Moral distress and protective work environment for healthcare workers during public health emergencies.

BACKGROUND: Public health emergencies, such as the Covid-19 pandemic, put great pressure on healthcare workers (HCW) across the world, possibly increasing the risk of experiencing ethically challenging situations (ECS). Whereas experiencing ECS as a HCW in such situations is likely unavoidable, mitigation of their adverse effects (e.g., moral distress) is necessary to reduce the risk of long-term negative consequences. One possible route of mitigation of these effects is via work environmental factors. OBJECTIVES: The current study aimed to examine: [1] risk factors associated with ECS among HCW [2], intensity of moral distress associated with ECS across various occupational factors (i.e., profession, degree of exposure to patients with Covid-19), and [3] the impact of work environmental factors on this association, in a sample of HCW during the pandemic. METHODS: We employed multiple logistic and linear regression to self-report data from 977 HCWs at four Norwegian hospitals responding to a survey at the fourth wave of the pandemic. RESULTS: About half of HCW in this study had experienced ECS during the pandemic, and levels of moral distress associated with such were higher than in previous studies using similar assessment methods. Younger age, female sex, geographical work area (mid-north of Norway), and profession (nurse) were all associated with higher odds (range of OR: 1.30-2.59) of experiencing ECS, as were direct contact with patients with Covid-19. Among those participants who reported that they had experienced ECS during the pandemic, moral distress levels when recalling those situations were moderate (Mean 5.7 on a 0-10 scale). Men reported somewhat lower intensity of moral distress (partial eta squared; ηp2 = 0.02). Reporting a manageable workload (ηp2 = 0.02), and greater opportunity to work according to best practice (ηp2 = 0.02), were associated with lower levels of moral distress. CONCLUSIONS: Our findings suggest that moral distress could potentially be mitigated on an organizational level, particularly by focusing on ensuring a manageable workload, and an ability to work according to best practice. To build sustainable healthcare systems robust enough to withstand future public health emergencies, healthcare organizations should implement measures to facilitate these aspects of HCWs' work environment.

Exploring the use of social network analysis methods in process improvement within healthcare organizations: a scoping review.

BACKGROUND: Communication breakdowns among healthcare providers have been identified as a significant cause of preventable adverse events, including harm to patients. A large proportion of studies investigating communication in healthcare organizations lack the necessary understanding of social networks to make meaningful improvements. Process Improvement in healthcare (systematic approach of identifying, analyzing, and enhancing workflows) is needed to improve quality and patient safety. This review aimed to characterize the use of SNA methods in Process Improvement within healthcare organizations. METHODS: Relevant studies were identified through a systematic search of seven databases from inception - October 2022. No limits were placed on study design or language. The reviewers independently charted data from eligible full-text studies using a standardized data abstraction form and resolved discrepancies by consensus. The abstracted information was synthesized quantitatively and narratively. RESULTS: Upon full-text review, 38 unique articles were included. Most studies were published between 2015 and 2021 (26, 68%). Studies focused primarily on physicians and nursing staff. The majority of identified studies were descriptive and cross-sectional, with 5 studies using longitudinal experimental study designs. SNA studies in healthcare focusing on process improvement spanned three themes: Organizational structure (e.g., hierarchical structures, professional boundaries, geographical dispersion, technology limitations that impact communication and collaboration), team performance (e.g., communication patterns and information flow among providers., and influential actors (e.g., key individuals or roles within healthcare teams who serve as central connectors or influencers in communication and decision-making processes). CONCLUSIONS: SNA methods can characterize Process Improvement through mapping, quantifying, and visualizing social relations, revealing inefficiencies, which can then be targeted to develop interventions to enhance communication, foster collaboration, and improve patient safety.

Mind over matter: mindfulness as a buffer against workplace incivility.

This study examines the relationship between co-worker incivility, emotional exhaustion, mindfulness, and turnover intention among nurses in public and private hospitals in North Cyprus. Drawing upon the Job Demand-Resources theory, the research aims to contribute to the existing literature by investigating the mediating role of emotional exhaustion and the moderating effect of mindfulness on the relationship between co-worker incivility and turnover intention. Data were collected from 238 nurses through questionnaires, and structural equation modeling was employed for data analysis. The results indicate a positive association between co-worker incivility and emotional exhaustion, as well as between co-worker incivility and turnover intention. Emotional exhaustion was found to mediate the relationship between co-worker incivility and turnover intention. Furthermore, mindfulness was identified as a moderator, attenuating the negative impact of co-worker incivility on turnover intention. The findings underscore the importance of addressing workplace incivility and promoting mindfulness to mitigate turnover intentions among nurses. Practical implications include the implementation of interventions to foster a supportive work environment and enhance nurses' emotional wellbeing.

Methods and Algorithms of Ensuring Data Privacy in AI-Based Healthcare Systems and Technologies.

This project seeks to devise novel algorithms and techniques leveraged in healthcare to guarantee data privacy in AI-powered systems. To bolster its credibility, the study review presents various modern approaches and technologies used to preserve data privacy of healthcare data. The project conducted an empirical study of the current development in healthcare regarding AI privacy protection to compile a steadfast literature on the subject.

If health organisations and staff engage in research, does healthcare improve? Strengthening the evidence base through systematic reviews.

BACKGROUND: There is an often-held assumption that the engagement of clinicians and healthcare organizations in research improves healthcare performance at various levels. Previous reviews found up to 28 studies suggesting a positive association between the engagement of individuals and healthcare organizations in research and improvements in healthcare performance. The current study sought to provide an update. METHODS: We updated our existing published systematic review by again addressing the question: Does research engagement (by clinicians and organizations) improve healthcare performance? The search covered the period 1 January 2012 to March 2024, in two phases. First, the formal updated search ran from 1 January 2012 to 31 May 2020, in any healthcare setting or country and focussed on English language publications. In this phase two searches identified 66 901 records. Later, a further check of key journals and citations to identified papers ran from May 2020 to March 2024. In total, 168 papers progressed to full-text appraisal; 62 were identified for inclusion in the update. Then we combined papers from our original and updated reviews. RESULTS: In the combined review, the literature is dominated by papers from the United States (50/95) and mostly drawn from the Global North. Papers cover various clinical fields, with more on cancer than any other field; 86 of the 95 papers report positive results, of which 70 are purely positive and 16 positive/mixed, meaning there are some negative elements (i.e. aspects where there is a lack of healthcare improvement) in their findings. CONCLUSIONS: The updated review collates a substantial pool of studies, especially when combined with our original review, which are largely positive in terms of the impact of research engagement on processes of care and patient outcomes. Of the potential engagement mechanisms, the review highlights the important role played by research networks. The review also identifies various papers which consider how far there is a "dose effect" from differing amounts of research engagement. Additional lessons come from analyses of equity issues and negative papers. This review provides further evidence of contributions played by systems level research investments such as research networks on processes of care and patient outcomes.

Trends in the availability of comprehensive services within outpatient substance use treatment facilities from 2018 to 2022.

Background: Little is known regarding the extent to which substance use disorder (SUD) treatment facilities adopt comprehensive services to meet patients' medical and social needs.Objective: To examine trends in the availability of comprehensive services within outpatient SUD treatment facilities from 2018 to 2022.Methods: We used data from the Mental Health and Addiction Treatment Tracking Repository, a national database of SUD treatment facilities (n = 13,793). We examined the availability of four domains of comprehensive services and four types of SUD treatment services from 2018 to 2022. We conducted bivariate and multivariate logistic regression predicting the availability of a comprehensive service model (defined as having at least one service from each service domain), controlling for organizational and community characteristics.Results: Comprehensive services were increasingly offered from 2018 to 2022. In unadjusted and adjusted models, facilities which were externally accredited (OR: 1.50; 95%CI: 1.30-1.74), accepted Medicaid (OR: 1.51; 95%CI: 1.30-1.74), performed community outreach (OR: 2.05; 95%CI: 1.80-2.33), provided naloxone and overdose education (OR: 3.50; 95%CI: 3.06-3.99), had a robust SUD treatment infrastructure (OR: 2.33; 95%CI; 2.08-2.62), and were located in a county with a lower percentage of White residents (OR: 0.99; 95%CI: 0.99-0.99), a higher percentage of residents in poverty (OR: 1.02; 95%CI: 1.00-1.03), and the Northeast compared with the South (OR: 1.21; 95%CI: 1.01-1.45), had significantly higher odds of adopting a comprehensive service model.Conclusion: Findings highlight the importance of factors reflecting experience with organizational change efforts and enhanced external support. Policymakers working to enhance the uptake of comprehensive services should focus on obtaining the financial and technical support necessary to develop these models.

Mitigating Job Burnout in Jordanian Public Healthcare: The Interplay between Ethical Leadership, Organizational Climate, and Role Overload.

In today's dynamic organizational landscape, characterized by rapid technological advancements and evolving workplace dynamics, understanding the factors influencing employee well-being is paramount. This study investigates the interplay between ethical leadership, organizational climate, role overload, and job burnout in public healthcare organizations across northern Jordan. By focusing on ethical leadership, organizational climate, and role overload as determinants of job burnout, this research provides insights into strategies for enhancing employee well-being. Drawing on ethical leadership theory, social exchange theory, and the job demands-resources model, this study employs PLS-SEM to analyze data collected from 260 employees working in Jordanian government hospitals. The findings reveal negative associations between ethical leadership and job burnout, highlighting the importance of ethical leadership behaviors in mitigating employee burnout. Additionally, a positive organizational climate is associated with lower levels of burnout, underscoring the impact of the broader organizational context on employee well-being. The study also explores the mediating role of organizational climate and the moderating effect of role overload in the relationship between ethical leadership and job burnout, providing insights into the complex dynamics at play in healthcare organizations. These findings enrich our understanding of the factors influencing employee well-being in healthcare contexts and underscore the importance of fostering ethical leadership and supportive organizational climates to mitigate job burnout.

Associations between negative patient safety climate and infection prevention practices.

The relationships among positive perceptions of safety climate and better healthcare worker behaviors have been increasingly documented in the literature. The potential influence of negative perceptions is underexplored and has not been examined in relationship to infection prevention practices. We begin to address this gap using data collected as part of a multi-site, cross-sectional study. This brief report describes associations identified between negative perceptions of patient safety climate and standard precaution adherence of hospital-based nurses.

Navigating moral and ethical dilemmas in digital transformation processes within healthcare organizations.

Objective: Healthcare systems around the world face a turbulent and unstable global and local ecosystem that changes daily and impacts the healthcare organization and its workforce. This challenging environment, coupled with economic pressures, is forcing healthcare systems to change and adopt strategic and technological processes to adapt to change at all levels of the system (macro-holistic multi-systemic, mezzo-organizational, and micro-personal). Methods: In this study, through 32 in-depth, semi-structured interviews with healthcare professionals working in public general hospitals in central Israel, we examined, mapped, and highlighted the conflicts and moral dilemmas they have faced in recent years, alongside the processes of strategic, technological, and digital changes that the healthcare system has undergone. Results: The findings from both a categorical-deductive approach and an inductive approach analysis reveals four main themes: innovation paradox, quality and treatment conflict, information and knowledge conflict, and personal needs and values. The themes and sub-themes are sorted across the three levels of the healthcare system. Conclusions: These findings represent a wide range of conflicts and moral dilemmas that arise from the implementation of strategic change and digital transformation, adding to the already numerous ethical issues and moral dilemmas in healthcare and bioethics that are associated with three levels of the system. These challenges and moral conflicts can be barriers to implementing the necessary changes, as well as challenging individuals' internal values, potentially leading to burnout and moral distress. Given the importance of this issue and the intensification of change processes over the next few years, it is up to the management and key stakeholders to implement these processes in a way that addresses the conflicts and challenges that health professionals face. Minimizing the level of challenges and moral distress in the health sector will be to the benefit of the system, its workers, and the patients it serves.

Social support from manager and co-workers in relation to registered nurses' work motivation in three healthcare settings: A cross-sectional study of a Swedish national sample.

BACKGROUND: Having more registered nurses (RNs) leave their workplace, with a shortage of RNs in healthcare as a consequence, might pose a risk to patient safety. According to the Job Demands Resource model, social support is a resource that can enhance work motivation, and if RNs are motivated at work, their willingness to remain in the workplace may increase. OBJECTIVE: The aims were to explore (1) differences in RNs' experiences of social support from their immediate manager and co-workers between different healthcare settings, (2) associations between RNs' experiences of social support and aspects of work motivation, and (3) if these associations differed in strength between healthcare settings. DESIGN: A cross-sectional study design. METHODS: A stratified population of Swedish RNs, n = 2290, working in either hospitals, primary care, or home healthcare, responded to a survey in 2022. Chi-squared tests and linear and logistic regression analyses were used to analyze the data. Interaction was measured by adding an interaction term to the fully adjusted regression models. The findings' generalizability was strengthened by including calibrating weights in all analyses. RESULTS: RNs in primary care reported higher social support from their immediate manager than RNs in hospitals and home healthcare. RNs in home healthcare reported lower social support from co-workers than RNs in hospitals and primary care. There were statistically significant associations between higher levels of social support from the immediate manager and co-workers, respectively, and higher ratings in all aspects of work motivation: work engagement (manager: beta coefficient [b] = 0.08, confidence interval [CI] 95% = 0.05; 0.10; co-workers: b = 0.12, CI 95% = 0.08; 0.16), job satisfaction (manager: b = 0.24, CI 95% = 0.21; 0.27; co-workers: b = 0.22, CI 95% = 0.16; 0.28), opportunities to provide high-quality care (manager: b = 0.15, CI 95% = 0.11; 0.18; co-workers: b = 0.19, CI 95% = 0.13; 0.24), satisfaction with the employer (manager: b = 0.46, CI 95% = 0.42; 0.50; co-workers: not statistically significant) and intention to remain at the workplace (manager: odds ratio = 1.89, CI 95% = 1.69; 2.13; co-workers: odds ratio = 1.42, CI 95% = 1.17; 1.72). The associations differed in strength between hospitals, primary care, and home healthcare. CONCLUSIONS: Strengthening social support from the immediate manager and co-workers appears to be a way to increase RNs' work motivation, including their intention to remain at the workplace. This may be important, particularly in primary care and home healthcare. CLINICAL RELEVANCE: To strengthen RNs' work motivation and willingness to stay in the workplace, it appears important for healthcare organizations to provide RN social support.

Artificial intelligence in the healthcare sector: comparison of deep learning networks using chest X-ray images.

Purpose: Artificial intelligence has led to significant developments in the healthcare sector, as in other sectors and fields. In light of its significance, the present study delves into exploring deep learning, a branch of artificial intelligence. Methods: In the study, deep learning networks ResNet101, AlexNet, GoogLeNet, and Xception were considered, and it was aimed to determine the success of these networks in disease diagnosis. For this purpose, a dataset of 1,680 chest X-ray images was utilized, consisting of cases of COVID-19, viral pneumonia, and individuals without these diseases. These images were obtained by employing a rotation method to generate replicated data, wherein a split of 70 and 30% was adopted for training and validation, respectively. Results: The analysis findings revealed that the deep learning networks were successful in classifying COVID-19, Viral Pneumonia, and Normal (disease-free) images. Moreover, an examination of the success levels revealed that the ResNet101 deep learning network was more successful than the others with a 96.32% success rate. Conclusion: In the study, it was seen that deep learning can be used in disease diagnosis and can help experts in the relevant field, ultimately contributing to healthcare organizations and the practices of country managers.

Psychosocial factors contributing to value creation in value-based healthcare: a scoping review.

Background: Healthcare systems constantly evolve to improve care quality and resource utilization. One way is implementing Value-Based Healthcare (VBHC) an economic approach. This scoping review aims to identify and describe the literature on VBHC, particularly its psychosocial aspects, to uncover research gaps. Method: The review followed the PRISMA guidelines for Scoping Reviews. We took the following 14 steps: (a) defining the research question; (b) identifying relevant studies; (c) selecting studies; (d) 15 mapping data; (e) collecting, synthesizing and reporting results. A detailed Boolean search was conducted from January 2021 to August 31, 2021, across APA PsycINFO and PubMed databases using keywords such as "Value-Based Healthcare" and "psychosocial perspective." Initially, three reviewers screened 70 e-records independently, assessing titles, abstracts, and full-text against the inclusion criteria. Discrepancies regarding the evaluation of the articles were resolved through consensus sessions between the reviewers. Results: The final review included 14 relevant e-records in English from peer-reviewed sources, focusing on quantitative and qualitative research. From the analysis, four areas emerged: (1) Value chains in Healthcare; (2) Styles, activities, and practices of value co-creation in Healthcare; (3) Value co-creation in the encounter process; (4) Value co-creation in preventive health services. Conclusion: The scoping review findings suggest several potential key aspects, including the interdependence between patients and healthcare organizations, organizational culture in healthcare, and the role of patient-centered approaches that focus on relationships, communication, and social support in healthcare. This can be achieved through patient engagement, patient-centered care and communication, health literacy, psychosocial support services, comprehensive psychosocial assessments, care coordination, and continuity of care. Integrating psychosocial elements in VHBC enhances quality and optimizes resource use. Findings highlight the need to develop practical guidance on how to implement a culture of value in care that takes into account the psychosocial aspects that have emerged, but not fully addressed. The pandemic teaches that the workforce poorly receives sudden and unsystematic changes. This review could provide an initial basis for the redesign of value in healthcare and a paradigm shift that has already begun with patient-centered medicine and patient engagement.

The Diversity Compass: a clinical ethics support instrument for dialogues on diversity in healthcare organizations.

BACKGROUND: Increasing social pluralism adds to the already existing variety of heterogeneous moral perspectives on good care, health, and quality of life. Pluralism in social identities is also connected to health and care disparities for minoritized patient (i.e. care receiver) populations, and to specific diversity-related moral challenges of healthcare professionals and organizations that aim to deliver diversity-responsive care in an inclusive work environment. Clinical ethics support (CES) services and instruments may help with adequately responding to these diversity-related moral challenges. However, although various CES instruments exist to support healthcare professionals with dealing well with morally challenging situations in healthcare, current tools do not address challenges specifically related to moral pluralism and intersectional aspects of diversity and social justice issues. This article describes the content and developmental process of a novel CES instrument called the Diversity Compass. This instrument was designed with and for healthcare professionals to dialogically address and reflect on moral challenges related to intersectional aspects of diversity and social justice issues that they experience in daily practice. METHODS: We used a participatory development design to develop the Diversity Compass at a large long-term care organization in a major city in the Netherlands. Over a period of thirteen months, we conducted seven focus groups with healthcare professionals and peer-experts, carried out five expert interviews, and facilitated four meetings with a community of practice consisting of various healthcare professionals who developed and tested preliminary versions of the instrument throughout three cycles of iterative co-creation. RESULTS: The Diversity Compass is a practical, dialogical CES instrument that is designed as a small booklet and includes an eight-step deliberation method, as well as a guideline with seven recommendations to support professionals with engaging in dialogue when they are confronted with diversity-related moral challenges. The seven recommendations are key components in working toward creating an inclusive and safe space for dialogue to occur. CONCLUSIONS: The Diversity Compass seeks to support healthcare professionals and organizations in their efforts to facilitate awareness, moral learning and joint reflection on moral challenges related to diversity and social justice issues. It is the first dialogical CES instrument that specifically acknowledges the role of social location in shaping moral perspectives or experiences with systemic injustices. However, to make healthcare more just, an instrument like the Diversity Compass is not enough on its own. In addition to the Diversity Compass, a systemic and structural approach to social justice issues in healthcare organizations is needed in order to foster a more inclusive, safe and diversity-responsive care and work environment in health care organizations.

Innovation Diffusion Across 13 Specialties and Associated Clinician Characteristics.

Diffusion of innovations, defined as the adoption and implementation of new ideas, processes, products, or services in health care, is both particularly important and especially challenging. One known problem with adoption and implementation of new technologies is that, while organizations often make innovations immediately available, organizational actors are more wary about adopting new technologies because these may impact not only patients and practices but also reimbursement. As a result, innovations may remain underutilized, and organizations may miss opportunities to improve and advance. As innovation adoption is vital to achieving success and remaining competitive, it is important to measure and understand factors that impact innovation diffusion. Building on a survey of a national sample of 654 clinicians, our study measures the extent of diffusion of value-enhancing care delivery innovations (i.e., technologies that not only improve quality of care but has potential to reduce care cost by diminishing waste, Faems et al., 2010) for 13 clinical specialties and identifies healthcare-specific individual characteristics such as: professional purview, supervisory responsibility, financial incentive, and clinical tenure associated with innovation diffusion. We also examine the association of innovation diffusion with perceived value of one type of care delivery innovation - artificial intelligence (AI) - for assisting clinicians in their clinical work. Responses indicate that less than two-thirds of clinicians were knowledgeable about and aware of relevant value-enhancing care delivery innovations. Clinicians with broader professional purview, more supervisory responsibility, and stronger financial incentives had higher innovation diffusion scores, indicating greater knowledge and awareness of value-enhancing, care delivery innovations. Higher levels of knowledge of the innovations and awareness of their implementation were associated with higher perceptions of the value of AI-based technology. Our study contributes to our knowledge of diffusion of innovation in healthcare delivery and highlights potential mechanisms for speeding innovation diffusion.

Back to the Future: What Healthcare Organizations Need to Thrive in the Face of Persistent Environmental Uncertainty.

While uncertainty has always been a feature of the healthcare environment, its pace and scope are rapidly increasing, fueled by myriad factors such as technological advancements, the threat and frequency of disruptive events, global economic developments, and increasing complexity. Contemporary healthcare organizations thus persistently face what is known as "deep uncertainty," which obscures their ability to predict outcomes of strategic action and decision-making, presenting them with novel challenges and threatening their survival. Persistent, deep uncertainty challenges us to revisit and reconsider how we think about uncertainty and the strategic actions needed by organizations to thrive under these circumstances. Simply put, how can healthcare organizations thrive in the face of deeply uncertain environments? We argue that healthcare organizations need to employ both adaptive and creative strategic approaches in order to effectively meet patients' needs and capture value in the long-term future. The chapter concludes by offering two ways organizations can build the dynamic capabilities needed to employ such approaches.

Examining alignment of community health teams' preferences for health, equity, and spending with state all-payer waiver priorities: A discrete choice experiment.

OBJECTIVE: The state of Vermont has a statewide waiver from the centers for medicare and medicaid services to allow all-payer Accountable Care Organizations (ACOs). The Vermont all-payer model (VAPM) waiver is layered upon previous reforms establishing regional community health teams (CHTs) and medical homes. The waiver is intended to incentivize healthcare value and quality and create alignment between health system payers, providers, and CHTs. The objective of this study was to examine CHT's trade-offs and preferences for health, equity, and spending and the alignment with VAPM priorities. DATA SOURCES/STUDY SETTING: Data were gathered from a survey and discrete choice experiment among CHT leadership and CHT team members of the 13 CHTs in Vermont. STUDY DESIGN: We used conditional logit models to model the choice as a function of its characteristics (attributes) and mixed logit models to analyze whether preferences for programs varied by persons and roles within CHTs. DATA COLLECTION/EXTRACTION METHODS: There were 60 respondents who completed the survey online with 14 choice tasks, with three program options in each task, for a total sample size of 2520. PRINCIPAL FINDINGS: We found that CHTs prioritized programs in the community health plan and those with quantitative evidence of effectiveness. They were less likely to choose either programs targeting racial and ethnic minorities or programs having a small effect on a large population. Preferences did not vary across individual or community attributes. Program priorities of the VAPM, especially healthcare spending, were not prioritized. CONCLUSIONS: The results suggest that the new VAPM does not automatically create system alignment: CHTs tended to prioritize local needs and voices. The statewide priorities are less important to CHTs, which have excellent internal alignment. This creates potential disconnection between state and community health goals. However, CHTs and the VAPM prioritize similar populations, indicating an opportunity to increase alignment by allowing flexible programs tailored to local needs. CHTs also prioritized programs with a strong evidence base, suggesting another potential avenue to create system alignment.

Financing community partnerships for health equity: Findings and insights from cross-sector professionals.

OBJECTIVE: To enhance understanding of financial alignment challenges facing cross-sector partnerships (CSPs) pursuing health equity and offer insights to guide research and practice. DATA SOURCES AND STUDY SETTING: We collected data through surveys and interviews with cross-sector professionals in 16 states, 2020-2021. STUDY DESIGN: We surveyed 51 CSP leaders and received 26 responses. Following administration of the surveys to CSP leaders, we also conducted interviews with cross-sector professionals. The data are analyzed descriptively, comparatively, and qualitatively using thematic analysis. DATA COLLECTION/EXTRACTION METHODS: For quantitative survey data, we compare partnership responses, differentiating perceived levels of alignment among partnerships certified by the Pathways Community HUB Institute (PCHI), partnerships interested in certification, and partnerships without connection to the PCHI® Model of care coordination. For interviews, we engaged CSP professionals and those who fund their work. Two research team members took notes for interviews, which were combined and made available for review by those interviewed. Data were analyzed independently by two team members who met to integrate, identify, and finalize thematic findings. PRINCIPAL FINDINGS: Our work supports previous findings that financing is a challenge for CSPs, while also suggesting that PCHI-certified partnerships may perceive greater progress in financial alignment than others. We identify four major financial barriers: limited and competitive funding; state health service delivery structures; cultural and practice divides across healthcare, social service, and public health sectors; and needs for further evidence of cross-sector service impacts on client health and costs. We also offer a continuum of measures of financial sustainability progress and identify key issues relating to financial incentivization/accountability. CONCLUSION: Findings suggest a need for public policy reviews and improvements to aid CSPs in addressing financial alignment challenges. We also offer a measurement framework and ideas to guide research and practice on financial alignment, based on empirical data.

Determinants of referral network size for screening colonoscopies in the Veterans Health Administration after the implementation of the MISSION Act.

OBJECTIVE: To measure key characteristics of the Veterans Health Administration's (VHA) Community Care (CC) referral network for screening colonoscopy and identify market and institutional factors associated with network size. DATA SOURCES: VHA electronic health records, CC claim data, and National Plan and Provider Enumeration System. STUDY DESIGN: In this retrospective cross-sectional study, we measure the size of the VHA's CC referral networks over time and by VHA parent facility (n = 137). We used a multivariable linear regression to identify factors associated with network size at the market-year level. Network size was measured as the number of physicians who performed at least one VHA-purchased screening colonoscopy per 1000 enrollees at baseline. DATA EXTRACTION: Data were extracted for all Veterans (n = 102,119) who underwent a screening colonoscopy purchased by the VHA from a non-VHA physician from 2018 to 2021. PRINCIPAL FINDINGS: From 2018 to 2021, median network volume of screening colonoscopies per 1000 enrollees grew from 1.6 (IQR: 0.6, 4.6) to 3.6 (IQR: 1.6, 6.6). The median network size grew from 0.63 (IQR: 0.30, 1.26) to 0.92 (IQR: 0.57, 1.63). Finally, the median procedures per physician increased from 2.5 (IQR: 1.6, 4.2) to 3.2 (IQR: 2.4, 4.7). After adjusting for baseline market characteristics, volume of screening colonoscopies was positively related to network size (ß = 0.15, 95% CI: [0.10, 0.20]), negatively related to procedures per physician (ß = -0.12, 95% CI: [-0.18, -0.05]), and positively associated with the percent of rural enrollees (ß = 0.01, 95% CI: [0.00, 0.01]). CONCLUSIONS: VHA facilities with a higher volume of VHA-purchased screening colonoscopies and more rural enrollees had more non-VHA physicians providing care. Geographic variation in referral networks may also explain differences in the effects of the MISSION Act on access to care and patient outcomes.

From Ties to Events in the Analysis of Interorganizational Exchange Relations.

Relational event models expand the analytical possibilities of existing statistical models for interorganizational networks by: (i) making efficient use of information contained in the sequential ordering of observed events connecting sending and receiving units; (ii) accounting for the intensity of the relation between exchange partners, and (iii) distinguishing between short- and long-term network effects. We introduce a recently developed relational event model (REM) for the analysis of continuously observed interorganizational exchange relations. The combination of efficient sampling algorithms and sender-based stratification makes the models that we present particularly useful for the analysis of very large samples of relational event data generated by interaction among heterogeneous actors. We demonstrate the empirical value of event-oriented network models in two different settings for interorganizational exchange relations-that is, high-frequency overnight transactions among European banks and patient-sharing relations within a community of Italian hospitals. We focus on patterns of direct and generalized reciprocity while accounting for more complex forms of dependence present in the data. Empirical results suggest that distinguishing between degree- and intensity-based network effects, and between short- and long-term effects is crucial to our understanding of the dynamics of interorganizational dependence and exchange relations. We discuss the general implications of these results for the analysis of social interaction data routinely collected in organizational research to examine the evolutionary dynamics of social networks within and between organizations.

DEPLOYR: a technical framework for deploying custom real-time machine learning models into the electronic medical record.

OBJECTIVE: Heatlhcare institutions are establishing frameworks to govern and promote the implementation of accurate, actionable, and reliable machine learning models that integrate with clinical workflow. Such governance frameworks require an accompanying technical framework to deploy models in a resource efficient, safe and high-quality manner. Here we present DEPLOYR, a technical framework for enabling real-time deployment and monitoring of researcher-created models into a widely used electronic medical record system. MATERIALS AND METHODS: We discuss core functionality and design decisions, including mechanisms to trigger inference based on actions within electronic medical record software, modules that collect real-time data to make inferences, mechanisms that close-the-loop by displaying inferences back to end-users within their workflow, monitoring modules that track performance of deployed models over time, silent deployment capabilities, and mechanisms to prospectively evaluate a deployed model's impact. RESULTS: We demonstrate the use of DEPLOYR by silently deploying and prospectively evaluating 12 machine learning models trained using electronic medical record data that predict laboratory diagnostic results, triggered by clinician button-clicks in Stanford Health Care's electronic medical record. DISCUSSION: Our study highlights the need and feasibility for such silent deployment, because prospectively measured performance varies from retrospective estimates. When possible, we recommend using prospectively estimated performance measures during silent trials to make final go decisions for model deployment. CONCLUSION: Machine learning applications in healthcare are extensively researched, but successful translations to the bedside are rare. By describing DEPLOYR, we aim to inform machine learning deployment best practices and help bridge the model implementation gap.