Effect of Health Information Technologies on Cardiovascular Risk Factors among Patients with Diabetes

Details

• Alternative Title:
  Curr Diab Rep
• Personal Author:
  Yoshida, Yilin ; Boren, Suzanne A. ; Soares, Jesus ; Popescu, Mihail ; Nielson, Stephen D. ; Koopman, Richelle J. ; Kennedy, Diana R. ; Simoes, Eduardo J.
• Description:
  Purpose of Review
  
  To identify a common effect of health information technologies (HIT) on the management of cardiovascular disease (CVD) risk factors among people with type 2 diabetes (T2D) across randomized control trials (RCT).
  
  Recent Findings
  
  CVD is the most frequent cause of morbidity and mortality among patients with diabetes. HIT are effective in reducing HbA1c; however, their effect on cardiovascular risk factor management for patients with T2D has not been evaluated.
  
  Summary
  
  We identified 21 eligible studies (23 estimates) with measurement of SBP, 20 (22 estimates) of DBP, 14 (17 estimates) of HDL, 14 (17 estimates) of LDL, 15 (18 estimates) of triglycerides, and 10 (12 estimates) of weight across databases. We found significant reductions in SBP, DBP, LDL, and TG, and a significant improvement in HDL associated with HIT. As adjuvants to standard diabetic treatment, HIT can be effective tools for improving CVD risk factors among patients with T2D, especially in those whose CVD risk factors are not at goal.
  
  Electronic supplementary material
  
  The online version of this article (10.1007/s11892-019-1152-3) contains supplementary material, which is available to authorized users.
  
  
• Subjects:
  Cardiovascular Risk Factor Health Information Technologies Macrovascular Complications In Diabetes (VR Aroda And A Getaneh, Section Editors) Type 2 Diabetes
• Source:
  Curr Diab Rep. 19(6)
• Pubmed ID:
  31030289
• Pubmed Central ID:
  PMC6486904
• Document Type:
  Journal Article
• Funding:
  1P30DK092950/National Institute of Diabetes and Digestive and Kidney Diseases/
• Volume:
  19
• Issue:
  6
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha256:3a7ca4e7c9570acec1617d5178cbf1c00bc664af672e02c35ffb4ae00186e47a
• Download URL:
  https://stacks.cdc.gov/view/cdc/78631/cdc_78631_DS1.pdf
• File Type:
  [PDF - 1.44 MB ]