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 .
Translating Cholesterol Guidelines Into Primary Care Practice: A Multimodal Cluster Randomized Trial
PURPOSE We wanted to determine whether an intervention based on patient activation and a physician decision support tool was more effective than usual care for improving adherence to National Cholesterol Education Program guidelines . METHODS A 1-year cluster r and omized controlled trial was performed using 30 primary care practice s ( 4,105 patients ) in southeastern New Engl and . The main outcome was the percentage of patients screened for hyperlipidemia and treated to their low-density lipoprotein ( LDL ) and non – high-density lipoprotein ( HDL ) cholesterol goals . RESULTS After 1 year of intervention , both r and omized practice groups improved screening ( 89 % screened ) , and 74 % of patients in both groups were at their LDL and non-HDL cholesterol goals ( P < .001 ) . Using intent-to-treat analysis , we found no statistically significant differences between practice groups in screening or percentage of patients who achieved LDL and non-HDL cholesterol goals . Post hoc analysis showed practice s who made high use of the patient activation kiosk were more likely to have patients screened ( odds ratio [ OR ] = 2.54 ; 95 % confidence interval [ CI ] , 1.97–3.27 ) compared with those who made infrequent or no use . Additionally , physicians who made high use of decision support tools were more likely to have their patients at their LDL cholesterol goals ( OR = 1.27 ; 95 % CI , 1.07–1.50 ) and non-HDL goals ( OR = 1.23 ; 95 % CI , 1.04–1.46 ) than low-use or no-use physicians . CONCLUSION This study showed null results with the intent-to-treat analysis regarding the benefits of a patient activation and a decision support tool in improving cholesterol management in primary care practice s. Post hoc analysis showed a potential benefit in practice s that used the e-health tools more frequently in screening and management of dyslipidemia . Further research on how to incorporate and increase adoption of user-friendly , patient-centered e-health tools to improve screening and management of chronic diseases and their risk factors 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 .