Advancing action on the political determinants of health in the United States.

In an era of political polarization, growing anti-science sentiment, and pervasive inequities in the social drivers of health, a rising tide of potentially harmful state policy proposals in the United States threaten to undermine the health of the public. In response, our health system's population health and government relations offices partnered with key health advocacy organizations in our state of New Hampshire to offer an interactive virtual learning series aimed at preparing diverse professionals and citizens to effectively advocate for sound health policies. Two hundred forty-seven individuals registered for the six-session series. Our findings indicate that participants experienced increased awareness of the political determinants of health, better understanding of specific legislative proposals in New Hampshire, and enhanced preparedness for advocacy, with many reporting greater active engagement in advocacy. Given its flexible and virtual nature, this innovative learning model could easily be adapted to promote dialogue and advocacy for sound health policy in diverse regional contexts.

The role of comorbidities, medications, and social determinants of health in understanding urban-rural outcome differences among patients with heart failure.

PURPOSE: There is now a 20% disparity in all-cause, excess deaths between urban and rural areas, much of which is driven by disparities in cardiovascular death. We sought to explain the sources of these disparities for Medicare beneficiaries with heart failure with reduced ejection fraction (HFrEF). METHODS: Using a sample of Medicare Parts A, B, and D, we created a cohort of 389,528 fee-for-service beneficiaries with at least 1 heart failure hospitalization from 2008 to 2017. The primary outcome was 30-day mortality after discharge; 1-year mortality, readmissions, and return emergency room (ER) admissions were secondary outcomes. We used hierarchical, logistic regression modeling to determine the contribution of comorbidities, guideline-directed medical therapy (GDMT), and social determinants of health (SDOH) to outcomes. RESULTS: Thirty-day mortality rates after hospital discharge were 6.3% in rural areas compared to 5.7% in urban regions (P < .001); after adjusting for patient health and GDMT receipt, the 30-day mortality odds ratio for rural residence was 1.201 (95% CI 1.164-1.239). Adding the SDOH measure reduced the odds ratio somewhat (1.140, 95% CI 1.103-1.178) but a gap remained. Readmission rates in rural areas were consistently lower for all model specifications, while ER admissions were consistently higher. CONCLUSIONS: Among patients with HFrEF, living in a rural area is associated with an increased risk of death and return ER visits within 30 days of discharge from HF hospitalization. Differences in SDOH appear to partially explain mortality differences but the remaining gap may be the consequence of rural-urban differences in HF treatment.

Cancer Epidemiology in the Northeastern United States (2013-2017).

We tested the hypotheses that adult cancer incidence and mortality in the Northeast region and in Northern New England (NNE) were different than the rest of the United States, and described other related cancer metrics and risk factor prevalence. Using national, publicly available cancer registry data, we compared cancer incidence and mortality in the Northeast region with the United States and NNE with the United States overall and by race/ethnicity, using age-standardized cancer incidence and rate ratios (RR). Compared with the United States, age-adjusted cancer incidence in adults of all races combined was higher in the Northeast (RR, 1.07; 95% confidence interval [CI] 1.07-1.08) and in NNE (RR 1.06; CI 1.05-1.07). However compared with the United States, mortality was lower in the Northeast (RR, 0.98; CI 0.98-0.98) but higher in NNE (RR, 1.05; CI 1.03-1.06). Mortality in NNE was higher than the United States for cancers of the brain (RR, 1.16; CI 1.07-1.26), uterus (RR, 1.32; CI 1.14-1.52), esophagus (RR, 1.36; CI 1.26-1.47), lung (RR, 1.12; CI 1.09-1.15), bladder (RR, 1.23; CI 1.14-1.33), and melanoma (RR, 1.13; CI 1.01-1.27). Significantly higher overall cancer incidence was seen in the Northeast than the United States in all race/ethnicity subgroups except Native American/Alaska Natives (RR, 0.68; CI 0.64-0.72). In conclusion, NNE has higher cancer incidence and mortality than the United States, a pattern that contrasts with the Northeast region, which has lower cancer mortality overall than the United States despite higher incidence. Significance: These findings highlight the need to identify the causes of higher cancer incidence in the Northeast and the excess cancer mortality in NNE.

A 'COVID Compass' for navigating the pandemic.

INTRODUCTION: The greatest challenge confronting political, public health, business, education and social welfare leaders in the COVID pandemic era is to restore the economy, businesses and schools without further risking public health. The 'COVID Compass' project aims to provide helpful information to guide local decisions by tracking state and local policies over time and their impact on a balanced set of outcomes-health metrics, economic trends and social hardship indicators. METHODS: We selected a parsimonious set of 'local level' health, economic and hardship outcomes and linked them to 'local level' actions aimed to decrease COVID-19 health effects and to mitigate hardship for people, businesses and the economy. Data trends will be released frequently (e.g. weekly and monthly) to show changes in health economic and social hardship 'outcomes' (based on quantitative data), alongside policy, health care, public health and individual/social 'actions' (based on both qualitative and quantitative data). RESULTS: Work on initial analytic and visualization prototypes of the COVID Compass is currently in progress at national, state and local levels. CONCLUSION: Building a national, regional and local integrated database platform that captures upstream policies, actions and behaviors and links them to downstream health, economic and social hardship outcomes will offer a more comprehensive view of the data necessary for decision-makers and citizens to more effectively and intelligently monitor and mitigate harms caused by the pandemic.

Predictors of colorectal cancer screening variation among primary-care providers and clinics.

OBJECTIVES: Colorectal cancer (CRC) screening is underutilized. To effect change, we must understand reasons for underuse at multiple levels of the health-care system. We evaluated patient, provider, and clinic factors that predict variation in CRC screening among primary-care clinics and primary-care providers (PCPs). METHODS: We analyzed electronic medical record (EMR) data for 34,319 adults eligible for CRC screening, 19 clinics, and 97 PCPs in a large, academic physician group. Detailed data on potential patient, provider, and clinic predictors of CRC screening were obtained from the EMR. PCP perceptions of CRC screening barriers were measured via survey. The outcome was completion of CRC screening at the patient level. Multivariate logistic regression with clustering on clinics obtained adjusted odds ratios and 95% confidence intervals for potential predictors of CRC screening at each level. RESULTS: Seventy-one percentage of patients completed CRC screening. Variation in screening rates was seen among clinics (51-80%) and among PCPs (51-82%). Significant predictors of completing CRC screening were identified at all levels: patient (older age, white race, being married, primarily English-speaking, having commercial insurance plans vs. Medicare or Medicaid, and higher health-care resource utilization), provider (larger panel size of patients eligible for CRC screening), and clinic (hospital-owned, shorter distance to nearest optical colonoscopy center). CONCLUSIONS: Variation in CRC screening exists among primary-care clinics and providers within a single clinic. Predictors of variation can be identified at patient, provider, and clinic levels. Quality improvement interventions addressing CRC screening need to be directed at multiple levels of the health-care system.

Effect of patient selection method on provider group performance estimates.

BACKGROUND: Performance measurement at the provider group level is increasingly advocated, but different methods for selecting patients when calculating provider group performance have received little evaluation. OBJECTIVE: We compared 2 currently used methods according to characteristics of the patients selected and impact on performance estimates. RESEARCH DESIGN, SUBJECTS, AND MEASURES: We analyzed Medicare claims data for fee-for-service beneficiaries with diabetes ever seen at an academic multispeciality physician group in 2003 to 2004. We examined sample size, sociodemographics, clinical characteristics, and receipt of recommended diabetes monitoring in 2004 for the groups of patients selected using 2 methods implemented in large-scale performance initiatives: the Plurality Provider Algorithm and the Diabetes Care Home method. We examined differences among discordantly assigned patients to determine evidence for differential selection regarding these measures. RESULTS: Fewer patients were selected under the Diabetes Care Home method (n=3558) than the Plurality Provider Algorithm (n=4859). Compared with the Plurality Provider Algorithm, the Diabetes Care Home method preferentially selected patients who were female, not entitled because of disability, older, more likely to have hypertension, and less likely to have kidney disease and peripheral vascular disease, and had lower levels of predicted utilization. Diabetes performance was higher under Diabetes Care Home method, with 67% versus 58% receiving >1 A1c tests, 70% versus 65% receiving ≥1 low-density lipoprotein (LDL) test, and 38% versus 37% receiving an eye examination. CONCLUSIONS: The method used to select patients when calculating provider group performance may affect patient case mix and estimated performance levels, and warrants careful consideration when comparing performance estimates.

Minority status and diabetes screening in an ambulatory population.

OBJECTIVE: Ethnicity has been identified as a risk factor not only for having type 2 diabetes but for increased morbidity and mortality with the disease. Current American Diabetes Association (ADA) guidelines advocate screening high-risk minorities for diabetes. This study investigates the effect of minority status on diabetes screening practices in an ambulatory, insured population presenting for yearly health care. RESEARCH DESIGN AND METHODS: This is a retrospective population-based study of patients in a large, Midwestern, academic group practice. Included patients were insured, had ≥1 primary care visit yearly from 2003 to 2007, and did not have diabetes but met ADA criteria for screening. Odds ratios (ORs), 95% confidence intervals (CI), and predicted probabilities were calculated to determine the relationship between screening with fasting glucose, glucose tolerance test, or hemoglobin A(1c) and patient and visit characteristics. RESULTS: Of the 15,557 eligible patients, 607 (4%) were of high-risk ethnicity, 61% were female, and 86% were ≥45 years of age. Of the eight high-risk factors studied, after adjustment, ethnicity was the only factor not associated with higher diabetes screening (OR = 0.90 [95% CI 0.76-1.08]) despite more primary care visits in this group. In overweight patients <45 years, where screening eligibility is based on having an additional risk factor, high-risk ethnicity (OR 1.01 [0.70-1.44]) was not associated with increased screening frequency. CONCLUSIONS: In an insured population presenting for routine care, high-risk minority status did not independently lead to diabetes screening as recommended by ADA guidelines. Factors other than insurance or access to care appear to affect minority-preventive care.