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Abstract Background In recent years, health systems have expanded the focus on health equity to include health-related social needs (HRSNs) screening. Community health workers (CHWs) are positioned to address HRSNs by serving as linkages between health systems, social services, and the community. This study describes a health system’s 12-month experience integrating CHWs to navigate HRSNs among primary care patients in Bronx County, NY. Methods We organized process and outcome measures using the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) implementation framework domains to evaluate a CHW intervention of the Community Health Worker Institute (CHWI). We used descriptive and inferential statistics to assess RE-AIM outcomes and socio-demographic characteristics of patients who self-reported at least 1 HRSN and were referred to and contacted by CHWs between October 2022 and September 2023. Results There were 4,420 patients who self-reported HRSNs in the standardized screening tool between October 2022 and September 2023. Of these patients, 1,245 were referred to a CHW who completed the first outreach attempt during the study period. An additional 1,559 patients self-reported HRSNs directly to a clinician or CHW without being screened and were referred to and contacted by a CHW. Of the 2,804 total patients referred, 1,939 (69.2%) were successfully contacted and consented to work with a CHW for HRSN navigation. Overall, 78.1% (n = 1,515) of patients reported receiving social services. Adoption of the CHW clinician champion varied by clinical team (median 22.2%; IQR 13.3–39.0%); however, there was no difference in referral rates between those with and without a clinician champion (p = 0.50). Implementation of CHW referrals via an electronic referral order appeared successful (73.2%) and timely (median 11 days; IQR 2–26 days) compared to standard CHWI practices. Median annual cost per household per CHW for the intervention was determined to be $184.02 (IQR $134.72 – $202.12). Conclusions We observed a significant proportion of patients reporting successful receipt of social services following engagement with an integrated CHW model. There are additional implementation factors that require further inquiry and research to understand barriers and enabling factors to integrate CHWs within clinical teams.

Abstract Introduction: Screening for health-related social needs (HRSNs) within health systems is a widely accepted recommendation, however challenging to implement. Aggregate area-level metrics of social determinants of health (SDoH) are easily accessible and have been used as proxies in the interim. However, gaps remain in our understanding of the relationships between these measurement methodologies. This study assesses the relationships between three area-level SDoH measures, Area Deprivation Index (ADI), Social Deprivation Index (SDI) and Social Vulnerability Index (SVI), and individual HRSNs among patients within one large urban health system. Methods: Patients screened for HRSNs between 2018 and 2019 (N = 45,312) were included in the analysis. Multivariable logistic regression models assessed the association between area-level SDoH scores and individual HRSNs. Bivariate choropleth maps displayed the intersection of area-level SDoH and individual HRSNs, and the sensitivity, specificity, and positive and negative predictive values of the three area-level metrics were assessed in relation to individual HRSNs. Results: The SDI and SVI were significantly associated with HRSNs in areas with high SDoH scores, with strong specificity and positive predictive values (∼83% and ∼78%) but poor sensitivity and negative predictive values (∼54% and 62%). The strength of these associations and predictive values was poor in areas with low SDoH scores. Conclusions: While limitations exist in utilizing area-level SDoH metrics as proxies for individual social risk, understanding where and how these data can be useful in combination is critical both for meeting the immediate needs of individuals and for strengthening the advocacy platform needed for resource allocation across communities.

Background: In 2017, the Canadian Partnership Against Cancer, a Canadian federally sponsored organisation, initiated a national multijurisdictional quality improvement (QI) initiative to maximise the use of synoptic data to drive cancer system improvements, known as the Evidence for Surgical Synoptic Quality Improvement Programme. The goal of our study was to evaluate the outcomes, determinants and learning of this nationally led initiative across six jurisdictions in Canada, integrating a mix of cancer surgery disease sites and clinicians., Methods: A mixed-methods evaluation (surveys, semistructured interviews and focus groups) of this initiative was focused on the ability of each jurisdiction to use synoptic reporting data to successfully implement and sustain QI projects to beyond the completion of the initiative and the lessons learnt in the process. Resources provided to the jurisdictions included operational funding, training in QI methodology, national forums, expert coaches, and ad hoc monitoring and support. The programme emphasised foundational concepts of the QI process including data literacy, audit and feedback reports, communities of practice (CoP) and positive deviance methodology., Results: 101 CoP meetings were held and 337 clinicians received feedback reports. There were 23 projects, and 22 of 23 (95%) showed improvements with 15 of 23 (65%) achieving the proposed targets. Enablers of effective data utilisation/feedback reports for QI included the need for clinicians to trust the data, have comparative data for feedback, and the engagement of both data scientists and clinicians in designing feedback reports. Enablers of sustainability of QI within each jurisdiction included QI training for clinicians, the ability to continue CoP meetings, executive and broad stakeholder engagement, and the ability to use pre-existing organisational infrastructures and processes. Barriers to continue QI work included lack of funding for core team members, lack of automated data collection processes and lack of clinician incentives (financial and other)., Conclusion: Success and sustainability in data-driven QI in cancer surgery require skills in QI methodology, data literacy and feedback, dedicated supportive personnel and an environment that promotes the process of collective learning and shared accountability. Building these capabilities in jurisdictional teams, tailoring interventions to facility contexts and strong leadership engagement will create the capacity for continued success in QI for cancer surgery., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Understanding universal aspects of quantum dynamics is an unresolved problem in statistical mechanics. In particular, the spin dynamics of the one-dimensional Heisenberg model were conjectured as to belong to the Kardar-Parisi-Zhang (KPZ) universality class based on the scaling of the infinite-temperature spin-spin correlation function. In a chain of 46 superconducting qubits, we studied the probability distribution of the magnetization transferred across the chain's center, [Formula: see text]. The first two moments of [Formula: see text] show superdiffusive behavior, a hallmark of KPZ universality. However, the third and fourth moments ruled out the KPZ conjecture and allow for evaluating other theories. Our results highlight the importance of studying higher moments in determining dynamic universality classes and provide insights into universal behavior in quantum systems.