In addition , the more CCM-incorporated the information technology-based interventions were , the more improvements there were in HbA1c levels .
CONCLUSIONS Information technology strategies combined with the other elements of chronic care models are associated with improved glycemic control in people with diabetes .
No clinical ly relevant impact was observed on low-density lipoprotein levels and blood pressure , but there was evidence that the cost of care was lower
BACKGROUND Information technology-based interventions are increasingly being used to manage health care .
However , there is conflicting evidence regarding whether these interventions improve outcomes in people with type 2 diabetes .
OBJECTIVE The objective of this study was to conduct a systematic review and meta- analysis of clinical trials , assessing the impact of information technology on changes in the levels of hemoglobin A1c ( HbA1c ) and mapping the interventions with chronic care model ( CCM ) elements .
Do automated calls with nurse follow-up improve self-care and glycemic control among vulnerable patients with diabetes?
PURPOSE We sought to evaluate the effect of automated telephone assessment and self-care education calls with nurse follow-up on the management of diabetes . SUBJECTS AND METHODS We enrolled 280 English- or Spanish-speaking adults with diabetes who were using hypoglycemic medications and who were treated in a county health care system . Patients were r and omly assigned to usual care or to receive an intervention that consisted of usual care plus bi-weekly automated assessment and self-care education calls with telephone follow-up by a nurse educator . Outcomes measured at 12 months included survey-reported self-care , perceived glycemic control , and symptoms , as well as glycosylated hemoglobin ( Hb A1c ) and serum glucose levels . RESULTS We collected follow-up data for 89 % of enrollees ( 248 patients ) . Compared with usual care patients , intervention patients reported more frequent glucose monitoring , foot inspection , and weight monitoring , and fewer problems with medication adherence ( all P -0.03 ) . Follow-up Hb A , , levels were 0.3 % lower in the intervention group ( P = 0.1 ) , and about twice as many intervention patients had Hb A1c levels within the normal range ( P = 0.04 ) . Serum glucose levels were 41 mg/dL lower among intervention patients than usual care patients ( P = 0.002 ) . Intervention patients also reported better glycemic control ( P = 0.005 ) and fewer diabetic symptoms ( P < 0.0001 ) , including fewer symptoms of hyperglycemia and hypoglycemia . CONCLUSIONS Automated calls with telephone nurse follow-up may be an effective strategy for improving self-care behavior and glycemic control , and for decreasing symptoms among vulnerable patients with diabetes
In addition , the more CCM-incorporated the information technology-based interventions were , the more improvements there were in HbA1c levels .
CONCLUSIONS Information technology strategies combined with the other elements of chronic care models are associated with improved glycemic control in people with diabetes .
No clinical ly relevant impact was observed on low-density lipoprotein levels and blood pressure , but there was evidence that the cost of care was lower
BACKGROUND Information technology-based interventions are increasingly being used to manage health care .
However , there is conflicting evidence regarding whether these interventions improve outcomes in people with type 2 diabetes .
OBJECTIVE The objective of this study was to conduct a systematic review and meta- analysis of clinical trials , assessing the impact of information technology on changes in the levels of hemoglobin A1c ( HbA1c ) and mapping the interventions with chronic care model ( CCM ) elements .