / Q000628:therapy*; D016009:Chi-Square Distribution; D020000:Decision Support Systems, Clinical; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000150:complications / Q000188:drug therapy*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000150:complications / Q000188:drug therapy*; D005260:Female; D005858:Germany; D006442:Glycated Hemoglobin / Q000378:metabolism; D007722:Health Knowledge, Attitudes, Practice; D006801:Humans; D007003:Hypoglycemia / Q000139:chemically induced; D007004:Hypoglycemic Agents / Q000009:adverse effects / Q000627:therapeutic use*; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory; D009313:National Health Programs; D015397:Program Evaluation; D012189:Retrospective Studies; D011795:Surveys and Questionnaires; D013997:Time Factors; D016896:Treatment Outcome
D015415:Biomarkers; D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; C517652:hemoglobin A1c protein, human