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 .
Randomized controlled trial of an informatics-based intervention to increase statin prescription for secondary prevention of coronary disease
OBJECTIVE : Suboptimal treatment of hyperlipidemia in patients with coronary artery disease ( CAD ) is well documented . We report the impact of a computer-assisted physician-directed intervention to improve secondary prevention of hyperlipidemia . DESIGN AND SETTING : Two hundred thirty-five patients under the care of 14 primary care physicians in an academically affiliated practice with an electronic health record were enrolled in this proof-of-concept physician-blinded r and omized , controlled trial . Each patient with CAD or risk equivalent above National Cholesterol Education Program-recommended low-density lipoprotein ( LDL ) treatment goal for greater than 6 months was r and omized , stratified by physician and baseline LDL . Physicians received a single e-mail per intervention patient . E-mails were visit independent , provided decision support , and facilitated “ one-click ” order writing . MEASUREMENTS : The primary outcomes were changes in hyperlipidemia prescriptions , time to prescription change , and changes in LDL levels . The time spent using the system was assessed among intervention patients . RESULTS : A greater proportion of intervention patients had prescription changes at 1 month ( 15.3 % vs 2 % , P=.001 ) and 1 year ( 24.6 % vs 17.1 % , P=.14 ) . The median interval to first medication adjustment occurred earlier among intervention patients ( 0 vs 7.1 months , P=.005 ) . Among patients with baseline LDLs > 130 mg/dL , the first postintervention LDLs were substantially lower in the intervention group ( 119.0 vs 138.0 mg/dL , P=.04 ) . Physician processing time was under 60 seconds per e-mail . CONCLUSION : A visit-independent disease management tool result ed in significant improvement in secondary prevention of hyperlipidemia at 1-month postintervention and showed a trend toward improvement at 1 year
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 .