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 .
Improving treatment intensification to reduce cardiovascular disease risk: a cluster randomized trial
Background Blood pressure , lipid , and glycemic control are essential for reducing cardiovascular disease ( CVD ) risk . Many health care systems have successfully shifted aspects of chronic disease management , including population -based outreach programs design ed to address CVD risk factor control , to non-physicians . The purpose of this study is to evaluate provision of new information to non-physician outreach teams on need for treatment intensification in patients with increased CVD risk . Methods Cluster r and omized trial ( July 1-December 31 , 2008 ) in Kaiser Permanente Northern California registry of members with diabetes mellitus , prior CVD diagnoses and /or chronic kidney disease who were high-priority for treatment intensification : blood pressure ≥ 140 mmHg systolic , LDL-cholesterol ≥ 130 mg/dl , or hemoglobin A1c ≥ 9 % ; adherent to current medications ; no recent treatment intensification ) . R and omization units were medical center-based outreach teams ( 4 intervention ; 4 control ) . For intervention teams , priority flags for intensification were added monthly to the registry data base with recommended next pharmacotherapeutic steps for each eligible patient . Control teams used the same data base without this information . Outcomes included 3-month rates of treatment intensification and risk factor levels during follow-up . Results Baseline risk factor control rates were high ( 82 - 90 % ) . In eligible patients , the intervention was associated with significantly greater 3-month intensification rates for blood pressure ( 34.1 vs. 30.6 % ) and LDL-cholesterol ( 28.0 vs 22.7 % ) , but not A1c . No effects on risk factors were observed at 3 months or 12 months follow-up . Intervention teams initiated outreach for only 45 - 47 % of high-priority patients , but also for 27 - 30 % of lower-priority patients . Teams reported difficulties adapting prior outreach strategies to incorporate the new information . Conclusions Information enhancement did not improve risk factor control compared to existing outreach strategies at control centers . Familiarity with prior , relatively successful strategies likely reduced uptake of the innovation and its potential for success at intervention centers . Trial registration Clinical Trials.gov Identifier
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 .