Allocation Of Care Resources Research Articles

Acceptance and use of extended reality in surgical training: an umbrella review

BackgroundExtended reality (XR) technologies which include virtual, augmented, and mixed reality have significant potential in surgical training, because they can help to eliminate the limitations of traditional methods. This umbrella review aimed to investigate factors that influence the acceptance and use of XR in surgical training using the unified theory of acceptance and use of technology (UTAUT) model.MethodsAn umbrella review was conducted in 2024 by searching various databases until the end of 2023. Studies were selected based on the predefined eligibility criteria and analyzed using the components of the UTAUT model. The quality and risk of bias of the selected studies were assessed, and the findings were reported descriptively.ResultsA total of 44 articles were included in this study. In most studies, XR technologies were used for surgical training of orthopedics, neurology, and laparoscopy. Based on the UTAUT model, the findings indicated that XR technologies improved surgical skills and procedural accuracy while simultaneously reducing risks and operating room time (performance expectancy). In terms of effort expectancy, user-friendly systems were accessible for the trainees with various levels of expertise. From a social influence standpoint, XR technologies enhanced learning by providing positive feedback from experienced surgeons during surgical training. In addition, facilitating conditions emphasized the importance of resource availability and addressing technical and financial limitations to maximize the effectiveness of XR technologies in surgical training.ConclusionsXR technologies significantly improve surgical training by increasing skills and procedural accuracy. Although adoption is facilitated by designing user-friendly interfaces and positive social influences, financial and resource challenges must be overcome, too. The successful integration of XR into surgical training necessitates careful curriculum design and resource allocation. Future research should focus on overcoming these barriers, so that XR can fully realize its potential in surgical training.

A Comprehensive Review of Intravenous Oncology Drug Preparation in Pharmacy: Safety, Efficiency, Innovations, and Stability

Introduction: Intravenous (IV) administration of oncology drugs is a critical component of cancer treatment, providing rapid and controlled delivery of therapeutic agents. The preparation of these drugs involves intricate processes that require stringent safety protocols, efficient workflows, and innovative technologies to ensure patient safety and therapeutic efficacy. This review aims to provide a comprehensive overview of current practices and advancements in the preparation of intravenous oncology drugs within pharmacy settings, focusing on safety, efficiency, innovation, and drug stability. Safety: Safety is paramount in the preparation of intravenous oncology drugs, given the hazardous nature of chemotherapeutic agents. Adherence to guidelines such as USP <797> and USP <800> is essential to minimize risks of contamination and exposure. Strategies to enhance safety include the use of personal protective equipment (PPE), engineering controls like biological safety cabinets (BSCs) and compounding aseptic containment isolators (CACIs), and rigorous training and education for pharmacy staff. Historical incidents, such as the New England Compounding Center contamination, underscore the critical need for strict safety protocols. Efficiency: Efficiency in drug preparation involves optimizing processes to meet high demand while maintaining safety and quality. Current methodologies include prescription verification, com-pounding, quality control, and dispensing. Technological advancements, such as automated compounding devices (ACDs) and pharmacy management software, have significantly improved efficiency by reducing preparation time and minimizing errors. However, balancing efficiency with safety remains a challenge, requiring careful resource allocation, ongoing staff training, and compliance with safety standards. Innovative Technologies: The integration of cutting-edge technologies, such as robotics, automation, and artificial intelligence (AI), has revolutionized the preparation of intravenous drugs. Robotic systems enhance precision and reduce human error, while advanced aseptic techniques and AI-driven systems optimize dosing and workflow. Future trends include the potential use of 3D printing, nanotechnology, and blockchain to further improve the safety, efficiency, and traceability of drug preparation processes. Stability: Maintaining the stability of compounded drugs is crucial to ensuring their efficacy and safety. Factors such as storage conditions, handling procedures, and compatibility with diluents and containers can significantly impact drug stability. Guidelines like USP <797> provide detailed recommendations for maintaining stability. Research on stabilizing agents, improved packaging, and real-time monitoring systems continues to advance the field, addressing stability challenges and enhancing patient outcomes. Conclusion: This review highlights the critical importance of safety, efficiency, innovation, and stability in the preparation of intravenous oncology drugs. Adhering to stringent safety protocols, optimizing workflows, embracing innovative technologies, and ensuring drug stability are essential for improving patient outcomes and enhancing pharmacy practices. Future research should focus on integrating emerging technologies, standardizing protocols, providing ongoing education, and implementing real-time monitoring systems to further advance the field. By addressing current challenges and embracing new solutions, the preparation of intravenous oncology drugs can achieve greater heights in patient safety and treatment efficacy.

Personal and workplace factors influencing the resilience of nurses caring for women with cervical cancer in a resource-constrained setting in Ghana.

Cervical cancer has been identified as the fourth most common form of malignancy affecting and killing women globally. Nurses caring for cervical cancer patients are exposed to emotional and psychological distress due to late presentation and the burden of care. Resilience has been identified as one of the effective ways of helping nurses to cope well with the stress of oncology nursing, but this remains undetermined in Ghana. This study explored personal and workplace factors influencing the resilience of nurses caring for women diagnosed with advanced cervical cancer (stage III and IV) in a resource-constrained setting in Ghana. Using a qualitative approach, we recruited twenty nurses and midwives who had worked for a year and above caring for advanced-stage cervical cancer patients at the national referral hospital in Ghana. We conducted in-depth interviews between July, 2022 to September, 2022 which were audio-taped with participants' consent. Transcription was done verbatim, and analysis conducted using thematic analysis approach with the aid of NVivo 10.0. The results revealed experience as a safety toolkit, inherent desire to help/care for the patient, emotional numbness and maintaining professional outlook as personal factors influencing resilience among the participants. Regarding the workplace factors influencing resilience, we identified the main theme of demands of caregiving for advanced cervical cancer patients with the following sub-themes; severity of cases managed, nature of care rendered, activities of care given, reshuffling, schedules and gender mirroring as an exacerbator of psychological suffering. Resilience among nurses and midwives caring for terminally ill cervical cancer patients is influenced by longer years of service, intrinsic motivation to work as a nurse, and the defense strategy of emotional numbness and professionalism at the individual level. Also, the huge demand of caregiving serves as a major workplace factor affecting the resilience of nurses and midwives. We recommend strategies such as regular ward conferences and in-service trainings aimed at enhancing job-experience, inherent desire to render care and professionalism be adopted in resource-constrained settings to improve nurses' resilience. In addition, political actors and management of hospitals must prioritize allocation of resources for advanced cervical cancer care with particular focus on providing more specialized nurses and midwives.

Our First Steps: A QI Project to Reduce NICU Admissions of Infants With NAS.

In 2020, the rate of newborns diagnosed with neonatal abstinence syndrome (NAS) in the United States was 6.3 for every 1000 newborn hospitalizations. Resources used to care for this population, particularly NICU beds, are being overwhelmed. In 2020, the state of Ohio saw a rate of 9.5 newborns with NAS for every 1000 newborn hospitalizations. To determine if using the Eat, Sleep, Console (ESC) model of care to guide management of neonates with NAS instead of the Finnegan Scale would reduce the number of admissions of neonates diagnosed with NAS to the neonatal intensive care unit (NICU). The PDSA (Plan, Do, Study, Act) method was used in the planning and implementation of this pilot quality improvement project. Education regarding the ESC model of care was provided to the Mother/Infant Unit (MIU), with ongoing education and resources provided and readily available on the unit. Fifteen neonates were managed with ESC. Of the 5 who would have been admitted to the NICU for pharmacological treatment if Finnegan Scores were the determining factor for admission, 2 were discharged home from the MIU having been managed with ESC. The use of the ESC model of care can be a useful tool in the management and assessment of neonates with NAS. Resource allocation for care of this population must be assessed to provide optimal non-pharmacological interventions.

Deep reinforcement learning for autonomous SideLink radio resource management in platoon-based C-V2X networks: An overview

Dynamic and autonomous SideLink (SL) Radio Resource Management (RRM) is essential for platoon-based cellular vehicular networks. However, this task is challenging due to several factors. These include the limited spectrum below 6 GHz, stringent vehicle-to-everything (V2X) communications requirements, uncertain and dynamic environments, limited vehicle sensing capabilities, and inherent distributed operation. These limitations often lead to resource collisions, data packet loss, and increased latency. Current standardized approaches in Long-Term Evolution-V2X (LTE-V2X) and New Radio-V2X (NR-V2X) rely on random resource selection, limiting their efficiency. Moreover, RRM is inherently a complex combinatorial optimization problem. It may involve conflicting objectives and constraints, making traditional approaches inadequate. Platoon-based communication necessitates careful resource allocation to support a diverse mix of communication types. These include safety-critical control messaging within platoons, less time-sensitive traffic management information between platoons, and even infotainment services like media streaming. Optimizing resource sharing inter- and intra- platoons is crucial to avoid excessive interference and ensure overall network performance. Deep Reinforcement Learning (DRL), combining Deep Learning (DL) and Reinforcement Learning (RL), has recently been investigated for network resource management. It offers a potential solution for these challenges. A DRL agent, represented by deep neural networks, interacts with the environment and learns optimal decision-making through trial and error. This paper overviews proposed DRL-based methods for autonomous SL RRM in single and multi-agent platoon-based C-V2X networks. It considers both intra- and inter-platoon communications with their specific requirements. We discuss the components of Markov Decision Processes (MDP) used to model the sequential decision-making of RRM. We then detail the DRL algorithms, training paradigms, and insights on the achieved results. Finally, we highlight challenges in existing works and suggest strategies for addressing them.

Health data analytics for population health management: A review of best practices and challenges

Health data analytics has become an indispensable tool for optimizing population health management by offering data-driven insights that improve healthcare outcomes, enhance preventive care, and inform policy-making. This review explores best practices in health data analytics, including predictive analytics, risk stratification, patient segmentation, and data integration. It highlights successful implementations in healthcare systems that demonstrate the positive impact of these practices on care coordination, resource allocation, and disease prevention. However, the paper also addresses several challenges hindering the widespread adoption of health data analytics, such as data privacy concerns, interoperability issues, and integrating diverse data sources. Ethical, technical, and operational barriers further complicate its effective use. The review concludes with recommendations for improving the adoption and effectiveness of health data analytics, emphasizing the need for strong data governance, improved interoperability, enhanced data quality, and workforce development. These strategies can maximize the benefits of health data analytics in advancing population health management.

Insights Into the Epidemiology of Peripheral Nerve Injuries in the United States: Systematic Review.

Peripheral nerve injuries (PNI) range from mild neurapraxia to severe transection, leading to significant morbidity. Despite their impact, the societal implications of PNI in the United States are not well understood. This study aims to systematically review the literature on PNI epidemiology in the United States. We hypothesize that this review will reveal significant gaps in the understanding of PNI incidence, demographics, and economic impact. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, we queried the literature for studies on PNI that reported at least one of the following: incidence rates, demographics, affected nerve distribution, injury mechanisms, surgical intervention rates, and associated direct costs. Exclusion criteria included non-English publications, abstracts, conference proceedings, reviews, or editorials, studies published before 2000, non-US studies, or studies focusing solely on digital nerves or plexus injuries. Fifteen studies met the inclusion criteria. Data indicate a higher incidence of upper extremity nerve injuries compared with lower extremity injuries. The literature lacks comprehensive reporting on surgical intervention rates, with no recent data since 2013. There is a notable absence of nationwide epidemiological data on PNI mechanisms and recent cost data, with most information over a decade old and primarily focused on inpatient costs, neglecting outpatient visits, physical therapy, and medication expenses. The epidemiological data on PNI are limited and outdated, highlighting the need for further research. Future studies should focus on recent trends in PNI incidence, injury mechanisms, and financial burden, including comprehensive reporting on surgical interventions, to inform strategies aimed at improving patient outcomes and health care resource allocation.

Temporal dynamics of unmet long-term care needs in China: an age period cohort analysis

Abstract Rapid demographic changes and heavy reliance on informal care pose significant challenges to meeting long-term care (LTC) needs in China. Understanding changes in unmet LTC needs across different times and places can inform future LTC system planning and care resource allocation, identifying emerging care needs and services gaps in different regions. Drawing on data from 6,030 urban and 5,070 rural residents in the Chinese Longitudinal Health Longevity Survey 2005–2017/18, this study investigates variations in unmet LTC needs across different age groups, periods and birth cohorts among Chinese older adults and their place-based rural–urban differences. We applied the age-period-cohort interaction model to disentangle the three temporal processes, and found that, overall, rural older adults experienced higher risk of unmet LTC needs and had larger variation in age effects, yet the age, period and cohort effects on unmet needs among rural older people differed from their urban counterparts. Although ‘younger’ older adults (aged below 85) had fewer care needs than older adults, they had a higher risk of experiencing unmet needs. The risk of having unmet needs did not change significantly over the 12 years, though unmet LTC needs were more pronounced among more-recent cohorts than previous generations, especially in urban areas. The findings contribute to the social gerontology debate regarding changing patterns in unmet LTC needs, and provide crucial policy insights, underscoring the necessity of targeted interventions to address ‘younger’ older adults’ care needs and increased investmed in the formal LTC system to tackle the escalating care gap.

The Role of Ethics Committees in Charity Care Allocation.

Hospital ethics committees (HECs) traditionally focus on clinical ethics but are increasingly recognized for their potential role in addressing organizational ethics, particularly in the allocation of charity care resources. This commentary explores the expanded role of HECs in charity care allocation, emphasizing the core ethical principles of justice, transparency, and accountability. We discuss the need for HECs to develop expertise in organizational ethics, differentiate between emergency and chronic resource allocation, and apply value-based insurance design principles to set service boundaries. By adopting an egalitarian approach to justice, HECs can help reduce health disparities and ensure equitable access to charity care. Enhanced transparency and accountability through clear criteria, regular audits, and public reporting are also vital. This paper underscores the importance of integrating these ethical principles into healthcare resource allocation to promote health equity and maintain the financial sustainability of healthcare institutions.

Temporal and regional trends in Canada for the epidemiology and management of diabetic foot ulcers.

Diabetic foot ulcers (DFUs) are a common downstream consequence of diabetes and pose significant concern to the health of affected individuals. There are currently limited data available that detail the epidemiology and inpatient burden of DFUs in Canada. This study aims to provide updated data on the epidemiological and economic burden of DFUs in Canada between 2015 and 2019. Using the Canadian Institute for Health Information Patient Cost Estimator the authors estimated, as the primary outcome, the number of DFU inpatient cases in Canada, the associated financial burden of these admissions on the Canadian healthcare system, physician compensation, and average patient length of hospitalisation. This analysis covered 12 Canadian jurisdictions and was stratified by age, sex, province and geographical region. The secondary outcome was to highlight temporal trends in the public health burden of DFUs by computing the average annual percentage change (AAPC; the weighted average of several annual percentage changes over multiple years) using Joinpoint (Surveillance Research Program National Cancer Institute, US) regression analysis. The total number of cases, average length of hospitalisation and physician costs across Canada were highest for patients over ≥60 years of age. By region, the total number of cases and standardised physician costs were highest in Central Canada, followed by Western Canada, and subsequently Eastern and Northern Canada. In 2019, there were >1800 patients with DFUs admitted to Canadian acute care hospitals. Despite having the lowest number of inpatient admissions, Northern Canada had the highest associated inpatient costs, followed by Central, then Western and, lastly, Eastern Canada. Overall, mean inpatient costs remained stable over time across all age groups (AAPC 0.61; 95% confidence interval: -1.87-3.15), with an average cost of >$10,000 CAD per case. Average physician cost across all jurisdictions was approximately $1000 CAD per case, with the mean hospitalisation time being nine days. The findings of this study emphasise the dynamic nature of the economic and epidemiological DFU burden in Canada, underscoring the need for targeted interventions, multidisciplinary care and evidence-based resource allocation for the optimal management of diabetes and DFUs.

Energy Efficiency of the Office Buildings in Italy: Insights for the European Taxonomy.

Abstract Sustainable investments have led the Italian real estate market over recent years. Large enterprises invest in renovating their building stocks to optimize costs, respond to institutional pressures, and enhance their Environmental, Social, and Governance (ESG) scores. The ESG criteria orient the preferences of today’s investors by measuring a company’s sustainability and profitability; however, the ESG rating systems lack transparency, exposing investors to misleading sustainable initiatives (greenwashing) and risks of financial losses. The EU Taxonomy for Sustainable Activities (EU Regulation 2020/852) defines technical thresholds for sustainability that support investors in making informed decisions. In the building sector, the Taxonomy distinguishes (i) new building construction and (ii) retrofitting existing buildings; the latter is sustainable if it reduces the existing building’s primary energy use by 30% compared to ante-opera or follows the retrofitting guidelines established by the EU directive 2010/31. This work aims to estimate the potential for energy savings and CO2 reduction of the Italian office building stock according to the Taxonomy guidelines. The Energy Efficiency Directive 2012/27/EU (EED) establishes a legislative framework for achieving the European energy efficiency targets. Article 8 of the EED introduced the obligation for large enterprises to submit an energy audit of their production sites every four years, starting from December 2015, and the Italian National Agency for New Technologies, Energy, and the Sustainable Economic Development (ENEA) collects and reviews such energy audits. This study analyzes the energy audits of office buildings submitted by large enterprises in the insurance and banking sectors last year. The database associates the technical features of each building with the main characteristics of its location (e.g., the climate and urban landscape) and energy use. Data show the benefits of retrofitting office building portfolios following the Taxonomy, showing a reduction of energy use and CO2 emissions up to 20% from the current state. Electrification of heating loads is particularly effective in cold climates. At the same time, intense reconstruction produces the highest benefits, but it needs careful resource allocation, driven by cost-benefit analysis.

Research on How the Digital Economy Contributes to Achieving A High-Level and Balanced Development of the Elderly Care Service Industry

Abstract China’s aging population has gained significant attention. Population aging implies that the demand for elderly care services will be on the rise. However, China’s aging exhibits a notable characteristic of getting old prior to achieving affluence, which directly constrains the enhancement of the level of elderly care services. The Communist Party of China and the government attach considerable importance to the issue of population aging and pensions. The Third Plenary Session of the 20th CPC Central Committee adopted the Decision of the CPC Central Committee on Further Comprehensively Deepening Reform and Promoting Chinese-Style Modernization, emphasizing that “we should actively respond to population aging and improve the development of elderly care and elderly care industry policy mechanisms.” Regarding the supply of pension services, due to the professional and long-term nature of pension services, the supply cost remains high. The contradiction between the low level of demand and the high cost of supply might lead to the “low-level equilibrium trap” of the elderly service industry. The digital economy has achieved remarkable effects in promoting the elderly care service industry. It has played a vital role in optimizing the allocation of elderly care resources, reducing the cost of elderly care services, and creating a superior elderly care ecosystem. In this context, it holds considerable academic value and practical significance to study the impact of the digital economy on the development of pension service industry, to analyze the digital divide and bridge the path for the development of the pension service industry, and to explore the countermeasures and ideas of the digital economy to facilitate the high-level, balanced, and high-quality development of the pension service industry.

The Practice Deviation and Governance of the Smart Care Policy——Take Jining City as an Example

Due to the difference between the supply and demand of the policy, as well as the multifaceted conundrum surrounding the policy’s implementation, it is necessary to define the subject’s boundaries of duty while implementing smart care policies. In order to examine the elements that lead to practice deviation and their governance plans, this study employs the research methodology of case analysis and literature analysis to examine Jining City’s smart care policy from the standpoint of public policy. With limited financial resources, it seeks to better serve the demands of the senior population, encourage the efficient development of the old-age care service system, and achieve better resource allocation for old-age care. As a result, the paper recommends enhancing the relationship between the supply of pension services and the demand from the elderly population, encouraging the efficient and well-balanced development of the pension service system, bolstering the development of professional talent, and making it clearer who is responsible for what when it comes to implementing wise pension policy.

Critical Success Factors and Acceptance of the Casemix System Implementation Within the Total Hospital Information System: Exploratory Factor Analysis of a Pilot Study.

The health care landscape is evolving rapidly due to rising costs, an aging population, and the increasing prevalence of diseases. To address these challenges, the Ministry of Health of Malaysia implemented transformation strategies such as the Casemix system and hospital information system to enhance health care quality, resource allocation, and cost-effectiveness. However, successful implementation relies not just on the technology itself but on the acceptance and engagement of the users involved. This study aims to develop and refine items of a quantitative instrument measuring the critical success factors influencing acceptance of Casemix system implementation within the Ministry of Health's Total Hospital Information System (THIS). A cross-sectional pilot study collected data from medical doctors at a hospital equipped with the THIS in the federal territory of Putrajaya, Malaysia. This pilot study's minimum sample size was 125, achieved through proportionate stratified random sampling. Data were collected using a web-based questionnaire adapted from the human, organization, and technology-fit evaluation framework and the technology acceptance model. The pilot data were analyzed using exploratory factor analysis (EFA), and the Cronbach α assessed internal reliability. Both analyses were conducted in SPSS (version 25.0; IBM Corp). This study obtained 106 valid responses, equivalent to an 84.8% (106/125) response rate. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.859, and the Bartlett test of sphericity yielded statistically significant results (P<.001). Principal component analysis identified 9 components explaining 84.07% of the total variance, surpassing the minimum requirement of 60%. In total, 9 unique slopes indicated the identification of 9 components through EFA. While no new components emerged from the other 7 constructs, only the organizational factors construct was divided into 2 components, later named organizational structure and organizational environment. In total, 98% (41/42) of the items had factor loadings of >0.6, leading to the removal of 1 item for the final instrument for the field study. EFA ultimately identified 8 main constructs influencing Casemix implementation within the THIS: system quality, information quality, service quality, organizational characteristics, perceived ease of use, perceived usefulness, intention to use, and acceptance. Internal reliability measured using the Cronbach α ranged from 0.914 to 0.969, demonstrating high reliability. This study provides insights into the complexities of EFA and the distinct dimensions underlying the constructs that influence Casemix system acceptance in the THIS. While the findings align with extensive technology acceptance literature, the results accentuate the necessity for further research to develop a consensus regarding the most critical factors for successful Casemix adoption. The developed instrument is a substantial step toward better understanding the multidimensional challenges of health care system transformations in Malaysia, postulating an underpinning for future fieldwork and broader application across other hospitals.

Digital services as alternative for in-person visits among clients with long-term illnesses

Abstract Background For individuals managing long-term illnesses and often requiring complex care across health and social care sectors, the transition to digital platforms holds considerable potential to facilitate management of one’s health. This study examined factors among people with long-term illnesses associated with their perception that digital services had replaced in-person visits in health and social care. Methods A total of 11,012 Finnish residents with long-term illnesses necessitating regular care (56% female, mean age 56.9, SE .23) responded to a nationwide population survey between September 2022 and March 2023. The Inverse Probability Weighting method was used to correct for bias. Complex samples binary logistic regression was used to examine whether factors related to self-rated health, distress, digital skills and perceived benefits of digital services were associated with the replacement of in-person visits by digital services. The model was adjusted for age, gender, education, and urbanicity. Results Approximately one third (35.8%) of the respondents indicated that the use of digital services had replaced in-person visits within the past 12 months. Respondents in poor or moderate health (OR 1.17, 95% CI 1.02-1.34) had greater odds of reporting the replacement compared to those in good health. Those with proficient digital skills (OR 1.84, 1.57-2.14) and those perceiving more benefits in digital services (OR 1.56, 1.47-1.74) had greater odds of reporting of the replacement compared to their counterparts. Conclusions Transition to digital services could facilitate access to care for individuals with long-term illnesses perceiving their health poorer. Promoting digital skills and perceptions of benefits of digital services can significantly increase the use of digital services as substitutes of in-person visits and contribute to more efficient allocation of health and social care resources. Key messages • Especially those reporting poorer health seem to use digital services as replacements of in-person visits, offering the potential to optimize resource utilization in health and social services. • Promotion of digital skills and perceptions of the benefits of digital services could increase the use of digital services as replacements for traditional visits with health and social professionals.

A New Natural Language Processing-Inspired Methodology (Detection, Initial Characterization, and Semantic Characterization) to Investigate Temporal Shifts (Drifts) in Health Care Data: Quantitative Study.

Proper analysis and interpretation of health care data can significantly improve patient outcomes by enhancing services and revealing the impacts of new technologies and treatments. Understanding the substantial impact of temporal shifts in these data is crucial. For example, COVID-19 vaccination initially lowered the mean age of at-risk patients and later changed the characteristics of those who died. This highlights the importance of understanding these shifts for assessing factors that affect patient outcomes. This study aims to propose detection, initial characterization, and semantic characterization (DIS), a new methodology for analyzingchanges in health outcomes and variables over time while discovering contextual changes for outcomes in large volumes of data. The DIS methodology involves 3 steps: detection, initial characterization, and semantic characterization. Detection uses metrics such as Jensen-Shannon divergence to identify significant data drifts. Initial characterization offers a global analysis of changes in data distribution and predictive feature significance over time. Semantic characterization uses natural language processing-inspired techniques to understand the local context of these changes, helping identify factors driving changes in patient outcomes. By integrating the outcomes from these 3 steps, our results can identify specific factors (eg, interventions and modifications in health care practices) that drive changes in patient outcomes. DIS was applied to the Brazilian COVID-19 Registry and the Medical Information Mart for Intensive Care, version IV (MIMIC-IV) data sets. Our approach allowed us to (1) identify drifts effectively, especially using metrics such as the Jensen-Shannon divergence, and (2) uncover reasons for the decline in overall mortality in both the COVID-19 and MIMIC-IV data sets, as well as changes in the cooccurrence between different diseases and this particular outcome. Factors such as vaccination during the COVID-19 pandemic and reduced iatrogenic events and cancer-related deaths in MIMIC-IV were highlighted. The methodology also pinpointed shifts in patient demographics and disease patterns, providing insights into the evolving health care landscape during the study period. We developed a novel methodology combining machine learningand natural language processing techniques to detect, characterize, and understand temporal shifts in health care data. This understanding can enhance predictive algorithms, improve patient outcomes, and optimize health care resource allocation, ultimatelyimproving the effectiveness of machine learning predictive algorithms applied to health care data. Our methodology can be applied to a variety of scenarios beyond those discussed in this paper.

Global, Regional, and National Burden of Intracerebral Hemorrhage in Young Adults From 1990 to 2021: A Population-Based Study.

Intracerebral hemorrhage (ICH) in young adults demands greater attention, given its poor prognosis; however, there has been a paucity of epidemiological data. The objective of this study is to estimate the temporal trends and distribution characteristics of the disease burden in 204 countries or territories between 1990 and 2021. The data, including incidence, mortality, prevalence, and disability-adjusted life year (DALY) rates were sourced from the Global Burden of Diseases Study 2021. From 1990 to 2021, there was a significant decline in the global incidence (estimated annual percentage change=-1.05), mortality (estimated annual percentage change=-0.92), and DALY (estimated annual percentage change=-1.00) rates of ICH in young adults. In 2021, the highest incidence, mortality, and DALY rates were observed in Southeast Asia, East Asia, and Oceania. Globally, high systolic blood pressure, smoking, and ambient particulate matter pollution were identified as the primary contributors to the largest proportion of DALYs associated with ICH in young adults. The health inequality of ICH in young adults has been reduced over the past 3 decades. There is a considerable degree of heterogeneity in the global burden of ICH in young adults. A decline in the incidence, mortality, prevalence, and DALY rates has been observed from 1990 to 2021, however, the number of absolute cases has increased. These results will enable health care professionals, policymakers, and researchers to refine the implementation of cost-effective policies, the allocation of health care resources, and the management of patients to further mitigate the burden of ICH in young adults.

Clinician Staffing and Quality of Care in US Health Centers

Health centers are vital primary care safety nets for underserved populations, but optimal clinician staffing associated with quality care is unclear. Understanding the association of clinician staffing patterns with quality of care may inform care delivery, scope-of-practice policy, and resource allocation. To describe the association of clinician staffing models and ratios with quality-of-care metrics in health centers. This cross-sectional study of US health centers used data from the 2022 Health Resources and Services Administration Uniform Data System (UDS). Clinician staffing ratios, expressed as the fraction of full-time equivalents (FTEs) per 1000 visits of physicians, advanced practice registered nurses (APRNs), and physician associates (PAs) to total clinician FTEs at each health center. Percentage of eligible patients receiving the corresponding service or outcome for 14 individual clinical quality metrics collected by the UDS, including infant immunizations; screening for cancer, depression, tobacco use, hypertension, HIV, and glycated hemoglobin levels; weight and body mass index (BMI) assessment; and appropriate statin, aspirin, and/or antiplatelet therapy. This analysis of 791 health centers serving 16 114 842 patients (56.6% female) identified 5 clinician staffing models: balanced (similar FTEs of physicians, APRNs, and PAs; 152 [19.2%] of health centers), higher FTEs of APRNs than physicians (174 [22.0%]), higher FTEs of physicians than APRNs (160 [20.2%]), approximately equal FTEs of physicians and APRNs (263 [33.2%]), and large scale (42 [5.3%]). Adjusted linear models showed positive associations between physician FTEs per 1000 visits and cervical (β, 14.9; 95% CI, 3.1-26.7), breast (β, 15.7; 95% CI, 3.2-28.1), and colorectal (β, 18.3; 95% CI, 6.0-30.6) cancer screening. Generalized additive models showed nonlinear positive associations beginning at a physician FTE ratio of 0.45 (95% CI, 0.02-6.22) for infant vaccinations, 0.39 (95% CI, 0.05-2.21) for cervical cancer screening, 0.39 (95% CI, 0.02-1.67) for breast cancer screening, 0.47 (95% CI, 0.00-5.76) for HIV testing, and 0.70 (95% CI, 0.18-19.96) for depression in remission; APRN FTE ratio of 0.45 (95% CI, 0.17-7.46) for adult BMI assessment; and PA FTE ratio of 0.16 (95% CI, 0.11-3.88) for infant vaccinations. Staffing models were not associated with 7 of the 14 metrics analyzed. In this cross-sectional study of health centers, physician FTE ratio was associated with higher performance in cancer screening, infant vaccinations, and HIV testing; APRN FTE ratio was associated with higher performance in preventative health assessments; and PA FTE ratio was associated with higher performance in infant vaccination. These findings suggest that targeted staffing strategies may be associated with quality of care in certain domains and that tailored approaches to health center staffing based on community-specific needs are warranted.

Management of myocardial infarction with non-obstructive coronary arteries (MINOCA) in Germany: a single-center study on hospital resources and healthcare economics.

Patients with myocardial infarction with non-obstructive coronary arteries (MINOCA) present as a main feature ≤50% stenosis upon angiography despite clinical symptoms and biomarker elevation related to acute coronary syndrome. Due to broad availability of high sensitivity troponin testing as well as invasive and non-invasive imaging, this clinical entity receives increasing clinical awareness. We aimed to investigate the in-hospital work flow and economic impact of MINOCA vs. MICAD (myocardial infarction with obstructive coronary artery disease) patients and related clinical outcomes in a single-center patient collective of a large university heart center in Germany. We retrospectively screened and analyzed all patients who were admitted to our hospital under the suspicion of an acute coronary syndrome within a 12-month period (2017-2018) for further diagnostics and treatment. All included patients showed a pathological troponin elevation and received invasive coronary angiography for acute coronary syndrome. Associated in-hospital costs, procedural and various clinical parameters as well as timelines and parameters of work-flow were obtained. After screening of 3,021 patients, we included 660 patients with acute coronary syndrome. Of those, 118 patients were attributed to the MINOCA-group. 542 patients presented with a "classical" myocardial infarction (MICAD group). MINOCA patients were less frail, more likely female, but showed no relevant difference in age or other selected comorbidities except for fewer cases of diabetes. In-hospital mortality (11% vs. 0%; p < 0.001) and 30-day mortality (17.3% vs. 4.2%; p < 0.001) after the index event were significantly higher in the "classical" myocardial infarction group (MICAD)- Despite a shorter overall length of hospital stay (9.5 ± 8.7 days vs. 12.3 ± 10.5 days, p < 0.01) with a significantly shorter duration of high care monitoring (intensive/intermediate care or chest pain units) (2.4 ± 2.1 days vs. 4.7 ± 3.3 days, p < 0.01) MINOCA patients consumed a relevant contingent of hospital resources. Thus, in a 12-months period a total sum of almost 300 days was attributed to high care monitoring for MINOCA patients with a mean difference of approximately 50% compared to patients with classical myocardial infarction. With average and median costs of 50% less per index, MINOCA treatment costs were lower compared to the MICAD group in the hospital reimbursement system of Germany. Consequently, MINOCA treatment was not associated with a relevant profit for these expanses and a relevant share of nearly 40% of the total costs was generated due to high care monitoring. In light of lower mortality than MICAD and growing scarcity of staff, financial and capacity resources the clinical symptom complex of MINOCA should be put under particular consideration for refining care concepts and resource allocation.

Examining Care Network Characteristics in Older Adults' Relocation to Residential Care Settings.

When older adults face increasing care needs or limited support, remaining safely and comfortably at home becomes challenging. Extant research has primarily concentrated on characteristics of the older adult or their primary caregiver on nursing home admission. This study examines the risk of older adults transitioning to residential care (e.g., assisted living, nursing home), focusing on the influence of their care network or involvement of multiple helpers. Using the National Health and Aging Trends Study, we conducted competing risk regression models that account for mortality, following 7,085 initially community-dwelling older adults across Rounds 1-9 (2011-2019). We assessed network composition, size, shared tasks, and the number of in-network specialists or generalists while controlling for individual sociodemographic and health factors. Individuals with care networks that shared medical tasks had the highest risk of moving to a residential care setting, followed by those sharing household tasks. Conversely, shared mobility or self-care and transportation responsibilities were associated with lower risks. Having more generalists, but not specialists, increased the risk. Larger networks were associated with heightened risk, although having close family members like a spouse was protective. The findings underscore that care network characteristics are critical to older adults' ability to age in place. Specifically, older adults with larger networks, lacking a spouse or child, and providing complex care are at greater risk for relocating. Understanding care networks can guide interventions related to care network coordination and resource allocation to help avoid or postpone a residential care move.