There was mixed evidence that provider-level computerized decision support improves outcomes .
There was more evidence in support of patient-level tools that provide connectivity to the healthcare system , as well as system-level interventions that involve data base monitoring and outreach by central ized care teams .
R and omized controlled trials show wide variability in the effects of HIT on lipid management outcomes .
Evidence suggests that multilevel HIT approaches that target not only providers but include patients and systems approaches will be needed to improve lipid treatment , adherence and quality
BACKGROUND Large gaps in lipid treatment and medication adherence persist in high-risk out patients in the United States .
Health information technology ( HIT ) is being applied to close quality gaps in chronic illness care , but its utility for lipid management has not been widely studied .
OBJECTIVE To perform a qualitative review of the impact of HIT interventions on lipid management processes of care ( screening or testing ; drug initiation , titration or adherence ; or referrals ) or clinical outcomes ( percent at low density lipoprotein cholesterol goal ; absolute lipid levels ; absolute risk scores ; or cardiac hospitalizations ) in out patients with coronary heart disease or at increased risk .
Simulated Physician Learning Intervention to Improve Safety and Quality of Diabetes Care: A Randomized Trial
OBJECTIVE To assess two physician learning interventions design ed to improve safety and quality of diabetes care delivered by primary care physicians ( PCPs ) . RESEARCH DESIGN AND METHODS This group r and omized clinical trial included 57 consenting PCPs and their 2,020 eligible adult patients with diabetes . Physicians were r and omized to no intervention ( group A ) , a simulated case-based physician learning intervention ( group B ) , or the same simulated case-based learning intervention with physician opinion leader feedback ( group C ) . Dependent variables included A1C values , LDL cholesterol values , pharmacotherapy intensification rates in patients not at clinical goals , and risky prescribing events . RESULTS Groups B and C had substantial reductions in risky prescribing of metformin in patients with renal impairment ( P = 0.03 ) . Compared with groups A and C , physicians in group B achieved slightly better glycemic control ( P = 0.04 ) , but physician intensification of oral glucose-lowering medications was not affected by interventions ( P = 0.41 ) . Lipid management improved over time ( P < 0.001 ) but did not differ across study groups ( P = 0.67 ) . CONCLUSIONS A simulated , case-based learning intervention for physicians significantly reduced risky prescribing events and marginally improved glycemic control in actual patients . The addition of opinion leader feedback did not improve the learning intervention . Refinement and further development of this approach is warranted
There was mixed evidence that provider-level computerized decision support improves outcomes .
There was more evidence in support of patient-level tools that provide connectivity to the healthcare system , as well as system-level interventions that involve data base monitoring and outreach by central ized care teams .
R and omized controlled trials show wide variability in the effects of HIT on lipid management outcomes .
Evidence suggests that multilevel HIT approaches that target not only providers but include patients and systems approaches will be needed to improve lipid treatment , adherence and quality
BACKGROUND Large gaps in lipid treatment and medication adherence persist in high-risk out patients in the United States .
Health information technology ( HIT ) is being applied to close quality gaps in chronic illness care , but its utility for lipid management has not been widely studied .
OBJECTIVE To perform a qualitative review of the impact of HIT interventions on lipid management processes of care ( screening or testing ; drug initiation , titration or adherence ; or referrals ) or clinical outcomes ( percent at low density lipoprotein cholesterol goal ; absolute lipid levels ; absolute risk scores ; or cardiac hospitalizations ) in out patients with coronary heart disease or at increased risk .