Is Health Human Resource Strain Associated with the Prevalence of Healthcare-Associated Infections in England? Analysis of a national point prevalence survey.

Medical malpractice imposes a substantial clinical and economic burden worldwide. Pressure injuries (PIs) are amongst the most frequently litigated adverse events and represent a major source of preventable patient harm. To characterise the medicolegal landscape of PI-related malpractice, the Westlaw legal database was queried for cases litigated between 1990 and 2024. A total of 590 cases met inclusion criteria, with data extracted from court documents. The mean patient age was 71 years; 53.4% were female and 46.6% male. Nursing homes were the most commonly named defendants (59.8%), followed by hospitals and outpatient surgical practices (37.3%) and individual physicians (14.1%). The mean settlement was $383 099, compared with a mean jury award of $2 100 787. Adverse legal outcomes were strongly associated with allegations of inadequate care, poor clinical outcomes and gross provider negligence. When prevention and timely management fail, the consequences extend beyond patient harm to substantial legal and financial liability. Targeted interventions such as standardised risk assessment, rigorous documentation, staff education, appropriate staffing ratios and institutional accountability may mitigate both PI incidence and litigation risk. Strengthening these measures represents a critical opportunity to improve patient safety whilst reducing medicolegal exposure.

This study evaluates the financial and operational performance of thirty-four Public Service Agency (BLU) Health Polytechnics over 2022 to mid-2025 within the framework of Government Regulation No. 74 of 2012 and Ministry of Finance Regulation No. 202/PMK.05/2022. The method was a multiple-case qualitative study using within-case and cross-case descriptive analyses of Monitoring of Financial and Operational Performance (MKKO) data, performance contracts, and focus group discussions, followed by descriptive and diagnostic analyses applying the 5 Whys and the 4P/S categories (People, Process, Policy, System). The results show high dependence on single tuition fees, limited diversification of non-tuition revenue, a large share of non-academic expenditures, gaps between revenue and academic cost per student, uneven admissions selectivity, strong graduate tracer coverage but highly varied job placement within six months, unbalanced research productivity and down streaming, and unproportional lecturer and staff ratios and ranks. Policy implications emphasize performance-based governance, minimum shares for academic spending, cost-per-service calculations in the business and budget plan, standardized tracer studies, workforce planning and workload rebalancing, and the acceleration of research down streaming and revenue diversification.

ABSTRACTPatient complaints are an important source of data, as they may help illuminate medication safety issues from the patient's perspective. We aimed to identify and describe medication errors (MEs) reported in patient complaints and compare them with MEs from safety incident reports. This descriptive hospital‐based study (1) compared patient complaints with and without MEs using the Health Complaint Analysis Tool (HCAT) and (2) analysed MEs identified in both patient complaints and incident reports using the standard taxonomy of the reporting system. Of 6301 complaints, 310 (4.9%) were related to MEs. Compared with other complaints, ME‐related complaints were more often submitted by family members (ratio 1.6), directed towards nursing staff (ratio 2.5), involved ward‐based events (ratio 4.3) and occurred during discharge or transfer (ratio 2.9). Following selection and additional deduplication procedures, 202 MEs were identified in patient complaints. Compared with 8364 MEs from safety incident reports, patient complaints revealed higher proportions of antiepileptic and antipsychotic medication (ratio: 1.9), prescribing errors (ratio: 1.5), wrong medicine errors (ratio: 1.6) and errors with severe or fatal outcomes (ratio: 14.6). Patient complaints may uncover unique MEs not captured by traditional reporting systems. They may serve as a valuable complement to safety incident reports.

Eastern Africa stands at a critical crossroad where environmental degradation, biodiversity loss, and pollution are intensifying climate vulnerability and deepening interconnected challenges such as food and nutrition insecurity, poverty, conflict, and public health risks. In this context, environmental science education is not merely an academic pursuit, but rather, it’s a strategic foundation for sustainable development across the region. This study presents a regional landscape analysis of environmental science training using a mixed-method evaluation of 42 academic programmes across 30 universities in Kenya, Uganda, Tanzania, Rwanda, and Ethiopia, complemented by insights from interviews with 30 faculty leaders. The findings reveal a sector struggling for relevance and impact, yet constrained by structural and resource limitations. Teaching capacity remains stretched with 57% of institutions operating as student: staff ratios between 20:1 and 40:1 which is well above global benchmarks – hence limiting meaningful mentorship, experiential learning, and research productivity. Infrastructure gaps are equally significant where fewer than 40% of programmes report adequate laboratory facilities, less than one-third have sufficient field equipment or reliable transport, and the post-pandemic transition to digital learning continues to be undermined by weak technological systems. Curriculum relevance also emerges as a pressing concern. While environmental challenges are increasingly localized, 70% of programmes rely on outdated learning materials. Indigenous and community knowledge systems are incorporated in only 35% of the curricula, and formal industry-linked internships exists in just 28% of programmes essentially leaving many graduated insufficiently prepared for practices oriented environmental problem solving. Although 62% of the programmes benefits from PhD qualified faculty, persistent brain drain threatens institutional continuity and leadership. Encouragingly, nearly 40% of institutions are currently undertaking curriculum reforms and strengthening inter-university collaboration. The study underscores that advancing sustainable development in Eastern Africa will require more than incremental improvements. It calls for systematic transformation through pedagogical innovations, strategic investment in learning infrastructure, and stronger partnership between universities, industry, and policy actors to align environmental science education with the regions urgent socio-ecological realities.

Postoperative placement of patients into a regular ward, an intermediate-care unit (IMC), or an intensive care unit (ICU) is critical for balancing patient safety against resource constraints. Most existing models collapse this decision into a binary ICU versus non-ICU choice and lack a mechanism to tune risk thresholds to local staffing ratios or definitions of ICU-level events. We developed Neuro-TACTIC, a cost-sensitive machine learning framework that stratifies postoperative neurosurgical patients into three monitoring levels: regular ward, intermediate care unit, and intensive care unit. An XGBoost-based classifier was trained on 27 demographic, intraoperative, and imaging-derived features from a retrospective cohort of 1072 patients undergoing elective craniotomy. A tunable parameter ζ integrates resource-related and harm-related costs to adjust the balance between over- and under-triage. Generalization was assessed in an independent cohort. Across repeated cross-validation and bootstrap analyses, the framework demonstrated stable behavior across cost settings. At the operating point ζ = 0.975, performance was AUCμ = 0.67 ± 0.03 and weighted F1 = 0.49 ± 0.03 in the development cohort, and AUCμ = 0.60 ± 0.04 and weighted F1 = 0.44 ± 0.06 in the independent evaluation cohort (n = 81). Feature importance analyses identified operative duration, tumor volume, surgical position, body mass index, and patient age as the most influential predictors. This study demonstrates the feasibility of cost-sensitive, three-tier postoperative triage modeling in neurosurgical patients. Neuro-TACTIC is a methodological proof-of-concept; prospective validation and multicenter evaluation are required before clinical deployment.

Labor unions representing workers in US nursing homes bargain for higher wages and safer working conditions, which may reduce staff turnover and increase the quality of care. However, if higher labor costs lead employers to reduce nurse staffing, unionization may reduce care quality. We used a difference-in-differences event study design to estimate the effects of unionization on nurse staffing ratios for total nurse staffing and separately for registered nurses (RNs), licensed practical nurses (LPNs), and certified nursing assistants (CNAs), as well as the effects of unionization on the quality of care, during the period 2013-21. We found that unionization had no effect on total nurse staffing levels but had opposing effects on RNs and LPNs. Unionization increased LPN staffing by roughly 2.7 nurse hours per day in the average nursing home, but it decreased RN staffing by roughly 3.2 nurse hours per day. Despite this substitution from RNs to LPNs, we found that unionization did not appear to reduce the quality of care, a result consistent with unions increasing nurse productivity.

To compare Little's law formula (LL) and a health care modification of LL (HCM) that includes efficiency and patient-to-staff ratio to estimate the staff needed for a veterinary anesthesia service. This study was conducted between May 7 and August 9, 2024. Calculations were performed for 1 to 25 cases with a mean duration of 60 to 300 minutes, at 30-minute intervals, using LL (N = [λ·T]/H, where N = the number of anesthesia personnel, λ = the number of cases per day, T = the mean duration of anesthesia [time from premedication to extubation], and H = work hours per day [shift length]) and HCM (N = [λ·T]/[H·EF·SR], where EF = efficiency factor [0.8], and SR = patient to staff ratio [1:1 for anesthesia]). Results were rounded up to the nearest whole number. For each duration interval, results from LL and the HCM were compared with a Wilcoxon signed rank test. A P value < .05 was used for significance. The HCM estimated a significantly larger number of staff for all case duration intervals compared to LL. Calculations utilizing a formula that included efficiency and patient-to-staff ratio resulted in an estimation of a larger number of anesthesia staff compared to calculations that did not. Modifications of LL that incorporate staff efficiency and patient-to-staff ratio may estimate higher staffing needs. Because of adaptability, the HCM may be useful to estimate staffing needs in other areas of veterinary medicine beyond anesthesia.

The pharmacist staffing ratios required for comprehensive patient care are not well defined, particularly in pediatrics. Understanding optimal clinical pharmacist staffing ratios for pediatrics may help in advocating for appropriate staffing and optimizing patient outcomes. The primary objective was to describe optimal pediatric clinical pharmacist staffing ratios in general pediatric, surgical, and hematology-oncology-bone marrow transplant (heme-onc-BMT) units in tertiary pediatric hospitals in Canada. The secondary objectives were to quantify how pediatric clinical pharmacists spend their time and to qualify their perspectives on current workload. Two electronic surveys were distributed. One survey, sent to leaders in tertiary pediatric health care centres, was designed to describe current staffing ratios. The second survey, sent to pediatric clinical pharmacists, aimed to estimate the frequency of and time spent on 13 comprehensive pharmaceutical care activities, as validated by a working group. The survey data were used to estimate pharmacist staffing ratios according to the World Health Organization workforce calculator. Seven (50%) of the 14 sites responded to the management survey, and 33 clinical pharmacists responded to the clinical pharmacist survey. Optimal pharmacist-to-patient ratios (based on clinical pharmacist survey responses) were estimated to be 1:11 for general pediatric units, 1:14 for pediatric surgery units, and 1:6 for pediatric heme-onc-BMT units, with median lengths of stay of 4.9, 2.5, and 7 days, respectively. Further research is needed to validate these ratios in various pediatric clinical pharmacy settings.

Prevalence and correlates of burnout among radiographers in Harare Metropolitan Province, Zimbabwe.

This study evaluated the readiness of 135 Indonesian hospitals (Type B and C) for mandatory EMR integration with the SATUSEHAT platform. Recognizing a critical research gap in evaluating maturity against specific HL7 FHIR interoperability and governance standards, the study utilized a Quantitative Secondary Data-Based Readiness Evaluation Design. Binary Logistic Regression identified the strongest predictors for successful integration. Results indicate that while basic infrastructure is adequate, readiness is hampered by advanced factors. The two most significant predictors were Data Security Certification ( ) and the IT Personnel to Clinical Staff Ratio ( ). This confirms that the primary hurdles are the Interoperability Governance Gap (low security compliance, ) and the lack of specialized technical human capital. Implications mandate a Targeted Intervention Strategy (TIS): linking digital transformation subsidies to mandatory Data Security Certification compliance and prioritizing the retention of specialized IT talent. Achieving national digital health requires immediate investment in formal data governance and dedicated technical staff.

BackgroundQuality of memory care varies across states and can affect health and quality of life outcomes for persons living with dementia (PLWD) within assisted living facilities (ALFs). This study evaluates regulations of memory care units in ALFs across six selected states as potential drivers of health and quality of life outcomes reported within the National Post‐acute and Long‐term Care Study (NPALS).MethodsEmpirical legal methods were used to map state regulations that guide training standards, staff ratios, and direct care staff time spent with residents. Comparative analysis was used to understand relationships between regulations and adverse events.ResultsWithin the six‐state snapshot, significant variation of regulations may affect quality of care in memory care centers. Day‐shift direct care staff ratios varied significantly across states (e.g., California: 1:10, Virginia: 4:40; compared to Wisconsin requires only presence of 1 Direct Care Staff). Yet, in Wisconsin, residents must receive 3 hours of individual nursing care per week and average hours per day/resident is 6.1 hours ‐ highest of all six states. Comparatively, average hours per resident/day were lowest in New Mexico (4.7 hours) and falls below the national average (4.9). California also falls below the national average (3.9). States requirements in care and daily living activities were consistent with Alzheimer's Association Memory Care Recommendations, except for New Mexico. Although, states with training requirements that are consistent with the Alzheimer's Association recommendations may not follow all eight of the recommendations. For example, California state regulations meet 7 of 8 the Alzheimer's Association recommendations. The findings from this study indicate that inclusion of standardized memory care training and greater direct care time with residents in ALF policy may enhance care quality. Standardization and inclusion of memory care curriculum and greater direct care time with residents also may enhance care quality.ConclusionThe results indicate that states with policy language that is more aligned with the Alzheimer's Association 2018 Dementia Care Recommendations may drive lower hospital visit rates, higher direct care staff time spent with residents, while staff ratio requirements may not. Aide and RN hours spent with residents may also influence the likelihood of resident ED visits.

Abstract Nursing home (NH) leaders face ongoing challenges in addressing workforce shortages while ensuring federally mandated person-centered care (PCC) for residents. This study explores NH leaders’ voices in managing staffing challenges while attempting to honor residents’ daily care preferences-a key aspect of PCC. This qualitative descriptive study utilized semi-structured interviews (n = 14) from four NHs in Pennsylvania. NH leaders (administrators, clinical directors and supervisors) participated in in-depth individual interviews, which were then evaluated using inductive thematic coding structured according to the Nurse Staffing Framework. Our data revealed four key themes. First, confirming honoring residents’ preferences is essential for PCC, with leaders emphasizing its benefits for resident well-being and staff satisfaction despite challenges such as perceived family interference and resource limitations. Second, workforce shortages pose a significant barrier to PCC, driven by negative perceptions of nursing, recruitment difficulties, and state-mandated staffing ratios, leading to staff overload and increased reliance on agency staff. Third, leaders employ various workforce management strategies, including pay adjustments, flexible scheduling, and staff recognition, to improve staff retention and maintain care quality. Finally, advocacy for policy reforms is perceived as crucial, with leaders stressing the need for regulatory changes to enhance staffing levels, workforce stability, and the overall sustainability of high-quality, resident-centered care in NHs. The paper will discuss insights into how workforce shortages impinge upon PCC, suggest effective workforce management strategies, as well as policy and regulatory reforms to strengthen both workforce stability and ensure the consistent delivery of PCC to residents in NHs.

Hospitals operate within highly complex and resource-constrained environments where decisions regarding beds, workforce, operating rooms, diagnostic services, and medical supplies directly influence patient safety, quality of care, operational efficiency, and financial sustainability. Persistent challenges such as emergency department overcrowding, prolonged waiting times, workforce shortages, and rising healthcare costs indicate systemic inefficiencies in traditional hospital resource allocation practices. Historically, hospital decision-making has relied on retrospective reporting, static staffing ratios, and managerial experience, approaches that are increasingly inadequate for managing real-time variability and interdependencies within modern healthcare systems. The rapid digitalization of healthcare, particularly through the widespread adoption of electronic health records and integrated hospital information systems, has created unprecedented opportunities to apply data analytics to hospital operations. Data analytics enables hospitals to transform large volumes of clinical and operational data into actionable insights that support evidence-based decision-making. This review examines the role of data analytics in optimizing hospital resource allocation and decision-making by synthesizing contemporary evidence across descriptive, diagnostic, predictive, and prescriptive analytics. It explores key analytical methodologies, including machine learning, process mining, simulation modeling, and optimization techniques, and evaluates their application in critical operational domains such as emergency department crowding, inpatient flow, length of stay prediction, workforce planning, and strategic capacity management. In addition, this review critically discusses implementation challenges that limit the real-world impact of hospital analytics, including data quality issues, interoperability barriers, governance gaps, privacy concerns, and algorithmic bias. The findings indicate that data analytics can substantially enhance hospital performance when embedded within clinical workflows and supported by robust organizational governance. However, sustainable benefits require alignment between analytical models, decision-making processes, ethical oversight, and institutional culture.

BackgroundIn Nepal, insufficient healthcare infrastructure and limited funding contribute to unmet public healthcare needs and reduced quality of care. While foreign health researchers have stepped in to support local research initiatives, their involvement has sparked ethical concerns regarding the sharing and ownership of data. This study aims to develop a locally governed framework for ethical healthcare data exchange, establish an evidence base to understand local challenges in data transfer, and to identify potential solutions for data sharing with international research teams.MethodThis cross-sectional qualitative study was conducted in Kathmandu, Nepal, using 11 multiple-choice and 12 open-ended questionnaire models. We conducted a pre-structured questionnaire survey to best identify local ethics issues related to international data transfer and proposed solutions for these challenges. The key representatives identified from the non-governmental and not-for-profit research institute (n = 14) and the life sciences society (n = 7) were invited to one-to-one blind interviews, and their recorded transcripts were coded using the QDA Miner Lite software (version 3.0) for analysis.ResultThe ratio of female to male participants was 2:3, while the ratio of junior-level staff to senior staff (≥3 years of experience in the sector) was 1:9. Approximately 42.86% of participants shared both raw and analytical data, while <5% shared no data with collaborators. Concerning knowledge, attitudes, and practices, most (38.46%) preferred open-access storage, while approximately 23.1% had limited knowledge, and 15.38% opted for confidentiality. Additionally, < 10% were in the learning process and sought training in data transfer procedures. Within this group of key representatives, participants faced main challenges in the data transfer process from four key categories: (i) the lack of standardized guidelines from government or institutes for data transfer, (ii) inadequate awareness and training in data sharing, (iii) problems related to data sharing, and (iv) problems related to biological sample transfer.ConclusionIn summary, this study emphasizes the importance of a standardized data-sharing platform, focusing on protecting intellectual property rights and establishing a centralized data repository in Nepal. It also recommends educational reforms, legal measures, well-defined agreements, and dedicated oversight to ensure data integrity and security, while streamlining sample transfer processes to enhance transparency and scientific progress in Nepal’s research landscape.

Functional recovery unit national map. FUN-RUN Map Project.

The paper addresses the structure, financing, and quality of primary and secondary school education in the EU and Bulgaria. Education is interpreted both as a process of acquiring knowledge, developing skills, and forming competencies and as an activity that encompasses learning, upbringing, and socialization of young people. The research aims to identify the reasons behind the unsatisfactory performance of Bulgarian students in international assessments. To this end, the study summarizes the specific features of education financing in Bulgaria and analyzes key indicators that characterize expenditures on primary and secondary education in the EU. From a comparative perspective, it discusses the absolute amount of funding, its share relative to GDP, the student–teacher and teaching staff ratios, as well as the number of teachers and graduates. The paper supports the view that the establishment of schools as centers for training highly qualified, motivated, and competitive professionals largely depends on the efficient use of resources and the possibilities for personalization of the learning process.

The ethical climate and work environment in healthcare are vital factors influencing nursing practice and patient care quality. Although widely studied internationally, little research has explored how these factors interact to affect nursing care quality in the United Arab Emirates (UAE), a region with a diverse workforce and evolving healthcare system. This study aimed to explore registered nurses’ perceptions of the ethical climate and its relationship to the quality of nursing care, and to examine how these perceptions are influenced by key characteristics of the work environment within the healthcare context of the UAE. A quantitative correlational study was conducted using survey data collected from 396 registered nurses. Validated instruments, including the Practice Environment Scale of the Nursing Work Index, the Revised Ethical Climate Questionnaire, and the Nursing Quality of Care scale, were used to assess the work environment, ethical climate, and quality of care. Descriptive and inferential statistical analyses, including Pearson correlation and analysis of variance, were performed to examine the relationships among the study variables. Descriptive analysis indicated a generally favorable perception of the work environment and nursing care quality, while the ethical climate was perceived as moderate. Significant positive correlations were found between the nursing work environment and ethical climate, particularly in the principled, benevolent, and egoism dimensions. Additionally, the ethical climate was positively associated with perceived quality of care. A positive nursing work environment combined with a supportive ethical climate is associated with higher perceptions of care quality. Promoting ethical leadership, fostering collaborative team dynamics, and ensuring adequate staffing are essential for improving nurse well-being and patient outcomes. Based on the study findings, healthcare organizations should prioritize structured ethics training, supportive leadership, and safe staffing ratios to strengthen the ethical climate and enhance quality of care. Creating psychologically safe, non-punitive systems and fostering nurse participation in decision-making can further improve ethical perceptions. Tailored support for clinical nurse specialists is also essential, given their complex roles.

Patients in the intensive care unit (ICU) require complex care with rapidly changing conditions, and missed nursing care (MNC) can lead to severe consequences. Investigating the current status and influencing factors of MNC in the ICU is essential to enhance patient safety, optimise care quality and improve nurse job satisfaction, providing evidence-based strategies for ICU nursing management. The aims of this study were to investigate the current status of MNC in ICU and to analyse its causes, providing insights to reduce missed care and improve the quality of nursing for critically ill patients. This is a cross-sectional study, using convenience sampling, 191 ICU nurses from five tertiary hospitals in Sichuan Province were selected as participants from 1 June 2024 to 30 June 2024. Data were collected through a general information questionnaire and the Missed Nursing Care in Intensive Care Units Scale. A total of 191 questionnaires were sent out in this survey, and finally, 185 were included for data analysis. The score for MNC in ICU was 72.14 ± 15.61 points. All nurses reported experiencing at least one instance of missed care during their shifts. The most frequently missed care items were as follows: assisting and guiding patients in early rehabilitation, analgesia and sedation management and psychosocial assessment of critically ill patients. Statistical analysis revealed that MNC in ICU was significantly influenced by nurses' gender, education level, professional title, ICU type and patient load (p < 0.05). The score for reasons behind MNC was 63.24 ± 18.53 points. The primary contributing factors were as follows: heavy nurse workload, excessive patient transfers, high frequency of patient condition changes and emergency events. ICU type (Internal Medicine ICU/comprehensive ICU), patients load (≥ 4 patients/nurse) and characteristics (master's degree and above, intermediate nurse) emerged as modifiable risk factors for MNC. Missed nursing care occurs frequently in ICU and is influenced by multiple factors. These findings suggest that nursing administrators should ensure adequate nurse staffing levels and enhance training programmes on MNC awareness, and improve nurses' understanding of this phenomenon. These measures would effectively reduce missed care occurrences and subsequently improve ICU nursing quality. This study identifies missed nursing care (MNC) in intensive care units (ICUs), particularly in rehabilitation, pain management and psychosocial support. Staffing/workload (≥ 4 patients/nurse) and unit type (medical/general ICUs) significantly increase MNC. Non-urgent but critical care (e.g., psychological support) is often deprioritised. Implement safe staffing ratios, train nurses on MNC consequences and optimise workflows (e.g., standardised handoffs).

High nurse workload can compromise quality of care in neonatal intensive care units, leading to preventable harm and worsening clinical outcomes. To evaluate differential effects of objective and subjective nurse workload on missed nursing care. The prospective, observational, longitudinal design of this cross-sectional study was used to evaluate associations between shift-level workload of participating nurses and missed care for assigned infants from April 2021 to May 2023. This study was conducted at 10 level II, III, and IV neonatal intensive care units among a convenience sample of registered nurses who provided direct patient care at least 16 hours biweekly, completed unit orientation, owned a smartphone, and did not work in a supervisory capacity. Deidentified electronic health record data from infants assigned to nurse participants were extracted through an honest broker arrangement. Data analysis was conducted from July 2023 to July 2025. Nurse workload was assessed each shift based on objective (maximum number of assigned infants, infant acuity score) and subjective (National Aeronautics and Space Administration [NASA] Task Load Index) measures. The primary outcome, infant-specific missed nursing care on a shift, was measured by nurse self-report of omission of 17 essential types of neonatal nursing care. A total of 247 nurses involved in direct care provided reports of staffing and workload corresponding to the care of 1468 individual infants across 11 364 matched nurse-infant shifts. Nurses were 98% female, and nurses' mean (SD) neonatal intensive care unit experience was 5.7 (7.1) years. When modeling workload variables separately, a shift-level staffing ratio of 3 infants per nurse was significantly associated with increased odds of missed care for individual infants in 9 of 17 types of care; a 2:1 ratio was associated with increased odds in 2 of 17 types of care. Higher subjective workload ratings were associated with increased odds of missed care in all 17 types of care. Negative effects of higher subjective workload persisted across all types of care in joint workload models, while effects of staffing ratios diminished. Few clinically meaningful effects of infant acuity scores on missed care were observed. In this cross-sectional study, nurses' subjective workload and shift-level staffing ratios exerted direct effects on reliable care delivery. High subjective workload and staffing ratios greater than 2 infants per nurse should be targets for workload reduction in neonatal intensive care units.