In this physician-randomized effectiveness study, mailed individualized CVD risk messages to patients with uncontrolled LDL cholesterol resulted in a doubling in the proportion of patients who received a new lipid-lowering drug prescription. Among the subgroup with uncontrolled hypertension and the subgroup not using aspirin at baseline, prescribing additional antihypertensive medication and prescribing aspirin, respectively, were more common in the intervention group. Blood pressure was lower in the intervention group. However, subgroups eligible for these interventions were small, and these results did not achieve statistical significance. This intervention showed no effect on the primary outcome at the prespecified study end point (having a repeat LDL-cholesterol level obtained within 9 months that was ≥ 30 mg/dl lower than baseline); but after 18 months, there was a significant effect of the intervention on this outcome.
Our primary outcome, which relied on lab testing during routine care, hindered our ability to detect differences in LDL cholesterol lowering, because most patients did not have a repeat LDL-cholesterol test during the study period. Unlike studies with patient-level enrollment and measurement of outcomes performed as part of the study design,10,11,13,21
we used a pragmatic design to test the effects of this intervention on the entire population of eligible patients cared for by study physicians. Physicians, but not patients, were enrolled, and outcomes were obtained from routine clinical care. Most patients who received a new prescription did not have a repeat LDL-cholesterol test performed during the study period, and many who had the test received it prior to starting treatment. If pharmacy dispensing information were routinely available, examining drug initiation and persistence would be valuable ways to explore the effects of this intervention.
Even though the physician-randomized design that does not include patient enrollment limits the outcomes that can be assessed, this design is an important way to study this kind of intervention for two reasons. First, it shows the effects for the entire clinical population to which this kind of intervention may be applied. Studies with patient-level enrollment may not be readily generalizable to overall patient populations. Second, the acts of enrollment and follow-up may exert a strong effect on the control groups, thereby diminishing the perceived benefits of interventions. One study of CVD risk messages showed a small favorable effect on LDL cholesterol, but this intervention may have yielded more dramatic findings had there not been such a large cholesterol reduction among the control group.10
Even though we eventually observed differences in cholesterol lowering, the intervention effect was small. In the intervention group, 83 % did not receive prescription lipid-lowering therapy after 18 months. However, this small effect size should be viewed in the context of the low resources required. Data from the EHR were prepared into a mailed intervention by a non-clinician staff member. Other CVD primary prevention studies achieved larger effects but required greater resources, and many included multiple contacts with clinicians.8,10,11,21–24
If a measurable positive effect of a more limited intervention like ours can be accomplished at a sufficiently low cost, it may be a worthwhile approach to adopt. If the process of delivering these messages can be fully automated (such as using a patient portal connected to the electronic health record), this may reduce the cost of providing this service further.
One potential reason for the small effect was that patients had only a single exposure to the messages. Prior studies with repeated exposure to risk messages and counseling have shown the most favorable results.8,10,11,22,23
An additional study is needed to examine whether repeated delivery increases efficacy.
Another reason that more intervention patients did not achieve the LDL control goal may have been that patients did not think their risk was particularly high. The mean 10-year risk for any CVD event was 24 %. A prior study in patients with diabetes showed that a decision aid for statin use made risk perception more accurate, but statin adherence was not changed.25
Having more than a three in four chance of not having a CVD event over 10 years may have made medication use not seem worthwhile. It is possible that placing more emphasis on CVD risk over a longer time horizon (i.e. lifetime risk) or making other changes to the framing of the risk could increase the impact.
It is possible that combining this approach with other physician-directed interventions, such as reminders, performance audit and feedback, or financial incentives, could produce additive effects. Computerized clinical decision support has been used successfully to promote guideline-based treatment of dyslipidemia in primary care.26
Future studies should aim to determine the optimal combination of quality improvement techniques.
These findings should be viewed with several additional limitations in mind. This study was performed at a single site, and as a result we do not know how the findings would differ in other settings. Intervention group physicians could have interacted with control group physicians, leading to alterations in their behavior, but since this was predominantly a patient-directed intervention, it is unlikely that there was a large contamination effect. The study size was adequate to safely exclude the 10 % increase in the primary outcome we sought to detect, but power was limited for outcomes that apply to the subgroups (uncontrolled hypertension, aspirin non-users, and current smokers). Lastly, the smoking outcome, which is based on patients’ self-report at the time of an office visit, may not be reliable.
This study demonstrated that practice-wide delivery of individualized CVD risk messages derived from EHR data to moderately-high and high-risk patients is feasible, and resulted in a modest increase in lipid-lowering drug prescribing. Ultimately, however, the absolute effects were small and most patients remained untreated. More powerful approaches are needed to address the burden of uncontrolled risk factors among individuals at increased risk for CVD. Providing patients with repeated individualized cardiovascular risk assessments with treatment recommendations may prove to be more effective than a single exposure.