Adam L. Beckman, BS

The coronavirus disease 2019 pandemic is magnifying preexisting health disparities whereby patients with limited English proficiency receive lower-quality health care and experience poorer outcomes. To address these realities, language interventions to date have focused on interpreter services and linguistically tailored health information. But these limited solutions fail to target a more upstream, overlooked, and modifiable factor: a patient’s access to improving their English proficiency and health literacy. We present recommendations for addressing language as a social determinant of health by improving access to English as a Second Language programs. This article outlines steps that health systems and policy makers can take to more directly treat upstream causes of language disparities.

We introduce how English as a Second Language (ESL) courses can address inequities in access to care and health outcomes—many of which have been magnified during the coronavirus disease 2019 pandemic. Further, we present solutions that health systems and policy makers can adopt to improve access to these programs. We anticipate that this article will catalyze debate and quality improvement work for patients with limited English proficiency. We also believe that our piece is of critical importance to health care administrators, clinicians, and other health professionals who affect the care trajectory of these patients, especially during a pandemic that has disproportionately affected communities of color.

The pandemic has further highlighted the importance of mitigating language-based disparities. By following the 3 points below, health care leaders can improve their health care delivery practices for patients with limited English proficiency:

improve health care delivery for populations with limited English proficiency,

partner with community-based organizations that teach ESL, and

leverage Medicaid and work with insurers to better manage the care of non–English-speaking patients.

Coronavirus disease 2019 (COVID-19) mortality data show that Latinxs are disproportionately dying in the United States.

 These findings parallel known health disparities for Latinxs, which can be attributed in part to language barriers. More than 25 million individuals in the United States have limited English proficiency (LEP), including 16 million Spanish speakers, and they are more likely to receive worse health care and experience poorer outcomes.

 COVID-19 is now magnifying these disparities that continue to persist in part because current language interventions, such as interpreter services and linguistically tailored health information, offer limited solutions to a more upstream, overlooked, and modifiable factor: a patient’s access to improving their English proficiency and health literacy.

When patients and their clinicians do not speak the same language, patients receive less health education and experience more testing, more readmissions, and longer lengths of stay, resulting in higher health care utilization.

 Beyond the clinical setting, language, like other social determinants of health, affects patients’ lived environments, including their ability to understand food labels, apply for public housing services, and access reliable community health information. This reality puts them at increased risk of downstream consequences such as mental health problems and chronic health conditions. When language barriers are present, patients suffer, clinicians fail to effectively deliver care, and the health care system faces increased costs.

Traditionally, language barriers have been addressed only by interpreters at the point of care. Interpreters improve patient satisfaction and clinical outcomes.

 However, interpreter use has been hampered by variable clinician use, patient disenfranchisement, limited availability in rural geographies, and absent or insufficient reimbursement.

 The increasing demand on clinician time during COVID-19 has likely only decreased interpreter use. Furthermore, the financial impact of COVID-19 on places with already strained financial budgets could lead to the deimplementation of poorly reimbursed interpreter services.

 Interpreters are essential, but their services are now constrained more than ever. They also do not directly modify the patient’s primary risk factor for poor outcomes—namely, having LEP.

Driven by risk-bearing payment structures, provider organizations are recognizing the relationship between an upstream cause of disease and patient well-being. But such systems largely overlook a critical opportunity to address language barriers and health literacy by increasing adoption of English as a Second Language (ESL) programs.

ESL programs are interactive didactic courses that teach non-English speakers the basics of the English language. By the end of the course, learners have higher reading comprehension and improved English-speaking skills. More germane to health professionals, however, is the courses’ ability to improve health literacy and, subsequently, patient health. Individuals enrolled in ESL courses that focus on health experience improved understanding of their illnesses (eg, diabetes, hepatitis B) and general nutrition. After course completion, many participants change their diets to avoid unhealthy foods and increase fruit and vegetable intake.

 Benefits even go beyond the individual, as participants report sharing preventive health content with their community. Improvements in clinical outcomes, including hyperlipidemia and blood pressure control, have also been linked with health-focused ESL programs. For individuals with some English proficiency, one 3-hour session improves general health knowledge. Those with more limited English skills typically require a few months.

Despite current policies in support of ESL programs, access to free ESL courses is limited; individuals can wait years for a spot. Demand is so high that almost 3 in 5 ESL providers have waiting lists, and some have discontinued classes due to lack of funding.

 The limited supply also damages the learning quality for those who do get a spot—programs are forced to combine learners with different levels of proficiency, creating challenges for instructors to teach effectively. As health care leaders and policy makers focus on social determinants of health and language services in the postpandemic era, access to health-focused ESL courses should be part of the conversation.

Addressing Language as a Social Determinant of Health

The provision of health-focused ESL courses can mitigate adverse health effects in the LEP population. We present recommendations for expanding the role of the health care system in addressing language as a social determinant of health and reducing language disparities that arise from patient-clinician interactions.

Hospitals can honor their role as anchor institutions by partnering with existing community-based ESL organizations. Expanding ESL health literacy resources through capital investments could allow for more classes and teachers to expand student capacity for high-risk patients. Funding could also be sought through the reintroduction of an Obama administration federal proposal that supported partnerships among states, adult education providers, higher education institutions, and private organizations.

 Bolstering language services with health-focused ESL courses may ultimately reduce health care spending and satisfy mandatory community health needs assessment implementation strategies. Currently, many hospitals prioritize “language” on their community health needs assessment, yet it is likely that none target the upstream opportunity of extending language resources.

More feasibly, hospitals can leverage Medicaid Section 1115 waivers—tickets that allow states to implement new health care delivery programs—to target language as a social determinant of health. For instance, North Carolina recently received $650 million from CMS to address housing instability, transportation security, food insecurity, interpersonal violence, and toxic stress.

 Language barriers could be added to that list for North Carolina and other states that utilize a waiver. Additionally, given the significant portion of privately insured Spanish speakers, insurers could provide vouchers for their LEP population to attend payable ESL courses that are often in lower demand because of their cost. This program could build from wellness initiatives, such as gym reimbursement programs, that provide financial incentives. Health systems can then evaluate the effectiveness of their courses internally or by partnering with the Department of Education, which provides funds for evaluation of adult education programs.

Access to health-focused ESL classes can be improved, but participation can still be hindered by day-to-day patient barriers, such as working multiple jobs and lacking transportation. Thus, ESL programs should not be implemented in isolation but rather as part of a larger infrastructure focused on addressing patients’ social needs. There may also be opportunities to harness virtual classes to meet patients’ varying daily challenges. Once these systems are in place, health care institutions should continue expanding linguistically diverse staff, clinicians should continue practicing culturally competent care, and hospitals should continue offering language assistance at the point of care. ESL programs that patients can opt into should not replace these services but instead augment them.

During this public health emergency, health systems may appropriately focus on clinical operations, but they need to soon turn their attention to addressing the upstream causes of language barriers. This strategy could better prepare us for the next pandemic by minimizing language discordance between a patient and their clinician or public health system. Clinical leaders can begin by partnering with existing community-based ESL organizations, leveraging Medicaid Section 1115 waivers, and providing voluntary at-risk patients with ESL course vouchers. Patient health and institutional financial sustainability could both be positively affected if language is treated like all other social determinants of health.

 Harvard Medical School (DEV, ALB, JAR), Boston, MA; Department of General Internal Medicine, Brigham and Women’s Hospital (JAR), Boston, MA.

 Mr Beckman is a former employee of and has received consulting fees unrelated to this article from Aledade Inc. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (DEV, ALB, JAR); drafting of the manuscript (DEV, ALB, JAR); critical revision of the manuscript for important intellectual content (DEV, ALB, JAR); and supervision (JAR).

 David E. Velasquez, BS, Harvard Medical School, 292 Eliot Mail Center, 101 Dunster St, Cambridge, MA 02138. Email: david_velasquez@hms.harvard.edu.

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Articles

In the article, we introduce how English as a Second Language courses can address inequities in access to care that have been magnified during the coronavirus disease 2019 pandemic.

The Missing Strategy in Addressing Language Barriers

Home-based care is on the rise. With this transition, a detailed exploration of the potential unintended consequences is necessary. This article discusses this trend and focuses on 3 effects that may be already underway:

increased informal caregiving and costs to society; and

failure to meaningfully engage clinicians.

The past century was dominated by facility-based care, but a transition to health care at home is underway. For the first time since the early 1900s, Americans are now more likely to die in their homes than in facilities.

 Medicare spending on traditional home health more than doubled between 2001 and 2017

; looking ahead, the agency projects an annual growth rate of 7% for home health, more than any other category, and it estimates that spending will reach $186 billion by 2027.

 These trends reflect not just growth but also substitution. For example, postsurgical patients who otherwise might have spent 30 days at a skilled nursing facility (SNF) are instead being discharged with home health.

 Demand for home-based services will only accelerate amid coronavirus disease 2019 imperatives to minimize patient contact and patients’ fear of entering health facilities.

The shift toward home care is often depicted as a panacea for achieving the Triple Aim of better care, improved quality, and lower costs. However, this trend may also create new challenges. As care in the United States is increasingly delivered at home, a detailed exploration of potential unintended consequences is needed. We focus on 3 that are already apparent in traditional home health services and home hospice.

First, current models of home-based care have meaningful—and sometimes unexpected—gaps in patient support. In home hospice, for instance, payment for all medications, equipment, and visits in routine home care—the most commonly used hospice service—is $200 or less daily, 10-fold lower than the $2000 cost of a hospital night. As a result, routine home hospice care offers relatively little direct support day-to-day, often with only a few in-person visits weekly. For many patients, their needs fall into the large gulf between the low-touch levels of support available at home and the high-touch care available in hospitals, SNFs, or inpatient hospice. In these cases, relying on home-based services may pose risks to patient safety. These gaps may in part explain why a 2019 Office of the Inspector General report found that 1 in 5 hospices had a situation in which the “health and safety of beneficiaries were in jeopardy.”

 Gaps in home-based care may also extend to postacute care home health. Despite saving Medicare money, discharging patients home with just a few hours of in-person paid care instead of to a SNF with around-the-clock services has been linked to a greater risk of readmission.

 Although many patients benefit, home-based services may provide insufficient access to support for some.

Second, although home hospice or home health can relieve caregiver duties for short periods, the substitution of institutional care with these services largely transfers responsibility from the health system to informal caregivers, like friends and family. The need to provide routine care at home can create new stressors for caregivers, detracting from their own work or medical needs. Respite care to provide relief for caregivers, although sorely needed, is frequently limited in duration and accessibility; one of the main programs funding support for caregivers, the Older Americans Act, appropriates less than 1% of the unpaid care informal caregivers provide. Moreover, estimates of spending reductions from home-based care compared with institutional care often do not account for informal caregiving, vastly underestimating the societal costs. With 1 in 10 adults providing long-term services assistance to a family member, the unpaid economic value of informal caregiving is enormous; informal care in 2017 amounted to $470 billion, more than the economic value of all paid long-term support services including postacute care.

 Although home hospice and home health may reduce direct health care spending, they may simultaneously reduce economic productivity by demanding unpaid labor from employable caregivers, limiting the overall benefit to society and risking harm to patients.

Third, just as families may be unfamiliar with the gaps in home health and hospice services, so too may the clinician who orders them. A recent study found that the vast majority of physicians certify plans of care for home health care services, yet nearly half spent less than 1 minute reviewing the care plan.

 This finding is consistent with earlier evidence that most primary care clinicians rarely read plans for home health carefully, suggesting that they may arrange a home-based service without understanding its scope or devoting sufficient attention to their role in it. Ideally, growth in home-based care would be accompanied by increased efforts to train clinicians about home services, each program’s features, and how to select the appropriate service for each patient—but signs that this trend is underway are lacking.

Ultimately, a greater role for home-based care is needed in the United States. Growing evidence, including a Cochrane review and subsequent randomized trial in the United States,

 shows that even hospital acuity-level care can be provided at home with at least minimal to no difference in effect on patient health outcomes. However, several measures should be taken simultaneously with this transition to address a slowly emerging crisis.

First, payers can start to align home-based services reimbursement to reward high-quality care; for example, the Medicare Home Health Value-Based Purchasing Model has shown early signs of not only reducing spending but also modestly improving quality metrics and utilization of unplanned inpatient care.

 Along with patient outcomes, caregiver outcomes should also be assessed for such home-based services. Second, to avoid a one-size-fits-all approach, payers and providers can establish more gradations of intensity for each home service, enabling clinicians to select the appropriate level for a patient and thereby grant the benefits of receiving care at home to even those patients who need more support. Third, much like telehealth training is becoming a necessity for clinicians, more intensive clinician exposure to and education about home services can enable better coordination of a patient’s otherwise piecemeal home care.

Decades ago, clinicians providing care in homes was deemed “a vanishing practice.”

 Enabled by financial incentives and digital tools, the pendulum is now swinging from facility- to home-based care. This transition could greatly benefit patients, but only if we use these services to improve health rather than pass the buck to another setting without deeper scrutiny.

 Harvard Medical School (ALB, SG), Boston, MA; Harvard Business School (ALB, SG), Boston, MA; Department of Health Care Policy and Management, Harvard T.H. Chan School of Public Health (MLB), Boston, MA; Division of General Internal Medicine and Primary Care, Department of Medicine, Brigham and Women’s Hospital (MLB), Boston, MA.

 Mr Beckman reports receiving consulting fees from and former employment with Aledade Inc. The remaining authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.

 Concept and design (ALB, SG, MLB); drafting of the manuscript (ALB, SG); critical revision of the manuscript for important intellectual content (ALB, SG, MLB); and supervision (MLB).

Michael L. Barnett, MD, MS, Department of Health Care Policy and Management, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Kresge 407, Boston, MA 02115. Email: mbarnett@hsph.harvard.edu.

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As home-based care utilization rises, an exploration of potential unintended consequences is necessary. The authors focus on support gaps, informal caregiving, and failure to meaningfully engage clinicians.

The Hidden Costs of Moving Care Home

 Although use of the Medicare Annual Wellness Visit (AWV) is increasing nationally, it remains unclear whether it can help contain healthcare costs and improve quality. In the context of 2 primary care physician—led accountable care organizations (ACOs), we tested the hypothesis that AWVs can improve healthcare costs and clinical quality.

A retrospective cohort study using propensity score matching and quasi-experimental difference-in-differences regression models comparing the differential changes in cost, emergency department (ED) visits, and hospitalizations for those who received an AWV versus those who did not from before until after the AWV. Logistic regressions were used for quality measures.

 Between 2014 and 2016, we examined the association of an AWV with healthcare costs, ED visits, hospitalizations, and clinical quality measures. The sample included Medicare beneficiaries attributed to providers across 44 primary care clinics participating in 2 ACOs.

 Among 8917 Medicare beneficiaries, an AWV was associated with significantly reduced spending on hospital acute care and outpatient services. Patients who received an AWV in the index month experienced a 5.7% reduction in adjusted total healthcare costs over the ensuing 11 months, with the greatest effect seen for patients in the highest hierarchical condition category risk quartile. AWVs were not associated with ED visits or hospitalizations. Beneficiaries who had an AWV were also more likely to receive recommended preventive clinical services.

 In a setting that prioritizes care coordination and utilization management, AWVs have the potential to improve healthcare quality and reduce cost.

In the context of 2 primary care physician (PCP)—led accountable care organizations, Medicare Annual Wellness Visits (AWVs) were associated with lower healthcare costs and improved clinical care quality for beneficiaries.

Our findings suggest that an AWV can achieve meaningful improvements in cost and quality, lending support that policy makers and payers should further facilitate the adoption of high-quality AWVs by PCPs.

Because Medicare reimburses $175 for an AWV per member per year and the AWV was associated with a $38 per member per month ($456 per member per year) decrease in costs, these data suggest that the additional expenditure on primary care can be worth the costs, particularly for a higher-risk population.

Future research can help guide policy with respect to whether AWVs should be billable only by the patient’s PCP and whether payment should be higher for higher-risk patients.

The Annual Wellness Visit (AWV) was introduced in 2011 by Medicare and made available to all eligible beneficiaries without deductibles or co-payments. Unlike a traditional periodic health examination or annual physical, which may be performed without a specified protocol,

 the AWV includes a list of required components

 that prioritize preventive care and investing in the relationship with the patient rather than addressing acute complaints or chronic disease (

). It includes assessing risk factors, inquiring about care support, creating a personalized care plan, and educating beneficiaries on how to maintain their health outside of an acute illness episode.

 Notably, the only physical examinations required of the visit are blood pressure measurement and height/weight measurement for body mass index (BMI), reflecting the US Preventive Services Task Force’s recommendation against routine physical examinations for asymptomatic adults 65 years or older.

Previous work has demonstrated growing adoption of AWVs since their introduction, but modest use overall,

 with 7% of Medicare beneficiaries receiving an AWV in 2011, increasing to 16% in 2014.

 More than 90% of AWVs nationally in 2014 were performed by a primary care physician (PCP).

 Although utilization of the service is increasing, the benefits of an AWV for improving patient outcomes and controlling healthcare costs continue to be debated.

 This lack of evidence regarding the possible impact of AWVs on important outcomes restrains providers and policy makers from optimally using the service.

In order to address these gaps, we examined the association of an AWV with healthcare costs, utilization, and measures of clinical quality among beneficiaries cared for by 2 PCP-led accountable care organizations (ACOs). We focused on beneficiaries cared for by PCPs in the ACOs formed in 2015 by Aledade, a national network of independent practices.

 Aledade has prioritized AWVs to improve quality and focus a primary care relationship on preventing adverse health events. It has supported its partners in performing AWVs by identifying high-risk beneficiaries, building user-friendly technology to schedule AWVs with these beneficiaries, providing face-to-face practice transformation support to optimize workflows, implementing templates in the electronic health record (EHR), providing data tools to support performance monitoring, and facilitating best practice sharing across a network of doctors.

 Evaluating the AWV in the context of a highly motivated and supported physician network leads to greater understanding of how AWVs can contribute to improving healthcare quality and reducing costs under optimal conditions.

 We used insurance claims from the CMS Claim and Claim Line Feed

 as our primary data source to assess the association of an AWV with cost and utilization. These data include services provided under Medicare parts A and B for patients assigned to 2 PCP-led ACOs. Data from these specific ACOs were used because they were the first ACOs that Aledade partnered with that had complete follow-up data. The observation period was from January 1, 2014, to December 31, 2016. Permission to use data for the study was granted through the Medicare Shared Savings Program data use agreement, and institutional review board (IRB) approval was granted by Hummingbird IRB (IRB #2017-278).

Intervention and control groups in primary data source

 Among patients attributed to ACOs 1 and 2 at the start of 2015, we identified intervention beneficiaries who had an AWV in 2015 (Current Procedural Terminology codes G0402, G0438, or G0439). We excluded beneficiaries who had missing data, died during the study period, or had received an AWV in 2014 (we wanted to focus on the effects from a first-time AWV, assuming that patients who did not receive an AWV in 2014 did not receive one in 2011-2013). To identify a control group, we matched the intervention beneficiaries to beneficiaries who did not have an AWV in 2015 and who met the same inclusion and exclusion criteria as the intervention group (for additional information about the matching process, see the 

]). Control patients were assigned the AWV month of the intervention patient to whom they matched. We removed the month that the AWV was done (and thus the cost of the AWV itself, because we wanted to focus on the subsequent AWV impact), which allowed us to define the 11 calendar months before the AWV as the pre-AWV period and the 11 calendar months after the AWV as the post-AWV period. Because Medicare only bills AWVs once every 12 months per patient, the intervention group by definition did not have any AWVs in the post-AWV period. After matching, we excluded all control patients who had an AWV in the post-AWV period, as well as all patients with outlier spend (to reduce skewness). For a visual definition of this cohort, see 

Secondary data source for quality of care

 To assess impact of an AWV on clinical quality, we used data on clinical quality measures reported to CMS as part of the ACO program.

 These data are reported to CMS for a different randomly selected sample of beneficiaries for each measure. Beneficiaries met exclusion/inclusion criteria as defined by each measure definition in accordance with Medicare specifications.

 Each sample was then divided into 2 groups: The control group included beneficiaries who did not receive a first-time AWV in 2015 (but could have received one in 2014 or 2016) and the intervention group included beneficiaries who did receive a first-time AWV in 2015 (including the “Welcome to Medicare” visit). We included all beneficiaries who were reported on by CMS regardless of whether they were in our final primary analytic sample.

The primary outcome was the differential change in healthcare cost (in the post-AWV period compared with the pre-AWV period) between those who did and did not receive an AWV. Costs in the month that the AWV was performed, including the approximately $175 cost of the AWV itself, were excluded. Cost was evaluated in separate analyses as total Medicare cost (all parts A and B Medicare spending) and category-specific costs within Part A (hospital acute care; hospital outpatient; hospital outpatient non—emergency department [ED]; skilled nursing facility, home health, other outpatient facility spending) and Part B (provider/supplier, durable medical equipment). The secondary outcomes included counts of ED visits and hospitalizations in the pre- and post-AWV periods. The outcomes for the quality measures analysis were 16 clinical quality measures with definitions specified by Medicare in 3 domains: preventive health, clinical care for at-risk populations, and care coordination.

Similar to other observational studies using real-world evidence, this study’s approach accounted for the likelihood that individuals who received AWVs differed from other patients in substantial ways that might affect the outcomes measured. In particular, issues may include that practices did not reach out to all patients with equal likelihood, practices succeeded in reaching patients at different rates, and patients who were willing and able to come in for a primary care visit differed from patients who were not. We used several analytic methods to explore the impact of such selection bias and account for it. We employed propensity score matching to identify control subjects who were similar to patients who received AWVs in key respects, including level of engagement with primary care in the pre-AWV period. We estimated the impact of AWVs by specifying a series of difference-in-differences (DID) regression models.

Specifically, for the primary data source, we checked the parallel trends assumptions and used a DID study design to assess changes in subsequent 11-month healthcare costs, ED visits, and hospitalizations between beneficiaries who did and did not receive an AWV in the index month. We used a mixed-effects negative binomial model for total cost and mixed-effects zero-inflated negative binomial (ZINB) models for category-specific costs and utilization. For the secondary data source, we used mixed-effects logistic regression models to assess the association between receiving an AWV and quality measures. In order to account for multiple comparisons, the Hochberg sequential procedure was used.

 For additional details on the modeling approach, see the eAppendix.

We also conducted a series of sensitivity analyses to evaluate the robustness of our results. First, we evaluated whether the intervention effect differed among those patients who received outreach using the Aledade app in 2015 versus those patients who did not receive outreach in 2015. Second, we used coarsened exact matching instead of propensity score matching to identify the comparison group. Third, we repeated our primary analysis (including the matching) only among beneficiaries who were continuously attributed throughout the entire pre- and post-AWV period. Fourth, we excluded intervention patients who matched to controls who had an AWV in the post-AWV period. Finally, we evaluated whether the AWV associations were different for “early” (January 2015—July 2015) versus “late” AWVs (August 2015–December 2015). (See eAppendix for additional details.)

All statistical analyses were conducted using R version 3.3.3 (R Foundation for Statistical Computing; Vienna, Austria). Propensity score and coarsened exact matching were conducted using the 

package, mixed-effects logistic models were fit using the 

 package, and the mixed-effects negative binomial and ZINB models were fit using the 

 Graphics and plots were generated using the 

The primary analysis sample of matched intervention and control beneficiaries included 8917 beneficiaries, of whom 4789 (54%) received a first-time AWV in 2015 (

). Differences in clinical and sociodemographic characteristics between the matched intervention and control groups were small. (For characteristics of the population of beneficiaries who entered the matching process, see the eAppendix.) The only covariate that was significantly different between those who did and did not receive an AWV in the final analytic sample was the specific ACO of the patient, and thus it was adjusted for in final regression models.

Association of AWV With Healthcare Costs and Utilization

In the pre-AWV period, average trends in healthcare cost were similar for the intervention and control groups (

). In 2015, a first-time AWV was associated with a 5.7% (95% CI, 0.3%-11.4%) reduction in total healthcare costs in the post-AWV period (excluding the cost of the AWV itself). This association translated to a $38 (95% CI, $9-$67) per-member-per-month (PMPM) reduction over 11 months of follow-up, or approximately $418 per beneficiary (

). The association between a first-time AWV and reduced costs was stronger among beneficiaries in the top hierarchical condition category (HCC) risk quartile. In this population, the adjusted differential change in total healthcare cost between the intervention and control groups was 6.3%, a PMPM decrease of $81 (95% CI, $12-$150) over 11 months of follow-up (Figure 1

Analysis of category-specific costs suggested that the primary drivers of this impact were reductions in hospital acute care costs (incidence rate ratio [IRR], 0.88; 95% CI, 0.80-0.97) and hospital outpatient non-ED costs (IRR, 0.93; 95% CI, 0.89-0.97). 

 reports the differential change in each category-specific cost between the intervention and control groups. With respect to healthcare utilization, first-time AWVs were not associated with a statistically significant change in the total number of ED visits (IRR, 0.97; 95% CI, 0.83-1.15) or hospitalizations (IRR, 0.95; 95% CI, 0.78-1.11).

Results of the sensitivity analyses were consistent with the main findings. Of note, the AWV association from the main analysis was not systematically different among beneficiaries who were invited by phone or email to schedule an AWV by the PCP practice (defined as receiving outreach) and beneficiaries who were not invited. In addition, using an alternative matching method to identify the comparison group and limiting the sample to those who were continuously attributed were consistent with a robust association between receipt of an AWV and reduced healthcare costs. Additionally, results were consistent with the main analysis when intervention patients who matched to controls who had an AWV in the post-AWV period were excluded. Finally, the effect of the AWV was not different between AWVs conducted in the early versus late part of the calendar year (See eAppendix for additional details.)

), a first-time AWV in 2015 was significantly associated with greater performance on 7 measures in adjusted analyses (all 

 <.01): fall risk screening (94% vs 15%), pneumococcal vaccination (86% vs 69%), tobacco screening and cessation (91% vs 77%), depression screening and follow-up planning (87% vs 18%), colorectal cancer screening (69% vs 60%), breast cancer screening (81% vs 66%), and controlled glycated hemoglobin (A1C) (77% vs 65%). AWVs were not statistically significantly associated with diabetes eye exams, use of aspirin, controlled hypertension, BMI screening, medication documentation, blood pressure control, influenza vaccination, diabetes therapy, or heart failure therapy. We speculate that AWVs had a lesser impact on these quality measures because they may already be prioritized in general primary care settings.

In this cohort of Medicare beneficiaries, first-time AWVs were associated with a significant improvement in use of preventive care and a reduction in total healthcare costs compared with matched controls. Rates of screening for fall risk and for clinical depression with follow-up plan, which are not typical components of a traditional evaluation and management visit but are components of an AWV and included in visit templates, were more than 70 percentage points higher among beneficiaries who received an AWV. These beneficiaries were also more likely to experience improved A1C control and to receive other key preventive services, including breast and colorectal cancer screening and tobacco use screening with cessation intervention. Changes in total healthcare costs were greatest among beneficiaries in the highest quartile of HCC and were driven by reductions in hospital acute care and hospital outpatient non-ED spending. Although there was a trend toward reduced hospital utilization, it was not as pronounced as that for hospital costs and did not achieve statistical significance. This would imply that the hospitalizations that did occur tended to have lower severity. These findings suggest that an AWV can be a helpful tool for improving care quality and containing costs within a primary care setting that prioritizes patient engagement, utilization management, and care coordination.

To our knowledge, this study is the first in the peer-reviewed literature to estimate the association of an AWV with measures of healthcare quality, costs, and utilization within the same study. Use of the AWV has been rising slowly since its introduction as a Medicare-reimbursable service in 2011, but there has been a paucity of evidence to guide AWV implementation into routine clinical practice in the primary care setting and to establish the potential value of this type of visit for ACOs and the Medicare program. Our findings add to a growing body of literature suggesting that the AWV can substantially improve rates of preventive services

 (which may be directly related to the administration of screening tools) while providing new evidence of substantial near-term effects on total cost of care. By further delineating that the association of the AWV with healthcare costs may be most pronounced among highest-risk patients, our findings lend support to a strategy of population risk segmentation for prioritization of AWV outreach efforts to maximize savings benefits. Furthermore, although there is general consensus that strong primary care is essential to containing healthcare costs,

 recent payment and delivery system innovations that intend to enhance primary care services beyond usual care have shown mixed results.

 Our study results suggest that a primary care service under a system that provides the right incentives for all may contribute to cost reductions.

The mechanisms explaining the cost reductions of AWVs are not well known, but we speculate that numerous aspects of the AWV might explain its benefits. A successful AWV means that practices are not merely “checking the box.” These screenings can be used to provide updates on medical history and self-reported data as an opportunity to step back from typical acute complaints and meaningfully engage in personalized conversations about risk factors, preventive needs, and a patient’s long-term health goals. This attention on wellness may improve clinical quality, including the delivery of general clinical preventive services and secondary prevention among patients with chronic conditions. An optimal AWV can include medication review and regimen optimization, identification of uncoordinated use of specialty care, and discussion of social or environmental barriers to self-care that may benefit from enhanced care coordination. This up-front investment in preventive care and care coordination may avert subsequent spending. By devoting time to explore the patient’s overall health status, risks, and values, the AWV may enrich the patient—provider relationship, improve patient engagement, and reinforce the core primary care tenets.

Several factors should be considered in the interpretation of this study. First, the results should be interpreted in the context of the specific setting studied. AWVs were a key strategy of the ACOs, and rates of AWVs (54%) were substantially higher than national averages. It is possible that the results of this study would be replicable only in a setting willing to undergo workflow optimization to accommodate a high-value visit. In addition, the cohort studied did not include beneficiaries at the end of life and those who may be less able to receive an AWV due to being homebound, institutionalized, hospitalized, or enrolled in hospice. Thus, the findings cannot be generalized to all Medicare beneficiaries. Second, as with all nonrandomized study designs, a possibility exists for selection bias and residual confounding due to unmeasured differences. However, we used propensity score matching to account for observable differences and a DID design to account for unobservable time-dependent changes in spend, as was done recently in a CMS evaluation of chronic care management.

 A key matching variable for cases and controls was the number of baseline primary care visits, to account for the level of engagement with a PCP and the ability to come in for a visit. Furthermore, the association between receipt of AWV and healthcare cost reductions did not vary by whether or not patients received outreach, providing little evidence to suggest that the intervention effect was driven by differential outreach to patients who were predisposed to favorable cost trajectories. Finally, we were not able to ascertain whether patients had an AWV prior to 2014, although data suggest that fewer than 16% of Medicare patients were receiving them in 2013.

These findings point to several priorities for payers and providers to consider. Because Medicare reimburses $175 for an AWV per member per year (PMPY), it is important to note that the true cost reduction may be smaller than the $456 PMPY effect estimate that we reported. However, given that the effect estimate is more than 2-fold the cost of the AWV itself, these data suggest that the additional expenditure on primary care can be worth the costs, particularly for a higher-risk population. It is also worth acknowledging that AWVs are one way to improve coding accuracy, and “upcoding” can be balanced by the legislatively afforded renormalization factor to account for risk inflation.

Future research can help guide policy with respect to whether AWVs should be billable only by the patient’s PCP, who may be in the best position to comprehensively assess patient risk factors and preventive care needs. Our findings show that an AWV may achieve meaningful improvements in cost and quality, lending support that policy makers should further facilitate the adoption of high-quality AWVs by PCPs. Given that underserved populations are less likely to adopt AWVs,

 policies should be explored to expand access to AWVs for this important subgroup of patients.

Additional research is still needed to further understand answers to several key questions. Given the recent introduction of the AWV, it will be important to understand whether the impact of an AWV changes over a longer time horizon. Future research should also attempt to differentiate effects of specific AWV components on outcomes. Additional outcomes of interest beyond the scope of this initial study include effects on patient satisfaction, health behaviors, self-management of chronic conditions, and care continuity.

Among beneficiaries cared for by PCPs affiliated with 2 ACOs, the AWV was associated with delivery of greater preventive care and lower total healthcare costs, particularly for those among the highest quartile of HCC risk. The AWV may therefore be an important service for achieving the triple aim of “improving the experience of care, improving the health of populations, and reducing per capita costs of health care.”

 Future research should focus on replicating these results among other populations, given that the current study used data from 2 specific ACOs. It will be important for future studies to test the efficacy of AWVs in different geographical areas and in ACOs with different characteristics in order to provide robust evidence of AWV impact. Furthermore, identifying tactics to further facilitate adoption and optimize the effectiveness of the AWV in primary care practice will be important avenues for future research.

Adam L. Beckman, BS, and Adan Z. Becerra, PhD, contributed equally to this work and are listed as co—first authors.

The authors first acknowledge the 114 independent primary care providers from Delaware ACO and Primary Care ACO who led the ACO efforts through 2016. They also appreciate editorial inputs from Travis Broome, MPH, vice president of policy at Aledade.

Aledade, Inc (ALB, AZB, AM, CAD, KL, EM, FM, JK), Bethesda, MD; Harvard Medical School (ALB), Boston, MA; Social & Scientific Systems (AZB), Silver Spring, MD.

 All authors were employed by Aledade when this study was conducted; as detailed in the manuscript, this is a peer-reviewed evaluation of our own program. Dr Becerra is now employed at Social & Scientific Systems, which was not involved in the study.

 Concept and design (ALB, AZB, KL, EM, FM, JK); acquisition of data (JK); analysis and interpretation of data (ALB, AZB, CAD, KL, EM, FM, JK); drafting of the manuscript (ALB, AZB, AM, CAD, EM, FM); critical revision of the manuscript for important intellectual content (ALB, AZB, CAD, KL, EM, FM, JK); statistical analysis (AZB, FM, JK); administrative, technical, or logistic support (AM, KL); supervision (EM, JK); and direct work with clinics (AM).

 Adam L. Beckman, BS, Aledade Inc, 4550 Montgomery Ave, Ste 950, Bethesda, MD 20814. Email: abeckman@aledade.com.

In the context of 2 primary care physician–led accountable care organizations, Medicare Annual Wellness Visits were associated with lower healthcare costs and improved clinical care quality for beneficiaries.

Adam L. Beckman, BS

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