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 .
Team-based care approach to cholesterol management in diabetes mellitus: two-year cluster randomized controlled trial.
BACKGROUND Creative , cost-effective interventions to improve the quality of care of chronic illnesses are needed . This study was design ed to evaluate the impact of remote physician-pharmacist team-based care on cholesterol levels in patients with diabetes mellitus ( DM ) . METHODS This 2-year prospect i ve , cluster r and omized controlled trial was conducted within the Providence Primary Care Research Network in Oregon . Participants at least 18 years of age were identified by a diagnosis of DM . The intervention included remote physician-pharmacist team-based care focused on cholesterol management in DM . All clinicians in the study had access to the health information technology tool CareManager , which provided automated DM-related point-of-care prompts , a Web-based registry , and performance feedback with benchmarking . Study outcomes included the difference in low-density lipoprotein cholesterol ( LDL-C ) goal attainment , mean LDL-C , prescribed lipid-lowering therapy , and patient satisfaction between the intervention and control arms . RESULTS A total of 6963 patients with DM cared for by 68 physicians in 9 clinics were evaluated . Patients in the intervention arm were more likely to achieve their target LDL-C levels compared with controls ( 78 % vs 50 % ; P = .003 ) . The mean LDL-C level was 12 mg/dL lower in the intervention arm compared with the control arm ( P < .001 ) . The rate of LDL-C testing was significantly higher in the intervention arm compared with the control arm . Patients in the intervention arm were also 15 % more likely to receive a prescription for a lipid-lowering medication ( P = .008 ) . There was no significant difference in patient satisfaction between study arms ( P = .15 ) . CONCLUSION Remotely located physician-pharmacist team-based care result ed in significantly improved LDL-C levels and goal attainment among patients with DM
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 .