The global COVID-19 response focused heavily on nonpharmaceutical interventions (NPIs) until vaccines became available. Even where vaccination coverage is low, over time governments have become increasingly reluctant to use NPIs. Inequities in vaccine and treatment accessibility and coverage, differences in vaccine effectiveness, waning immunity, and immune-escape variants of concern of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinforce the long-term need for mitigation. Initially, the concept of NPIs, and mitigation more broadly, was focused on prevention of SARS-CoV-2 transmission; however, mitigation can and has done more than prevent transmission. It has been used to address the clinical dimensions of the pandemic as well. The authors propose an expanded conceptualization of mitigation that encompasses a continuum of community and clinical mitigation measures that can help reduce infection, illness, and death from COVID-19. It can further help governments balance these efforts and address the disruptions in essential health services, increased violence, adverse mental health outcomes, and orphanhood precipitated by the pandemic and by NPIs themselves. The COVID-19 pandemic response revealed the benefits of a holistic and layered mitigation approach to public health emergencies from the outset. Lessons learned can inform the next phases of the current pandemic response and planning for future public health emergencies.

Attention to 10th Revision of the International Classification of Disease (ICD-10)-CM Z-codes as a mechanism for capturing social risk has grown over the years. However, it remains unclear whether the use of Z-codes has changed over time. This study sought to examine the trends in Z-code use between their introduction in 2015 and the end of 2019 across 2 markedly different states. Using the Healthcare Cost and Utilization Project, all emergency department visits or hospitalizations at short-term general hospitals in Florida and Maryland from 2015 Q4 through 2019 were identified. This study focused on a subset of the Z-codes that are intended to capture social risk to identify the percentage of encounters with a Z-code, percentage of facilities using Z-codes, and facility median of number of encounters with a Z-code per 1000 encounters across quarters, states, and care settings. In total, 495,212 (0.84%) of 58,993,625 encounters had a Z-code. Despite Florida's higher area deprivation, Z-codes were less frequently used and increasing more slowly than when compared with those in Maryland. There were 2.1 times the use of Z-codes in Maryland than in Florida at the encounter level. This difference was also seen when evaluating the median number of encounters with a Z-code, per 1000 encounters (12.1 vs. 3.4). Z-codes were more commonly used at major teaching facilities, and for patients who were uninsured or on Medicaid. The use of ICD-10-CM Z-codes has increased over time, with this increase occurring at nearly all short-term general hospitals. Their use was higher in Maryland than in Florida and among major teaching facilities.

As health systems attempt to contain utilization and costs, care management programs are proliferating. However, there are mixed findings on their impact. In 2018, Rhode Island initiated a care management program for dually eligible Medicare and Medicaid beneficiaries at high risk of hospitalization or institutionalization. The objective of this study is to evaluate the association between health care utilization and costs and care management for dual-eligible participants (n = 169). The authors employed an interrupted time series analysis of administrative claims data using the Rhode Island All Payer Claims Database, which includes data from all major payers in the state, for 11 quarters (January 1, 2017 until September 1, 2019). On average, participants were younger (46.2% were 19–64 years of age vs. 41.9% of non-participants), female (71% vs. 62.6% of non-participants), and had a higher comorbidity burden (more commonly had anemia, atrial fibrillation, chronic kidney disease, chronic obstructive pulmonary disease, depression, diabetes, heart failure, hyperlipidemia, hypertension, ischemic heart disease, and stroke). Participation was associated with significantly fewer hospital admissions (118 fewer admissions per 1000 admissions per quarter; 95% confidence interval [CI] −11 to −22), and a reduction in Medicaid ($1841 less spent per quarter, 95% CI −2407 to −1275) and total ($2570 less spent per quarter; 95% CI −$4645 to −$495) costs. Participation was not significantly associated with a change in Emergency Department (ED) visits, preventable ED visits, Skilled Nursing Facility stays, or Medicare costs. These results suggest that targeted care management programs may provide dual-eligible beneficiaries with needed services while diverting inefficient health care utilization.

The objective of this study was to assess the impact of local health department (LHD) expenditures on population health measures using counties as the unit of analysis. An observational research design is used to examine whether public health benefits are associated with higher levels of public health funding. Linear probability multivariate regression models with the use of local level cross-sectional and panel data are employed. A 1-year and a 2-year lag structure are also used to quantify the longer term public health effects of changes in LHD expenditures. Analyses were performed at the county level using local data representing 2120 LHDs, covering 48 US states. Expenditure data from the National Association of County and City Health Officials Profile Surveys and public health measures from County Health Rankings Annual Reports are used. Four public health measures are examined—obesity prevalence, sexually transmitted diseases, diabetes prevalence, and human immunodeficiency virus prevalence. Results from cross-sectional, pooled ordinary least squares, and panel data with fixed effects reveal that increased LHD expenditures per capita were not associated with any of the population health outcomes studied. Multivariate linear regression results using a 1- and 2-year lag structure reveal similar results: funding was not significantly predictive of better public health outcomes. The study design did not control for the potential endogeneity of public health funding. More detailed data and robust research approaches are needed to disentangle the effect and effectively answer whether increased public funding translates to improved population health.

This study investigated the clinical and economic impact of anti-obesity medications (AOMs; orlistat, liraglutide, phentermine/topiramate extended-release [ER], naltrexone ER/bupropion ER) among United States Veterans with obesity participating in Motivating Overweight/Obese Veterans Everywhere! (MOVE!), a government-initiated weight management program. The study population was identified from electronic medical records of the Veterans Health Administration (2010–2020). Clinical indices of obesity and health care resource utilization and costs were evaluated at 6, 12, and 24 months after the initial dispensing of an AOM in the AOM+MOVE! cohort (N = 3732, mean age 57 years, 79% male) or on the corresponding date of an inpatient or outpatient encounter in the MOVE! cohort (N = 7883, mean age 58 years, 81% male). At 6 months postindex, the AOM+MOVE! cohort had better cardiometabolic indices (eg, systolic blood pressure, diastolic blood pressure, total cholesterol, low-density lipoprotein cholesterol, hemoglobin A1c) than the MOVE! cohort, with the trends persisting at 12 and 24 months. The AOM+MOVE! cohort was significantly more likely than the MOVE! cohort to have weight decreases of 5%–10%, 10%–15%, and >15% and lower body mass index at 6, 12, and 24 months. The AOM+MOVE! cohort also had fewer inpatient and emergency department visits than the MOVE! cohort, which was associated with lower mean total medical costs including inpatient costs. These results suggest that combining AOM treatment with the MOVE! program could yield long-term cost savings for the Veterans Affairs network and meaningful clinical improvements for Veterans with obesity.

Individuals at increased risk for severe coronavirus disease-2019 (COVID-19) outcomes, due to compromised immunity or other risk factors, would benefit from objective measures of vulnerability to infection based on vaccination or prior infection. The authors reviewed published data to identify a specific role and interpretation of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) spike-targeted serology testing. Specific recommendations are provided for an evidence-based and clinically-useful interpretation of SARS-CoV-2 spike-targeted serology to identify vulnerability to infection and potential subsequent adverse outcomes. Decreased vaccine effectiveness among immunocompromised individuals is linked to correspondingly high rates of breakthrough infections. Negative results on SARS-CoV-2 antibody tests are associated with increased risk for subsequent infection. “Low-positive” results on semiquantitative SARS-CoV-2 spike-targeted antibody tests may help identify persons at increased risk as well. Standardized SARS-CoV-2 spike-targeted antibody tests may provide objective information on the risk of SARS-CoV-2 infection and associated adverse outcomes. This holds especially for high-risk populations that demonstrate a relatively high rate of seronegativity. The widespread availability of such tests presents an opportunity to refine risk assessment for individuals with suboptimal SARS-CoV-2 antibody levels and to promote effective interventions. Interim federal guidance would support physicians and patients while additional investigations are pursued.

Mental health issues often result in significant impairment and financial challenges, both at home and in the workplace. Solutions vary widely in their usage and cost-effectiveness. This study presents an analysis of medical and prescription drug spending and utilization data for the employees of 4 companies who were eligible for an evidence-based workforce mental health program (WMHP). A variation of coarsened exact matching paired WMHP users to nonusers, based on demographics, location, and medical factors. Individuals included 2791 pairs of members whose medical claims were incurred in 2018 and 3883 pairs with claims in 2019. Using a cost efficiency measurement process, mean cost and utilization per person per year (PPPY) were compared. WMHP users had lower medical (−$2295 in 2018; −$2304 in 2019) and prescription drug spending (−$295 in 2018; −$312 in 2019). Over half of the cost reduction (−$1252 in 2018; −$1211 in 2019) resulted from shifting therapy services from the medical benefit to WMHP. WMHP users attended about 12 sessions PPPY, whereas the comparison group of nonusers attended about 7 mental health office visits PPPY under the medical benefit. WMHP users had more mental health-related visits in both years, but had fewer visits on the medical plan, and fewer emergency department visits for mental health than comparison group members. These results provide evidence that high-quality, evidence-based mental health services can reduce total expenditures and change utilization patterns. Evidence-based WMHP may represent a prudent investment for employers in providing mental health care to employees.

Background: The Whole Health model is a holistic approach to facilitate whole health practices by addressing (1) the physical, mental, and social health of individuals and (2) associated support systems. Several national organizations such as the Institute for Healthcare Improvement's (IHI) Age-Friendly Health Systems (AFHS) movement and, the U.S. Department of Veterans Affairs have implemented whole health frameworks with many common elements and promoted whole health practice and skills. However, implementing a Whole Health model across communities and health systems will require evidence of effectiveness. Generating evidence on the effectiveness of the Whole Health model's effect on health outcomes requires data-driven intelligence. Methods: We identified the national public-use data sets that are most often used in health research with a machine-assisted literature search of PubMed and Scopus for peer-reviewed journal articles published from 2010 through the end of 2021, including preprints, using Python [3.7]. We then assessed if the 8 most commonly used datasets include variables associated with whole health. Results: The number of publications examining whole health has increased annually in the last decade, with more than 2800 publications in 2020 alone. Since 2010, 24,811 articles have been published using 1 of these data sets. However, we also found a lack of data (ie, data set includes all of the whole health variables) to examine whole health in national data sets. Conclusions: We support a call to expand data collection and standardization of critical measures of whole health.

Black individuals with diabetes have high rates of emergency department (ED) use. This randomized controlled trial compared the efficacy of Diabetes Interprofessional Team to Enhance Adherence to Medical Care (DM I-TEAM) versus Usual Medical Care (UMC) to reduce number of return ED visits/hospitalizations over 12 months in 200 Black individuals with diabetes after an ED visit. DM I-TEAM consisted of community health worker-delivered diabetes education and behavior activation, telehealth visits with a diabetes nurse educator and primary care physicians, and clinical pharmacist recommendations to reduce potentially inappropriate medications (PIMs). Secondary outcomes included glycemic control, PIMs use, diabetes self-management, diabetes self-efficacy, depression, and medical trust. Participants had a mean age of 64.9 years and 73.0% were women. The 2 treatment groups were similar in baseline characteristics. Sixty-eight (69.4%) DM I-TEAM participants and 69 (67.6%) UMC participants had at least 1 incident ED visit/hospitalization over 12 months. The adjusted incidence rate ratio for DM I-TEAM versus UMC was 1.11 (95% confidence interval 0.79–1.56; P = 0.54). DM I-TEAM participants attained significantly better diabetes self-management, diabetes self-efficacy, and institutional trust than UMC participants. There were no treatment group differences in hemoglobin A1c level nor PIMs use. Among Black individuals with diabetes, a novel culturally relevant intervention was no better than usual care at preventing return ED visits/hospitalizations over 1 year. Before reasonable clinical interventions such as DM I-TEAM can be effective, reducing system-level barriers to health, building community health care capacity, and designing interventions that better align with the everyday realities of patients' lives are necessary. clinicaltrials.gov NCT03393338

Maternal mortality and morbidity in the United States are high compared with those in similar countries, and racial/ethnic disparities exist, with many of these events occurring in the later postpartum period. Proposed federal and recently enacted state policy interventions extend pregnancy Medicaid from covering 60 days to a full year postpartum. This study estimates the association between maintaining Medicaid eligibility in the later postpartum period (relative to only having pregnancy Medicaid eligibility) with postpartum checkup attendance and depressive symptoms using regression analysis, overall and stratified by race/ethnicity. People with postpartum Medicaid eligibility were 1.0%–1.4% more likely to attend a postpartum checkup relative to those with only pregnancy Medicaid eligibility overall, primarily driven by a 3.8%–4.0% higher likelihood among Hispanic postpartum people. Conversely, postpartum Medicaid is associated with a 2.2%–2.3% lower likelihood of postpartum checkup attendance for Black postpartum people. Postpartum eligibility is also associated with a 9.7%–11.6% lower likelihood of self-reported depressive symptoms compared with only pregnancy Medicaid eligibility for White postpartum people only. Postpartum Medicaid eligibility is associated with some improvements in maternal health care utilization and mental health, but differences by race and ethnicity imply that inequitable systems and structures that cannot be overcome by insurance alone may also play an important role in postpartum health.

There is increased acceptance that social and behavioral determinants of health (SBDH) impact health outcomes, but electronic health records (EHRs) are not always set up to capture the full range of SBDH variables in a systematic manner. The purpose of this study was to explore rates and trends of social history (SH) data collection—1 element of SBDH—in a structured portion of an EHR within a large academic integrated delivery system. EHR data for individuals with at least 1 visit in 2017 were included in this study. Completeness rates were calculated for how often SBDH variable was assessed and documented. Logistic regressions identified factors associated with assessment rates for each variable. A total of 44,166 study patients had at least 1 SH variable present. Tobacco use and alcohol use were the most frequently captured SH variables. Black individuals were more likely to have their alcohol use assessed (odds ratio [OR] 1.21) compared with White individuals, whereas White individuals were more likely to have their “smokeless tobacco use” assessed (OR 0.92). There were also differences between insurance types. Drug use was more likely to be assessed in the Medicaid population for individuals who were single (OR 0.95) compared with the commercial population (OR 1.05). SH variable assessment is inconsistent, which makes use of EHR data difficult to gain better understanding of the impact of SBDH on health outcomes. Standards and guidelines on how and why to collect SBDH information within the EHR are needed.

Differences in preference-weighted health-related quality of life (HRQOL) scores by race/ethnicity may be due to social factors. Here, Short-Form Six-Dimension (SF-6D) scores are analyzed among men in a prostate cancer prevention trial to explore such differences. Selenium and vitamin E cancer prevention trial participants who completed the SF-6D at baseline, and in at least 1 of follow-up years 1, 3, and 5 were included. This study compared mean SF-6D scores across race/ethnicity at each point using a linear mixed model controlling for demographic and clinical characteristics. At baseline, 9691 men were eligible for analysis, of whom 7556 (78%) were non-Hispanic White, 1592 (16.4%) were non-Hispanic Black, and 543 (5.6%) were Hispanic. Hispanic and White participants had higher unadjusted mean SF-6D scores than Black participants at every time point (P < 0.05), while white participants had lower mean scores than Hispanic participants at every time point after baseline (P < 0.05). After adjusting for covariates, statistically significant differences in HRQOL among the 3 groups persisted. Hispanic participants had higher preference scores than White participants by 0.073 (P < 0.001), 0.075 (P < 0.001), and 0.040 (P < 0.001) in follow-up years 1, 3, and 5, respectively. Black participants had lower scores than White participants by 0.009 (P = 0.004) and 0.008 (P = 0.02) in follow-up years 1 and 3, respectively. The results suggest there is a preference-weighted HRQOL difference by race/ethnicity that cannot be explained by social and clinical variables alone. Understanding how individuals belonging to different racial/ethnic categories view their own HRQOL is necessary for culturally competent care and cost-effectiveness analyses.

Behavioral health integration (BHI) within primary care settings is shown to improve outcomes. However, achieving BHI requires identifying best practices and a reliable tool that can be used to measure existing levels and progress toward BHI. The objective of this study was to develop and apply a conceptual framework to measure BHI, test the approach, and examine challenges to achieving BHI. Surveys and interviews were conducted with key informants within 17 designated public hospitals in California at the midpoint of participating in a 5-year project to establish BHI. A framework and coding methodology were developed to assess BHI best practices at each hospital. BHI status was assessed in the domains of infrastructure and process. Each domain included 5 themes such as electronic health record integration and functionality (infrastructure) and interprovider communication (process). Themes were assessed using a 6-point scale for various activities under a theme and associated weights. Theme-specific values were standardized from 0% to 100% to compare BHI scores between hospitals. Overall progress toward BHI ranged from scores of 52% to 83% (mean 63%) and indicated greater contribution of infrastructure versus process implementation. Within the infrastructure domain, scores were higher for having institutional and provider support, but lagged in establishing provider proximity. Within the process domain, scores were highest for implementation of behavioral health screening, but were frequently lower for other themes such as use of care coordination and referral processes. Further research is needed to test the robustness of this approach in other settings.

The COVID-19 pandemic has underscored the urgency to focus on the essential value of public health systems (PHSs) in fostering health equity across the US health care delivery system. PHS integration and care coordination can be successfully achieved through health information technology systems. The objective of the study was to examine the association between PHS partnerships (PHSPs), telehealth postdischarge, and racial and ethnic disparities in health care. The analysis used 2017 Centers for Medicare and Medicaid Services Medicare 100% inpatient claims data, the Medicare Beneficiary Summary File, the American Hospital Association Annual Survey, and the American Community Survey. Results showed that compared with those treated in hospitals with neither PHSP nor telehealth postdischarge services, beneficiaries treated in hospitals with PHSP encountered significantly lower Medicare payment and inpatient and readmission rates. Black patients experienced significantly lower cost, inpatient visits, and readmission rates when treated in hospitals with PHSP and telehealth postdischarge services (coefficient = −0.051, P < 0.001; incidence rate ratio [IRR] = 0.982, P = 0.007; IRR = 0.891, P = 0.003). The results of the study demonstrated the importance of combining PHSP and telehealth postdischarge services to improve the efficiency of the health care delivery system and health equity. It is urgent to ensure that PHSs have adequate funding and telehealth infrastructure to support population health.

The United States has one of the highest cumulative mortalities of coronavirus disease 2019 (COVID-19) and has reached 1 million deaths as of May 19th, 2022. Understanding which community and hospital factors contributed to disparities in COVID-19 mortality is important to inform public health strategies. This study aimed to explore the potential relationship between hospital service area (1) community (ie, health professional shortage areas, market competition, and uninsured percentage) and (2) hospital (ie, teaching, system, and ownership status) characteristics (2013–2018) on publicly available COVD-19 (February to October 2020) mortality data. The study included 2514 health service areas and used multilevel mixed-effects linear model to account for the multilevel data structure. The outcome measure was the number of COVID-19 deaths. This study found that public health, as opposed to acute care provision, was associated with community health and, ultimately, COVID-19 mortality. The study found that population characteristics including more uninsured greater proportion of those over 65 years, more diverse populations, and larger populations were all associated with a higher rate of death. In addition, communities with fewer hospitals were associated with a lower rate of death. When considering region in the United States, the west region showed a higher rate of death than all other regions. The association between some community characteristics and higher COVID-19 deaths demonstrated that access to health care, either for COVID-19 infection or worse health from higher disease burden, is strongly associated with COVID-19 deaths. Thus, to be better prepared for potential future pandemics, a greater emphasis on public health infrastructure is needed.

The extent to which cumulative social disadvantage—defined as aggregate social risk resulting from multiple co-occurring adverse social determinants of health (SDOH)—affects the risk of all-cause mortality, independent of demographic and clinical risk factors, is not well understood. The objective of this study was to examine the association between cumulative social disadvantage, measured using a comprehensive 47-factor SDOH framework, and mortality in a nationally representative sample of adults in the United States. The authors conducted secondary analysis of pooled data for 63,540 adult participants of the 2013–2015 National Death Index-linked National Health Interview Survey. Age-adjusted mortality rates (AAMRs) were reported by quintiles of aggregate SDOH burden, with higher quintiles denoting greater social disadvantage. Cox proportional hazards models were used to examine the association between cumulative social disadvantage and risk of all-cause mortality. AAMR increased significantly with greater SDOH burden, ranging from 631 per 100,000 person-years (PYs) for participants in SDOH-Q1 to 1490 per 100,000 PYs for those in SDOH-Q5. In regression models adjusted for demographics, being in SDOH-Q5 was associated with 2.5-fold higher risk of mortality, relative to Q1 (adjusted hazard ratio [aHR] = 2.57 [95% confidence interval, CI = 1.94–3.41]); the observed association persisted after adjusting for comorbidities, with over 2-fold increased risk of mortality for SDOH-Q5 versus Q1 (aHR = 2.02 [95% CI = 1.52–2.67]). These findings indicate that cumulative social disadvantage is associated with increased risk of all-cause mortality, independent of demographic and clinical factors. Population level interventions focused on improving individuals' social, economic, and environmental conditions may help reduce the burden of mortality and mitigate persistent disparities.

Screening for social determinants of health (SDOH) is recommended, but numerous barriers exist to implementing SDOH screening in clinical spaces. In this study, the authors identified how both active and passive information retrieval methods may be used in clinical spaces to screen for SDOH and meet patient needs. The authors conducted a retrospective sequential cohort analysis comparing the active identification of SDOH through a patient-led digital manual screening process completed in primary care offices from September 2019 to January 2020 and passive identification of SDOH through natural language processing (NLP) from September 2016 to August 2018, among 1735 patients at a large midwestern tertiary referral hospital system and its associated outlying primary care and outpatient facilities. The percent of patients identified by both the passive and active identification methods as experiencing SDOH varied from 0.3% to 4.7%. The active identification method identified social integration, domestic safety, financial resources, food insecurity, transportation, housing, and stress in proportions ranging from 5% to 36%. The passive method contributed to the identification of financial resource issues and stress, identifying 9.6% and 3% of patients to be experiencing these issues, respectively. SDOH documentation varied by provider type. The combination of passive and active SDOH screening methods can provide a more comprehensive picture by leveraging historic patient interactions, while also eliciting current patient needs. Using passive, NLP-based methods to screen for SDOH will also help providers overcome barriers that have historically prevented screening.

This study evaluated relationships between county-level social vulnerability and broadband access using spatial clustering and regression approaches. County-level broadband availability (Federal Communications Commission [FCC] and Microsoft; 2019–2020), social vulnerability (COVID-19 Community Vulnerability Index [CCVI]; 2020), and primary care access (Area Health Resource File; 2019–2020) data sets were used. Two measures of broadband availability were considered: (1) Microsoft system-reported proportion of county population with broadband and (2) difference in FCC-reported and Microsoft-reported proportions of county population with broadband. Cluster maps were constructed using local Moran's I, and spatial Durbin models were estimated using primary care shortage designation and CCVI themes (socioeconomic status, minority status, housing/transportation/disability, epidemiological risk, health care system, high-risk environment, and population density). Among 3102 counties, county-level broadband coverage varied widely between Microsoft (0.39) and FCC (0.84), with greater coverage in the East and West, and larger discrepancies between FCC and Microsoft data in the South and Appalachia. In spatial regressions, a one-point increase in socioeconomic status vulnerability (0—least; 10—most vulnerable), was associated with a 2.0 percentage point (pp) reduction in broadband access (P < 0.001). Similar inverse relationships were observed with housing, epidemiological, and health care system variables. There were greater divergences between FCC and Microsoft measures with each one-point increase in socioeconomic status (1.4 pp), epidemiological risk (0.6 pp), and health care system (0.7 pp) vulnerability. More vulnerable counties had lower broadband and larger divergences between FCC and Microsoft data. Broadband is necessary for utilizing telehealth services; careful considerations in measuring broadband access can facilitate policies that improve equitable access to care.

Community coalitions have been leading the multisector response to the opioid epidemic in the Unites States. However, with the medicalization of opioid use disorder and changing health care policies, hospitals have moved to the forefront, becoming more active in collaborating with community coalitions. Little is currently known about how community coalitions view and approach collaborating with hospitals despite its importance for understanding and advancing interorganizational approaches to combating the opioid epidemic. Using data from semistructured interviews (n = 119) conducted from November 2019 to January 2020 as part of the HEALing Communities Study (ClinicalTrials.gov: NCT04111939), the authors examined how community coalition members perceive hospital collaborations and explored the opportunities and challenges of these partnerships. They characterized 3 emergent themes: coalition approaches to collaborating with hospitals, barriers to collaboration, and opportunities for sustainable relationships. This new evidence highlights the value that coalitions place on hospital collaborations, as well as mechanisms that may help support ongoing partnerships.

Oral antivirals for COVID-19 can be game changers in low- and middle-income countries (LMICs). Challenges that may hinder current and future oral antiviral rollouts span use in special populations, drug–drug and herb–drug interactions, adverse events, development of resistance, black markets, and equity in access and prescribing. Future antivirals may address some of these barriers; however, health systems around the world should be equipped to receive and administer COVID-19 oral antivirals. Improvements in manufacturing capacity, community engagement, capacity for testing and linkage to care, and systems for surveillance and safety monitoring could “change the game” for LMICs, irrespective of any specific antiviral drug. Investments in health care infrastructure can promote resilience, not only for COVID-19 but also for future local and global health crises.

Rising prescription costs, poor medication adherence, and safety issues pose persistent challenges to employer-sponsored health care plans and their beneficiaries. Comprehensive medication management (CMM), a patient-centered approach to medication optimization, enriched by pharmacogenomics (PGx), has been shown to improve the efficacy and safety of pharmaceutical regimens. This has contributed to improved health care outcomes, reduced costs of treatments, better adherence, shorter durations of treatment, and fewer adverse effects from drug therapy. Despite compelling clinical and economic evidence to justify the application of CMM guided by PGx, implementation in clinical settings remains sparse; notable barriers include limited physician adoption and health insurance coverage. Ultimately, these challenges may be overcome through comprehensive programs that include clinical decision support systems and education through employer-sponsored population health management channels to the benefit of the employees, employers, health care providers, and health care systems. This article discusses benefits, considerations, and barriers of scalable PGx-enriched CMM programs in the context of self-insured employers.

Managed care organizations (MCOs) are increasingly engaging community health workers (CHWs) to support service delivery for their members, particularly in the realm of social determinants of health. Some states now require MCOs to offer CHW services. Although the roles and activities of CHWs working in other contexts (eg, clinics, hospitals, community-based organizations) are well established, there is sparse knowledge about how MCOs are operationalizing CHW roles and whether CHW activities differ based on whether CHWs are employed directly by MCOs or contracted through other organizations. In 2021, 2 CHW professional associations and a university partnered to conduct a national cross-sectional survey of CHWs working with MCOs. Respondents (n = 146) represented 29 states. CHWs employed by MCOs reported receiving significantly more training and benefits from their employers than CHWs who were contracted through other organizations. MCO-based CHWs were more likely to support members with high-cost conditions and high service use, whereas contracted CHWs were more likely to engage in population-focused interventions, which may produce less immediately visible financial returns. Health plans would do well to ensure the CHWs they support, whether through contract or direct hiring, receive appropriate compensation and training, and have the freedom to engage in the full range of CHW roles, including community-level interventions.

The Medicaid Delivery System Reform Incentive Payment (DSRIP) program has been among the most widely adopted value-based payment strategies to drive improved population health management among safety net populations. Using comprehensive claims data from New Jersey and difference-in-differences modeling, the authors examine the impact of DSRIP pay-for-performance disease management programs on outcomes related to targeted chronic conditions. The authors find DSRIP reduced asthma hospitalizations and emergency department visits, pneumonia readmissions, and improved alcohol and drug treatment. Positive program-specific findings are encouraging for future DSRIP-like initiatives and demonstrate provider ability to successfully adapt to payment reforms.

Despite increasing resources dedicated to identifying and addressing social risks in health care settings, many patients screening positive for social risks either decline assistance or do not follow up with offered resources. This study assessed predictors of engagement with offered social care assistance through guided self-navigation or in-person assistance. Data came from a cross-sectional analysis of 6-month follow-up survey data from an ongoing trial of participants with poorly controlled diabetes and a positive social risk screen randomized to guided online self-navigation or in-person social care assistance. Multivariable logistic regression models estimated participant characteristics associated with engagement with offered assistance. Mean age was 55 years (standard deviation = 12). Of 407 participants, 41% (n = 165) engaged with offered assistance: 76% (n = 137) of those in the guided self-navigation arm and 13% (n = 28) of those in the in-person assistance arm. A sizable proportion of participants endorsed already using assistance for medications (30%), food (26%), and employment (22%). Female gender [OR 1.57, 95% CI (1.03–2.40), P < 0.05] and being out of the workforce [OR 1.71, 95% CI (1.07–2.73), P < 0.05] predicted engagement with social care assistance. Those already using assistance for medications [OR 4.71, 95% CI (1.69–13.15), P < 0.05] and blood glucose supplies [OR 6.25, 95% CI (1.45–26.78) P < 0.05] were also more likely to engage with offered assistance. Fewer than half of individuals engaged with offered social assistance through either guided online self-navigation or in-person assistance; limited demographic and clinical factors predicted uptake. More investments are needed to understand how best to support uptake of offered assistance.

Health care systems continue to struggle with preventing 30-day readmissions to their institutions. Social determinants of health (SDOH) are important predictors of repeat visits to the hospital. In many health systems, SDOH data are limited to those variables that are most relevant to care delivery or payment (eg, race, gender, insurance status). Despite calls for integrating a more robust set of measures (eg, measures of health behaviors and living conditions) into the electronic health record (EHR), these data often have missing values necessitating the use of imputation to build a comprehensive picture of patients who are likely to return to the health system. Using logistic regression analyses and imputation of missing data from 2017 to 2018, this study uses measures found in the EHR (eg, tobacco use, living situation, problems at home, education) to assess those SDOH that might predict a return to the emergency department within 30 days of discharge from a health system. In both imputed and raw data, the total number of recorded health conditions was the most important predictor and collectively SDOH variables made a relatively small contributions in determining the likelihood of a return to the hospital. Although SDOH variables might be important in the design of programs aimed at preventing readmissions, they may not be useful in readmission predictive models.

Cannabis policy is rapidly changing and more individuals are using cannabis nationally. Despite increased use and known adverse outcomes to cannabis use, there is a lack of understanding of health care utilization for cannabis-related conditions. The objectives of this study were: (1) To understand the change in the incidence of cannabis-related diagnoses from 2012 to 2015 nationally and (2) to describe the relationship between regional cannabis policies and changes in the incidence of cannabis-related diagnoses from 2012 to 2015. National Inpatient Sample (NIS) data from the Healthcare Cost and Utilization Project for 2012 and 2015 were analyzed using SPSS software for incidence of cannabis diagnoses. Previously defined NIS regions were assigned a policy status related to medical and recreational cannabis laws. Comparisons were made at the national and regional levels to better understand change in incidence of diagnoses. From 2012 to 2015, there was a 26.7% increase in cannabis-related diagnoses in the inpatient setting nationally. All 9 regions showed increases in the incidence of cannabis-related diagnoses ranging from 15.5% to 41.9% regardless of cannabis policy. As cannabis policy increased legal access, cannabis-related diagnoses increased nationally and regionally across the United States from 2012 to 2015 regardless of cannabis policy. Continued tracking of cannabis-related diagnoses is needed to identify where interventions are necessary to reduce negative impacts of increased cannabis use.

The observed increase in osteoarthritis (OA) of the knee as a result of an aging population and the obesity epidemic has led to a concomitant increase in the rates of total knee replacement (TKR), placing an additional financial and social burden on the ability of health care systems to control medical costs. Our study shows how a home-based, noninvasive biomechanical intervention reduced the rate of progression to surgery for a cohort of 237 patients with knee OA deemed eligible for TKR based on pre-established clinical selection criteria. Over the 24-month study period, 204 patients (86%) avoided surgery, with only 33 patients (14%, 95% confidence interval 82%–91%) progressing to a TKR with an average length of time to TKR of 324 days (ranging from 31 to 671 days). The application of this intervention provides health plans and provider networks managing patient care under financial risk arrangements an opportunity to realize significant cost savings without compromising quality of care or clinical outcomes.

Despite widespread vaccination, the COVID-19 pandemic continues to cause global disruption. Authors describe the pace of COVID-19 vaccination in Israel and examine differences in morbidity and mortality rates over time between vaccinated and unvaccinated populations. Retrospective data were obtained between December 2020 and December 2021 on daily vaccine uptake by age group (20–39, 40–59, 60+ years): rate of hospitalized severely ill cases, vaccination status and age group, and death rate per 100,000 by date and vaccination status. Uptake of first and second doses was slower in 20–59-year olds, whereas in 60+-year olds, it occurred without delay. Once most adults were vaccinated, a gap appeared with much higher severe cases and deaths in unvaccinated versus vaccinated populations; this gap attenuated by late May with very low rates in both vaccinated and unvaccinated populations until mid-July, when rates began to rise again. A herd-immunity-like period occurred in Spring 2021, with unvaccinated benefitting from a highly vaccinated population. Staggered vaccine uptake led to unsynchronized high immunity, which contributed to the fourth pandemic wave. Population vaccination within a shorter timeframe or shorter intervals between boosters may be important to reduce viral transmission.

Patients enrolled in Medicaid have significantly higher social needs (SNs) than others. Using claims and electronic health records (EHRs) data, managed care organizations (MCOs) could systemically identify high-risk patients with SNs and develop population health management interventions. Impact of SNs on models predicting health care utilization and costs was assessed. This retrospective study included claims and EHRs data on 39,267 patients younger than age 65 years who were continuously enrolled during 2018–2019 in a Medicaid-managed care plan. SN marker was developed suggesting presence of International Classification of Diseases, 10th revision codes in any of the 5 SN domains. Impact of SN marker was compared across demographic and 2 diagnosis-based (ie, Charlson and Adjusted Clinical Groups risk score) prediction models of emergency department (ED) visit and hospitalizations, and total, medical, and pharmacy costs. After combining data sources, prevalence of documented SN marker increased from 11% and 13% to 18% of the study population across claims, EHRs, and both combined, respectively. SN marker improved predictions of demographic models for all utilization and total costs outcomes (area under the curve [AUC] of ED model increased from 0.57 to 0.61 and R² of total cost model increased from 10.9 to 12.2). In both diagnosis-based models, adding SN marker marginally improved outcomes prediction (AUC of ED model increased from 0.65 to 0.66). This study demonstrated feasibility of using claims and EHRs data to systematically capture SNs and incorporate in prediction models that could enable MCOs and policy makers to adjust and develop effective population health interventions.

The increasing prevalence of prediabetes and diabetes in the United States poses a serious threat to the health of the population. Closely associated with obesity, hypertension, dyslipidemia, and cardiovascular disease, a diagnosis of diabetes or prediabetes carries with it life-altering demands. Critically important among these is the requirement for frequent glucose level checks—typically performed with blood obtained from a fingerstick. Innovative real-time continuous glucose monitoring (rtCGM) technology makes it possible for patients and their clinicians to receive continuous glucose level measurements around the clock without finger sticks. Accruing evidence shows that rtCGM is an effective tool for patients and their clinicians in managing diabetes (ie, maintaining glucose levels within the recommended target range) and in understanding how lifestyle behaviors directly influence glucose levels. In recent years, a number of large payer organizations (eg, private health insurers, employers) have incorporated rtCGM in their diabetes management programs as a means of addressing the dual challenge of achieving/maintaining control of glucose levels and preventing or delaying the onset of complications. Programmatic integrated approaches have been used successfully and cost-effectively for managing other chronic conditions. Incorporating rtCGM in similar integrated approaches in diabetes management may be of value in improving quality outcomes and reducing costs on a population level. The evidence supports broader adoption and continued study to evaluate models that incorporate the use of rtCGM.

Limited sample size, incomplete measures, and inadequate risk adjustment adversely influence accurate health care quality measurements, surgical quality measurements, and accurate comparisons among hospitals. Since these measures are linked to resources for quality improvement and reimbursement, improving the accuracy of measurement has substantial implications for patients, clinicians, hospital administrators, insurers, and purchasers. The team examined risk-adjusted differences of postoperative cardiac events among 20 geographically dispersed, community-based medical centers within an integrated health care system and compared it with the National Surgical Quality Improvement Program (NSQIP) hospital-specific differences. The exposure included the hospital at which patients received noncardiac surgical care, with stratification of patients by the acuity of surgery (elective vs. urgent/emergent). Among 157,075 surgery patients, the unadjusted risk of cardiac event per 1000 ranged among hospitals from 2.1 to 6.9 for elective surgery and from 10.3 to 44.5 for urgent/emergent surgery. Across the 20 hospitals, hospital rankings estimated in the present analysis differed significantly from ranking reported by NSQIP (P for difference: elective, P = 0.0001; urgent/emergent, P < 0.0001) with significantly and substantially lower variation after risk adjustment. Current surgical quality measures may not adequately account for limitations of sample size, data capture, adequate risk adjustment, and surgical acuity in a given hospital, particularly for rare outcomes. These differences have implications for quality reporting and may introduce bias into hospital comparisons, particularly for hospitals with incomplete capture of their patients' baseline risk and acuity.

Disparities in cardiovascular outcomes are persistent in our society. The objective was to track the trends before and after the passage of the Affordable Care Act in socioeconomic status (SES) disparities in utilization of cardiovascular disease (CVD) preventive services among nonelderly adults aged 18–64 years. This study used the National Health Interview Survey (2011–2017) to compare utilization of blood pressure, cholesterol, glycemic screening, and diet and smoking cessation advice over time between groups stratified by SES and race using difference-in-difference analysis. This study also measured the differences over time in specific vulnerable population subgroups (Hispanic, low-income and uninsured vs. White, middle–high-income, and insured). The study population included 176,961 surveyed individuals (mean age 40 [±13] years; 51% female; 67.7% non-Hispanic White) between 2011 and 2017, translating to 194.8 million nonelderly US adults per year. Most individuals were from high-income SES (40.0%), followed by middle-income (28.1%), low-income (13.6%), and lowest income SES (18.3%). The proportion of CVD preventive services increased over all SES categories through the study period. The biggest relative changes were seen among low-income individuals. The difference in blood pressure checks, cholesterol checks, and smoking cessation advise between high- and lowest income groups showed a statistically significant decrease at 5.2%, 4.8%, and 11.2%, respectively, between 2011 and 2017. The findings demonstrate a trend in reduction of CVD preventive care disparities between SES groups. However, a gap still exists, and this study highlights the need for continuous improvement to eliminate SES disparities.

This study aimed to determine whether there are disparities in the utilization of home-based care services according to income level among people aged 75 years or older in Japan. The research team used administrative claims data from April 2014 to March 2018 for people aged 75 years or older in Fukuoka Prefecture. Subjects were categorized according to income level using medical insurance claim data. Associations between income level and usage days of inpatient care, outpatient care, home medical care, and usage number of home-based long-term care (LTC) services were evaluated. Furthermore, medical and LTC costs were evaluated and adjusted for gender, age, and level of LTC needs. The team used generalized linear models (GLMs) to estimate medical and LTC services utilization, as well as the potential influence of gender, age, care needs level, and death as risk factors. The study analyzed 31,322 subjects, among whom 17,288 were in low-, 12,755 were in middle-, and 1399 were in high-income groups. The results of GLMs showed the number of home medical care days was 59.45, 62.24, and 69.66 days for users from low-, middle-, and high-income groups, respectively. Correspondingly, the number of home-based LTC services used was 668.84, 709.59, and 833.14 times. This study suggests that older adults with lower incomes had relatively low utilizations of home-based care services and high utilizations of nonhome-based LTC services. Policymakers should implement policies focused on people who need care to tackle socioeconomic inequalities in home-based care.

Health care systems have made concerted efforts to improve value for individuals with complex and chronic disease. Despite these efforts, this population (and the Medicaid population in particular) has been historically difficult to impact as many members are disproportionately impacted by social determinants of health that interfere with their ability to engage the health care system effectively. Transactional, solutions-based interventions to resolve barriers to care have been ineffective at either improving outcomes or reducing cost in the long term. The authors identify 3 core barriers that prevent time-limited, transactional interventions from effectively solving complex health and social problems: trust, self-efficacy, and complexity. By evolving from a transactional framework to a relational framework, case managers can develop relationships with clients that will help overcome these barriers. More specifically, clinical case management can be utilized to resolve these barriers by implementing a long-term, relational approach with clients through 5 key principles: ensuring continuity of care, leveraging the case management relationship, titrating support and structure, engaging flexibility, and facilitating patient resourcefulness. This article discusses how these principles resolve the identified barriers and how such a model is currently being executed in University Hospital's system. RWJF Grant I.D Number is 98426.

Vaginitis is a common condition that affects women of reproductive age. Early and accurate diagnosis and identification of the causative agents (ie, fungi, protozoa, bacterial species, etc.) help to avoid incorrect treatment and subsequent visits that add costs and therapies, which increase overall health care utilization. A prior study by Kong et al presented a cost analysis demonstrating that women who received a nucleic acid amplification test (NAAT) on the day of their vaginitis diagnosis had significantly lower 12-month follow-up costs than women who received a direct probe (DP) test or women who received clinical evaluation without the use of a molecular test. This prior analysis included pregnant women, which may have influenced the findings. The objective of this analysis is to determine whether the exclusion of pregnant women from the study cohort impacts the previously observed NAAT cost-savings results. The current analysis adds evidence that nonpregnant women diagnosed with NAAT at their initial visit have significantly lower 12-month overall health care costs than women evaluated through DP or other clinical methods.

Hospitals have demonstrated the benefits of both voluntary and mandatory bundled payments for joint replacement surgery. However, given generalizability and disparities concerns, it is critical to understand the availability of care through bundled payments to historically marginalized groups, such as racial and ethnic minorities and individuals with lower socioeconomic status (SES). This cross-sectional analysis of 3880 US communities evaluated the relationship between the proportion of Black and Hispanic individuals (minority share) or Medicare/Medicaid dual-eligible individuals (low SES share) and community-level participation in Bundled Payments for Care Improvement initiative (BPCI) (being a BPCI community) and Comprehensive Care for Joint Replacement (CJR) model (being a CJR community). An increase from the lowest to highest quartile of minority share was not associated with differences in the probability of being a BPCI community (3.5 percentage point [pp] difference, 95% confidence interval [CI] −1.2% to 8.3%, P = 0.15), but was associated with a 16.1 pp higher probability of being a CJR community (95% CI 10.3% to 22.0%, P < 0.0001). An increase from the lowest to highest quartile of low SES share was associated with a 6.0 pp lower probability of being a BPCI community (95% CI −10.9% to −1.2%, P = 0.02) and 19.0 pp lower probability of being a CJR community (95% CI −24.9% to −13.0%, P < 0.0001). These findings highlight that the greater the proportion of lower SES individuals in a community, the lower the likelihood that its hospitals participated in either voluntary or mandatory bundled payments. Policymakers should consider community socioeconomic characteristics when designing participation mechanisms for future bundled payment programs.

This study assesses cost savings associated with specific contraceptive methods provided to beneficiaries enrolled in South Carolina Medicaid between 2012 and 2018. Incremental cost-effectiveness ratios, defined as the additional cost of contraception provision per live birth averted, were estimated for 4 contraceptive methods (intrauterine devices [IUDs], implants, injectable contraceptives, and pills), relative to no prescription method provision, and savings per dollar spent on method provision were calculated. Costs associated with publicly funded live births were derived from published sources. The analysis was conducted for the entire Medicaid sample and separately for individuals enrolled under low-income families (LIFs), family planning, and partners for healthy children (PHC) eligibility programs. Sensitivity analysis was performed on contraceptive method costs. IUDs and implants were the most cost-effective with cost savings of up to $14.4 and $7.2 for every dollar spent in method provision, respectively. Injectable contraceptives and pills each yielded up to $4.8 per dollar spent. However, IUDs and implants were less cost-effective than injectable contraceptives and pills if the average length of use was less than 2 years. Medicaid's savings varied across Medicaid eligibility programs, with the highest and lowest savings from contraceptive provision to women in the LIFs and PHC eligibility programs, respectively. The results suggest the need to account for unique needs and preferences of beneficiaries in different Medicaid eligibility categories during contraception provision. The findings also inform program administration and provide evidence to justify legislative appropriations for Medicaid reproductive health care services.

The coronavirus disease (COVID-19) pandemic has highlighted the link between individual behavior and public health, along with the importance of evidence-based efforts to promote prosocial individual behavior. Insights from behavioral science can inform the design of effective behavior change techniques, or nudges, to influence individual behavior. The MINDSPACE framework organizes 9 behavioral science principles that can be used to guide policy design: Messenger, Incentives, Norms, Defaults, Salience, Priming, Affect, Commitments, and Ego. Using MINDSPACE as an organizing framework, this article provides a review of the literature on nudges to influence prosocial behaviors relevant during a pandemic: handwashing, avoidance of social gatherings, self-isolation and social distancing, and sharing public health messages. Additionally, empirical evidence on the use of nudges during the first several months of the COVID-19 pandemic in 2020 is summarized. Recommendations regarding the use of nudges to achieve public health policy goals during pandemics are provided. Organizational leaders, policymakers, and practitioners can use nudges to promote public health when mandates are not politically feasible or enforceable.

In the United States, the top 1% and top 5% of health care spenders account for 23% and 50% of total health care spending, respectively. These high spenders have been coined the term super utilizers (SU). The aim of this study was to identify the characteristics associated with these patients to aid in developing public health interventions aimed at transitioning patients out of the SU category and thus ultimately helping to control health care costs. The authors utilized the Utah All-Payer Claims Database and Utah Population Database from 2013 to 2015 to identify demographics, comorbid conditions, health care utilization, and cost characteristics of persistent super utilizers (PSU) (≥3 hospitalizations per year for 3 years) of health care compared with persistent nonsuper utilizers (PNSU) (<3 hospitalizations per year for 3 years). Multivariable logistic regression was utilized to identify the characteristics associated with PSU versus PNSU. Higher outpatient/Emergency Department/noninpatient (eg, visits with imaging and Centers for Medicare & Medicaid Services preventive visits) health care utilization and spending, and prevalence of comorbid disease and psychosocial conditions were associated with PSU. In multivariable analysis, factors such as heart disease, chronic kidney disease (CKD), diabetes, alcohol abuse, and depression were statistically significantly associated with higher odds of PSU, with the most noteworthy being CKD (odds ratio [OR] 6.85, 95% confidence interval [95% CI] 5.84–8.02; P < 0.001), alcohol abuse (OR 5.90, 95% CI 4.49–7.69; P < 0.001), and heart diseases (OR 4.41, 95% CI 3.74–5.18; P < 0.001). The annual health care cost of a PSU is about 11.5 times greater than a PNSU ($54,776 vs. $4801; P < 0.001).

Many studies have assessed the factors associated with overall video visit use during the COVID-19 pandemic, but little is known about who is most likely to continue to use video visits and why. The authors combined a survey with electronic health record data to identify factors affecting the continued use of video visit. In August 2020, a stratified random sample of 20,000 active patients from a large health care system were invited to complete an email survey on health care seeking preferences during the COVID. Weighted logistic regression models were applied, adjusting for sampling frame and response bias, to identify factors associated with video visit experience, and separately for preference of continued use of video visits. Actual video visit utilization was also estimated within 12 months after the survey. Three thousand three hundred fifty-one (17.2%) patients completed the survey. Of these, 1208 (36%) reported having at least 1 video visit in the past, lowest for African American (33%) and highest for Hispanic (41%). Of these, 38% would prefer a video visit in the future. The strongest predictors of future video visit use were comfort using video interactions (odds ratio [OR] = 5.30, 95% confidence interval [95% CI]: 3.57–7.85) and satisfaction with the overall quality (OR = 3.94, 95% CI: 2.66–5.86). Interestingly, despite a significantly higher satisfaction for Hispanic (40%–55%) and African American (40%–50%) compared with Asian (29%–39%), Hispanic (OR = 0.46, 95% CI: 0.12–0.88) and African American (OR = 0.54, 95% CI: 0.16–0.90) were less likely to prefer a future video visit. Disparity exists in the use of video visit. The association between patient satisfaction and continued video visit varies by race/ethnicity, which may change the future long-term video visit use among race/ethnicity groups.