Health Care Delivery Research Articles

"How can we help you?": results of a scoping review on the perceived needs of people living with chronic pain regarding physiotherapy.

Physiotherapy is effective to reduce pain and improve the quality of life of people living with chronic pain. To offer high-quality physiotherapy services, these services must be patient-centred and respond to patients' needs. However, few studies seem to target patients' perceived needs, whereas more studies tend to focus on needs assessed by healthcare experts, which are not always in line with patients' perceived needs. In addition, people living with chronic pain are often faced with several health inequities and may have varied perceived needs depending on their personal conditions. To offer services that truly meet patients' needs, it is therefore crucial to understand these needs. This scoping review aims to identify and map the perceived needs of people living with chronic pain towards physiotherapy services. To conduct this review, we followed the six stages framework proposed by Arksey and O'Malley. We searched four databases (Medline, Embase, CINHAL and APA PsycINFO) as well as the grey literature. We included all studies describing the needs, demands, preferences or expectations of adults living with chronic pain towards physiotherapy. We then performed an inductive thematic analysis of the results and discussion sections of these studies to identify the perceived needs. Once those needs were identified, we mapped them into the seven dimensions of the patient-centred healthcare delivery framework. Our review included 96 studies. Various perceived needs were identified through the thematic analysis, such as the needs for an empathetic relationship; for a clear, adapted and supervised exercise program; and for personalized treatment. Our mapping into the patient-centred healthcare delivery framework showed that most studies reported needs associated with the dimensions of interpersonal care, individualized healthcare and professional care. Needs associated with the other dimensions of the framework (access; coordination and continuity; services and facilities; data and information) were less frequently mentioned. The results of this review have enabled us to identify and better understand multiple needs perceived by people living with chronic pain regarding physiotherapy services. The perceived needs identified through this scoping review were mapped within the seven dimensions of the Patient-centred healthcare delivery framework.

OGC SO04 - Impact of COVID-19 on Decision-making and Survival in Esophago-Gastric Cancer Treatment: Insights from a Multidisciplinary Approach

Abstract Background The COVID-19 pandemic necessitated rapid adaptation in healthcare delivery, affecting cancer care pathways. This study assesses the impact of these changes on multidisciplinary team (MDT) decision-making and survival outcomes in esophago-gastric cancer patients across pre-pandemic, peak pandemic, and post-pandemic periods. Method A retrospective cohort study involving patients referred to a UK tertiary EG cancer center during distinct six-month intervals mirroring the pandemic's evolution. Analysis focused on MDT recommendations, treatment pathways, and two-year survival rates, comparing deviations from standard care across periods. Results The study revealed a significant reduction in patient referrals and expedited treatment decisions during the pandemic peak, with a shift towards palliative care in post-pandemic cases. Although no statistically significant difference in two-year survival rates was observed, the post-pandemic period showed an increase in tumor aggressiveness and positive resection margins, suggesting potential long-term impacts of delayed diagnosis and treatment. Conclusion COVID-19 has significantly influenced MDT decision-making and patient pathways in esophago-gastric cancer care, underlining the necessity of resilient healthcare systems. Despite maintaining survival rates, the observed increase in tumor aggressiveness post-pandemic highlights the critical need for uninterrupted cancer diagnosis and treatment services during global health emergencies.

Unethical conduct as a multifaceted phenomenon in psychiatric care: Nurse leaders' perspectives.

Background: Mental healthcare can be considered a unique practice due to its ethical characteristics, and an awareness of ethics is crucial when working in a mental health setting. Several ethical challenges exist, and professionals may not always recognize the ethical aspects of psychiatric care. Research on psychiatric care from nurse leaders' perspective is scarce but important, because nurse leaders can impact and cultivate workplace culture. Aim: To explore the phenomenon of unethical conduct in a psychiatric inpatient context from nurse leaders' perspectives. Research design: Qualitative exploratory design. In-depth semi-structured interviews. Participants and research context: Eight nurse leaders from two different healthcare organizations in Finland. Leadership experience ranged between 2 and 30 years. Ethical considerations: Research ethics permission was received from a Research Ethics Board where the researchers are domiciled. Guidelines on good scientific practice as delineated by the Finnish Advisory Board on Research Integrity TENK were followed. Findings: Six main categories were generated: Unethical conduct and violations against patients, Unethical conduct and violations against staff, Unethical conduct and violations by staff against other staff, Unethical conduct and violations against leaders, Reasons underlying unethical conduct, and Consequences of unethical conduct and the positive development of psychiatric care. Conclusions: Unethical conduct was seen to be a multifaceted phenomenon, and patients and staff alike can experience and engage in unethical conduct. Unethical conduct against patients was linked to power imbalance (nature of involuntary care, staff attitudes) and a focus on rules based in historical precedent (paternalistic, routine-focused, not patient-centered). Unethical conduct against staff was linked to the nature of involuntary care and patient ill-health. Unethical conduct by staff against other staff was linked to a lack of understanding for others' work, interpersonal chemistry, (length of) work experience, and staff character. Unethical conduct against leaders was linked to leaders being perceived as the organization.

Approaches, enablers and barriers to govern the private sector in health in low- and middle-income countries: a scoping review

IntroductionThe private sector plays a substantial role in delivering and financing healthcare in low- and middle-income countries (LMICs). Supporting governments to govern the private sector effectively, and so improve outcomes...

Estimates of resource use in the public-sector health-care system and the effect of strengthening health-care services in Malawi during 2015-19: a modelling study (Thanzi La Onse).

In all health-care systems, decisions need to be made regarding allocation of available resources. Evidence is needed for these decisions, especially in low-income countries. We aimed to estimate how health-care resources provided by the public sector were used in Malawi during 2015-19 and to estimate the effects of strengthening health-care services. For this modelling study, we used the Thanzi La Onse model, an individual-based simulation model. The scope of the model was health care provided by the public sector in Malawi during 2015-19. Health-care services were delivered during health-care system interaction (HSI) events, which we characterised as occurring at a particular facility level and requiring a particular number of appointments. We developed mechanistic models for the causes of death and disability that were estimated to account for approximately 81% of deaths and approximately 72% of disability-adjusted life-years (DALYs) in Malawi during 2015-19, according to the Global Burden of Disease (GBD) estimates; we computed DALYs incurred in the population as the sum of years of life lost and years lived with disability. The disease models could interact with one another and with the underlying properties of each person. Each person in the Thanzi La Onse model had specific properties (eg, sex, district of residence, wealth percentile, smoking status, and BMI, among others), for which we measured distribution and evolution over time using demographic and health survey data. We also estimated the effect of different types of health-care system improvement. We estimated that the public-sector health-care system in Malawi averted 41·2 million DALYs (95% UI 38·6-43·8) during 2015-19, approximately half of the 84·3 million DALYs (81·5-86·9) that the population would otherwise have incurred. DALYs averted were heavily skewed to children aged 0-4 years due to services averting DALYs that would be caused by acute lower respiratory tract infection, HIV or AIDS, malaria, or neonatal disorders. DALYs averted among adults were mostly attributed to HIV or AIDS and tuberculosis. Under a scenario whereby each appointment took the time expected and health-care workers did not work for longer than contracted, the health-care system in Malawi during 2015-19 would have averted only 19·1 million DALYs (95% UI 17·1-22·4), suggesting that approximately 21·3 million DALYS (20·0-23·6) of total effect were derived through overwork of health-care workers. If people becoming ill immediately accessed care, all referrals were successfully completed, diagnostic accuracy of health-care workers was as good as possible, and consumables (ie, medicines) were always available, 28·2% (95% UI 25·7-30·9) more DALYS (ie, 12·2 million DALYs [95% UI 10·9-13·8]) could be averted. The health-care system in Malawi provides substantial health gains with scarce resources. Strengthening interventions could potentially increase these gains, so should be a priority for investigation and investment. An individual-based simulation model of health-care service delivery is valuable for health-care system planning and strengthening. The Wellcome Trust, UK Research and Innovation, the UK Medical Research Council, and Community Jameel.

The Promise of Remote Patient Monitoring.

The promise of remote patient monitoring (RPM) lies in its ability to revolutionize health care delivery by enabling continuous, real-time tracking of patient health outside traditional clinical settings. The COVID-19 pandemic accelerated the adoption of RPM, particularly in underserved and rural populations, highlighting both its potential and the persistent barriers that limit its widespread use. This paper explores the critical role of technological advancements-such as wearables, artificial intelligence (AI), and broadband expansion-in sustaining and optimizing RPM in the postpandemic era. We examine Michigan as a microcosm of national health care challenges, focusing on its diverse population and geographic barriers, and propose condition-specific RPM protocols to address these inequities. Key facilitators and barriers to RPM implementation are discussed, with a focus on AI integration, community engagement, and digital infrastructure. We also explore the role of policy reform and public-private partnerships in supporting RPM's scalability and long-term sustainability. Our findings suggest that while RPM offers a powerful tool for improving health care access and outcomes, especially for chronic conditions and rural maternal health, sustained investment in technology and infrastructure is critical. By addressing these challenges, RPM can become a cornerstone of modern health care, reducing disparities and improving care delivery for underserved populations.

The screening and management of skin diseases in remote African regions: a narrative review.

Skin diseases in remote African regions are often exacerbated due to a lack of resources and expertise with little current research addressing the challenges that patients and healthcare systems experience. Although skin diseases in remote African regions are prevalent and pose a substantial health burden, they remain neglected and understudied. This review aims to explore current challenges in the diagnosis and management of skin diseases in African regions and focus on the need for enhanced understanding and improved healthcare strategies. We reviewed papers that were retrieved from PubMed, Google Scholar, and other relevant academic search sites to analyze the prevalence, screening techniques, as well as management strategies and obstacles associated with dermatological diseases in remote African regions. Current literature suggests there is indeed a high prevalence of skin diseases where other infections are predominant. Further, different factors, such as socioeconomic status and environmental conditions, make it challenging for optimal screening and treatment of skin diseases in remote African regions. Common screening methods for skin diseases involve clinical examination and laboratory tests, while management includes pharmacotherapy, surgery, and counseling approaches. Overall, access to medications and adequate healthcare services remains limited. Early diagnosis and management of skin diseases in remote African regions have significant challenges, including a lack of funding for dermatology, education, and research. Future promising strategies such as teledermatology, point-of-care diagnostic technologies, and task shifting show promise in improving access to care. However, there is a need for sustained efforts to address the underlying socioeconomic factors and improve healthcare delivery in remote African regions.

Development and validation of situational judgement test for assessment of behavioural competencies required for effective medical practice in Nigeria.

The personal qualities of health workers determine the way health services are provided to clients. Some key personal qualities (also called behavioural competencies) of physicians that contribute to quality healthcare delivery include ethical responsibility, empathy, patient-centeredness, diligence, good judgment, respectful, teamwork, team leadership/conflict management, ability to take correction and tolerance. In this study, we developed and validated clinical scenarios (dilemmas) for assessing priority behavioural competencies for medical practice in Nigeria. Drawing on prioritized competencies generated via a scoping review and nominal group technique (NGT) exercises in a previous study in the study series, Faculty members from the University of Nigeria Teaching Hospital were consulted to develop or adapt clinical scenarios that could be used to assess these competencies in a physician. The clinical scenarios and options were framed as situational judgement tests (SJTs) and these tests were administered to a random sample of 192 undergraduate and 111 postgraduate medical doctors in a tertiary hospital in Enugu State. Using Kane's validity argument framework, we assessed scoring and generalization inferences of situational judgment tests (SJT) based on the developed scenarios. Scoring inference - difficulty and discrimination index - shows that most of the SJT items are good test items and can differentiate between high and low performers. The corrected point biserial correlations show positive correlation for most of the items. Generalization inference shows the items represent the domains of interest and are internally consistent. However, few items that show poor difficulty and discrimination index were subjected to re-evaluation and possible elimination. This study has produced a set of valid clinical scenarios that can be used to evaluate specific behavioural competencies among trainee medical doctors. It demonstrates that SJTs can be used to assess behavioural competencies for medical practice. However, further research is needed to establish the applicability of SJT beyond the immediate context, such as the medical school, in which it is developed.

Machine Learning in Health Anylitics and Patient Monitoring Solomon Kavuta and Mr Joel Mulepa Dmi St John The Baptist University, Lilongwe, Malawi

The integration of machine learning techniques in healthcare has revolutionized the way predictive analytics and patient monitoring are conducted. This transformation is reshaping traditional healthcare practices by harnessing the power of advanced computational methods to analyze vast amounts of patient data. Machine learning algorithms, which excel at detecting patterns and making predictions, leverage this data to forecast disease onset, progression, and treatment outcomes. This capability enables healthcare providers to adopt proactive measures, facilitating early intervention and the development of personalized treatment plans tailored to individual patients' needs. The potential of machine learning in healthcare is vast and multifaceted. By continuously analyzing real-time patient data streams from various sources such as electronic health records (EHRs), medical imaging, genomic information, and data from wearable devices, these algorithms can identify subtle changes in a patient's condition that may indicate the early stages of a disease or the risk of an adverse event. This continuous monitoring allows for timely interventions that can prevent complications, reduce the severity of diseases, and improve overall patient outcomes. For example, machine learning can help predict the likelihood of a patient developing conditions like diabetes or heart disease, allowing for lifestyle changes and medical interventions that can mitigate these risks before they become severe health issues. Moreover, machine learning facilitates remote patient monitoring, which has become increasingly important in the context of modern healthcare. With the advent of wearable devices and Internet of Things (IoT) sensors, it is now possible to collect and analyze health data outside of traditional clinical settings. These technologies enable healthcare providers to monitor patients in real-time, regardless of their location, ensuring continuous care and oversight. This is particularly beneficial for managing chronic diseases, where regular monitoring can significantly improve patient management and outcomes. For instance, remote monitoring of patients with heart conditions can detect early signs of arrhythmias or other issues, prompting immediate medical responses that can prevent more serious complications. The transformative impact of machine learning on healthcare delivery extends beyond patient monitoring and predictive analytics. It also includes enhancing diagnostic accuracy, optimizing treatment protocols, and streamlining administrative processes. By reducing the need for frequent hospital visits and enabling more efficient use of healthcare resources, machine learning can help lower healthcare costs while improving the quality of care provided to patients. Additionally, the ability to analyze large datasets quickly and accurately can aid in medical research, uncovering new insights into disease mechanisms and potential treatments.

Remote Assistance for Bone-Fractured Patients using Deep Learning Models

ABSTRACT Remote diagnosis enables healthcare professionals to evaluate and diagnose patients from a distance using telecommunication technologies, enhancing healthcare delivery by improving accessibility, especially for those in remote or underserved areas. One of the significant sustainability challenges in remote medical diagnostics is offering timely assistance to vulnerable groups like the elderly, disabled, mentally impaired individuals, and wounded military personnel in combat zones. This becomes particularly difficult in emergencies when rapid analysis of medical records is needed, especially if the data is stored on secure blockchain networks. The proposed work addresses these challenges by deploying a comprehensive framework for large-scale analysis, utilizing both document and image classification for dual validation. It integrates advanced techniques such as Inception V3, VGG-16, VGG-19, RESNET-50, and Densenet-201 for bone fracture detection, with Inception V3 achieving the highest accuracy of 95.1%. In addition, a Document Classification Analysis (DCA) method is proposed, which automatically classifies the severity of fractures. Object detection techniques are also introduced for detecting minor fractures using region-based image segmentation, ensuring precise diagnosis even for subtle injuries. This pioneering integration of technologies provides a holistic solution for remote medical diagnostics.

Professional nurses’ perspectives on the implementation of integrated chronic disease management model

Background: The integrated chronic disease management (ICDM) model is seen to be a promising strategy as it is gaining global acceptance as an approach to enhance healthcare delivery.Objectives: The study objectives were to explore and describe professional nurses’ perspectives on the model, identify challenges experienced during implementation and identify factors that could improve the model implementation.Method: An explorative, descriptive qualitative design was used, nine professional nurses from three selected facilities were interviewed. Data obtained from semi-structured individual interviews were analysed using thematic analysis and NVivo software.Results: Three main themes emerged: the professional nurses’ perceived benefits of the model, challenges experienced during implementation and recommendations to ensure effective implementation of the model. The perceived benefits of the model included the integration of care, adequate medication and the alleviation of stigma related to diseases. However, the challenges of the model included a shortage of staff, poor infrastructure and patients missing scheduled appointments. The study noted the need for adequate staff, infrastructure and ongoing training for the successful implementation of the model.Conclusion: Despite challenges in the South African healthcare system, professional nurses perceived the implementation of the model positively. The study highlighted the need for adequate staff, adequate infrastructure and ongoing training for staff.Contribution: This study outlined the challenges and recommendations identified, enabling healthcare organisations, policymakers and educators to develop targeted strategies for successful implementation. The findings will also inform future research focussed on optimising the utilisation of the model in the study setting and similar contexts

Evaluating the efficacy of a mindfulness mobile app for stress reduction in nurses

Objective: All Nurses experience work stress that can take their focus away from patient care. Healthcare organizations strive to identify successful, cost-effective stress reduction programs. Mindfulness Based Stress Reduction (MBSR) training is a validated approach to stress reduction, usually in a class format. However, financial and time constraints make it inaccessible to most practicing nurses. Alternatively, mobile mindfulness apps offer an approach to mindfulness that can reach large populations, are available 24/7, anonymous, and cost effective.Methods: This prospective, study evaluated the efficacy of a mindfulness mobile app for stress reduction in nurses utilizing Whil, a Mobile App that offers mindfulness training specifically geared towards health professionals. Eight hundred and fifty-two nurses were recruited from twelve sites (71 per site) within a large Health Care System in the Northeast United States.Results: Two scales were used to test results. Nurses Stress Scale (NSS) results indicated that nurses experienced a reduction in stress level with use and time spent in the app. Nurses in the 31-40 age range and nurses on 12-hour shifts experienced greater stress levels.Conclusions: Significant differences were seen in the Subscales Conflict with Physicians, Conflict with other Nurses, and Lack of Support. There was no change in the Mindfulness Attention Awareness Scale (MAAS) over time. Spearman’s correlation showed a significant and negative correlation between NSS and MAAS scores. The Whil Mobile App is effective for stress reduction in practicing nurses on all shifts and is cost effective.

Navigation literacy of primary health care personnel (using the example of the heads of medical and obstetric centers in Orenburg region)

Objective. To assess navigation literacy of primary health care personnel (using the example of the heads of medical and obstetric centers in Orenburg region). Materials and methods. Navigation literacy of primary health care personnel was assessed among all heads of medical and obstetric centers in Orenburg region (n = 58). For this purpose, a single-stage continuous online survey was conducted using a combined questionnaire developed by the Central Research Institute for Healthcare Organization and Informatization of the Ministry of Heath of the Russian Federation. Results. The level of navigation literacy among the heads of the medical and obstetric centers of Orenburg region in 65.7 % of cases was excellent and sufficient. In the list of navigation skills, the heads of the medical and obstetric centers noted difficulties in the implementation of: issues of medical insurance (48.3 %), legal aspects of medical care and protection of patients' rights (27.5-48.3 %), healthcare reform (36.2 %). It was found out that from 63.7 % to 91.4 % of the heads of the medical and obstetric centers are aware of the ongoing state measures in the field of public health. The majority of the respondents (60.0 %) noted that they search for necessary information for professional purposes using digital tools. However, every third respondent (32.7 %) mentioned the difficulties in finding it on legislative issues, interpreting the quality and safety of food products according to their product labeling (27.6 %), solving problems related to mental health and well-being (18.9 %). These data demonstrate the need to improve navigation literacy of medical and obstetric centers managers in the digital environment. Conclusions. The modern multilevel and multicomponent healthcare system is associated with the need to improve the navigation literacy of medical personnel. The data obtained determined the main directions for improving navigation literacy of the heads of medical and obstetric centers.

Addressing Lean and Safety Readiness Assessment in Territorial Ambulatory Healthcare

Within the international healthcare landscape, it is incumbent upon all organisations to proactively address individual patient needs by offering a wide range of services. In this context, Territorial Ambulatory Healthcare (TAH) is critical to promote equal access to care as the primary point of contact between National Healthcare Systems and individuals. To achieve this goal, the adoption of Lean and Safety Management (L&SM), a managerial approach to proactively reduce clinical risk and process inefficiencies, can support organisations in pursuing high quality care objectives. Despite the positive benefits associated with the adoption of this approach, the feasibility of guaranteeing a sustainable care quality over time may encounter several challenges. Among these, key contributors to failure include the lack of tailored tools and practices suitable for the healthcare environment, insufficient readiness of the context for implementation, and the absence of a comprehensive system-wide performance strategy. Recent studies in literature address these issues presenting theoretical and practical models to assess readiness levels, highlighting opportunities for future developments of these topics. The current empirical study contributes to the existing knowledge by creating a framework to assess the level of readiness for L&SM implementations within TAH. While this context is essential for ensuring high-quality care and equitable access to care services, successfully implementing L&SM initiatives within TAH is challenging due to the organizational complexity and the involvement of multiple, fragmented stakeholders and care providers. Addressing weak Critical Readiness Factors (CRFs) before starting a project can significantly contribute to successfully implement L&SM and sustain improvement over time. This study will be conducted within the TAH setting of a healthcare organisation in Northern Italy and aims 1) to evaluate the specific care setting readiness for L&SM implementations and 2) to develop practical guidelines to support the organisation in increasing its actual readiness level. The theoretical framework will be grasped integrating prior research on Lean readiness assessment, along with specific literature on L&SM sustainability implementation factors within TAH. Once refined and tested with the purpose of developing a practical assessment tool, the framework will be applied within the selected setting, leading to the identification of practical guidelines to facilitate project success and improvements sustainability. Overall, this research will contribute to enrich the knowledge about L&SM implementation within TAH, supporting health organisations, managers, and clinical leadership to sustainably improve care quality, enhancing the role of territorial care to foster social well-being.

Recommendations for Clinicians, Technologists, and Healthcare Organizations on the Use of Generative Artificial Intelligence in Medicine: A Position Statement from the Society of General Internal Medicine.

Generative artificial intelligence (generative AI) is a new technology with potentially broad applications across important domains of healthcare, but serious questions remain about how to balance the promise of generative AI against unintended consequences from adoption of these tools. In this position statement, we provide recommendations on behalf of the Society of General Internal Medicine on how clinicians, technologists, and healthcare organizations can approach the use of these tools. We focus on three major domains of medical practice where clinicians and technology experts believe generative AI will have substantial immediate and long-term impacts: clinical decision-making, health systems optimization, and the patient-physician relationship. Additionally, we highlight our most important generative AI ethics and equity considerations for these stakeholders. For clinicians, we recommend approaching generative AI similarly to other important biomedical advancements, critically appraising its evidence and utility and incorporating it thoughtfully into practice. For technologists developing generative AI for healthcare applications, we recommend a major frameshift in thinking away from the expectation that clinicians will "supervise" generative AI. Rather, these organizations and individuals should hold themselves and their technologies to the same set of high standards expected of the clinical workforce and strive to design high-performing, well-studied tools that improve care and foster the therapeutic relationship, not simply those that improve efficiency or market share. We further recommend deep and ongoing partnerships with clinicians and patients as necessary collaborators in this work. And for healthcare organizations, we recommend pursuing a combination of both incremental and transformative change with generative AI, directing resources toward both endeavors, and avoiding the urge to rapidly displace the human clinical workforce with generative AI. We affirm that the practice of medicine remains a fundamentally human endeavor which should be enhanced by technology, not displaced by it.

Abstract 4122590: Sex Differences in the Prescription of P2Y12 Inhibitor Agents Following Percutaneous Coronary Intervention

Background: There remain significant gender inequalities in the delivery of healthcare. Third generation P2Y12 inhibitors (P2Y12i), Prasugrel and Ticagrelor, are the standard of care for dual antiplatelet therapy (DAPT), especially in the setting of acute coronary syndrome (ACS). We hypothesized that women are less likely to be prescribed 3 rd generation P2Y12i than clopidogrel, due to concealed gender inequalities. Methods: We examined gender differences in post percutaneous coronary intervention (PCI) care in a cohort of 12,354 PCI cases from all 14 hospitals within the Steward Health Care system in the United States of America (USA). After removal of duplicates, 10,415 patients were included in the final analysis, with 7,191 males (69.04%) and 3,224 (30.96%) females. We conducted statistical analyses using the Chi-Square test of independence to explore associations between categorical variables, and logistic regression analysis to model the probability of clopidogrel prescription based on patient characteristics, adjusting for confounders. Results: We found that women were less likely than men to be prescribed 3 rd generation P2Y12i compared to clopidogrel with an odds ratio (OR) of 0.74 (CI 0.69-0.80, p<0.001). We adjusted for the following variables: age, weight, insurance type, number of stents, and relevant co-morbidities. The association remained significant with an OR of 0.83 (CI 0.76-0.90, p<0.001). In a subgroup of ACS patients, the association was also statistically significant with an OR of 0.77 (CI 0.67-0.88, p<0.001). Conclusions: Our study reveals that significant gender disparities exist in the prescription of P2Y12i after PCI, with women having a greater likelihood of being prescribed clopidogrel compared to more effective and guideline directed, 3 rd generation agents. This association held true after accounting for confounding variables including older age and an increased prevalence of co-morbidities in the female group. Our conclusions are likely to have been influenced by unmeasured socioeconomic factors, such as household income and medication costs. Therefore, further research ought to be conducted to better understand the reasons behind the association observed.

A Scientific Approach for Optimizing Patient Bed Occupancy in an Overcrowded Teaching Hospital in Sri Lanka

Background: In Sri Lanka, the healthcare system predominantly relies on the public sector, which delivers nearly 95% of inpatient care and approximately 50% of outpatient care. Effective monitoring of bed occupancy rates is crucial for optimizing resource allocation amidst limited hospital resources and fluctuating patient demands.Objectives: This study aims to develop a scientific approach to enhance patient bed utilization at Colombo South Teaching Hospital (CSTH) in Sri Lanka.Methodology: A mixed-method approach was employed, integrating quantitative analysis of historical patient data from CSTH's medical record room with qualitative insights from key stakeholders, including hospital administrators, consultants, medical officers, and nursing staff.Results and Discussion: In 2023, CSTH reported an overall bed occupancy rate of 80%, surpassing both national and global averages, indicating strain on healthcare delivery. The study identifies disparities in occupancy rates across different wards, highlighting overcrowding in medical and surgical units alongside underutilization in other specialities.Recommendations and Conclusions: Revising the consultant-based ward allocation system, implementing patient-centric ward clustering based on occupancy rates, appointing bed managers, and expanding facilities in high-demand units like Medical, Accident Service Unit, Emergency Treatment Unit, and Nephrology. Implementing these strategies could mitigate overcrowding, improve bed availability, and enhance the quality and safety of patient care services at CSTH.

Managing Angiography Unit Failure in Interventional Radiology: Lessons in Crisis Management and Considerations in Prevention.

Functional and efficient medical equipment is at the core of modern healthcare delivery, particularly in medical imaging. Growing healthcare costs and constrained budgets can delay equipment renewal. Aging equipment risks malfunction, potentially causing injury to patients and staff, and downtimes delaying patient care and impacting departmental revenue. Extensive equipment failure can lead to significant operational disruption which can compromise the delivery of timely and quality healthcare. Although extensive equipment failure is uncommon, 2 interventional radiology divisions at tertiary academic hospitals in Canada and the UK recently faced such a crisis. Their experiences of crisis and recovery inform this review of angiography equipment failure, and the principles learned. The concept of organizational resilience is introduced as a framework through which we review the crises. This concept can be split into successive and cooperative stages of anticipation, coping, and adaptation. Resilient organizations can identify potential threats, cope with unexpected crises, and recover swiftly to ensure future success. The author's experience of critical angiography unit failure, their response, and lessons learned are reviewed. We find these principles are broadly applicable to other medical imaging divisions and relevant to any system reliant on technology for healthcare delivery.

Exploring participants’ characteristics and self-assessed readiness to conduct clinical trials in general practice – baseline analysis of the RaPHaeL practice-based research network

Background Primary care is integral to healthcare systems extending beyond traditional illness management to include preventive care, chronic disease management, and health promotion. Practice-based research networks (PBRNs) have emerged as essential infrastructures for conducting clinical research in primary care. This study explores the establishment of the ‘Research-Practices Halle-Leipzig’ (RaPHaeL) PBRN in Germany, evaluating the characteristics and research readiness of participating practices. Methods A cross-sectional survey (MORNING II) was conducted among all general practitioners (GPs) joining the RaPHaeL PBRN, assessing socio-demographic characteristics, practice infrastructure, and research readiness. After a descriptive analysis, we compared data with a previous study (MORNING) to examine potential differences between PBRN participants and non-participants. We developed a research readiness score (RRS) to quantify practices’ ability to perform clinical research subtasks. Results The response rate was 97.1% and our participants were often male, involved in undergraduate education, generally interested in research or had previous research experiences. However, they differed widely in age and size, staff structure, and patient demographics of their practices. Initially, around two-thirds of the practices were not sufficiently prepared to conduct clinical trials (self-assessed feasibility of relevant subtasks). If further research and documentation tasks are required, patient recruitment estimations are lower than for patient identification and information. Conclusion This study highlights the variability in research readiness among GP practices and shows the need for targeted training. By systematically assessing and enhancing research capabilities of participating GPs, PBRNs can facilitate high-quality clinical research in primary care to improve patient outcomes and healthcare delivery.

Sepsis: key insights, future directions, and immediate goals. A review and expert opinion.

This review explores the current landscape and evolving understanding of sepsis, highlighting both challenges and future directions. Sepsis remains a major global health burden, with diverse clinical presentations complicating timely diagnosis and management. Existing definitions, including the Sepsis-3 criteria, emphasize the importance of organ dysfunction, yet early sepsis detection remains limited by available tools. The Sequential Organ Failure Assessment (SOFA) score, though widely used, may not fully capture early stages of infection or account for complex presentations like noncatecholamine-resistant shock. Additionally, the review underscores the pressing need for standardized terminology across sepsis and shock characterization to ensure consistency in diagnosis and treatment strategies. Accessible, resource-adapted solutions are particularly crucial in low- and middle-income countries where sepsis-related mortality rates are higher due to limited resources. Future research should focus on developing and validating integrated, multi-parameter tools that combine clinical, biochemical, and microbiological data to improve sepsis outcomes globally. Advancing sepsis care will require both technological innovation and collaborative, globally consistent guidelines to bridge disparities in healthcare delivery.