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Background: We investigated the implementation process of an Integrated Community Approach (ICA) applied in four low socio-economic status neighbourhoods in Maastricht, the Netherlands. The ICA is a Population Health Management initiative and aims to improve population health, quality of care, professional's satisfaction and decrease costs of care. This study addresses the facilitators and barriers for implementing the ICA from a stakeholder perspective, including steering group members, professionals and citizens. Methods: We conducted a mixed-methods study using a triangulation of methods to investigate the implementation from 1 December 2016 to 31 December 2020. The Consolidated Framework for Implementation Research guided data collection and data-analysis for evaluating the implementation process. In total, 77 interviews, 97 observations, seven focus groups, 65 collected documents and two surveys with open-ended questions were conducted. Results: Facilitators for implementation were the use of citizen science to bring residents' needs into sharp focus, the integration of the ideology of Positive Health into the working routines of the professionals and leadership at the steering group level to overcome barriers in the ICA. The existing accounting and financial infrastructure obstructed combining budgets at neighbourhood level. Conclusions: Engaging citizens and professionals at an early stage is an important facilitator for implementation. The use of a shared vision on health also worked as a facilitator since it created a shared language among professionals, which is important in Population Health Management initiatives where multiple professionals are expected to collaborate. Trial Registration: NTR 6543; registration date, 25 July 2017. [ABSTRACT FROM AUTHOR]

Interventions designed to address COVID-19 needed to be rapidly scaled up to the population level, and to address health equity by reaching historically marginalized populations most affected by the pandemic (e.g., racial/ethnic minorities and rural and low socioeconomic status populations). From February 2021 to June 2022, SCALE-UP Utah used text messaging interventions to reach 107 846 patients from 28 clinics within seven safety-net health care systems. Interventions provided informational and motivational messaging regarding COVID-19 testing and vaccination, and were developed using extensive community partner input. (Am J Public Health. 2024;114(11):1207–1211. https://doi.org/10.2105/AJPH.2024.307770) [ABSTRACT FROM AUTHOR]

Population segmentation can be a powerful tool in healthcare management, in helping to match interventions and resources to individuals of a common health state and condition. However, studies to date indicate a lack of alignment to risk stratification – another key tool in Population Health Management – and insufficient demonstration of how segmentation can be used in practice. In this study, we obtain a five-cohort segmentation derived through four incremental thresholds on the risk-based Cambridge Multimorbidity Score, which is calculated for each member of the 762,117 adult population in and around Bristol, England. Appropriately selecting the four thresholds – 0.09, 0.69, 1.59, 2.95 – yields a segmentation with the convenient property that, with increasing risk, segments halve in size and double in per-person spend. The segmentation has been used to support various planning and management activities within the Bristol healthcare system; two of which are detailed here as case studies in demonstrating the practical value of the segmentation model. [ABSTRACT FROM AUTHOR]

Objectives: To assess the impact of the COVID-19 pandemic on disability insurance grants and related costs for workerswith cancer. Methods: This ecological time series study uses the inflection point regression model and the federal government's open-access dataset. We analyze the annual grant and cost rates of cancer-related disability insurance in Brazil (2010-2021). Results: In 2020, the number of disability insurance grants due to malignant neoplasms decreased by 62.26%, and the total annual cost decreased by 62.94% compared to those in 2019. All illnesses and injuries were reduced by 2.56% and 20.02%, respectively. Between 2010 and 2021, the COVID-19 pandemic has reversed the increasing trend in annual disability insurance granted due to cancer and its associated expenses to a stable trend. Conclusion: The COVID-19 pandemic has harmed the provision of disability insurance for workers with cancer. [ABSTRACT FROM AUTHOR]

The health care industry is experiencing a transformative shift from traditional fee-for-service models to value-based care (VBC), emphasizing improved patient outcomes, enhanced quality, and reduced costs. While Centers for Medicare & Medicaid Services Innovation Center models focus on financial and quality outcomes, a critical opportunity for reform lies in organizational culture. VBC signifies a cultural and systemic evolution aligned with the quintuple aim of enhancing equitable patient outcomes, improving quality, reducing costs, and prioritizing provider well-being. Cultural impacts play a pivotal role in this transformation. [ABSTRACT FROM AUTHOR]

The integration of genetic information (GI) into the electronic health record (EHR) seems inevitable as the mainstreaming of genomics continues. Such newly provided accessibility to GI could be beneficial for improving health care, as well as for supporting clinical decision‐making and health management. Notwithstanding these promising benefits, the automatic integration of GI into the EHR, allowing unrestricted access to one's GI through patient portals, carries various knowledge‐related risks for patients. This article is focused on the potential case of inadvertently revealing misattributed parentage through such practice. The article aims to identify key clinical and ethical implications of such revelation for adult patients. Clinical implications include, for example, altering the physician‐patient interaction and the need to enhance physician's genetic literacy to improve genetic‐information‐specific communication skills. Ethical implications yield arguments supporting disclosure of MP, such as autonomy, individuals' right to know medical information pertaining to them, and the right to know one's genetic origins. Arguments opposing disclosure of MP centre on the right not to know GI and concerns for post‐disclosure family relationships. Following the clinical and ethical analyses of these respective implications, we consider how such integration of GI into the EHR ought to be carried out, ethically. We therefore suggest a solution, featuring an autonomy‐based approach, built around EHR users' right not to know. Our solution of nuanced consent options (including a 'genetic ignorance option') is designed to enable patients' informed exposure to GI through the EHR, allowing them some control over their self‐ and familial narrative. [ABSTRACT FROM AUTHOR]

Background: Ground crossing borders are considered a threat to health security due to their complex and challenging environments. The objective of this scoping review is to identify the main themes crucial for implementing effective health management at ground crossing borders to maintain health security. Methods: This scoping study was conducted following the methodological framework developed by Arksey and O'Malley and the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). Documents published from January 2005 to December 2023 were searched for using PubMed, Scopus, Web of Science, and UN databases. Two reviewers screened and reviewed eligible studies in three stages: duplicate identification and elimination, title and abstract screening, and full-text assessment. Data were charted and grouped into themes, the frequency of each theme and its percentage was calculated, and then thematic analysis was conducted. Results: Forty-five studies met the inclusion criteria. Areas of research were grouped into eight themes: "Infection Prevention and Control measures (IPC) (17%)", "Collaboration, Coordination, and Partnership (17%)", "Research and Data Sharing (15%)", "Build Border Health Capacity (13.5%)", "Planning (13.5%)", "Communication (13%)", "Legislations and Frameworks (7%)", and "Services and Assistance for At-Risk Groups (4%)". Through this scoping review, we found that the eight themes are interconnected, and are crucial for implementing effective health management at the ground crossing borders and for better emergency preparedness responses among countries. [ABSTRACT FROM AUTHOR]

Abstract Background The Adjusted Clinical Groups (ACG) System is a validated electronic risk stratification system. However, there is a lack of studies on the association between different ACG risk scores and the utilisation of different healthcare services using different sources of input data. The aim of this study was therefore to assess the validity of the association between five different ACG risk scores and the utilisation of a range of different healthcare services using input data from either general practitioners (GPs) or hospitals. Methods Registry-based study of all adult inhabitants in four Norwegian municipalities that received somatic healthcare in one year (N = 168 285). The ACG risk scores resource utilisation band, unscaled ACG concurrent risk, unscaled concurrent risk, frailty flag and chronic condition count were calculated using age, sex and diagnosis codes from GPs and a hospital, respectively. Healthcare utilisation covered GP, municipal and hospital services. Areas under the receiver operating curve (AUC) were calculated and compared to the AUC of a model using only age and sex. Results Utilisation of all healthcare services increased with increasing scores in the “resource utilisation band” (RUB) and all other investigated ACG risk scores. The risk scores overall distinguished well between levels of utilisation of GP visits (AUC up to 0.84), hospitalisation (AUC up to 0.8) and specialist outpatient visits (AUC up to 0.72), but not out-of-hours GP visits (AUC up to 0.62). The score “unscaled ACG concurrent risk” overall performed best. Risk scores based on data from either GPs or hospitals performed better for the classification of healthcare services in their respective domains. The model based on age and sex performed better for distinguishing between levels of utilisation of municipal services (AUC 0.83–0.90 compared to 0.46–0.79). Conclusions Risk scores from the ACG system is valid for classifying GP visits, hospitalisation and specialist outpatient visits. It does not outperform simpler models in the classification of utilisation of municipal services such as nursing homes and home services and outpatient emergency care in primary healthcare. The ACG system can be applied in Norway using administrative data from either GPs or hospitals.

Braeden A Terpou,1 Marissa Bird,1,2 Diya Srinivasan,1 Shalu Bains,3 Laura C Rosella,1,4 Laura Desveaux1,2 1Institute for Better Health, Trillium Health Partners, Mississauga, Ontario, Canada; 2Institute of Health Policy, Management, and Evaluation, University of Toronto, Toronto, Ontario, Canada; 3Mississauga Hospital, Trillium Health Partners, Mississauga, Ontario, Canada; 4Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, CanadaCorrespondence: Laura Desveaux, Institute for Better Health, Trillium Health Partners, 2085 Hurontario Street, Mississauga, ON, L5B 1B8, Canada, Tel +1 437772-6836, Email Laura.Desveaux@thp.caPurpose: As the COVID-19 pandemic recedes, the importance of population health has come into sharp focus, prompting many health systems to explore leveraging population health data (PHD) for operational planning. This approach requires that healthcare leaders embrace the dual priorities of maintaining excellence in patient care while promoting the overall health of populations. However, many leaders are new to population-based thinking, posing a threat to successful operationalization if mental models are not aligned.Patients and Methods: This qualitative case study explored the alignment of mental models among 13 senior leaders at Trillium Health Partners (THP), one of Canada’s largest community hospitals, as they embark on embedding PHD within operational workflows.Results: All leaders recognized the necessity of adopting a population health approach amid resource constraints and growing pressures. When discussing the operationalization of PHD, two distinct mental models emerged among leaders: one focused on patient care and the other on population health. While executive leaders demonstrated a fluidity in their thinking between the two, programmatic leaders favoured one over the other. For example, some viewed the organization’s focus on PHD as competing with their patient care responsibilities, while others saw the use of PHD as a solution to the organization’s operational pressures. Despite these divergences, leaders unanimously stressed the importance of increasing the organization’s risk tolerance and devolving decision-making as a necessary precursor to realizing the transformation to a PHD-driven approach.Conclusion: These divergent mental models highlight a need to clarify the shared vision for the use of PHD along with its impact on leadership roles and accountabilities. These findings illustrate the current state from which THP aims to evolve and underscore the importance of aligning leaders’ mental models as a critical step to facilitating successful integration of PHD and advancing a collective vision for healthcare transformation.Keywords: health equity, population health management, healthcare leaders, qualitative study

Background With the development of society and the improvement of people's living standards, health issues are receiving increasing attention. The aging population and the high incidence of chronic diseases have made health management an urgent problem that needs to be addressed. Primary healthcare institutions, as the "main battlefield" for residents' health, play a crucial role in health management. However, in the current implementation of health management, primary healthcare institutions still face numerous challenges, and their proactivity remains unclear. Objective To understand the current implementation status of health management in primary healthcare institutions in Shanghai and to discuss strategies for enhancing the implementation of proactive health-oriented health management. Methods From February 2023 to May 2023, a survey was conducted on 33 primary healthcare institutions in Shanghai. The survey aimed to understand the implementation of health management, assessment of high-risk factors and disease screening, execution of health education and information dissemination, coordination of health management resources and functional services, as well as the status of online health management services and health monitoring. Additionally, interviews were conducted with institution heads to gather information on implementation difficulties and suggestions. Results The research results showed that all participating institutions carried out health management for chronic disease patients, with 93.9% (31/33) covering key populations, 72.7% (24/33) involving rehabilitation populations, and 54.6% (18/33) including healthy populations. A total of 81.8% (27/33) of institutions utilized health data platforms, with the main functions including contract management, health record management, data querying, and health indicator management. Furthermore, 97.0% (32/33) of institutions conducted high-risk factor assessments and disease screenings, as well as follow-up, diagnosis, and management. The majority of institutions carried out health education and information dissemination activities through various platforms. Additionally, 87.9% (29/33) of institutions collaborated with other units to implement health management projects, providing diverse functional services. About 63.6% (21/33) of institutions offered online services, and 42.4% (14/33) were equipped with health monitoring devices. Managers believed that primary healthcare institutions and their staff have significant advantages in implementing proactive health-oriented management, but they also face challenges due to a lack of policy and financial support. Conclusion Primary healthcare institutions in Shanghai have made positive progress in implementing proactive health-oriented management. However, comprehensive measures are still needed to address existing challenges, in order to further improve the quality and efficiency of health management services and better meet the health needs of residents.

The imbalance between the supply and demand of pediatric medical resources and health management services in our country has been a long-standing issue, primary healthcare institutions are particularly prominent in this context. How to achieve integration and optimization of pediatric medical resources at the grassroots medical and health institutions is an urgent problem that needs to be addressed. This article primarily summarizes and analyzes the concept and framework of integrated health management services for children, including children's health assessment, early intervention, long-term follow-up, and case studies and practical experiences. Through a review of domestic and international literature, it concludes feasible models of integrated health services for children. This review suggests that integrated health management services have broad potential and promising applications, providing personalized and efficient health management and intervention for children.

Background: Community-based coalitions are a common strategy for community engagement efforts targeting the improvement of a variety of population health outcomes. The typical processes that coalitions follow to organize efforts include steps that are sequential, slow, and time intensive. These processes also limit local decision-making to the selection of evidence-based policies or programs. Methods: We present a process control theory-based Community Action Process, Investigate-Design-Practice-Reflect (IDPR), where community hubs (i.e., coalitions) organize agile efforts in a non-sequential, rapid, and efficient manner to harness local assets and data to make decisions regarding the provision and production of population health services. Using qualitative methods, we illustrate and analyze the use of IDPR in a one community case study as part of Wellscapes, a Type 3-hybrid implementation-effectiveness community randomized controlled trial to improve children's population health physical activity. Results: We found community members followed the IDPR Community Action Process to rapidly design, organize, deliver, and receive feedback on a community-based, children's population physical activity prototype, an afterschool Play-in-the-Park opportunity for all children. Discussion: Following IDPR afforded the community coalition timely learning through feedback within a process that coordinated decisions regarding what community services met community needs (provision decisions) and how to organize the production of the population health services (production decisions). [ABSTRACT FROM AUTHOR]

Objectives: Maternal mortality and morbidity disproportionately affect birthing people from racialized populations. Unfortunately, researchers can often compound these poor outcomes through a lack of authentic community engagement in research beyond the role of the research subject, leading to ineffective strategies for improving care and increasing equity. This article details the real-life strategies utilized to develop a community-engaged research project of a phased federally funded grant employing community engagement principles of co-leadership and co-creation. It also includes reflections from the researchers and advisory board on promising practices and lessons learned for equitably engaging patients and community partners in research. Methods: This article details the application of principles of community-engaged research in a federally funded phased research project focused on understanding disparities in maternal sepsis to develop better clinical and community interventions. Specifically, it discusses early steps in the research partnership to create a sustainable partnership with a Community Leadership Board guided by the principles of transparency, respect, compensation, and increasing research justice. Results: Based on the authors' experience, recommendations are provided for funders, researchers, and institutions to improve the quality and outcomes of communityengaged research. This work adds to community-based participatory and community-engaged research literature by providing concrete and practical steps for equitably engaging in research partnerships with a variety of collaborators. Conclusions: In conclusion, integrated patient and community co-leadership enhances research by providing insight, access to communities for education and dissemination of information, and identifying critical areas needing change. This report may help others address fundamental principles in this journey. Significance: Community-engaged research can be an equitable approach to research that involves communities most affected by empowering them to guide the research as equal partners. This article serves as a guide for researchers to form these critical partnerships, sustain relationships, and recommend solutions to common challenges based on the reflections of the researchers and advisory board. [ABSTRACT FROM AUTHOR]

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Simple Summary: This study looks at how combining real-world/time data/evidence (RWTD/E) with traditional clinical studies (known as randomized controlled trials) can improve healthcare research and ultimately patient care. Unlike past methods that often rely on outdated information, RWTD/E provides up-to-the-minute data on patient health, making it a powerful tool for doctors and researchers. This approach is especially useful in areas like sarcoma, a type of cancer, where understanding each patient's unique situation can lead to improved treatment plans. We discuss how this mix of real-world/time data and traditional research can lead to more personalized medicine, helping to create treatments tailored to individual patient needs. It also aids in managing health at a community level by spotting trends and improving health policies, making care more efficient and focused on what patients truly benefit from. Furthermore, we explore how applying new methods, like creating digital twins of patients' health profiles to RWTD/E can help in predicting individualized treatment effects. This study aims to elaborate that using prospective RWTD/E alongside traditional clinical trials can make healthcare more effective, patient-focused, and ready to adapt to new discoveries and technologies. This manuscript examines the synergistic potential of prospective real-world/time data/evidence (RWTD/E) and randomized controlled trials (RCTs) to enrich healthcare research and operational insights, with a particular focus on its impact within the sarcoma field. Through exploring RWTD/E's capability to provide real-world/time, granular patient data, it offers an enriched perspective on healthcare outcomes and delivery, notably in the complex arena of sarcoma care. Highlighting the complementarity between RWTD/E's expansive real-world/time scope and the structured environment of RCTs, this paper showcases their combined strength, which can help to foster advancements in personalized medicine and population health management, exemplified through the lens of sarcoma treatment. The manuscript further outlines methodological innovations such as target trial emulation and their significance in enhancing the precision and applicability of RWTD/E, underscoring the transformative potential of these advancements in sarcoma care and beyond. By advocating for the strategic incorporation of prospective RWTD/E into healthcare frameworks, it aims to create an evidence-driven ecosystem that significantly improves patient outcomes and healthcare efficiency, with sarcoma care serving as a pivotal domain for these developments. [ABSTRACT FROM AUTHOR]

Introduction: Population health management is increasingly being used to support place-based models of care. This case study provides an account of the use of the Population Health Management – Maturity Index (PHM-MI) tool to inform the future development of a neighbourhood model of care for older people in the Central Coast region of Australia. Description: The PHM-MI tool comprises a set of six evidence-informed elements known to be important in enabling PHM in practice. As part of a joint strategic needs assessment, 17 selected stakeholders from key regional organizations were invited to undertake the PHM-MI tool survey. Three follow-up workshops were held to interpret the results and determine priority actions. Discussion: The PHM-MI scores revealed that the overall maturity of the Central Coast to successfully deliver PHM was low across all six elements, findings that were corroborated through participant workshops. Systemic fragmentations, most pertinently of funding and regulation, incentivised silo-based working. The need to formalise and strengthen regional collaborations, enable data integration, find creative ways to use existing funding streams, and promote community engagement were highlighted as core priorities. Conclusion: Using the PHM-MI tool was enabled by it being embedded within a pre-existing regional strategic process. The results were used to inform future regional priorities. The PHM-MI tool has the potential for use across regional or national contexts. [ABSTRACT FROM AUTHOR]

Population Health Management – often abbreviated to PHM – is a relatively new approach for healthcare planning, requiring the application of analytical techniques to linked patient level data. Despite expectations for greater uptake of PHM, there is a deficit of available solutions to help health services embed it into routine use. This paper concerns the development, application and use of an interactive tool which can be linked to a healthcare system's data warehouse and employed to readily perform key PHM tasks such as population segmentation, risk stratification, and deriving various performance metrics and descriptive summaries. Developed through open-source code in a large healthcare system in South West England, and used by others around the country, this paper demonstrates the importance of a scalable, purpose-built solution for improving the uptake of PHM in health services. [ABSTRACT FROM AUTHOR]

Aims: This study aimed to present the Johns Hopkins Adjusted Clinical Groups (ACG) System risk stratification profile of a total adult population of somatic health-care users when using data from either general practitioners (GPs) or hospital services and to compare the number and characteristics of individuals identified as having complex and long-term health-care needs in each data source. Methods: This was a registry-based study that included all adult residents (N =168,285) in four municipalities in Central Norway who received somatic health care during 2013. Risk profiles were generated using the ACG System based on age, sex and diagnoses registered by GPs or the local hospital. ACG output variables on number of chronic conditions, frailty and concurrent resource utilisation were chosen as indicators of complexity. Results: Nearly nine out of 10 (83.9%) of the population had been in contact with a GP, and 35.4% with the hospital. The mean number of diagnoses (3.0) was equal in both sources. A larger proportion of the population had higher risk scores in all variables except frailty when comparing hospital data to GP data. This was also found when comparing individuals identified as having complex and long-term health-care needs. A similar proportion of the population was found to have complex and long-term health-care needs (hospital 6.7%, GP 6.3%), but only one in five (21.5%) were identified in both data sets. Conclusions: As data from GPs and hospitals identified mostly different individuals with complex and long-term health-care needs, combining data sources is likely to be the best option for identifying those most in need of special attention. [ABSTRACT FROM AUTHOR]

Improving the overall care of children with medical complexity (CMC) is often beset by challenges in proactively identifying the population most in need of clinical management and quality improvement. The objective of the current study was to create a system to better capture longitudinal risk for sustained and elevated utilization across time using real-time electronic health record (EHR) data. A new Pediatric Population Management Classification (PPMC), drawn from visit diagnoses and continuity problem lists within the EHR of a tristate health system, was compared with an existing complex chronic conditions (CCC) system for agreement (with weighted κ) on identifying CCMC, as well as persistence of elevated charges and utilization from 2016 to 2019. Agreement of assignment PPMC was lower among primary care provider (PCP) populations than among other children traversing the health system for specialty or hospital services only (weighted κ 62% for PCP vs. 82% for non-PCP). The PPMC classification scheme, displaying greater precision in identifying CMC with persistently high utilization and charges for those who receive primary care within a large integrated health network, may offer a more pragmatic approach to selecting children with CMC for longitudinal care management. [ABSTRACT FROM AUTHOR]

The accelerations of globalization, climate change, and population aging gradually increase the complex challenges to human health. Globalization-induced global health issues significantly increase the speed and range of infectious disease transmission, causing a more profound impact. Climate change not only directly affects human health but also indirectly increases the risk of infectious disease outbreaks by altering ecosystems and the distribution of disease vectors. Meanwhile, population aging has escalated the burden of chronic non-infectious diseases and highlighted complex health issues like comorbidities, posing significant challenges to healthcare systems and social service assurance systems. Technological innovations offer unprecedented opportunities to address these health challenges. Advanced techniques like precision medicine and artificial intelligence (AI) are emerging innovations to deal with current health issues. Advancements in technology are reshaping our health management paradigms. Technological innovations are not only the driving forces for the development of modern medicine, but also the key to addressing future health issues. In the future, it is essential to strengthen health system construction, innovate mechanisms for medical and preventive integration, enhance scientific and technological research and innovation, and empower primary healthcare with AI, aiming to further tackle health challenges and improve human well-being.

Background Direct oral anticoagulants (DOACs) have complex dosing regimens and are often incorrectly prescribed. We evaluated a nationwide DOAC population management dashboard rollout whose purpose includes pharmacist review and correction of off‐label dosing prescriptions. Methods and Results Using data from Veterans Health Affairs, we identified all patients prescribed DOACs for atrial fibrillation or venous thromboembolism between August 2015 and December 2019. Sites were grouped on the basis of the timing of moderate‐high usage of the DOAC population management tool dashboard. Effectiveness was defined as the monthly rate of off‐label DOAC prescribing and the rate of clinical adverse events (bleeding, composite of stroke or venous thromboembolism). Implementation was evaluated as the percentage of off‐label DOAC prescriptions changed within 7 days. Among the 128 652 patients receiving DOAC therapy at 123 centers, between 6.9% and 8.6% had off‐label DOAC prescriptions. Adoption of the DOAC population management tool dashboard before July 2018 was associated with a decline in off‐label dosing prescriptions (8.7%–7.6%). Only 1 group demonstrated a significant reduction in monthly rates of bleeding following implementation. All sites experienced a reduction in the composite of venous thromboembolism or stroke following dashboard adoption. There was no difference in the implementation outcome of DOAC prescription change within 7 days in any of the adoption groups. Conclusions Early adoption of the DOAC population management tool dashboard was associated with decreased rates of off‐label DOAC dosing prescription and reduced bleeding. Following adoption of the DOAC population management tool dashboard, all sites experienced reductions in venous thromboembolism and stroke events.

This article points out deficiencies in present-day definitions of public health surveillance, which include data collection, analysis, interpretation and dissemination, but not public health action. Controlling a public health problem of concern requires a public health response that goes beyond information dissemination. It is undesirable to have public health divided into data generation processes (public health surveillance) and data use processes (public health response), managed by two separate groups (surveillance experts and policy-makers). It is time to rethink the need to modernize the definition of public health surveillance, inspired by the authors’ enhanced Data, Information, Knowledge, Intelligence and Wisdom model. Our recommendations include expanding the scope of public health surveillance beyond information dissemination to comprise actionable knowledge (intelligence); mandating surveillance experts to assist policy-makers in making evidence-informed decisions; encouraging surveillance experts to become policy-makers; and incorporating public health literacy training – from data to knowledge to wisdom – into the curricula for all public health professionals. Work on modernizing the scope and definition of public health surveillance will be a good starting point.

Background: Technological burden and medical complexity are significant drivers of clinician burnout. Electronic health record(EHR)-based population health management tools can be used to identify high-risk patient populations and implement prophylactic health practices. Their impact on clinician burnout, however, is not well understood. Our objective was to assess the relationship between ratings of EHR-based population health management tools and clinician burnout. Methods: We conducted cross-sectional analyses of 2018 national Veterans Health Administration(VA) primary care personnel survey, administered as an online survey to all VA primary care personnel (n = 4257, response rate = 17.7%), using bivariate and multivariate logistic regressions. Our analytical sample included providers (medical doctors, nurse practitioners, physicians' assistants) and nurses (registered nurses, licensed practical nurses). The outcomes included two items measuring high burnout. Primary predictors included importance ratings of 10 population health management tools (eg. VA risk prediction algorithm, recent hospitalizations and emergency department visits, etc.). Results: High ratings of 9 tools were associated with lower odds of high burnout, independent of covariates including VA tenure, team role, gender, ethnicity, staffing, and training. For example, clinicians who rated the risk prediction algorithm as important were less likely to report high burnout levels than those who did not use or did not know about the tool (OR 0.73; CI 0.61-0.87), and they were less likely to report frequent burnout (once per week or more) (OR 0.71; CI 0.60-0.84). Conclusions: Burned-out clinicians may not consider the EHR-based tools important and may not be using them to perform care management. Tools that create additional technological burden may need adaptation to become more accessible, more intuitive, and less burdensome to use. Finding ways to improve the use of tools that streamline the work of population health management and/or result in less workload due to patients with poorly managed chronic conditions may alleviate burnout. More research is needed to understand the causal directional of the association between burnout and ratings of population health management tools. [ABSTRACT FROM AUTHOR]

This research seeks to assess the potential of regionally integrated health management for specific sub-populations, including the incorporation of selfmanagement initiatives. It will achieve this by conducting a thorough stratification analysis of hospital data, utilizing the Adjusted Clinical Groups (ACG) classification system. The approach involves a retrospective review of healthcare data spanning five years, which includes patient demographics, health outcomes, and healthcare utilization metrics. We intend to use the ACG method to classify the patient population into pertinent groups that mirror their health requirements and resource use. The insights obtained from this analysis will be used to create a localized adaptation of the Kaiser Permanente Pyramid Model of Care. This adaptation aims to identify the distribution of costs among patients treated in the Rivierenland Hospital. We anticipate that stratifying data with the ACG method will identify distinct multimorbid subgroups. These subgroups will have unique healthcare requirements. Early interventions and customized health management strategies, based on these insights, could enhance health outcomes and resource efficiency for high-risk patients. This analysis will serve as a foundation for constructive discussions with hospital management and clinical staff, fostering a deeper comprehension of the patients' burden of disease. It might also foster multidisciplinary collaboration opportunities between medical specialties as with regional healthcare partners such as general practitioners (GPs), mental health and other long-term care organizations. Moreover, we anticipate that self-care initiatives, supported by customized health information, will encourage increased patient engagement and strategies for enhancing lifestyle improvements. This strategy is expected to enable the personalization of advanced care planning based on individual needs profiles, thereby improving the management of complex and chronic conditions, and encouraging self-care practices. Our anticipated findings highlight the potential benefits of a data-informed approach to advancing healthcare outcomes and present opportunities for future investigations to refine and implement such integrated care models across the region. [ABSTRACT FROM AUTHOR]

Background: The 'agentic demand' of population health interventions (PHIs) refers to the capacity, resources and freedom to act that interventions demand of their recipients to benefit, which have a socio-economical pattern. Highly agentic interventions, e.g. information campaigns, rely on recipients noticing and responding to the intervention and thus might affect intervention effectiveness and equity. The absence of an adequate framework to classify agentic demands limits the fields' ability to systematically explore these associations. Methods: We systematically developed the Demands for Population Health Interventions (Depth) framework using an iterative approach: (1) developing the Depth framework by systematically identifying examples of PHIs aiming to promote healthier diets and physical activity, coding of intervention actors and actions and synthesising the data to develop the framework; (2) testing the Depth framework in online workshops with academic and policy experts and a quantitative reliability assessment. We applied the final framework in a proof-of-concept review, extracting studies from three existing equity-focused systematic reviews on framework category, overall effectiveness and differential socioeconomic effects and visualised the findings in harvest plots. Results: The Depth framework identifies three constructs influencing agentic demand: exposure — initial contact with intervention (two levels), mechanism of action — how the intervention enables or discourages behaviour (five levels) and engagement — recipient response (two levels). When combined, these constructs form a matrix of 20 possible classifications. In the proof-of-concept review, we classified all components of 31 interventions according to the Depth framework. Intervention components were concentrated in a small number of Depth classifications; Depth classification appeared to be related to intervention equity but not effectiveness. Conclusions: This framework holds potential for future research, policy and practice, facilitating the design, selection and evaluation of interventions and evidence synthesis. [ABSTRACT FROM AUTHOR]

Background/Aims: Identifying health inequalities can require substantial data and analytical resources. A healthcare setting that may be particularly exposed to inequality is elective care, where hospital waiting times have substantially lengthened since the COVID-19 pandemic. This study aimed to investigate how routine health data and standard analytical methods could be used to identify inequalities in waiting times relating to age, sex, ethnicity and socioeconomic deprivation. Methods: Decision trees were fitted to data on waiting times for 78 510 completed elective treatments from a large NHS organisation in England for the calendar year of 2021. Data were sourced from the Waiting List Minimum Dataset and combined with a local dataset on patient attributes. Analysis was stratified by treatment specialty and whether the treatment was delivered in an outpatient or inpatient setting. A decision tree was fitted to the data at each stratum to assess three questions: To what extent can variation in waiting times be explained by age, sex, ethnicity and socioeconomic deprivation? Which variables are most explanatory? In what 'direction' is this explanation (eg for sex, did male or female patients wait longer?). Results: Across the elective hospital specialties assessed, a maximum of 12% of variation in waiting times could be explained by age, sex, ethnicity and socioeconomic deprivation. For all decision trees, age appeared as the most important explanative 'branching' variable in 54% of cases, followed by socioeconomic deprivation (2%) and sex (1%). Ethnicity was not a statistically significant explanatory variable. Where variation did exist, waiting times were longer for younger patients, female patients and those from areas with greater socioeconomic deprivation. Conclusions: According to the approach taken in this study, there is little evidence of significant waiting time inequality dependent on sex, socioeconomic deprivation and ethnicity. Analysis of this nature does not confirm a causal association between younger age and longer waiting time, but instead highlights the need for further explorative analysis. Healthcare managers should be cautious about the use of routine health data and standard analytical methods in efforts to identify health inequalities. [ABSTRACT FROM AUTHOR]

During the last years, the COVID-19 pandemic determined different clinical and radiological scenarios, sometimes difficult to manage, in particular in breast units. On these bases, we tried to understand what we have learned and how to improve the management of breast cancer screening and breast cancer patients.We included a total number of 16 studies. Most published papers about managing breast units during the spread of COVID-19 were editorial, followed by original articles and reviews. Even if the COVID spread followed a bimodal distribution, most papers were published during the first wave, without significant improvement in 2021 and 2022, and were published in journals belonging to general speciality, followed by surgical and radiological journals.One of the most common topics reported in the final included studies is prioritizing patients in the clinical setting according to individual characteristics (first of all, age), risk factors, and time since the last imaging examination. For biopsies, prioritization has been suggested according to the risk of malignant lesions. In the screening setting, this was suspended in most reported studies, also for BRCA+ patients, and then resumed with different modalities according to different centres. Moreover, some proposed the establishment of mobile units for screening or the decentralization of more screening mammograms to smaller clinics or hospital admittance for screening patients via telemedicine.The majority of analyzed papers underlined that all patients, before admittance into the diagnostic rooms, should be screened for suspicious symptoms directly on-site or by asking by phone. In the case of patients with a high suspicion of COVID-19 infection, some papers proposed to delay all breast imaging studies and others to use dedicated departments or areas of the cancer center. In this setting, telemedicine for radiologists has also been suggested. Moreover, other suggestions should be considered: reducing patients' time in the hospital, increasing the distance between patients in the waiting room, and creating additional waiting areas.

Abstract Background Although local initiatives commonly express a wish to improve population health and wellbeing using a population health management (PHM) approach, implementation is challenging and existing tools have either a narrow focus or lack transparency. This has created demand for practice-oriented guidance concerning the introduction and requirements of PHM. Methods Existing knowledge from scientific literature was combined with expert opinion obtained using an adjusted RAND UCLA appropriateness method, which consisted of six Dutch panels in three Delphi rounds, followed by two rounds of validation by an international panel. Results The Dutch panels identified 36 items relevant to PHM, in addition to the 97 items across six elements of PHM derived from scientific literature. Of these 133 items, 101 were considered important and 32 ambiguous. The international panel awarded similar scores for 128 of 133 items, with only 5 items remaining unvalidated. Combining literature and expert opinion gave extra weight and validity to the items. Discussion In developing a maturity index to help assess the use and progress of PHM in health regions, input from experts counterbalanced a previous skewedness of item distribution across the PHM elements and the Rainbow Model of Integrated Care (RMIC). Participant expertise also improved our understanding of successful PHM implementation, as well as how the six PHM elements are best constituted in a first iteration of a maturity index. Limitations included the number of participants in some panels and ambiguity of language. Further development should focus on item clarity, adoption in practice and item interconnectedness. Conclusion By employing scientific literature enriched with expert opinion, this study provides new insight for both science and practice concerning the composition of PHM elements that influence PHM implementation. This will help guide practices in their quest to implement PHM.

At present, the incidence and mortality of primary liver cancer (hereafter referred to as liver cancer) in China are high with heavy economic and disease burden. Standardized screening and health surveillance management for population as risk of liver cancer are important measures to effectively reduce the related burden of liver cancer. Currently, patients with liver cancer in primary care institutions in China lack the awareness of the necessity of liver cancer screening and surveillance with poor compliance, and the existing screening tools are less sensitive and cost-effective. This paper discusses the strategies of liver cancer screening and health surveillance management in primary care institutuons in terms of stratification of liver cancer risk assessment and screening in primary care institutions of chronic liver disease population in China, the current status of enhanced screening and long-term surveillance for population at high risk of liver cancer, to provide a reference for the standardization of screening, early diagnosis and treatment of liver cancer in China, with the aim of improving the screening coverage and control effects of liver cancer in primary care in China.

Background and aimsPatient-reported outcome measures (PROMs) provide a wholesome view of patient well-being. We conducted a retrospective cohort study to evaluate whether PROMs inform risk of unplanned healthcare utilization in patients with IBD.MethodsWe identified adult patients with IBD who completed at least two surveys in a large Internet-based cohort within 1 year. We evaluated the association between baseline patient characteristics, disease activity indices, medication use, and PROMs, assessed using NIH Patient-Reported Outcome Measurement Information System (PROMIS) and subsequent risk of incident hospitalization (at time of first follow-up) within 1 year, and readmission within 1 year (in patients with hospitalization at first follow-up), using multivariable logistic regression.ResultsOf 7902 patients with IBD (45.5 year, 72% females, 63% Crohn's disease), 1377 (17.4%) were hospitalized within 1 year. Among PROMs, pain interference (adjusted OR per 5-point increase in PROMIS, 1.09; 95% CI 1.05-1.14), but not depression, anxiety, fatigue or sleep disturbance, was predictive of higher risk of hospitalization. Prior surgery or hospitalization, symptomatic disease, biologic, and corticosteroid use were also associated with higher risk of hospitalization. Of 521 patients hospitalized with IBD, 133 (25.5%) were readmitted within 1 year. Anxiety and pain interference were predictive of higher risk of readmission, whereas depression was associated with lower risk of readmission.ConclusionsIn a large Internet-based cohort study, PROMs may have a modest effect on modifying risk of unplanned healthcare utilization in patients with IBD, with pain interference being most consistently associated with increased risk of hospitalization and readmission.

Frailty represents an integrative prognostic marker of risk that associates with a myriad of age-related adverse outcomes in older adults. As a concept, frailty can help to target scarce resources and identify subgroups of vulnerable older adults that may benefit from interventions or changes in medical management, such as pursing less aggressive glycaemic targets for frail older adults with diabetes. In practice, however, there are several operational challenges to implementing frailty screening outside the confines of geriatric medicine. Electronic frailty indices (eFIs) based on the theory of deficit accumulation, derived from routine data housed in the electronic health record, have emerged as a rapid, feasible and valid approach to screen for frailty at scale. The goal of this paper is to describe the early experience of three diverse groups in developing, implementing and adopting eFIs (The English National Health Service, US Department of Veterans Affairs and Atrium Health—Wake Forest Baptist). These groups span different countries and organisational complexity, using eFIs for both research and clinical care, and represent different levels of progress with clinical implementation. Using an implementation science framework, we describe common elements of successful implementation in these settings and set an agenda for future research and expansion of eFI-informed initiatives. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic highlighted the United States' lack of a nationwide infrastructure for collecting, sharing, and using health data, especially for secondary uses (e.g., population health management and public health). The federal government is taking several important steps to upgrade the nation's health data ecosystem—notably, the Centers for Disease Control and Prevention's Data Modernization Initiative and the Office of the National Coordinator for Health Information Technology's Trusted Exchange Framework and Common Agreement. However, substantial barriers remain. Inconsistent regulations, infrastructure, and governance across federal and state levels and between states significantly impede the exchange and analysis of health data. Siloed systems and insufficient funding block effective integration of clinical, public health, and social determinants data within and between states. In this analytic essay, we propose strategies to develop a nationwide health data ecosystem. We focus on providing federal guidance and incentives to develop state-designated entities responsible for the collection, integration, and analysis of clinical, public health, social determinants of health, claims, administrative, and other relevant data. These recommendations include a regulatory clearinghouse, federal guidance, model legislation and templated regulation, funding to incentive enterprise architecture, regulatory sandboxes, and a 3-pronged research agenda. (Am J Public Health. 2024;114(2):209–217. https://doi.org/10.2105/AJPH.2023.307477) [ABSTRACT FROM AUTHOR]

Background: Although local initiatives commonly express a wish to improve population health and wellbeing using a population health management (PHM) approach, implementation is challenging and existing tools have either a narrow focus or lack transparency. This has created demand for practice-oriented guidance concerning the introduction and requirements of PHM. Methods: Existing knowledge from scientific literature was combined with expert opinion obtained using an adjusted RAND UCLA appropriateness method, which consisted of six Dutch panels in three Delphi rounds, followed by two rounds of validation by an international panel. Results: The Dutch panels identified 36 items relevant to PHM, in addition to the 97 items across six elements of PHM derived from scientific literature. Of these 133 items, 101 were considered important and 32 ambiguous. The international panel awarded similar scores for 128 of 133 items, with only 5 items remaining unvalidated. Combining literature and expert opinion gave extra weight and validity to the items. Discussion: In developing a maturity index to help assess the use and progress of PHM in health regions, input from experts counterbalanced a previous skewedness of item distribution across the PHM elements and the Rainbow Model of Integrated Care (RMIC). Participant expertise also improved our understanding of successful PHM implementation, as well as how the six PHM elements are best constituted in a first iteration of a maturity index. Limitations included the number of participants in some panels and ambiguity of language. Further development should focus on item clarity, adoption in practice and item interconnectedness. Conclusion: By employing scientific literature enriched with expert opinion, this study provides new insight for both science and practice concerning the composition of PHM elements that influence PHM implementation. This will help guide practices in their quest to implement PHM. [ABSTRACT FROM AUTHOR]

Introduction. With the increasing accessibility of smartphones, their use has been considered in healthcare services. Mobile applications have played a pivotal role in providing health services during COVID-19. This study is aimed at identifying the features, advantages, and disadvantages of health management mobile applications during COVID-19. Methods. This systematic review was conducted in PubMed, Scopus, and Web of Science using the related keywords up to November 2021. The original articles in English about the health management mobile applications in COVID-19 were selected. The study selection was done by two researchers independently according to inclusion and exclusion criteria. Data extraction was done using a data extraction form, and the results were summarized and reported in related tables and figures. Results. Finally, 12 articles were included based on the criteria. The benefits of mobile health applications for health management during COVID-19 were in four themes and 19 subthemes, and the most advantages of the application were in disease management and the possibility of recording information by users, digital tracking of calls, and data confidentiality. Furthermore, the disadvantages of them have been presented in two themes and 14 subthemes. The most common disadvantages are reduced adherence to daily symptom reports, personal interpretation of questions, and result bias. Conclusion. The study results showed that mobile applications have been effective in controlling the prevalence of COVID-19 by identifying virus-infested environments, identifying and monitoring infected people, controlling social distancing, and maintaining quarantine. It is suggested that usability, ethical and security considerations, protection of personal information, and privacy of users be considered in application design and development. [ABSTRACT FROM AUTHOR]

BACKGROUND: Dental caries (cavities) experience is prevalent in US children, and national data show rates to be increasing among young children. Disparities are found for those in the low‐income and non‐Hispanic Black and Hispanic/Latinx groups. Use of caries prevention, specifically dental sealants, is low, even among school‐based programs. CONTRIBUTIONS TO THEORY: A population health management (PHM) framework may support targeted school‐based case management to reduce oral health disparities. PHM‐oriented tools were applied to a school‐based oral health intervention and developed into a conceptual model. From 2014 to 2019, Chicago‐based Oral Health Forum (OHF) developed a case management intervention in schools, utilizing PHM tools. Through programmatic and school‐based partnerships, the PHM tools informed intervention to incorporate community‐based organizations, case management staffing, oral health education, targeted community outreach, and Community Dental Health Coordinators' training. CONCLUSIONS: Through a PHM framework, school‐based oral health partnerships targeting high‐need children was implemented. Use of PHM tools in school‐based health programs should be considered in other high caries schools. [ABSTRACT FROM AUTHOR]

Introduction: Population Health Management (PHM) focusses on keeping the whole population as healthy as possible. As such, it could be a promising approach for longterm health improvement in type 2 diabetes. This scoping review aimed to examine the extent to which and how PHM is used in the care for people with type 2 diabetes. Methods: PubMed, Web of Science, and Embase were searched between January 2000 and September 2021 for papers on self-reported PHM initiatives for type 2 diabetes. Eligible initiatives were described using the analytical framework for PHM. Results: In total, 25 studies regarding 18 PHM initiatives for type 2 diabetes populations were included. There is considerable variation in whether and how the PHM steps are operationalized in existing PHM initiatives. Population identification, impact evaluation, and quality improvement processes were generally part of the PHM initiatives. Triple Aim assessment and risk stratification actions were scarce or explained in little detail. Moreover, cross-sector integration is key in PHM but scarce in practice. Conclusion: Operationalization of PHM in practice is limited compared to the PHM steps described in the analytical framework. Extended risk stratification and integration efforts would contribute to whole-person care and further health improvements within the population. [ABSTRACT FROM AUTHOR]

To introduce a novel next level of care (NLC) protocol used in our breast imaging practice to bypass additional imaging and image-guided biopsy orders and to examine the impact of NLC on breast biopsy wait times compared with thyroid biopsy wait times, which do not use NLC. Our institutional review board deemed this retrospective analysis to be exempt. NLC was implemented for breast imaging in late 2014. Two 6-month periods before and after the COVID-19 shutdown were sampled and compiled. Data were queried from departmental database and electronic health record for all breast and thyroid biopsies during this time. Time to biopsy (TTB) was defined as the number of days from the diagnostic imaging evaluation recommending the biopsy to the completion of the biopsy. To determine the effect of NLC, TTB was compared between breast and thyroid biopsies. Of the 1,114 breast biopsies and 154 thyroid biopsies included, the mean TTB was 9 days (95% confidence interval 8.4-9.3) for breast and 23 days (95% confidence interval 20.5-25.0) for thyroid. There was a 61% reduction in the mean TTB for patients in the breast group compared with patients in the thyroid group. The effect of the NLC was comparable among different races and ethnicities in the breast group, but a significantly higher mean TTB (24% higher, P =.025) was observed for thyroid biopsies in Black patients compared with thyroid biopsies in Hispanic patients. NLC protocol facilitates imaging evaluations and reduces the time interval to image-guided biopsies. [ABSTRACT FROM AUTHOR]

Background: The World Health Organization predicts that the number of older adults will nearly double between 2015 and 2050. Older adults are at a higher risk of developing medical conditions such as chronic pain. However, there is little information about chronic pain and its management in older adults especially those residing in remote and rural areas. Aim: To explore views, experiences, and behavioural determinants of older adults regarding chronic pain management in remote and rural settings in Scottish Highlands. Method: Qualitative one-to-one telephone interviews were conducted with older adults with chronic pain residing in remote and rural areas in the Scottish Highlands. The interview schedule was developed by the researchers, validated, and piloted prior to use. All interviews were audio-recorded, transcribed, and independently thematically-analysed by two researchers. Interviews continued until data saturation. Results: Fourteen interviews were conducted with three key themes emerging: views and experiences with chronic pain, need to enhance pain management, and perceived barriers to pain management. Overall, pain was reported as severe and negatively impacted lives. Majority of interviewees used medicines for pain relief but noted that their pain was still poorly controlled. Interviewees had limited expectation for improvement since they considered their condition a normal consequence of ageing. Residing in remote and rural areas was perceived to complicate access to services with many having to travel long distances to see a health professional. Conclusion: Chronic pain management in remote and rural areas remains a significant issue among older adults interviewed. Thus, there is a need to develop approaches to improve access to related information and services. [ABSTRACT FROM AUTHOR]

Purpose of Review: To review current evidence, discuss key knowledge gaps and identify opportunities for development, validation and application of polysocial risk scores (pSRS) for cardiovascular disease (CVD) risk prediction and population cardiovascular health management. Recent Findings: Limited existing evidence suggests that pSRS are promising tools to capture cumulative social determinants of health (SDOH) burden and improve CVD risk prediction beyond traditional risk factors. However, available tools lack generalizability, are cross-sectional in nature or do not assess social risk holistically across SDOH domains. Available SDOH and clinical risk factor data in large population-based databases are under-utilized for pSRS development. Recent advances in machine learning and artificial intelligence present unprecedented opportunities for SDOH integration and assessment in real-world data, with implications for pSRS development and validation for both clinical and healthcare utilization outcomes. Summary: pSRS presents unique opportunities to potentially improve traditional "clinical" models of CVD risk prediction. Future efforts should focus on fully utilizing available SDOH data in large epidemiological databases, testing pSRS efficacy in diverse population subgroups, and integrating pSRS into real-world clinical decision support systems to inform clinical care and advance cardiovascular health equity. [ABSTRACT FROM AUTHOR]

ABSTRACT OBJECTIVE Describe the implementation of a digital diagnostic and territorial monitoring tool in primary healthcare. METHODS Quantitative and qualitative study, developed in 14 basic healthcare units in São Paulo, with community health workers, coordinators, nurses, and physicians. Data collection occurred in four phases: analysis of the instruments used by the team for territory management; development of the digital tool; training and implementation; and evaluation after 90 days using focus groups. Descriptive analyses were conducted by calculating absolute and relative frequencies to treat quantitative data. Qualitative data were subjected to content analysis. RESULTS Three hundred thirty-four professionals participated in the study. In the first step, territory management’s main challenges were filling out various instruments, system failures, data inconsistency, internet infrastructure/network, and lack of time. Therefore, a digital tool was developed consisting of 1) a spreadsheet recording the number of family members and markers of health conditions, date of visit, and number of return visits; 2) a spreadsheet with a summary of families visited, not visited, and refusals; and 3) a panel with a summary of the data generated instantly. In the evaluation, after the initial use of the tool, the themes that emerged were integration of the tool into daily work, evaluation of the digital tool implementation process, and improvement and opportunities for improvement. CONCLUSIONS Faced with the challenges faced by family healthcare teams when filling out systems and managing the territory, the tool developed provided greater reliability and agility in data visualization, reduced the volume of instruments, and optimized the work process.

ABSTRACT OBJECTIVE Investigate evidence of validity of the Family Vulnerability Scale (EVFAM-BR) as an instrument to support population-based management in primary health care (PHC), in the scope of Health Care Planning (PAS). METHODS This is a psychometric study to assess any additional evidence of the internal structure of EVFAM-BR using confirmatory factor analysis (CFA) and network analysis (NA). A preliminary version of the scale with 38 items was submitted to patients of PHC facilities that use the PAS methodology, distributed across the five regions of Brazil. For the primary CFA data, factor loadings and predictive power (R2) of the item were used. Seven model adjustment indices were adopted and reliability was measured by three indicators, using Bayesian estimation. RESULTS The preliminary version of the scale was applied to 1,255 patients. Using the AFC, factor loadings ranged from 0.66 to 0.90 and R2 from 0.44 to 0.81. Both the primary indicators and the model adequacy indices presented satisfactory and consistent levels. According to the NA, the items were appropriately associated with their peers, respecting the established dimensions, thus demonstrating sustainability and stability of the proposed model. CONCLUSIONS The evidence of validity presented by EVFAM-BR indicates, for the first time in Brazil, a concise instrument that is able to assertively measure family vulnerability, potentially supporting population-based management.