Opportunities for Consistent and Holistic Metrics to Support Food Systems Transformation: A Summary of a Symposium Presented at Nutrition 2023.

There is an urgent need for global food systems transformation to realize a future where planetary health reaches its full potential. Paramount to this vision is the ability of stakeholders across sectors to understand how foods and dietary patterns impact food systems inclusive of all domains of sustainability-environmental, nutrition/health, economic and social. This article is a synopsis of presentations by 3 food systems experts to share the latest science in a session entitled "How do you measure sustainability? Opportunities for consistent and holistic metrics to support food systems transformation" at the American Society for Nutrition's 2023 annual conference. As summarized here, global population data showing widespread malnutrition underscore the important role of dietary diversity through a balance of plant- and animal-source foods to achieve nutritionally adequate diets and reduce risk of noncommunicable diseases. Yet, recent international audits of countries, companies, and organizations and their sustainability targets largely demonstrate an underrepresentation of robust nutrition/health metrics to support public nutrition and health progress. Addressing limitations in diet-sustainability modeling systems provides a viable opportunity to accurately reflect the important contributions and trade-offs of diets across all domains of sustainability to ultimately support evidence-based decision making in advancing healthy food systems.

Perceptions and experiences of undergraduate medical students regarding social accountability: a cross-sectional study at a Subsaharan African medical school.

BACKGROUND: Medical schools are called to be socially accountable by medical education and healthcare system stakeholders. Social accountability is a feature of excellent medical education. Medical students are essential to the development of socially accountable medical schools. Therefore, understanding the perceptions and experiences of medical students regarding social accountability is critical for efforts to improve social accountability practices and outcomes. METHODS: This cross-sectional online questionnaire-based survey used Google Forms and involved medical students in their fourth and fifth years of study at the Makerere University School of Medicine. The survey was conducted between September 2022 and October 2023. We used a study questionnaire and a validated toolkit designed by students as part of The Training for Health Equity Collaborative to gauge a school's progress towards social accountability in medical schools to collect data on demographics, perceptions and experiences and evaluate social accountability. RESULTS: Out of 555 eligible medical students, 426 responded to the online questionnaire. The response rate was 77%. The mean age of the students was 25.24 ± 4.4 years. Almost three fourths of the students were male (71.3%), and slightly less than two thirds were in their fourth year of study (65%). Almost half of the students (48.1%%) evaluated the school as doing well with regard to social accountability. The evaluation items referring to community-based research and positive impact on the community had the highest mean scores. Only 6 (3.6%) students who reported hearing of social accountability had a clear understanding of social accountability. Students receiving career guidance in secondary school was associated with evaluating social accountability in the medical school as strong (p-0.003). CONCLUSIONS: Medical students evaluated the medical school favorably forsocial accountability despite lacking a clear understanding of social accountability. Receiving career guidance in secondary school was significantly associated with a positive evaluation of social accountability.

Insider Threats to the Military Health System: A Systematic Background Check of TRICARE West Providers.

Background: To address the pandemic, the Defense Health Agency (DHA) expanded its TRICARE civilian provider network by 30.1%. In 2022, the DHA Annual Report stated that TRICARE's provider directories were only 80% accurate. Unlike Medicare, the DHA does not publicly reveal National Provider Identification (NPI) numbers. As a result, TRICARE's 9.6 million beneficiaries lack the means to verify their doctor's credentials. Since 2013, the Department of Health and Human Services' (HHS) Office of Inspector General (OIG) has excluded 17,706 physicians and other providers from federal health programs due to billing fraud, neglect, drug-related convictions, and other offenses. These providers and their NPIs are included on the OIG's List of Excluded Individuals and Entities (LEIE). Patients who receive care from excluded providers face higher risks of hospitalization and mortality. Objective: We sought to assess the extent to which TRICARE screens health care provider names on their referral website against criminal databases. Methods: Between January 1-31, 2023, we used TRICARE West's provider directory to search for all providers within a 5-mile radius of 798 zip codes (38 per state, ≥10,000 residents each, randomly entered). We then copied and pasted all directory results' first and last names, business names, addresses, phone numbers, fax numbers, degree types, practice specialties, and active or closed statuses into a CSV file. We cross-referenced the search results against US and state databases for medical and criminal misconduct, including the OIG-LEIE and General Services Administration's (GSA) SAM.gov exclusion lists, the HHS Office of Civil Rights Health Insurance Portability and Accountability Act (HIPAA) breach reports, 15 available state Medicaid exclusion lists (state), the International Trade Administration's Consolidated Screening List (CSL), 3 Food and Drug Administration (FDA) debarment lists, the Federal Bureau of Investigation's (FBI) list of January 6 federal defendants, and the OIG-HHS list of fugitives (FUG). Results: Our provider search yielded 111,619 raw results; 54 zip codes contained no data. After removing 72,156 (64.65%) duplicate entries, closed offices, and non-TRICARE West locations, we identified 39,463 active provider names. Within this baseline sample group, there were 2398 (6.08%) total matches against all exclusion and sanction databases, including 2197 on the OIG-LEIE, 2311 on the GSA-SAM.gov list, 2 on the HIPAA list, 54 on the state Medicaid exclusion lists, 69 on the CSL, 3 on the FDA lists, 53 on the FBI list, and 10 on the FUG. Conclusions: TRICARE's civilian provider roster merits further scrutiny by law enforcement. Following the National Institute of Standards and Technology 800, the DHA can mitigate privacy, safety, and security clearance threats by implementing an insider threat management model, robust enforcement of the False Claims Act, and mandatory security risk assessments. These are the views of the author, not the Department of Defense or the US government.

Malaria elimination: situation analysis of cases in India, the state of Madhya Pradesh in central India, and district Mandla of Madhya Pradesh.

India contributed approximately 66% of the malaria cases in the WHO South-East Asia region in 2022. In India, approximately 44% of cases have been reported to be disproportionately contributed by approximately 27 districts. A comparative analysis of reported malaria cases between January 2017 and December 2022 was performed in Mandla district, which is the site of a model malaria elimination demonstration project (MEDP) in Madhya Pradesh (MP), India. Compared to 2017, the decrease in malaria cases in Mandla from 2018 to 2022 was higher than MP and the rest of the country. The reduction of cases was significant in 2018, 2019, and 2021 (p < 0.01) (Mandla vs. MP) and was highly significant during 2018-2022 (p < 0.001) (Mandla vs. India). Robust surveillance and real-time data-based decisions accompanied by appropriate management, operational controls, and independent reviews, all designed for resource optimisation, were the reasons for eliminating indigenous malaria in Mandla district. The increase in infection rates during the months immediately following rains suggests that surveillance, vector control, and case management efforts should be specifically intensified for eliminating imported and indigenous cases in the near-elimination districts to work towards achieving the national elimination goal of 2030.

How Health Professionals Identify and Respond to Perpetrators of Domestic and Family Violence in a Hospital Setting: A Scoping Review.

There is heightened awareness that a whole-of-systems approach to perpetrator responses is key to addressing domestic and family violence (DFV). This paper reports on the findings from a scoping review which mapped the international literature on how health professionals identify and respond to perpetrators of DFV within a hospital setting. A comprehensive scoping review methodology was used. The search, spanning January 2010 to January 2022, yielded 12,380 publications from four databases. Eligibility for inclusion included peer-reviewed literature with any reference to inpatient hospital health professionals identifying or responding to perpetrators of DFV. Fourteen articles were included in the final review. The review presents the literature categorized by levels of prevention, from primary, secondary, through to tertiary preventive interventions. An additional category "other practices" is added to capture practices which did not fit into existing levels. Despite glimpses into how health professionals can identify, and respond to perpetrators of DFV, the current knowledge base is sparse. The review did not identify any mandated or formal procedures for identifying and/screening or responding to perpetration of abuse in hospitals. Rather, responses to perpetrators are inconsistent and rely on the motivation, skill, and self-efficacy of health professionals rather than an embedded practice that is driven and informed by hospital policy or procedures. The literature paints a picture of missed opportunities for meaningful work with perpetrators of DFV in a hospital setting and highlights a disjuncture between policy and practice.

Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals.

As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for maximizing benefits while mitigating potential pitfalls. This paper explores the evolving relationship among clinician trust in LLMs, the transition of data sources from predominantly human-generated to artificial intelligence (AI)-generated content, and the subsequent impact on the performance of LLMs and clinician competence. One of the primary concerns identified in this paper is the LLMs' self-referential learning loops, where AI-generated content feeds into the learning algorithms, threatening the diversity of the data pool, potentially entrenching biases, and reducing the efficacy of LLMs. While theoretical at this stage, this feedback loop poses a significant challenge as the integration of LLMs in health care deepens, emphasizing the need for proactive dialogue and strategic measures to ensure the safe and effective use of LLM technology. Another key takeaway from our investigation is the role of user expertise and the necessity for a discerning approach to trusting and validating LLM outputs. The paper highlights how expert users, particularly clinicians, can leverage LLMs to enhance productivity by off-loading routine tasks while maintaining a critical oversight to identify and correct potential inaccuracies in AI-generated content. This balance of trust and skepticism is vital for ensuring that LLMs augment rather than undermine the quality of patient care. We also discuss the risks associated with the deskilling of health care professionals. Frequent reliance on LLMs for critical tasks could result in a decline in health care providers' diagnostic and thinking skills, particularly affecting the training and development of future professionals. The legal and ethical considerations surrounding the deployment of LLMs in health care are also examined. We discuss the medicolegal challenges, including liability in cases of erroneous diagnoses or treatment advice generated by LLMs. The paper references recent legislative efforts, such as The Algorithmic Accountability Act of 2023, as crucial steps toward establishing a framework for the ethical and responsible use of AI-based technologies in health care. In conclusion, this paper advocates for a strategic approach to integrating LLMs into health care. By emphasizing the importance of maintaining clinician expertise, fostering critical engagement with LLM outputs, and navigating the legal and ethical landscape, we can ensure that LLMs serve as valuable tools in enhancing patient care and supporting health care professionals. This approach addresses the immediate challenges posed by integrating LLMs and sets a foundation for their maintainable and responsible use in the future.

Ethics guidelines for environmental epidemiologists: 2023 revision.

Recognition of the importance to environmental epidemiology of ethical and philosophical deliberation led, in 1996, to the establishment of Ethics Guidelines for the profession. In 1999, these guidelines were adopted by the International Society for Environmental Epidemiology. The guidelines were revised in 2012 and again in 2023 to ensure continued relevance to the major issues facing the field. Comprising normative standards of professional conduct, the guidelines are structured into four subsections: (1) obligations to individuals and communities who participate in research; (2) obligations to society; (3) obligations regarding funders/sponsors and employers; and (4) obligations to colleagues. Through the 2023 revision of the Ethics Guidelines, the International Society for Environmental Epidemiology seeks to ensure the highest possible standards of transparency and accountability for the ethical conduct of environmental epidemiologists engaged in research and public health practice.

Iranian and Turkish EFL instructors' Critical Openness, Reflective Skepticism, Innovative Thinking and Accountability: A comparative study.

The increasing interest in Turkish educational programs has led to the increasing interest in educational migration among the younger Iranian generations. Instructors, as the executive part of educational programs, can also play a key role in satisfying students' expectations and educational goals. The aim of this study was to identify and compare the Critical Openness (CO), Reflective Skepticism (RS), innovative thinking (IT), external accountability (EA), and internal accountability (IA) for the Iranian and Turkish English as Foreign Language (EFL) instructors through an online survey with Critical Thinking Theory and the 21st century skill consideration lens. To this end, a convenient sample of Iranian (N = 286) and Turkish (N = 281) EFL instructors were invited to take part in the online survey voluntarily. The scales consisted of the Likert scales of Rosenblatt (2017) [1], Semerci (2007) [2], and Sosu (2013) [3], because the conceptual frameworks were also taken from these studies. In the analysis stage, MANOVA was conducted to compare the results of the online survey between Iranian and Turkish EFL instructors in terms of their level of CO, RS, IT, EA, and IA. The analysis of the collected data uncovered that Turkish EFL instructors got higher scores in CO, RS, EA, and IA than Iranian EFL instructors while Iranian EFL instructors received higher scores in the employment of IT. The implications of the results would suggest collaborations between educational policymakers and teacher training course designers.

Toward Fairness, Accountability, Transparency, and Ethics in AI for Social Media and Health Care: Scoping Review.

BACKGROUND: The use of social media for disseminating health care information has become increasingly prevalent, making the expanding role of artificial intelligence (AI) and machine learning in this process both significant and inevitable. This development raises numerous ethical concerns. This study explored the ethical use of AI and machine learning in the context of health care information on social media platforms (SMPs). It critically examined these technologies from the perspectives of fairness, accountability, transparency, and ethics (FATE), emphasizing computational and methodological approaches that ensure their responsible application. OBJECTIVE: This study aims to identify, compare, and synthesize existing solutions that address the components of FATE in AI applications in health care on SMPs. Through an in-depth exploration of computational methods, approaches, and evaluation metrics used in various initiatives, we sought to elucidate the current state of the art and identify existing gaps. Furthermore, we assessed the strength of the evidence supporting each identified solution and discussed the implications of our findings for future research and practice. In doing so, we made a unique contribution to the field by highlighting areas that require further exploration and innovation. METHODS: Our research methodology involved a comprehensive literature search across PubMed, Web of Science, and Google Scholar. We used strategic searches through specific filters to identify relevant research papers published since 2012 focusing on the intersection and union of different literature sets. The inclusion criteria were centered on studies that primarily addressed FATE in health care discussions on SMPs; those presenting empirical results; and those covering definitions, computational methods, approaches, and evaluation metrics. RESULTS: Our findings present a nuanced breakdown of the FATE principles, aligning them where applicable with the American Medical Informatics Association ethical guidelines. By dividing these principles into dedicated sections, we detailed specific computational methods and conceptual approaches tailored to enforcing FATE in AI-driven health care on SMPs. This segmentation facilitated a deeper understanding of the intricate relationship among the FATE principles and highlighted the practical challenges encountered in their application. It underscored the pioneering contributions of our study to the discourse on ethical AI in health care on SMPs, emphasizing the complex interplay and the limitations faced in implementing these principles effectively. CONCLUSIONS: Despite the existence of diverse approaches and metrics to address FATE issues in AI for health care on SMPs, challenges persist. The application of these approaches often intersects with additional ethical considerations, occasionally leading to conflicts. Our review highlights the lack of a unified, comprehensive solution for fully and effectively integrating FATE principles in this domain. This gap necessitates careful consideration of the ethical trade-offs involved in deploying existing methods and underscores the need for ongoing research.

Co-worker unprofessional behaviour and patient safety risks: an analysis of co-worker reports across eight Australian hospitals.

A key component of professional accountability programmes is online reporting tools that allow hospital staff to report co-worker unprofessional behaviour. Few studies have analysed data from these systems to further understand the nature or impact of unprofessional behaviour amongst staff. Ethos is a whole-of-hospital professional accountability programme that includes an online messaging system. Ethos has now been implemented across multiple Australian hospitals. This study examined reported unprofessional behaviour that staff indicated created a risk to patient safety. This study included 1310 Ethos submissions reporting co-worker unprofessional behaviour between 2017 and 2020 across eight Australian hospitals. Submissions that indicated the behaviour increased the risk to patient safety were identified. Descriptive summary statistics were presented for reporters and subjects of submissions about unprofessional behaviour. Logistic regression was applied to examine the association between each unprofessional behaviour (of the six most frequently reported in the Ethos submissions) and patient safety risk reported in the submissions. The descriptions in the reports were reviewed and the patient safety risks were coded using a framework aligned with the World Health Organization's International Classification for Patient Safety. Of 1310 submissions about unprofessional behaviour, 395 (30.2%) indicated that there was a risk to patient safety. Nurses made the highest number of submissions that included a patient safety risk [3.47 submissions per 100 nursing staff, 95% confidence interval (CI): 3.09-3.9] compared to other professional groups. Medical professionals had the highest rate as subjects of submissions for unprofessional behaviour with a patient safety risk (5.19 submissions per 100 medical staff, 95% CI: 4.44-6.05). 'Opinions being ignored' (odds ratio: 1.68; 95% CI: 1.23-2.22; P < .001) and 'someone withholding information which affects work performance' were behaviours strongly associated with patient safety risk in the submissions (odds ratio: 2.50; 95% CI: 1.73-3.62; P < .001) compared to submissions without a patient safety risk. The two main types of risks to patient safety described were related to clinical process/procedure and clinical administration. Commonly reported events included staff not following policy or protocol; doctors refusing to review a patient; and interruptions and inadequate information during handover. Our findings indicate that unprofessional behaviour was associated with risks to patient safety. Co-worker reports about unprofessional behaviour have significant value as they can be used by organizations to better understand how unprofessional behaviour can disrupt work practices and lead to risks to patient safety.

Exploring equity in global health collaborations: a qualitative study of donor and recipient power dynamics in Liberia.

IntroductionGlobal health collaborations between individuals from high-resource and low-resource settings are complex and often built on hierarchical structures and power differentials that are difficult to change. There have been many calls and frameworks developed to facilitate more equity within these collaborations, yet little is known about the lived experiences of global health donors and recipients working within such collaborations and how those experiences can facilitate more equitable collaboration. Liberia, a postconflict, post-Ebola country, provides an ideal setting to study lived experiences of global health collaborations.MethodsOur qualitative analysis used key informant interviews representing the perspectives of those working on behalf of the Liberian government, Liberian academics, foreign donors and non-governmental organisations and implementing partners. Thematic analysis guided this analysis to explore topics such as financial control, accountability and decision making.ResultsThe first phase of the analysis mapped the existing patterns of priority setting. Priority-setting power was most strongly held by those with financial control (donors), and implementation plans tended to be built on metrics that aim to meet donor expectations. The second phase of the analysis explored the interplay between underlying factors that we identified in our data associated with driving collaborative inequity: history of prior of engagement, level of transparency and patterns of accountability.ConclusionsOur findings highlight that global health collaborations in Liberia are structured to hinder equitable partnerships. The power structure tied to financial ownership offers little space for recipients to have an equitable role in collaborations, which maintains dependence on external aid and ensures that weak systems remain weak. While our study is limited to Liberia, we anticipate that these dynamics are common elsewhere and reinforce the importance of intentional efforts to ensure equitable decision making and power structures in similar settings worldwide.

Best Practices in Evolving Privacy Frameworks for Patient Age Data: Census Data Study.

BACKGROUND: Over the previous 4 decennial censuses, the population of the United States has grown older, with the proportion of individuals aged at least 90 years old in the 2010 census being more than 2 and a half times what it was in the 1980 census. This suggests that the threshold for constraining age introduced in the Safe Harbor method of the HIPAA (Health Insurance Portability and Accountability Act) in 1996 may be increased without exceeding the original levels of risk. This is desirable to maintain or even increase the utility of affected data sets without compromising privacy. OBJECTIVE: In light of the upcoming release of 2020 census data, this study presents a straightforward recipe for updating age-constrained thresholds in the context of new census data and derives recommendations for new thresholds from the 2010 census. METHODS: Using census data dating back to 1980, we used group size considerations to analyze the risk associated with various maximum age thresholds over time. We inferred the level of risk of the age cutoff of 90 years at the time of HIPAA's inception in 1996 and used this as a baseline from which to recommend updated cutoffs. RESULTS: The maximum age threshold may be increased by at least 2 years without exceeding the levels of risk conferred in HIPAA's original recommendations. Moreover, in the presence of additional information that restricts the population in question to a known subgroup with increased longevity (for example, restricting to female patients), the threshold may be increased further. CONCLUSIONS: Increasing the maximum age threshold would enable the data user to gain more utility from the data without introducing risk beyond what was originally envisioned with the enactment of HIPAA. Going forward, a recurring update of such thresholds is advised, in line with the considerations detailed in the paper.

Justice at the Forefront: Cultivating felt accountability towards Artificial Intelligence among healthcare professionals.

The advent of AI has ushered in a new era of patient care, but with it emerges a contentious debate surrounding accountability for algorithmic medical decisions. Within this discourse, a spectrum of views prevails, ranging from placing accountability on AI solution providers to laying it squarely on the shoulders of healthcare professionals. In response to this debate, this study, grounded in the mutualistic partner choice (MPC) model of the evolution of morality, seeks to establish a configurational framework for cultivating felt accountability towards AI among healthcare professionals. This framework underscores two pivotal conditions: AI ethics enactment and trusting belief in AI and considers the influence of organizational complexity in the implementation of this framework. Drawing on Fuzzy-set Qualitative Comparative Analysis (fsQCA) of a sample of 401 healthcare professionals, this study reveals that a) focusing justice and autonomy in AI ethics enactment along with building trusting belief in AI reliability and functionality reinforces healthcare professionals' sense of felt accountability towards AI, b) fostering felt accountability towards AI necessitates ensuring the establishment of trust in its functionality for high complexity hospitals, and c) prioritizing justice in AI ethics enactment and trust in AI reliability is essential for low complexity hospitals.

The importance of insufficient national data on sexual and reproductive health and rights in international databases.

Looking at SRHR as an isolated set of elements, as is the current practice, does not do justice to the needs and rights of people and communities and may be one of the reasons why challenges remain in the attainment of SRHR for all. SRHR Infographic snapshots were developed for all 194 WHO Member States and included 120 indicators covering a broad range of policy, health systems and service delivery interventions. The snapshots were created using data less than 10 years old publicly available in data repositories maintained by international and global agencies. Data availability was not consistent across countries with low and lower-middle income countries having higher data availability (71%) compared to high income countries (40%). SRHR data that is easily accessible and consistently reported can improve accountability and opportunities for learning to improve people-centred approaches to accelerate the attainment of SRHR for all.

Safety: A collective and embedded competency. An ethnographic study of safety practices at an industrial workplace in the Netherlands.

INTRODUCTION: Organizations place strong emphasis on the standardized occupational health and safety procedures to reduce work-related illnesses and workplace accidents. However, standardized procedures are not always followed up in daily work practices. Organizations must cope with the differences between standardized procedures and local adaptation by employees. METHODS: This ethnographic field study at an industrial workplace in the Netherlands provides insights into employees' everyday work practices, how these work practices are shaped, and how they relate to local occupational health and safety procedures. Acknowledging safety as a competency embedded in work practices, as introduced by Gherardi and Nicolini (2002), offers a theoretical point of view for looking beyond the dichotomy of standardization and local adaptations. RESULTS: The results show that a standardized and noncontextualized occupational health and safety management system that focuses on accident-free days and compliance actually leads to ignorance of practical and tacit competences of workers and no learning and improvement of safety procedures can take place. However, our findings also illustrate how employees in their informal everyday work practices reduce the risks produced by the safety system itself. CONCLUSION: Overall, the results indicate that social interactions among employees, leaders, and management within the organization play an important role in workplace safety. The analysis highlights the value of vulnerability and trust in relationships at work to be able to learn and develop safety procedures that align with local demands. PRACTICAL APPLICATIONS: This study emphasizes the need for participatory approaches in creating safer and healthier workplaces. The cocreation of occupational health and safety (OHS) rules and procedures, however, can only function if they are combined with a responsive leadership style.

Analyzing the characteristics of mission statements in Korean medical schools based on the Korean Doctor's Role framework.

PURPOSE: This study assessed the alignment between Korean medical schools' mission statements (MSs) and Korean Doctor's Role (KDR) domains, considering school characteristics. METHODS: We analyzed the South Korean medical school's MS characteristics using a mixed-methods approach. Quantitative analysis preprocessed MS text data to identify concept words, while qualitative content analysis categorized information into predefined KDR domains and extracted themes from other parts. RESULTS: At the KDR domain level, "social accountability" was the most frequent, followed by "education and research" and "patient care," while "professionalism" had the least frequency. At the competency level, the most frequent domains were "involvement in public and global health initiatives," while "self-regulation based on professional leadership" and "professionalism and self-management" were not present. CONCLUSION: The study found that the majority of MSs had a homogeneous pattern and included traditional themes. Medical schools should evaluate and incorporate missing elements in their MSs to reflect the institution's own purpose and current societal needs.