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[...]only 7% of employers report offering low-wage workers any type of financial subsidy for health benefits. 4 As a result, low-wage workers may need to spend a disproportionately greater percentage of their income on health care5 to achieve equitable health outcomes. In the health care services setting, low-wage workers may also be challenged by unmet health-related social needs, health benefits access concerns, health and health benefits literacy limitations, implicit bias exhibited by clinicians, and medical mistrust.6 Chronic stress7 and weathering8 experienced by many lowwage workers may also exacerbate health issues, particularly among minority populations. Whereas focus groups may be more practical in smaller, single-site studies, for larger and geographically dispersed populations, surveys likely provide the most efficient and scalable means for data collection from low-wage workers. Bruce W. Sherman https://orcid.org/0000-0002-0659-2129 CONFLICTS OF INTEREST B. W. Sherman reports receiving honoraria or consulting fees from Merck, Amgen, Lilly, Compass Pathways, Pittsburgh Business Group on Health, National Alliance of Healthcare Purchaser Coalitions, American Heart Association, and the National Pharmaceutical Council.

Individuals with multiple chronic conditions (MCCs) represent a growing proportion of the adult population in the United States, particularly among lower-income individuals and people of color. Despite ongoing efforts to characterize this population and develop approaches for effective management, individuals with MCCs continue to contribute substantially to health care expenditures. Based on a review of recent literature, several identified barriers limit the effectiveness of care for patients with MCCs. Health care delivery system structural limitations, evidence-based care concerns, patient-clinician relationship constraints, and barriers to inclusion of patient-centered priorities may singly or in combination negatively affect outcomes for individuals with MCCs. The COVID-19 pandemic has shed further light on inequities contributing to suboptimal MCC patient management. Awareness of the prevalence and demographic attributes of patients with MCCs and the identified barriers to care may help improve patient engagement and treatment outcomes for this high-cost population. This paper provides recommendations for enhancing MCC patient care outcomes in the current and post-COVID-19 health care delivery settings.Individuals with multiple chronic conditions (MCCs) represent a growing proportion of the adult population in the United States, particularly among lower-income individuals and people of color. Despite ongoing efforts to characterize this population and develop approaches for effective management, individuals with MCCs continue to contribute substantially to health care expenditures. Based on a review of recent literature, several identified barriers limit the effectiveness of care for patients with MCCs. Health care delivery system structural limitations, evidence-based care concerns, patient-clinician relationship constraints, and barriers to inclusion of patient-centered priorities may singly or in combination negatively affect outcomes for individuals with MCCs. The COVID-19 pandemic has shed further light on inequities contributing to suboptimal MCC patient management. Awareness of the prevalence and demographic attributes of patients with MCCs and the identified barriers to care may help improve patient engagement and treatment outcomes for this high-cost population. This paper provides recommendations for enhancing MCC patient care outcomes in the current and post-COVID-19 health care delivery settings.

Objectives: To evaluate the prevalence of social determinants of health (SDoH) factors in a large commercially-insured population and to characterize the prevalence of common conditions (eg, diabetes, behavioral health issues) and addressable health services utilization concerns (eg, lack of preventive care) for which employers offer no- and low-cost benefit programs. Methods: We identified groups with SDoH challenges within a commercially-insured population of 5.1 M through administrative data and self-report. Using medical claims and health assessment data, we identified populations with SDoH needs who had common conditions for which employers often provide no- or low-cost benefit programs (ie, diabetes, behavioral health conditions, high-risk pregnancy, overweight/obesity). Additionally, we sought populations with common addressable health services utilization concerns such as avoidable emergency room visits, lack of preventive care services, or non-adherence to medications. We used univariate analyses to describe the prevalence of SDoH risks in the population of interest. Results: Twenty-seven percent of this commercially-insured population live in a zip code where the median income is at or below 200% of the Federal Poverty Line. Respondents identified cost (55%) and family, school, or work responsibilities (26%) as key barriers to care. ER overutilization rates are higher in lower income zip codes than wealthier zip codes (34% vs 9%) as is the prevalence of diabetes, overweight/obesity, and behavioral issues, and decreased use of preventive services. Fifteen percent of the study population live in a low-access food area. There is considerable variability in access to employer-sponsored resources to address these needs (70% of employers provide behavioral health programs; 63% provide telehealth programs, but only 1% offer healthy food programs and less than 0.5% offer either child care or transportation support programs). Conclusions: Commercially insured populations could benefit from employer-sponsored programs or benefits that address key SDoH barriers such as financial support, healthy food programs, child-care, and transportation.

Opioid prescriptions in the perioperative setting are a known risk factor for long-term opioid use and misuse. Recent initiatives in the United States to address the issue have focused on judicious prescribing patterns and quality measurement to minimize opioid dispensing. However, policy gaps have limited the effectiveness of current interventions. Expanded policy considerations are warranted, including patient-focused opioid risk screening and preferences for nonopioid pain management, with broader plan coverage for multimodal opioid-sparing pain management (OSPM). Additionally, formalized clinician education regarding specific nonopioid pain management alternatives may increase utilization, as will incorporation into perioperative OSPM clinical pathways. It is also important for patients to have access to the option for multimodal OSPM in the perioperative setting without financial disincentives, which may arise in surgery-specific bundled payment models. Finally, expansion of research activities regarding clinical and cost-efficacy outcomes may help to advance use of these options, laying the groundwork for development of a broader set of quality measures reflecting utilization and outcomes of multimodal OSPM in the perioperative setting.

Employers have been challenged by low employee participation rates in health-related programs, and have often relied on incentives and other engagement approaches to overcome this difficulty. One of the apparent barriers to employee engagement in health-related activities is represented by social determinants of health. According to some, these factors comprise as much as 40% of an individualʼs health status, and while they have been the focus of attention in the public health domain, their role in the workplace has not been broadly recognized. In this manuscript, we provide an overview of the significance of social determinants of health in the workplace, addressing their influence on employee involvement in health-related offerings. We also acknowledge the unique role of the workplace as both a physical and social determinant of worker health.

[...]The American Journal of Managed Care® (AJMC®) is soliciting the submission of research and commentary manuscripts aimed at better informing our readership of the breadth and extent of existing disparities and evaluations of potential solutions implemented to reduce them. Identifying and addressing unmet social needs to the exclusion of attention to other contributors—most significantly in the absence of a trusting relationship—is unlikely to yield the desired outcome. [...]in order to meaningfully address systematic inequities, an expansive, patient-centered approach with an emphasis on trust building is warranted. For many, collection and documentation of SDOH data has become an incremental clinical responsibility—reinforced by the CMS Framework for Health Equity7 and the National Committee for Quality Assurance health equity initiatives.8 Although these are well intended, concerns have arisen that another administrative requirement for an already overburdened workforce that is increasingly prone to burnout may not achieve the goals of trust building and better patient health outcomes.9 At a foundational level, achieving health equity necessitates an enhanced focus on what matters to patients. In his 2011 book, The Checklist Manifesto: How to Get Things Right, Atul Gawande, MD, MPH, highlighted the value of the checklist as a simple tool to help overcome the volume and complexity of medical knowledge that limits clinician ability to consistently, correctly, and safely deliver health care services.13 In relation to health equity, checklists to identify SDOH have been broadly recommended.14 Although these are designed to facilitate more equitable clinical care delivery, current lists are frequently more clinician centered than patient centered, largely due to the use of standardized checklists that limit patient input to responses only to the items included on the list.

Employees face an increasing financial burden for health services as health care costs increase relative to earnings. Yet little is known about health care utilization patterns relative to employee wages. To better understand this association and the resulting implications, we examined patterns of health care use and spending by wage category during 2014 among 42,936 employees of four self-insured employers enrolled in a private health insurance exchange. When demographics and other characteristics were controlled for, employees in the lowest-wage group had half the usage of preventive care (19 percent versus 38 percent), nearly twice the hospital admission rate (31 individuals per 1,000 versus 17 per 1,000), more than four times the rate of avoidable admissions (4.3 individuals per 1,000 versus 0.9 per 1,000), and more than three times the rate of emergency department visits (370 individuals per 1,000 versus 120 per 1,000) relative to top-wage-group earners. Annual total health care spending per patient was highest in both the lowest-wage ($4,835) and highest-wage ($5,074) categories relative to the middle two wage groups ($3,952 and $3,987, respectively). These findings provide new insights about wage-associated variations in health care use and spending in employer-sponsored plans. For policy makers, these findings can inform employer benefit design strategies and research priorities, to encourage effective use of health care services.

The relationship between employee wage status and mental health care utilization has not been characterized in large-scale analyses. This study assessed health care utilization and cost patterns for mental health diagnoses according to wage category among employees with health insurance. This was an observational, retrospective cohort study for the year 2017 among 2,386,844 adult full-time employees (254,851 with mental health disorders; subgroup of 125,247 with depression) enrolled in self-insured plans in the IBM Watson Health MarketScan research database. Participants were stratified into annual wage categories: $34,000 or less; more than $34,000 to $45,000; more than $45,000 to $69,000; more than $69,000 to $103,000; and more than $103,000. Health care utilization and costs were analyzed via regression analyses. Prevalence of diagnosed mental health disorders was 10.7% (9.3% in the lowest-wage category); prevalence of depression was 5.2% (4.2% in the lowest-wage category). Severity of mental health, and specifically depression episodes, was greater in lower-wage categories. All-cause utilization of health care services was higher in patients with mental health diagnoses vs the total population. Among patients with mental health diagnoses, specifically depression, utilization was highest in the lowest- vs highest-wage category for hospital admissions, emergency department visits, and prescription drug supply (all P < .0001). All-cause health care costs were higher in the lowest- vs highest-wage category among patients with mental health diagnoses ($11,183 vs $10,519; P < .0001), specifically depression ($12,206 vs $11,272; P < .0001). Lower mental health condition prevalence and greater use of high-intensity health care resources highlight the need to more effectively identify and manage mental health conditions among lower-wage workers.

Prior descriptive epidemiology studies have shown that smokers have lower compliance rates with preventive care services and lower chronic medication adherence rates for preventive care services in separate studies. The goal of this study was to perform a more detailed analysis to validate both of these findings for current smokers versus nonsmokers within the benefit-covered population of a large US employer. This study involved the analysis of incurred medical and pharmacy claims for employee and spouse health plan enrollees of a single US-based employer during 2010. Multivariate regression models were used to compare data by active or never-smoker status for preventive care services and medication adherence for chronic conditions. Analysis controlled for demographic variables, chronic condition prevalence, and depression. Controlling for demographic variables and comorbid conditions, smokers had significantly lower cancer screening rates, with absolute reductions of 6%-13%. Adherence to chronic medication use for hypertension was also significantly lower among smokers, with nearly 7% fewer smokers having a medication possession ratio of ≥80%. Smokers were less adherent to depression medications (relative risk =0.79) than nonsmokers (P=0.10). While not statistically significant, smokers were consistently less adherent to all other medications than nonsmokers. Current smokers are less compliant with recommended preventive care and medication use than nonsmokers, likely contributing to smoking-related employer costs. Awareness of these care gaps among smokers and direct management should be considered as part of a comprehensive population health-management strategy.