The influence of community health on hospitals attainment of Magnet designation: Implications for policy and practice.

AIMS: To determine if there is an association between better County Health Rankings and the increased odds of a hospital gaining Magnet designation in subsequent years (2014-2019) compared with counties with lower rankings. BACKGROUND: The Magnet hospital model is recognized to have a great effect on nurses, patients and organizational outcomes. Although Magnet hospital designation is a well-established structural marker for nursing excellence, the effect of County Health Rankings and subsequent hospital achievement of Magnet status is unknown. DESIGN: A descriptive, cross-sectional quantitative approach was adopted for this study. METHODS: Data were derived from 2010 to 2019 U.S. County Health Rankings, American Hospital Association, and American Nursing Credentialing Center databases. Logistic regression models were utilized to determine associations between county rankings for health behaviours, clinical care, social and economic factors, physical environment and counties with a new Magnet hospital after 2014. RESULTS: Counties with the worst rankings for clinical care and socio-economic status had reduced odds of obtaining a Magnet hospital designation compared with best-ranking counties. While middle-ranking counties for the physical environment ranking had increased odds of having Magnet designation compared with best-ranking counties. Additionally, having an increased percent of government non-federal hospital or a higher percentage of critical access hospitals in the county reduced the odds of having a Magnet-designated facility after 2014. CONCLUSION: The findings underscore the important associations between Magnet-designated facilities' location and the health of its surrounding counties. This study is the first to examine the relationship between County Health Rankings and a hospital's likelihood of obtaining Magnet status and points to the need for future research to explore outcomes of care previously identified as improved in Magnet-designated hospitals. IMPLICATIONS: Recognizing the benefits of Magnet facilities, it is important for health care leaders and policy makers to seek opportunities to promote centres of excellence in higher need communities through policy and financial intervention.

Racial differences in primary sclerosing cholangitis mortality is associated with community socioeconomic status.

BACKGROUND AND AIMS: Natural history and outcomes data in PSC are mostly derived from cohorts where Blacks have been underrepresented. It is unknown if there are differences in mortality between Blacks and Whites with PSC. METHODS: PSC patients seen at our institution from June 1988 to Jan 2019 were identified by merging prospective ERCP hepatology-clinic databases and liver-transplant registry. Data on race, clinical events, and death was obtained through chart review. Data on community health were collected using indices from county health rankings. Cumulative incidence of death was calculated using liver transplant (LT) as a competing risk. RESULTS: Of 449 patients, 404 were White and 45 were Black. The median-duration of follow-up was 7 years (IQR:3, 13). Black patients were younger at presentation than White patients (36.3 vs 42.5 years., P = .013). Disease severity as indicated by Mayo Risk Score categories (low 27% vs 31%, intermediate 54% vs 49% and high 19% vs 19%, P = .690), comorbidity burden and frequency of cirrhosis (42% vs 35%, P = .411) were similar between Blacks and Whites. Cumulative incidence of liver-related death, with LT as a competing risk was significantly higher in Blacks compared to Whites (sHR 1.80, 95%CI 1.25, 2.61, P = .002). There was a significant interaction between race and community socioeconomic factors that attenuated the racial difference in mortality (sHR 1.01, 95%CI 0.99, 1.04, P = .345). CONCLUSIONS: Blacks with PSC present at a younger age with a similar disease severity as Whites but have higher liver related mortality that is mediated in part through community health.

Are US degree-granting institutions associated with better community health determinants and outcomes?

OBJECTIVES: The impact of individual education level on health outcomes is well-established, but the effect of degree-granting institutions on county health rankings (CHRs) is unknown. The objective of this study is to determine if there is an association between the presence of degree-granting institutions and CHRs. STUDY DESIGN: This is an ecologic study. METHODS: Data for 3062 counties were derived from the Robert Wood Johnson County Health Rankings and the Integrated Postsecondary Education Data System for year 2016. Ordinal logistic regression was utilized to determine the association between presence of a degree-granting institution and county rankings for health behaviors, health outcomes, clinical care, social and economic factors, and physical environment. All models were adjusted for potential confounding factors including age, sex, race/ethnicity, English language proficiency, and urban/rural location. RESULTS: The presence of a degree-granting institution was positively associated with CHRs for length of life (odds ratio [OR] = 1.28; 95% confidence interval [CI]: 1.05, 1.58), health behaviors (OR = 1.46; 95% CI: 1.19, 1.79), and clinical care (OR = 1.36; 95% CI: 1.11, 1.67). Counties with the highest rankings in one health category were more likely to score in the highest rankings for other health categories. CONCLUSIONS: These findings suggest that degree-granting institutions are associated with CHRs. Partnerships between public health agencies and degree-granting institutions are recommended to improve population health.

County health ranking: untangling social determinants of health and other factors associated with short-term bariatric surgery outcomes.

BACKGROUND: The complex interplay of the social determinants of health, race/ethnicity, and traditional surgical risk factors on outcomes following metabolic surgery is poorly understood. OBJECTIVE: To evaluate the relationship between the social determinants of health as measured by county health ranking (CHR) and short-term metabolic surgery outcomes. SETTING: Five accredited bariatric program sites at a national academic health system. METHODS: Data were collected from 5 sites of a single health system from 2010 to 2021. Current procedural terminology codes identified primary and revisional cases. Patient characteristics, procedural data, and 30-day occurrences were collected. CHRs for health factors were determined by ZIP Code and stratified into best, middle, and worst terciles. The primary outcome was 30-day complications, readmissions, or reinterventions/reoperations. Logistic regression assessed the correlation between CHR tercile and morbidity. RESULTS: We analyzed 4,315 primary and 370 revisional metabolic surgery cases. Overall, 64.0%, 27.4%, and 8.6% of patients lived in the best, middle, and worst CHR terciles, respectively. Patients in the middle and worst CHR terciles were more commonly older; non-Hispanic Black or Hispanic; suffered from preexisting chronic obstructive pulmonary disease or hypertension, were dialysis dependence, were on therapeutic anticoagulation, or had inferior vena cava filters. Middle and worst CHR tercile patients were more likely to undergo index sleeve gastrectomy or robotic-assisted surgery and have surgery performed by a self-designated general surgeon. Thirty-day outcomes were similar across CHR terciles. Racial disparity in multiple short-term outcomes persisted despite adjustment for CHR tercile. CONCLUSION: Higher-risk patients are more likely to be from counties with lower CHRs, but CHR was not independently associated with 30-day outcomes after metabolic surgery.

A community health case for psychiatric care: A cross-sectional study of county health rankings.

OBJECTIVES: To determine if there is an association between the provision of mental health services and county health rankings in the United States. METHODS: We used retrospective population-based, 2016 U.S. county level cross-sectional analysis to determine the association of mental health services provision on U.S. counties health rankings. The key dependent variables in this study were the county health factor rankings (CHR). The presence of inpatient, outpatient and other facilities which may provide mental health services are identified for each county. Multilevel mixed effects ordinal logistic regression models were used to account for nesting effects utilizing two levels of data which include hospital- and county-level data. RESULTS: Better county health rankings were associated with the presence of Outpatient services (OR = 0.69, 95% CI: 0.55-0.85) and Psychiatric hospital (OR = 0.55, 95% CI: 0.40-0.74). CONCLUSION: These findings suggest a significant association between psychiatric care and community health. Access to psychiatric services is associated with improved population health.