PMID- 21527112
OWN - NLM
STAT- MEDLINE
DCOM- 20111129
LR  - 20211020
IS  - 1932-2968 (Electronic)
IS  - 1932-2968 (Linking)
VI  - 5
IP  - 2
DP  - 2011 Mar 1
TI  - Design of a decision support system to help clinicians manage glycemia in 
      patients with type 2 diabetes mellitus.
PG  - 402-11
AB  - OBJECTIVE: We sought to develop a computerized clinical decision support for 
      clinicians treating patients with type 2 diabetes mellitus (T2DM). METHODS: We 
      designed, developed, and tested a computer-assisted decision support (CADS) 
      system using statistical analyses of self-monitoring of blood glucose data, 
      laboratory data, medical and medication history, and individualized hemoglobin 
      A1c goals. A rule-based expert system generated recommendations for changes in 
      therapy and accompanying explanations. RESULTS: A clinical decision support 
      system (CADS) was developed that considers 9 classes of medications and 69 
      regimens with combinations of up to 4 therapeutic agents. The preferred sequences 
      of regimens can be customized. The program is integrated with a "comprehensive 
      diabetes management system," electronic medical record systems, and a method for 
      uploading data from memory glucose meters via telephone without use of a computer 
      or the Internet. The software provides a report to the clinician regarding the 
      overall quality of glycemic control and identifies problems, e.g., hypoglycemia, 
      hyperglycemia, glycemic variability, and insufficient data. The program can 
      recommend continuation of current therapy, adjustment of dosages of current 
      medications, or change of regimen and can provide explanations for its 
      recommendations. If the user rejects the recommendations, the program will 
      recommend alternative approaches. The CADS also provides access to Food and Drug 
      Administration-approved prescribing information, guidelines from professional 
      organizations, and selections from the general medical literature. The system has 
      been extensively tested with real and synthetic data and is ready for evaluation 
      in multicenter clinical trials. CONCLUSION: A clinical decision support system to 
      assist with the management of patients with T2DM was designed, developed, tested, 
      and found to perform well.
CI  - (c) 2011 Diabetes Technology Society.
FAU - Rodbard, David
AU  - Rodbard D
AD  - Biomedical Informatics Consultants LLC, Potomac, Maryland 20854-4721, USA. 
      drodbard@comcast.net
FAU - Vigersky, Robert A
AU  - Vigersky RA
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20110301
PL  - United States
TA  - J Diabetes Sci Technol
JT  - Journal of diabetes science and technology
JID - 101306166
RN  - 0 (Blood Glucose)
RN  - 0 (Insulin)
RN  - 9100L32L2N (Metformin)
SB  - IM
MH  - Administration, Oral
MH  - Algorithms
MH  - Blood Glucose/analysis
MH  - *Decision Support Systems, Clinical
MH  - *Decision Support Techniques
MH  - Diabetes Mellitus, Type 2/*blood/*therapy
MH  - Female
MH  - Humans
MH  - Hyperglycemia/*blood
MH  - Insulin/administration & dosage
MH  - Male
MH  - Metformin/administration & dosage
MH  - Models, Statistical
MH  - Software
PMC - PMC3125935
EDAT- 2011/04/30 06:00
MHDA- 2011/12/13 00:00
PMCR- 2012/03/01
CRDT- 2011/04/30 06:00
PHST- 2011/04/30 06:00 [entrez]
PHST- 2011/04/30 06:00 [pubmed]
PHST- 2011/12/13 00:00 [medline]
PHST- 2012/03/01 00:00 [pmc-release]
AID - dst.5.2.0402 [pii]
AID - 10.1177/193229681100500230 [doi]
PST - epublish
SO  - J Diabetes Sci Technol. 2011 Mar 1;5(2):402-11. doi: 10.1177/193229681100500230.