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 .
Effects Of Internet-Based Tailored Advice on the Use of Cholesterol-Lowering Interventions: A Randomized Controlled Trial
Background Elevated low-density lipoprotein ( LDL ) cholesterol is a leading risk factor for cardiovascular disease . Despite the availability of proven interventions to lower LDL cholesterol , their use remains subobtimal . Many websites provide interactive , tailored advice on cardiovascular risk in an attempt to help bridge this evidence - practice gap , yet there is little evidence that provision of such a tool is effective in changing practice . Objectives The objective was to define the effects on use of  cholesterol-lowering interventions of a consumer-targeted tailored advice website . Methods This was a prospect i ve , double-blind , r and omized controlled trial open to any adult Australian with access to the Internet . A total of 2099 participants were r and omized . Of these , 45 % were male , the mean age of all participants was 56 , and 1385 ( 66 % ) self-reported hypercholesterolemia . Follow-up information was obtained for 1945 ( 93 % ) . Participants completed a brief online question naire . Individuals assigned to intervention received immediate , fully automated , personally tailored advice ( based on current guidelines ) regarding the need for commencement of statin therapy , increased statin therapy in those already on treatment , and nondrug intervention strategies . Control group participants were directed to static Web pages providing general information about cholesterol management . Results The primary outcome was the proportion of participants that commenced or increased use of prescribed cholesterol-lowering therapy . Of the total 2099 r and omized participants , 304 ( 14 % ) met eligibility criteria for cholesterol-lowering therapy but were not prescribed treatment , and 254 ( 12 % ) were prescribed treatment but were not achieving the recommended target level . Treatment was commenced or increased in 64 ( 6.0 % ) of the 1062 intervention group participants and 79 ( 7.6 % ) of the 1037 control group participants ( % difference = -1.6 % , 95 % confidence interval [ CI ] -3.75 to 0.57 , P = .15 ) . No differences were found between the r and omized groups for the secondary outcomes of “ discussed treatment with a health professional ” ( % difference = -3.8 % , 95 % confidence interval [ CI ] -8.16 to 0.19 , P = .08 ) , “ had their cholesterol checked ” ( % difference = -1.5 % , 95 % CI -5.79 to 2.71 , P = .48 ) , “ had their blood pressure checked ” ( % difference = 1.4 % , 95 % CI -2.55 to 5.34 , P = .49 ) or made a lifestyle change ( P values between .49 and .96 ) . Conclusions Despite providing specific carefully tailored advice , this website had no detectable effect on cholesterol management strategies . This finding raises considerable uncertainty about the value of Internet-based tools providing tailored advice directly to consumers . Trial Registration NCT00220974 ; http:// clinical trials.gov/ct2/show/NCT00220974 ( Archived by WebCite at http://www.webcitation.org/5sdq63rrY
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 .