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 .
Impact of computer-generated personalized goals on HbA(1c).
OBJECTIVE The public is increasingly aware of the importance of HbA(1c ) testing , yet the vast majority of patients with diabetes do not know their HbA(1c ) status or goal . We set forth to evaluate the impact of a system that provides uniquely formatted and personalized reports of diabetes status and goals on changes in HbA(1c ) levels . RESEARCH DESIGN AND METHODS A total of 150 patients with diabetes were r and omized to receive either st and ard care or intervention  inclusive of a computer-generated 11 " x 17 " color poster depicting an individual 's HbA(1c ) status and goals along with personalized steps to aid in goal achievement . All patients enrolled received diabetes education during the 3 months before enrollment .  HbA(1c )  was performed at baseline and 6 months . RESULTS At baseline , there were no significant differences between patient groups in terms of age , sex , education level , race , and HbA(1c ) or lipid levels . Among patients with baseline HbA(1c ) > or = 7.0 % , there was an 8.6 % ( 0.77 % absolute ) reduction in HbA(1c ) among control subjects compared with a 17.0 % ( 1.69 % absolute ) decline in the intervention group ( P = 0.032 ) . There were no differences between the control and intervention groups with respect to the frequency of patients experiencing any decline in HbA(1c ) ( 63 vs. 69 % , P = 0.87 ) ; among these patients experiencing a decline , the most substantial reductions were seen with the control group , which had a 13.3 % ( 1.15 % absolute ) decline compared with the intervention patients , who reduced their HbA(1c ) by 24.2 % ( 2.26 % absolute reduction ; P = 0.0048 ) . At study close , 77 % of the patients had their poster displayed on their refrigerator . CONCLUSIONS This unique and personalized computer-generated intervention result ed in HbA(1c ) lowering comparable to that of hypoglycemic agents
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 .