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ObjectiveThe purpose of this analysis is to examine the effect of an algorithm-driven online diabetes prevention program on changes in eating habits, physical activity and wellness/productivity factors.MethodsThe intervention, Alive-PD, used small-step individually tailored goal setting and other features to promote changes in diet and physical activity. A 6-month randomized controlled trial was conducted among patients from a healthcare delivery system who had confirmed prediabetes (n =339). Change in weight and glycemic markers were measured in the clinic. Changes in physical activity, diet and wellness/productivity factors were self-reported. Mean age was 55 (s.d. 8.9) years, mean body mass index was 31 (s.d. 4.4) kg m(-2), 68% were white and 69% were male.ResultsThe intervention group increased fruit/vegetable consumption by 3.71 (95% confidence interval (CI) 2.73, 4.70) times per week (effect size 0.62), and decreased refined carbohydrates by 3.77 (95% CI 3.10, 4.44) times per week both significantly (P

Introduction: This study evaluates the real-world impact of a lifestyle change program (LCP) on healthcare utilization in a large health system., Methods: Using electronic health record data from a large health system in northern California, U.S., LCP participant and propensity-score-matched nonparticipant outcomes were compared in the second year post-participation: (1) overall healthcare utilization and (2) utilization and medications related to cardiometabolic conditions and obesity. Adult LCP participants between 2010 and 2017 were identified and matched 1:1 with replacement to comparable nonparticipants. Participants without electronic health record activity in the 12-36 months before baseline, or with conditions or procedures associated with substantial weight change, were excluded. Statistical analysis and modeling were performed in 2021-22., Results: Compared to matched nonparticipants, LCP participants in the 12-24 months post-baseline were more likely to have specialty-care visits (+4.7%, 95% CI +1.8%, +7.6%), electronic communications (8.6%, 95% CI +5.6%, +11.7%), and urgent-care visits (+6.5%, 95% CI +3.0%, 10.0%). Participants also had more office visits for cardiometabolic conditions and obesity (+1.72 visits/patient, 95% CI +1.05, +2.39)., Conclusions: Compared with matched nonparticipants, LCP participation was associated with higher utilization of outpatient services post-participation. Additional research could assess whether this indicates an increase in preventive care that could lead to improved future outcomes., (Copyright © 2023 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

The impacts of homelessness on health and health care access are detrimental. Intervention and efforts to improve outcomes and increase availability of affordable housing have mainly originated from the public health sector and government. The role that large community-based health systems may play has yet to be established. This study characterizes patients self-identified as homeless in acute care facilities in a large integrated health care system in Northern California to inform the development of collaborative interventions addressing unmet needs of this vulnerable population. The authors compared sociodemographic characteristics, clinical conditions, and health care utilization of individuals who did and did not self-identify as homeless and characterized their geographical distribution in relation to Sutter hospitals and homeless resources. Between July 1, 2019 and June 30, 2020, 5% ( N  = 20,259) of the acute care settings patients had evidence of homelessness, among which 51.1% age <45 years, 66.4% males, and 24% non-Hispanic Black. Patients experiencing homelessness had higher emergency department utilization and lower utilization of outpatient and urgent care services. Mental health conditions were more common among patients experiencing homelessness. More than half of the hospitals had >5% of patients who identified as homeless. Some hospitals with higher proportions of patients experiencing homelessness are not located near many shelter resources. By understanding patients who self-identify as homeless, it is possible to assess the role of the health system in addressing their unmet needs. Accurate identification is the first step for the health systems to develop and deliver better solutions through collaborations with nonprofit organizations, community partners, and government agencies.

Objective: To determine whether inequities in COVID-19 infection and hospitalization differ from those for common medical conditions: influenza, appendicitis, and all-cause hospitalization., Design: Retrospective study based on electronic health records of three healthcare systems in San Francisco (university, public, and community) examining (1) racial/ethnic distribution in cases and hospitalization among patients with diagnosed COVID-19 (March-August 2020) and patients with diagnosed influenza, diagnosed appendicitis, or all-cause hospitalization (August 2017-March 2020), and (2) sociodemographic predictors of hospitalization among those with diagnosed COVID-19 and influenza., Results: Patients 18 years or older with diagnosed COVID-19 ( N  = 3934), diagnosed influenza ( N  = 5932), diagnosed appendicitis ( N  = 1235), or all-cause hospitalization ( N  = 62,707) were included in the study. The age-adjusted racial/ethnic distribution of patients with diagnosed COVID-19 differed from that of patients with diagnosed influenza or appendicitis for all healthcare systems, as did hospitalization from these conditions compared to any cause. For example, in the public healthcare system, 68% of patients with diagnosed COVID-19 were Latine, compared with 43% of patients with diagnosed influenza, and 48% of patients with diagnosed appendicitis ( p  < 0.05). In multivariable logistic regressions, COVID-19 hospitalizations were associated with male sex, Asian and Pacific Islander race/ethnicity, Spanish language, and public insurance in the university healthcare system, and Latine race/ethnicity and obesity in the community healthcare system. Influenza hospitalizations were associated with Asian and Pacific Islander and other race/ethnicity in the university healthcare system, obesity in the community healthcare system, and Chinese language and public insurance in both the university and community healthcare systems., Conclusions: Racial/ethnic and sociodemographic inequities in diagnosed COVID-19 and hospitalization differed from those for diagnosed influenza and other medical conditions, with consistently higher odds among Latine and Spanish-speaking patients. This work highlights the need for disease-specific public health efforts in at-risk communities in addition to structural upstream interventions.

Objective: Evaluations of lifestyle modification interventions (LMIs), modeled after the Diabetes Prevention Program, have repeatedly shown a dose-response relationship between session attendance and weight loss. Despite this, not all participants had "average" weight loss experiences. Nearly one-third of LMI participants experienced unexpected, paradoxical outcomes (i.e., high attendance with little weight loss, and low attendance with clinically significant weight loss). Paradoxical weight-loss outcomes were characterized based on session attendance among participants in a group-based LMI in a real-world healthcare setting. This group-based LMI was delivered over 1 year to participants with the possibility of attending up to 25 sessions total., Methods: LMI participants identified in 2010-2017 from electronic health records were characterized as having low (<75%) or high (≥75%) session attendance. Weight-loss outcomes were defined as expected (≥5%, high-attendance; <5%, low-attendance) or paradoxical (≥5%, low-attendance; <5%, high-attendance). Paradoxical-outcome-associated characteristics were identified using logistic regression., Results: Among 1813 LMI participants, 1498 (82.6%) had low and 315 (17.4%) high session attendance; 555 (30.6%) had paradoxical outcomes, comprising 415 (74.8%) responders (≥5% weight-loss) and 140 (25.2%) non-responders (<5% weight-loss). Among participants with high session attendance, paradoxical non-responders were more likely to be female (odds ratio [OR]: 2.76; 95% confidence interval [CI]: 1.32, 5.77) and have type 2 diabetes (OR: 3.32; 95% CI: 1.01, 10.95). Among low-attendance participants, paradoxical responders were more likely to be non-Hispanic White and less likely to be non-Hispanic Black (OR: 0.35; 95% CI: 0.18, 0.69), non-Hispanic Asian (OR: 0.40; 95% CI: 0.22, 0.73), or Hispanic (OR: 0.53; 95% CI: 0.35, 0.80)., Conclusions: In a healthcare setting, nearly one-third of LMI participants experienced paradoxical outcomes. More research is needed to understand the facilitators and barriers to weight loss above and beyond session attendance., Competing Interests: The authors declare no conflicts of interest., (© 2023 The Authors. Obesity Science & Practice published by World Obesity and The Obesity Society and John Wiley & Sons Ltd.)

Arterial blood oxygen saturation as measured by pulse oximetry (peripheral oxygen saturation (SpO2)) may be differentially less accurate for people with darker skin pigmentation, which could potentially affect the course of coronavirus disease 2019 (COVID-19) treatment. We analyzed pulse oximeter accuracy and its association with COVID-19 treatment outcomes using electronic health record data from Sutter Health, a large, mixed-payer, integrated health-care delivery system in Northern California. We analyzed 2 cohorts: 1) 43,753 non-Hispanic White (NHW) or non-Hispanic Black/African-American (NHB) adults with concurrent arterial blood gas oxygen saturation/SpO2 measurements taken between January 2020 and February 2021; and 2) 8,735 adults who went to a hospital emergency department with COVID-19 between July 2020 and February 2021. Pulse oximetry systematically overestimated blood oxygenation by 1% more in NHB individuals than in NHW individuals. For people with COVID-19, this was associated with lower admission probability (-3.1 percentage points), dexamethasone treatment (-3.1 percentage points), and supplemental oxygen treatment (-4.5 percentage points), as well as increased time to treatment: 37.2 minutes before dexamethasone initiation and 278.5 minutes before initiation of supplemental oxygen. These results call for additional investigation of pulse oximeters and suggest that current guidelines for development, testing, and calibration of these devices should be revisited, investigated, and revised., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Participant engagement in structured lifestyle change programs (LCPs) is essential for adopting behaviors that promote weight loss; however, the challenges to, and facilitators that promote, engagement with such programs are not well understood. We conducted a mixed-methods study among real-world LCP participants to assess factors associated with program engagement and to examine the reasons for withdrawal. Using electronic health records (EHR), we identified LCP eligible participants between 2010 and 2017. Multivariable logistic regression was used to assess associations between program engagement and baseline characteristics. Semi-structured interviews with LCP participants were conducted and thematically analyzed to examine reasons for withdrawal. A total of 1,813 LCP participants were included. The median number of sessions attended was 10 of 21-25 sessions. Highest LCP engagement was associated with factors potentially related to self-efficacy/motivation, such as older age, higher baseline weight, prior healthcare utilization and an absence of a history of smoking or depression. Engagement was also negatively associated with being Non-Hispanic Black versus White. The qualitative analysis of the interviews revealed four general themes pertaining to participants' withdrawal: competing priorities, perceived program effectiveness, characteristics of the program, and facilitator-related factors. Taken together, results from this mixed-methods study suggest that motivation and self-efficacy are important for program engagement; future LCP enhancements should incorporate flexible formats that may help participants manage competing priorities and maximize personal and cultural relevance for all racial/ethnic groups, especially those who have not benefitted fully. Furthermore, participants should be encouraged to set realistic goals to manage expectations., (© Society of Behavioral Medicine 2023. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: Over the past decade, numerous efforts have encouraged the realization of the learning health system (LHS) in the United States. Despite these efforts, and promising aims of the LHS, the full potential and value of research conducted within LHSs have yet to be realized. New technology coupled with a catalyzing global pandemic have spurred momentum. In addition, the LHS has lacked a consistent framework within which "best evidence" can be identified. Positive deviance analysis, itself reinvigorated by recent advances in health information technology (IT) and ubiquitous adoption of electronic health records (EHRs), may finally provide a framework through which LHSs can be operationalized and optimized., Methods: We describe the synergy between positive deviance and the LHS and how they may be integrated to achieve a continuous cycle of health system improvement., Results: As we describe below, the positive deviance approach focuses on learning from high-performing teams and organizations., Conclusion: Such learning can be enabled by EHRs and health IT, providing a lens into how digital clinical interventions are successfully developed and deployed., Competing Interests: This work was not supported by grant funding. The authors report the following disclosures. Kristen Azar has received funding from the National Institute of Health (NIH), Janssen Scientific Affairs, and the Patient‐Centered Outcomes Research Institute (PCORI) Mark J. Pletcher has received research grants from the PCORI. Alice R. Pressman has received funding from the NIH. All the other authors declare that they have no conflicts of interest., (© 2022 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.)

Background: It is increasingly recognized that policies have played a role in both alleviating and exacerbating the health and economic consequences of the COVID-19 pandemic. There has been limited systematic evaluation of variation in U.S. local COVID-19-related policies. This study introduces the U.S. COVID-19 County Policy (UCCP) Database, whose objective is to systematically gather, characterize, and assess variation in U.S. county-level COVID-19-related policies., Methods: In January-March 2021, we collected an initial wave of cross-sectional data from government and media websites for 171 counties in 7 states on 22 county-level COVID-19-related policies within 3 policy domains that are likely to affect health: (1) containment/closure, (2) economic support, and (3) public health. We characterized the presence and comprehensiveness of policies using univariate analyses. We also examined the correlation of policies with one another using bivariate Spearman's correlations. Finally, we examined geographical variation in policies across and within states., Results: There was substantial variation in the presence and comprehensiveness of county policies during January-March 2021. For containment and closure policies, the percent of counties with no restrictions ranged from 0% (for public events) to more than half for public transportation (67.8%), hair salons (52.6%), and religious gatherings (52.0%). For economic policies, 76.6% of counties had housing support, while 64.9% had utility relief. For public health policies, most were comprehensive, with 70.8% of counties having coordinated public information campaigns, and 66.7% requiring masks outside the home at all times. Correlations between containment and closure policies tended to be positive and moderate (i.e., coefficients 0.4-0.59). There was variation within and across states in the number and comprehensiveness of policies., Conclusions: This study introduces the UCCP Database, presenting granular data on local governments' responses to the COVID-19 pandemic. We documented substantial variation within and across states on a wide range of policies at a single point in time. By making these data publicly available, this study supports future research that can leverage this database to examine how policies contributed to and continue to influence pandemic-related health and socioeconomic outcomes and disparities. The UCCP database is available online and will include additional time points for 2020-2021 and additional counties nationwide., (© 2022. The Author(s).)

Introduction: Latino men have been drastically under-represented in research to identify effective behavioral weight-loss interventions. This trial compared 2 interventions for weight loss: (1) a culturally adapted intervention (HOMBRE) and (2) a minimal-intensity intervention., Study Design: Randomized controlled trial., Setting/participants: Latino men with a BMI ≥27 kg/m 2 and 1 or more cardiometabolic risk factors (N=424) were recruited (February 15, 2017‒October 2, 2018) from 14 medical centers and randomized to receive 1 of the 2 interventions., Intervention: HOMBRE provided men a choice among 3 options: coach-facilitated group sessions using online video conferencing, coach-facilitated group sessions in person, and prerecorded videos of group sessions available online., Main Outcome Measures: The primary outcome was the proportion of participants sustaining clinically significant (≥5% of baseline) weight loss at 18 months. Secondary outcomes included weight loss trajectory over time, 3% and 10% weight loss, cardiometabolic risk factors, health behaviors, and psychosocial well-being at baseline and 18 months. Data were analyzed from October 6, 2020 to January 15, 2022., Results: Participants were predominantly middle aged (47.0 [SD=11.9] years), were married (74.3%), were with at least some college experience (79.7%), and had middle to upper incomes (72.4% with annual family incomes >$75,000). Their average BMI was 33.1 kg/m 2 (SD=5.1). The proportion achieving clinically significant weight loss at 18 months was 27.4% in the HOMBRE intervention and 20.6% in the minimal-intensity intervention (mean difference=7.2%, 95% CI= -1.8, 17.0; p=0.13). Mean difference between the HOMBRE vs the minimal-intensity group was ‒1.25 kg at 6 months (95% CI= -2.28, -0.21; p=0.02) and ‒1.11 kg at 12 months (95% CI= -2.11, -0.10; p=0.03) using weight measurement data abstracted from the Electronic Health Record and by self report. There were no significant differences in secondary outcomes., Conclusions: Among Latino men with overweight and obesity, HOMBRE was not more effective for clinically significant weight loss than a minimal-intensity intervention at 18 months., (Copyright © 2022 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: There is increased recognition in clinical settings of the importance of documenting, understanding, and addressing patients' social determinants of health (SDOH) to improve health and address health inequities. This study evaluated a pilot of a standardized SDOH screening questionnaire and workflow in an ambulatory clinic within a large integrated health network in Northern California., Methods: The pilot screened for SDOH needs using an 11-question Epic-compatible paper questionnaire assessing eight SDOH and health behavior domains: financial resource, transportation, stress, depression, intimate partner violence, social connections, physical activity, and alcohol consumption. Eligible patients for the pilot receiving a Medicare wellness, adult annual, or new patient visits during a five-week period (February-March, 2020), and a comparison group from the same time period in 2019 were identified. Sociodemographic data (age, sex, race/ethnicity, and payment type), visit type, length of visit, and responses to SDOH questions were extracted from electronic health records, and a staff experience survey was administered. The evaluation was guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework., Results: Two-hundred eighty-nine patients were eligible for SDOH screening. Responsiveness by domain ranged from 55 to 67%, except for depression. Half of patients had at least one identified social need, the most common being stress (33%), physical activity (22%), alcohol (12%), and social connections (6%). Physical activity needs were identified more in females (81% vs. 19% in males, p < .01) and at new patient/transfer visits (48% vs. 13% at Medicare wellness and 38% at adult wellness visits, p < .05). Average length of visit was 39.8 min, which was 1.7 min longer than that in 2019. Visit lengths were longer among patients 65+ (43.4 min) and patients having public insurance (43.6 min). Most staff agreed that collecting SDOH data was relevant and accepted the SDOH questionnaire and workflow but highlighted opportunities for improvement in training and connecting patients to resources., Conclusion: Use of evidence-based SDOH screening questions and associated workflow was effective in gathering patient SDOH information and identifying social needs in an ambulatory setting. Future studies should use qualitative data to understand patient and staff experiences with collecting SDOH information in healthcare settings., (© 2021. The Author(s).)

Devastating disparities in COVID-19 infection and outcomes among socioeconomically marginalized groups have resulted in a public outcry to address longstanding societal inequities that have contributed to the present situation. Nurse leaders have an opportunity and an obligation in this moment to lend their skills as scientists, innovators, advocates, and educators to lead in these efforts, advancing health equity for all., (2021 by Elsevier Inc.)

To measure disparities in coronavirus disease 2019 (COVID-19) hospitalization and intensive care unit (ICU) transfer among racially/ethnically marginalized groups before and after implementation of the California statewide shelter-in-place (SIP) policy, we conducted a retrospective cohort study within a health-care system in California. COVID-19 patients diagnosed from January 1, 2020, to August 31, 2020, were identified from electronic health records. We examined hospitalizations and ICU transfers by race/ethnicity and pandemic period using logistic regression. Among 16,520 people with COVID-19 (mean age = 46.6 (standard deviation, 18.4) years; 54.2% women), during the post-SIP period, patients were on average younger and a larger proportion were Hispanic. In adjusted models, odds of hospitalization were 20% lower post-SIP as compared with the SIP period, yet all non-White groups had higher odds (odds ratios = 1.6-2.1) than non-Hispanic White individuals, regardless of period. Among hospitalized patients, odds of ICU transfer were 33% lower post-SIP than during SIP. Hispanic and Asian patients had higher odds than non-Hispanics. Disparities in hospitalization persisted and ICU risk became more pronounced for Asian and Hispanic patients post-SIP. Policy-makers should consider ways to proactively address racial/ethnic inequities in risk when considering future population-level policy interventions for public health crises., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The objective of this study was to assess the relationship between public protests and county-level, novel coronavirus disease (COVID-19) hospitalization rates across California. Publicly available data were included in the analysis from 55 of 58 California state counties (29 March-14 October 2020). Mixed-effects negative binomial regression models were used to examine the relationship between daily county-level COVID-19 hospitalizations and two main exposure variables: any vs. no protests and 1 or >1 protest vs. no protests on a given county-day. COVID-19 hospitalizations were used as a proxy for viral transmission since such rates are less sensitive to temporal changes in testing access/availability. Models included covariates for daily county mobility, county-level characteristics, and time trends. Models also included a county-population offset and a two-week lag for the association between exposure and outcome. No significant associations were observed between protest exposures and COVID-19 hospitalization rates among the 55 counties. We did not find evidence to suggest that public protests were associated with COVID-19 hospitalization within California counties. These findings support the notion that protesting during a pandemic may be safe, ostensibly, so long as evidence-based precautionary measures are taken.

Purpose: The coronavirus pandemic has created the greatest public health crisis in a century, causing >500,000 deaths in the United States alone. Minoritized and socioeconomically disadvantaged groups have borne a disproportionate burden of severe illness, hospitalization, and death from COVID-19. Recently developed FDA-approved vaccines have been shown to significantly reduce severe COVID-19-related outcomes. Vaccination campaigns have the potential to advance health equity by prioritizing allocation to those at highest risk while striving for herd immunity. Large integrated health systems have been faced with the daunting task of meeting the rapidly evolving needs of diverse patient populations for the provision of population-based testing, treatment, education, and now vaccine distribution. We have designed a COVID-19 vaccine equity index (CVEI) to guide health system vaccination strategy. Methods: We considered proportion unvaccinated within a health care system. We then used real-time readily available electronic health record (EHR) COVID-19 testing positivity and proportion hospitalized to measure burden of illness by race/ethnicity. We used conditional probability and statistical theory to measure equity for unvaccinated individuals and to derive an index to highlight these inequities for specific subgroups. Results: We present an illustrative hypothetical example using simulated data for which we calculated the CVEI for non-Hispanic White, non-Hispanic Black, non-Hispanic Asian, and Hispanic patients. In the example, non-Hispanic Black and Hispanic patients had inequitable outcomes. Conclusion: The index can be widely implemented to promote more equitable outcomes among racial/ethnic groups, reducing morbidity and mortality within the overall population as we pursue the collective goal of herd immunity through mass vaccination., Competing Interests: No competing financial interests exist., (© Alice R. Pressman et al., 2021; Published by Mary Ann Liebert, Inc.)

Centers for Disease Control and Prevention aligned lifestyle change programs are effective in promoting weight loss among those with elevated cardiometabolic risk; yet, variability in weight outcomes among participants is high. Little is known about heterogeneity of short-term weight changes among participants in real-world clinical practice. We sought to identify short-term weight trajectory clusters among lifestyle change program participants in real-world clinical practice and to examine the relationship between cluster membership and long-term weight outcomes. We identified participants from the electronic health records (2010-2017) with weight measured ≤30 days prior to program initiation (baseline) and in four intervals (3-week segments) in the 12 weeks after baseline. Clustering analysis was performed to identify distinct trajectories in percent weight change over 12 weeks. Cluster-specific differences in weight change at 12 and 52 weeks were assessed. Among 1,148 participants, across 18 clinic sites, three clusters were identified: minimal-to-no weight loss (MWL), delayed-minimal weight loss (DWL), and steady-moderate weight loss (SWL), corresponding to mean weight changes of 0.4%, -2.3%, and -4.8% at 12 weeks follow-up, respectively. Mean weight changes were 0.4%, -1.8%, and -5.1% for MWL, DWL, and SWL clusters, respectively, at 52 weeks follow-up, which correlated in direction and magnitude with short-term weight changes. Clustering analysis reveals heterogeneous, short-term weight trajectories among lifestyle change program participants in real-world clinical practice. Given the relationship between the magnitudes of short- and long-term weight change, individual participant weight trajectories may be useful in identifying potential non-responders in need of adjunctive or alternative therapy., (© Society of Behavioral Medicine 2019. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Frequent emergency department (ED) utilization is an indicator of unmet health and social needs, especially among patients with mental and physical health problems. The authors aimed to characterize frequent ED utilizers and drivers of multiple ED use, including presence of serious mental illness (SMI), across 2 large health care systems in Northern California. Using electronic health records and a data-sharing platform, a cross-sectional analysis was conducted of patients aged 18+ years with ≥10 ED visits in 2016. Logistic regression was used to determine factors associated with multiple ED use versus single ED use. Among the 8036 patients who met inclusion criteria, the mean age was 55.9 years (95% CI = 55.5-56.4), 53% were female, 54% were non-Hispanic white, and 38% had any SMI. Overall, 51% of patients were single ED utilizers. Patients ages ≥65 years were less likely to use multiple EDs compared to younger patients (ages 18-23) (OR = 0.3, 95% CI = 0.2-0.4). African Americans exhibited more than 3 times the likelihood of multi-ED use compared to non-Hispanic whites (OR = 3.8, 95% CI = 3.3-4.3). A diagnosis of any SMI (OR = 2.3 [95% CI: 2.1-2.6]), major depressive disorder (OR = 1.3, 95% CI = 1.1-1.4), schizophrenia (OR = 2.1, 95% CI = 1.6-2.6), or suicidal attempts/ideation (OR = 2.7, 95% CI = 2.1-3.6) was significantly associated with increased likelihood of multi-ED use. Findings indicate heterogeneity in regional utilization patterns among frequent ED utilizers, with mental illness increasing the likelihood of multi-ED use.

Introduction: Translational lifestyle change programs for community and clinical settings have been available for a decade, yet there are limited data on their comparative effectiveness. This study examines the effectiveness of a Centers for Disease Control and Prevention-aligned lifestyle change program relative to usual care in clinical practice., Methods: This was an electronic health record-based retrospective cohort study conducted in a community-based healthcare system. Investigators identified adult program participants and usual-care patients in the electronic health record between 2010 and 2018 and defined their index date (baseline) as the first lifestyle change program encounter or a random encounter date, respectively. Participants were matched 1:2 to usual-care patients on baseline demographics and clinical characteristics using propensity-score methods. Changes in body weight and blood pressure were examined from baseline through 24 months., Results: The authors identified 2,833 program participants and 438,432 usual-care patients meeting study eligibility criteria. A total of 2,833 program participants were matched to 4,776 usual-care patients; the average age was 54 years, and 80% of the participants were female. Program participation was associated with a 1.9- and 1.6-fold higher prevalence of clinically meaningful (≥5%) weight loss at 12- and 24-month follow-up than usual care and a higher prevalence of blood pressure control at 12 months but not at 24 months. Patients without type 2 diabetes at baseline had more pronounced outcomes than those with type 2 diabetes., Conclusions: This study demonstrates the effectiveness of an evidence-based, Centers for Disease Control and Prevention-aligned lifestyle change program in reducing cardiometabolic risk factors compared with usual care in clinical practice, with long-term reductions in weight and transient reductions in blood pressure., (Copyright © 2020 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

As the novel coronavirus disease (COVID-19) pandemic spreads throughout the United States, evidence is mounting that racial and ethnic minorities and socioeconomically disadvantaged groups are bearing a disproportionate burden of illness and death. We conducted a retrospective cohort analysis of COVID-19 patients at Sutter Health, a large integrated health system in northern California, to measure potential disparities. We used Sutter's integrated electronic health record to identify adults with suspected and confirmed COVID-19, and we used multivariable logistic regression to assess risk of hospitalization, adjusting for known risk factors, such as race/ethnicity, sex, age, health, and socioeconomic variables. We analyzed 1,052 confirmed cases of COVID-19 from the period January 1-April 8, 2020. Among our findings, we observed that compared with non-Hispanic white patients, non-Hispanic African American patients had 2.7 times the odds of hospitalization, after adjustment for age, sex, comorbidities, and income. We explore possible explanations for this, including societal factors that either result in barriers to timely access to care or create circumstances in which patients view delaying care as the most sensible option. Our study provides real-world evidence of racial and ethnic disparities in the presentation of COVID-19.

Background: Group-based lifestyle change programs based on the Diabetes Prevention Program (DPP) are associated with clinically significant weight loss and decreases in cardiometabolic risk factors. However, these benefits depend on successful real-world implementation. Studies have examined implementation in community settings, but less is known about integration in healthcare systems, and particularly in large, multi-site systems with the potential for extended reach., Objective: To examine the barriers and facilitators to successful DPP implementation in a large multi-site healthcare system., Design: Semi-structured interviews, based on the RE-AIM framework, were conducted in person for 30-90 min each., Participants: Past and present DPP lifestyle coaches in the healthcare system identified using purposive sampling., Approach: Thematic analysis of qualitative data to identify key factors influencing the success of DPP implementation. An iterative consensus process was used to model the relationships among factors., Key Results: We conducted 33 interviews across 20 clinic sites serving 12 counties. Participants described six key factors as potential barriers or facilitators to implementation, including (1) Broader Context, including the surrounding physical and sociodemographic context; (2) Institutional Context, including finances, infrastructure, and personnel; (3) Program Provision, including curriculum, administration, cost, goals, and visibility; (4) Recruitment Process, including screening and referrals; (5) Lifestyle Coaches, including their characteristics, behaviors, and morale; and (6) Cohort, including group attrition/retention and interpersonal dynamics. These factors were both highly interconnected in their impact on implementation and widely variable across sites within the healthcare system, as illustrated in our multi-level conceptual framework., Conclusions: This study identified key factors that could serve as barriers or facilitators in the implementation of DPP in large healthcare systems, from the perspective of lifestyle coaches. With further examination, the conceptual model presented here may be used for planning and managing the implementation of group-based behavioral interventions in these settings.

Background: A better understanding of patterns in statin utilization and low-density lipoprotein cholesterol (LDL-C) among patients with atherosclerotic cardiovascular disease (ASCVD) in a clinical practice setting is needed., Objectives: The objective of this study was to examine statin utilization and LDL-C among new statin users with ASCVD., Methods: This retrospective study used an electronic health record database from a community-based health care system. We identified ASCVD patients ≥21 years of age with a new statin prescription during the study period (2002-2016). Outcomes included high-intensity statin therapy (HIST) prescribing at treatment initiation, medication adherence (defined as proportion of days covered ≥0.80), statin therapy titrations rates, and changes in LDL-C during follow-up., Results: Among 6199 eligible patients, mean follow-up was 16.8 months. At treatment initiation, 16.6% of patients received HIST. Approximately 53% of patients were adherent to statin regimens. Mean percent reduction in LDL-c was 25% during follow-up; 18% of patients, overall, and 30% of those initiating on HIST attained LDL-C reductions >50%. Rates of statin intensity-level increases were 8.4 per 100 person-years. HIST prescribing increased over time, beginning after generic atorvastatin availability and preceded treatment guidelines by two years. Initiation on HIST, higher adherence, and treatment intensification during follow-up were independent predictors of attaining LDL-C goals of <70 mg/dL or <100 mg/dL., Conclusions: In a community-based health care system, modest LDL-C lowering for secondary ASCVD prevention is likely driven by suboptimal adherence and low HIST prescribing and treatment intensification rates. Clinician and patient education are needed to reduce clinical inertia and improve medication adherence to better manage ASCVD., (Copyright © 2020 National Lipid Association. Published by Elsevier Inc. All rights reserved.)

Introduction: The RAINBOW randomized clinical trial validated the efficacy of an integrated collaborative care intervention for obesity and depression in primary care, although the effect was modest. To inform intervention optimization, this study investigated within-treatment variability in participant engagement and progress., Methods: Data were collected in 2014-2017 and analyzed post hoc in 2018. Cluster analysis evaluated patterns of change in weekly self-monitored weight from week 6 up to week 52 and depression scores on the Patient Health Questionnaire-9 (PHQ-9) from up to 15 individual sessions during the 12-month intervention. Chi-square tests and ANOVA compared weight loss and depression outcomes objectively measured by blinded assessors to validate differences among categories of treatment engagement and progress defined based on cluster analysis results., Results: Among 204 intervention participants (50.9 [SD, 12.2] years, 71% female, 72% non-Hispanic White, BMI 36.7 [6.9], PHQ-9 14.1 [3.2]), 31% (n = 63) had poor engagement, on average completing self-monitored weight in <3 of 46 weeks and <5 of 15 sessions. Among them, 50 (79%) discontinued the intervention by session 6 (week 8). Engaged participants (n = 141; 69%) self-monitored weight for 11-22 weeks, attended almost all 15 sessions, but showed variable treatment progress based on patterns of change in self-monitored weight and PHQ-9 scores over 12 months. Three patterns of weight change (%) represented minimal weight loss (n = 50, linear β1 = -0.06, quadratic β2 = 0.001), moderate weight loss (n = 61, β1 = -0.28, β2 = 0.002), and substantial weight loss (n = 12, β1 = -0.53, β2 = 0.005). Three patterns of change in PHQ-9 scores represented moderate depression without treatment progress (n = 40, intercept β0 = 11.05, β1 = -0.11, β2 = 0.002), moderate depression with treatment progress (n = 20, β0 = 12.90, β1 = -0.42, β2 = 0.006), and milder depression with treatment progress (n = 81, β0 = 7.41, β1 = -0.23, β2 = 0.003). The patterns diverged within 6-8 weeks and persisted throughout the intervention. Objectively measured weight loss and depression outcomes were significantly worse among participants with poor engagement or poor progress on either weight or PHQ-9 than those showing progress on both., Conclusions: Participants demonstrating poor engagement or poor progress could be identified early during the intervention and were more likely to fail treatment at the end of the intervention. This insight could inform individualized and timely optimization to enhance treatment efficacy., Trial Registration: ClinicalTrials.gov# NCT02246413., Competing Interests: The authors declare that no competing interests existed for the research as reported. Dr. Lenard Lesser’s affiliation with 1Life Healthcare/One Medical constituted no competing interests. Dr. Lesser had originally supported on the NIH grant for his role as a study physician on this study while he was an employee at the Palo Alto Medical Foundation Research Institute (PAMFRI) where the study was conducted. Starting from 07/2016 till 10/2017, Dr. Lesser transitioned from PAMFRI to 1Life Healthcare, Inc/One Medical. At that time, his continuous involvement in the study was compensated through a research contract as an independent consultant with PAMFRI specifically for the NIH grant supporting the study. 1Life Healthcare/One Medical provided no support of any form for the study; and had no role in the study design, data collection/analysis, decision to publish, or preparation of the manuscript. This does not alter our adherence to PLOS ONE policies on sharing data and materials.”

Introduction: An integrated collaborative care intervention was successful for treating comorbid obesity and depression. The effect of the integrated intervention on secondary outcomes of quality of life and psychosocial functioning were examined, as well as whether improvements in these secondary outcomes were correlated with improvements in the primary outcomes of weight and depressive symptoms., Study Design: This RCT compared an integrated collaborative care intervention for obesity and depression to usual care. Data were analyzed in 2018., Setting/participants: Adult primary care patients (n=409) with a BMI ≥30 (≥27 if Asian) and 9-Item Patient Health Questionnaire score ≥10 were recruited from September 30, 2014 to January 12, 2017 from primary care clinics in Northern California., Intervention: The 12-month intervention integrated a behavioral weight loss program and problem-solving therapy with as-needed antidepressant medications for depression., Main Outcome Measures: A priori secondary outcomes included health-related quality of life (Short Form-8 Health Survey), obesity-specific quality of life (Obesity-Related Problems Scale), sleep disturbance and sleep-related impairment (Patient-Reported Outcomes Measurement Information System), and functional disability (Sheehan Disability Scale) at baseline and 6 and 12 months., Results: Participants randomized to the intervention experienced significantly greater improvements in obesity-specific problems, mental health-related quality of life, sleep disturbance, sleep-related impairment, and functional disability at 6 months but not 12 months. Improvements in obesity-related problems (β=0.01, 95% CI=0.01, 0.02) and sleep disturbance (β= -0.02, 95% CI= -0.04, 0) were associated with lower BMI. Improvements in the physical (β= -0.01, 95% CI= -0.01, 0) and mental health components (β= -0.02, 95% CI= -0.03, -0.02) of the Short Form-8 Health Survey as well as sleep disturbance (β=0.01, 95% CI=0.01, 0.02) and sleep-related impairment (β=0.01, 95% CI=0, 0.01) were associated with fewer depressive symptoms., Conclusions: An integrated collaborative care intervention for obesity and depression that was shown previously to improve weight and depressive symptoms may also confer benefits for quality of life and psychosocial functioning over 6 months., Trial Registration: This study is registered at clinicaltrials.gov NCT02246413., (Copyright © 2019 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.)

Background: Today, approximately one in five United States adolescents age 12 to 19 years is obese and just over a third are either overweight or obese. This study examines how parents and peers influence diet and physical activity behaviors of older adolescents (14-18 years) with overweight or obesity to inform weight management interventions., Methods: Adolescent participants included 14 to 18-year-olds with a Body Mass Index (BMI) greater than the 85th percentile for their age and sex who were receiving care in a large healthcare system in Northern California. Adolescents and their parents participated in separate focus groups and interviews (if not able to attend focus groups) that were held at the same time in the same location. We used qualitative thematic analysis to identify common themes discussed in the adolescent and parent focus groups as well as paired analysis of adolescent-parent dyads., Results: Participants included 26 adolescents and 27 parents. Adolescent participants were 14 to 18 years old. Half were female and the participants were almost evenly distributed across year in school. The majority self-identified as White (56%) and Asian (36%).Three themes were identified which included 1) parents overestimated how supportive they were compared to adolescents' perception 2) parents and adolescents had different views regarding parental influence on adolescent diet and physical activity behaviors 3) parents and adolescents held similar views on peers' influential role on lifestyle behaviors., Conclusion: Parents' and adolescents' differing views suggest that alignment of parent and adolescent expectations and behaviors for supporting effective weight management could be incorporated into interventions.

Background: Group-based Diabetes Prevention Programs (DPP), aligned with recommendations from the Centers for Disease Control and Prevention, promote clinically significant weight loss and reduce cardio-metabolic risks. Studies have examined implementation of the DPP in community settings, but less is known about its integration in healthcare systems. In 2010, a group-based DPP known as the Group Lifestyle Balance (GLB) was implemented within a large healthcare delivery system in Northern California, across three geographically distinct regional administration divisions of the organization within 12 state counties, with varying underlying socio-demographics. The regional divisions implemented the program independently, allowing for natural variation in its real-world integration. We leveraged this natural experiment to qualitatively assess the implementation of a DPP in this healthcare system and, especially, its fidelity to the original GLB curriculum and potential heterogeneity in implementation across clinics and regional divisions., Methods: Using purposive sampling, we conducted semi-structured interviews with DPP lifestyle coaches. Data were analyzed using mixed-method techniques, guided by an implementation outcomes framework consisting of eight constructs: acceptability, adoption, appropriateness, cost, feasibility, fidelity, penetration, and sustainability., Results: We conducted 33 interviews at 20 clinics across the three regional administrative divisions. Consistencies in implementation of the program were found across regions in terms of satisfaction with the evidence base (acceptability), referral methods (adoption), eligibility criteria (fidelity), and strategies to increase retention and effectiveness (sustainability). Heterogeneity in implementation across regions were found in all categories, including: the number and frequency of sessions (fidelity); program branding (adoption); lifestyle coach training (adoption), and patient-facing cost (cost). Lifestyle coaches expressed differing attitudes about curriculum content (acceptability) and suitability of educational level (appropriateness). While difficulties with recruitment were common across regions (feasibility), strategies used to address these challenges differed (sustainability)., Conclusions: Variation exists in the implementation of the DPP within a large multi-site healthcare system, revealing a dynamic and important tension between retaining fidelity to the original program and tailoring the program to meet the local needs. Moreover, certain challenges across sites may represent opportunities for considering alternative implementation to anticipate these barriers. Further research is needed to explore how differences in implementation domains impact program effectiveness.

Purpose: The purpose of this electronic health record (EHR)-based retrospective cohort study was to characterize a population of patients participating in a 12-month, lifestyle change program in a community-based health system and to examine longitudinal weight outcomes., Methods: Program participants were identified in the EHRs of a health care delivery system across 18 sites between 2010 and 2017. Outcomes were mean weight change and proportion of patients with ≥5% weight loss through 24 months from program initiation., Results: Among 4463 program participants, 3156 met study eligibility criteria, with a mean ± SD age of 53.5 ± 13.1 years; 77.7% were women. Mean baseline weight ± SD was 101.3 ± 23.8 kg. Three main cardiometabolic risk groups were identified: prediabetes/high risk for diabetes (47.3%), overweight/obese in the absence of elevated diabetes risk (27.2%), and existing diabetes (23.9%). Maximal mean weight loss was 3.9% at 6 months from baseline. At 12 and 24 months from baseline, mean weight loss was 3.2% and 2.3%, respectively, with 31% and 29% of participants attaining ≥5% weight loss. Long-term weight outcomes were similar across risk groups., Conclusions: A lifestyle change program in a clinical practice setting is associated with modest weight loss, sustained through 24 months, among participants with a range of cardiometabolic risk factors. More than one-quarter of participants achieve ≥5% weight loss, regardless of cardiometabolic risk.

Disparities in outcomes for preventive and primary health care services often result when vulnerable patients rely on episodic encounters for emergency services that do not meet their long-term health needs. Understanding health outcomes in socially or economically disadvantaged subgroups is crucial to improving community health, and it requires innovative analytics and dynamic application of clinical and population data. While it is common practice to use proxy indicators, such as quality of life and mortality, when discussing health equity, these have shown limited utility and are rarely applied at a population-level within a health system. Therefore, we designed and implemented an index, calculated as the ratio of observed-to-expected encounters, to identify and quantify health inequalities in health care systems. Providing equitable care, as measured by health outcomes, is analogous to precision medicine applied to social determinants. For health systems, the use of this index will facilitate the development of specially-tailored interventions to address inequity and provides a tool to measure the impact of such programs., Competing Interests: No competing financial interests exist.

Latino men bear a disproportionate burden of obesity, diabetes, and cardiovascular disease.However, limited behavioral lifestyle intervention research has focused on Latino men. This trial compares two approaches to weight loss for overweight and obese Latino men: 1) HOMBRE is a culturally adapted intervention that provides individual choice of either self-directed online videos, coach-facilitated in-person groups, and coach-facilitated online groups; and 2) a minimal intensity intervention that uses online videos with a coach available, if solicited by the participant.Latino men with a Body Mass Index (BMI) of ≥27 kg/m 2 and one or more cardiometabolic risk factors (n = 424) will be randomly assigned to receive one of the two approaches.The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework guides the planned evaluations.The primary aim is to determine the effectiveness of the HOMBRE intervention (the "E" in RE-AIM) on clinically significant weight loss (≥5% of baseline weight) at 18 months. We hypothesize that a significantly higher proportion of HOMBRE participants will maintain ≥5% of weight loss compared with those in the minimal intensity intervention.Secondary aims are to determine the effectiveness of HOMBRE on cardiometabolic risk factors (e.g., blood pressure, waist circumference), health behaviors (e.g., diet and physical activity), and psychosocial well-being (e.g., quality of life and depressive symptoms) and to evaluate the other attributes of RE-AIM. These findings have real word applicability with value to clinicians, patients, and other decision makers considering effective diabetes prevention programs for Latino men in primary care., (Copyright © 2018. Published by Elsevier Inc.)

Research is rapidly extending its focus to develop and evaluate weight management interventions that incorporate eHealth technologies. Comparative effectiveness of eHealth interventions is partly limited by the extensive heterogeneity in intervention design, variation in use of eHealth tools, and expanding development of novel tools to promote weight management. We closely examined, characterized, and categorized the use and function of eHealth tools across a wide range of eHealth interventions for weight management in order to first create a novel schematic framework for eHealth interventions and, second, to evaluate eHealth interventions using this framework. We examined 49 randomized controlled trials from two systematic reviews evaluating the effectiveness of eHealth interventions for weight loss. Further characterization of each intervention identified common use and function of eHealth tools represented within interventions and thus important to include in the proposed framework. This resulted in six descriptive domains. We then categorized each eHealth intervention within the context of the newly developed framework. Last, we examined efficacious interventions in the context of the framework. Twenty-five randomized controlled trials reported significantly more weight loss between the intervention group utilizing eHealth, compared to a non-eHealth control intervention and/or within an eHealth intervention group. Of these 25 interventions, 15 (60%) used automated feedback (Domain 1), 13 (52%) used non-eHealth tailored feedback by a health care provider (Domain 5), and 8 (32%) used tailored feedback from a health care professional through an electronic channel (Domain 2). The proposed schematic framework offers an alternative and novel approach for comparing across interventions and informing the development and evaluation of eHealth interventions.

Moderate and severe obesity (BMI ≥35 kg/m 2 ) affect 15% of US adults, with a projected increase over the next two decades. This study reviews evidence of behavioral lifestyle interventions for weight loss in this population. We searched PubMed, PsychInfo, CINAHL®, and Scopus through February 2016 for experimental and quasi-experimental studies that tested a dietary and/or physical activity intervention with a behavioral modification component versus a comparator; and had ≥six-month follow-up and a weight-related primary outcome. Twelve studies representing 1862 participants (mean BMI 37.5-48.3, mean age 30-54 years) were included. Nine studies compared different behavioral interventions and three tested behavioral intervention(s) versus pharmacological or surgical treatments. Among the 25 behavioral interventions in the 12 studies, 18 reported percent of participants achieving clinically significant weight loss up to 12months (32-97% achieving 5% or 3-70% achieving 10%). Three studies measured other cardiometabolic risk factors, but showed no significant risk reduction. Seven interventions with greater effectiveness (i.e., at least 31% achieving ≥10% or 62% achieving ≥5% weight loss up to one year) included multiple components (diet, physical activity, and behavioral strategies), long duration (e.g., one year), and/or intensive contacts (e.g., inpatient stays for clinic-based interventions, weekly contacts for community-based ones). Evidence for the effectiveness of behavioral interventions versus pharmacological or surgical treatment was limited. Comprehensive and intensive behavioral interventions can result in clinically significant, albeit modest, weight loss in this obese subpopulation but may not result significant improvements in other cardiometabolic risk factors. More research on scalable and sustainable interventions is needed., (Copyright © 2017 Elsevier Inc. All rights reserved.)