Background The COVID-19 pandemic affected outpatient care delivery and patients' access to health care. However, no prior studies have documented telehealth use among patients with cardiovascular disease. Methods and Results We documented the number of telehealth and in-person outpatient encounters per 100 patients with cardiovascular disease and the percentage of telehealth encounters from January 2019 to June 2021, and the average payments per telehealth and in-person encounters across a 12-month period (July 2020-June 2021) using the MarketScan commercial database. From February 2020 to April 2020, the number of in-person encounters per 100 patients with cardiovascular disease decreased from 304.2 to 147.7, whereas that of telehealth encounters increased from 0.29 to 25.3. The number of in-person outpatient encounters then increased to 280.7 in June 2020, fluctuated between 268.1 and 346.4 afterward, and ended at 268.1 in June 2021, lower than the prepandemic levels. The number of telehealth encounters dropped to 16.8 in June 2020, fluctuated between 8.8 and 16.6 afterward, and ended at 8.8 in June 2021, higher than the prepandemic levels. Patients who were aged 18 to 35 years, women, and living in urban areas had higher percentages of telehealth encounters than those who were aged 35 to 64 years, men, and living in rural areas, respectively. The mean (95% CI) telehealth and in-person outpatient encounter costs per visit were $112.8 (95% CI, $112.4-$113.2) and $161.4 (95% CI, $160.4- $162.4), respectively. Conclusions There were large fluctuations in telehealth and in-person outpatient encounters during the pandemic. Our results provide insight into increased telehealth use among patients with cardiovascular disease after telehealth policy changes were implemented during the pandemic.

Hypertension, a major contributor to cardiovascular disease (CVD) including heart disease and stroke, is one of the leading contributors of global burden of disease and a growing public health problem worldwide.1 In the U.S., about 75.2 million adults (one in every three) had hypertension during 2013–2014.2 In 2014, hypertension was listed as a primary or contributing cause of 427,631 American deaths, and heart disease and stroke were the first-and fifth-leading causes of death respectively.3 Economically, hypertension cost the nation about $51.2 billion per year, and total CVD cost the nation about $316.1 billion per year during 2012–2013.4 Reducing the health and economic burden of hypertension and CVD is a public health priority. | Substantial knowledge regarding the epidemiology, pharmacologic and non-pharmacologic treatments, and genetics of hypertension is available; however, many people with hypertension remain undiagnosed or undertreated because health systems cannot efficiently identify or treat them, often because of poor access to health care.5 Hypertension control remains a major public health challenge.6 To promote effective hypertension prevention and control, a better understanding of the economic aspects of hypertension is important. The Division for Heart Disease and Stroke Prevention (DHDSP), Centers for Disease Control and Prevention, routinely conducts applied research that evaluates program cost, cost of illness, and cost effectiveness to address this need. This commentary highlights some challenges in quantifying the economic impact, recent research, and future research opportunities of hypertension based on the applied research from DHDSP.

Calls for government-funded activities to be “evidence based” are ubiquitous. “Gold standard” studies, including randomized controlled trials and systematic reviews (Isett, Head, and VanLandingham 2016), have expanded the availability of evidence-based programs and practices (VanLandingham and Silloway 2016). However, because of their complexity, large-scale policies (comprising services, laws, rules, and regulations implemented at the population level) are more difficult to study experimentally, resulting in evidence gaps. | Public policies should be informed by the best information available. This article focuses on the utility of early evidence assessment and provides an example of one approach called the Quality and Impact of Component (QuIC) Evidence Assessment. This approach provides a systematic and timely method for policy analysis that can be applied to many types of emerging and complex public policies.

An essential strategy expected to reduce the global burden of chronic and cardiovascular disease is evidence-based policy. However, it is often unknown what specific components should constitute an evidence-based policy intervention. We have developed an expedient method to appraise and compare the strengths of the evidence bases suggesting that individual components of a policy intervention will contribute to the positive public health impact of that intervention. Using a new definition of "best available evidence," the Quality and Impact of Component (QuIC) Evidence Assessment analyzes dimensions of evidence quality and evidence of public health impact to categorize multiple policy component evidence bases along a continuum of "emerging," "promising impact," "promising quality," and "best." QuIC was recently applied to components from 2 policy interventions to prevent and improve the outcomes of cardiovascular disease: public-access defibrillation and community health workers. Results illustrate QuIC's utility in international policy practice and research.

Policy is generally understood to be a set of guidelines or acourse of action that may be shaped as a law, regulation, rule,procedure, or practice.1Whether public or organizational,policy aims to effect and focus change. In health promotionand health protection, policy can be an efficient strategy foradvancing health initiatives, influencing whole systems, andshifting cultural norms.2,3Evaluative thinking offers a way to consider problemsand potential policy solutions through the lens of logicalreasoning, explicit criteria, and data. Such thinkingexamines how problems are defined and what assumptionsare being made about the underlying causes of a problem.Although many tools and frameworks exist for planningand evaluating health-related programs, fewer resourcesare available for developing and evaluating policies forhealth promotion and disease prevention. Fortunately, themind-set of evaluative thinking that guides programplanning and evaluation methods can be used tostrengthen a policy development process, shape policyoptions, and set the stage for successful policy im-plementation and impact evaluation. When evaluationfindings demonstrate a policy’s effectiveness in advancinghealth goals, this information can become a powerfulmechanism for encouraging the adoption of the policy in other contexts, thus broadening the reach of health-promoting policies.

The primary goal of this workshop was to identify the most appropriate method to estimate the potential effect of reduction in sodium consumption on mortality. Difficulty controlling hypertension at the individual level has motivated international, federal, state, and local efforts to identify and implement population-wide strategies to better control this problem; reduction of sodium intake is one such strategy. Published estimates of the impact of sodium consumption on mortality have used different modeling approaches, effect sizes, and levels of sodium consumption, and thus their estimates of preventable deaths averted vary widely, and are not comparable. In response to this problem, the Centers for Disease Control and Prevention's Division for Heart Disease and Stroke Prevention (DHDSP) convened and facilitated a workshop to examine different methods of estimating the effect of sodium reduction on mortality. The panelists agreed that any of the methodologies presented could provide reasonable estimates, and therefore discussion focused on challenges faced by all methods. The panel concluded that future sodium modeling efforts should generate multiple estimates employing the same scenarios and effect sizes while using different modeling techniques; in addition, future efforts should include outcomes other than mortality (morbidity, costs, and quality of life). Varying reductions in sodium should be modeled at the population level over different time intervals. In an effort to better address some of the uncertainties highlighted by this workshop, the panelists are currently considering developing multiple estimates in a collaborative manner to clarify the potential impact of population-based interventions to reduce sodium consumption.