INTRODUCTION

Patient- (e.g., health literacy), provider- (e.g., clinical inertia), and system-level (e.g., under-empowered care teams) barriers have contributed to suboptimal cardiovascular disease (CVD) risk management among US Veterans.1 Among Veterans using the Veterans Health Administration (VHA), more than 80% have at least two CVD risk factors,2 with approximately 34% and 49% having a diagnosis of hypertension and dyslipidemia, respectively.3 Innovative care delivery models that use patient-generated health data, integrate non-physician providers into the primary care team, and facilitate patient-provider interaction have the potential to control CVD risk factors at the individual- and population-level.4, 5 Therefore, the objective of the Team-supported, Electronic health record (EHR)–leveraged, Active Management (TEAM) pilot study was to assess the feasibility of a multi-component CVD risk management intervention among Veterans in rural North Carolina.

METHODS

TEAM consisted of the following steps: (1) population health manager (PHM) reviewed clinical data and used established algorithms to identify adults (aged 18–79) with uncontrolled blood pressure (systolic blood pressure > 140 mmHg) and/or meeting criteria for, but not prescribed, statin therapy; (2) patients identified by the PHM received a letter which communicated patient-specific CVD risk and associated health implications, self-management strategies, and topics to discuss with their primary care team; (3) PHM entered care plan (detailed CVD risk profile, clinical guidelines, and treatment recommendations) in the EHR to facilitate treatment discussions between patients and their primary care team at the point of care; (4) primary care team member(s) ordered treatment (pharmaceutical or behavioral) as appropriate; and (5) PHM monitored and reported patients’ progress.

We reviewed EHRs at 45 and 90 days after the intervention to document changes in blood pressure and to identify Veterans’ engagement with the healthcare system (e.g., scheduled/attended appointments).

RESULTS

Over 4 months, 100 Veterans received personalized CVD risk letters, of which 46 received a letter prior to their primary care appointment and 54 received a letter without having a scheduled appointment (Table 1). In the 90 days following the intervention, 83% (38/46) of patients attended scheduled appointments and 61% (33/54) of Veterans who did not have an appointment at the time of the letter scheduled one. Notably, 62% (62/100) of Veterans contacted a healthcare provider to check their blood pressure, modify their medications, or obtain a referral for another health service (e.g., smoking cessation program).

Table 1 Characteristics of Veterans Who Received a Cardiovascular Disease Risk Letter
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Responding to healthcare provider and patient recommendations, the letter was modified to better inform patients of their immediate CVD risk (blood pressure was used instead of Atherosclerotic Cardiovascular Disease Risk Score). In the 45 days following receipt of the revised intervention, 40% (20/50) of Veterans had blood pressure measurements < 140/90 mmHg (Table 2). Compared with baseline, 45-day systolic blood pressure and diastolic blood pressure decreased an average 11 mmHg and 5 mmHg, respectively.

Table 2 Baseline and 45-Day Blood Pressure Measurements
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DISCUSSION

TEAM was a relatively low-touch intervention that used tailored messaging to communicate CVD risk and empowered an existing non-physician provider as a PHM. These factors prompted patient engagement with the healthcare system and improvements in both systolic and diastolic blood pressure. As the primary care infrastructure is increasingly stretched thin, this two-pronged approach may be a sustainable solution to address uncontrolled CVD risk factors for it promotes patients’ awareness and management of their CVD risk and enables a single member of the primary care team to oversee a large patient panel.

Limitations included a predominantly male patient population; thus, we were unable to account for potential gender differences in CVD risk management and health-seeking behaviors. Additionally, we used a pre/post study design without a control group and could not discern which intervention component(s) drove observed clinical and behavioral changes. Lastly, our study focused on rural Veterans receiving care at an integrated healthcare system, which limits generalizability to other healthcare settings.

Despite these limitations, our study has important clinical implications. First, personalized CVD risk letters have the potential to educate a large population of at-risk patients and thus increase patient self-management and participation in healthcare decision-making. Second, interactions with a PHM may ensure patients are prepared to discuss treatment options with their provider, therefore resulting in timely treatment initiation or intensification. Finally, engaging existing non-physician providers as PHMs may reduce the burden of primary care physicians and thus allow them to focus on more complex cases.