Cardiovascular Disease (CVD) Risk Factors Clinical Trial
Official title:
Feedback of Treatment Intensification Data to Reduce Cardiovascular Disease Risk (FIT)
The primary research question of this study is to determine whether measuring, reporting and feeding back information to primary care teams on the need for treatment intensification in patients at high risk for cardiovascular disease (CVD) can improve rates of treatment intensification and reduce levels of poorly controlled systolic blood pressure, LDL-c, and A1c.
Project Description: We propose a cluster randomized trial intervention involving eight or
more medical facilities of Kaiser Permanente Northern California (KP) and more than 65,000
patients at high risk for CVD. At intervention facilities, patient-level information
obtained from KP's electronic health record on the need for treatment intensification (for
systolic blood pressure, LDL-c, and A1c) and on recent medication adherence are added to a
population management database and fed back through software currently used by staff working
with primary care providers. Staff at control facilities continue to use the same population
management database and software but only receive information on risk factor levels and
selected medications.
Specific Aims:
1. Evaluate the effectiveness of measurement and feedback of treatment intensification
information in patients at high risk of CVD for improving rates of treatment
intensification and for reducing levels of poorly controlled systolic blood pressure,
LDL-c, and A1c.
2. Evaluate the impact of the intervention, compared with current practice, on total
numbers of patient contacts, outpatient visits, and costs of care in relation to
improvements in risk factor control.
3. Evaluate the effect of this innovation on physician and staff perceptions of the value
(effectiveness and efficiency) of the population management program for high-risk
patients.
Relevance: If this translational study shows that feedback of information on treatment
intensification leads to higher rates of intensification and improved risk factor control,
this finding will have shown a population-level use of health information technology for
improving clinical quality and will also have validated treatment intensification as a
metric of clinical quality.
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Allocation: Randomized, Endpoint Classification: Efficacy Study, Intervention Model: Parallel Assignment, Masking: Single Blind (Subject)