Musculoskeletal surgery imposes extended recovery periods and significant financial burdens that can undermine individual and system-level health security. Patients undergoing musculoskeletal surgery often face prolonged recovery and substantial post-discharge costs, yet longitudinal evidence on their healthcare use remains limited. This study quantified two-year post-discharge utilization and identified predictors of high expenditure among Korean musculoskeletal surgery patients. A retrospective cohort was constructed from the 2019-2021 Korea Health Panel. Adults (n = 182) hospitalized for spinal, knee, shoulder or other musculoskeletal disorders between July 2019 and June 2020 were followed for 24 months. Outcomes were total healthcare expenditure (log-transformed) and in the top 25% cost group ("high-expenditure") in the second post-discharge year. Among 182 adults hospitalized for musculoskeletal surgery, first-year post-discharge spending averaged US $848 but fell to US $487 in the second year. Readmission fell from 19.2% to 7.1%, and Western-medicine outpatient visits declined from 18.3 ± 25.9 to 13.6 ± 22.9 per person. By contrast, Traditional Korean Medicine (TKM) visits rose from 2.3 ± 6.5 to 3.3 ± 10.0. In multivariable models, metropolitan residence, obesity, additional chronic conditions, and heavier first-year inpatient and outpatient use independently predicted higher second-year costs. Lower household income was associated with lower spending. Index diagnoses were pivotal: spinal disorders and shoulder disorders markedly increased the odds of falling into the top-cost quartile. Among the first-year TKM, frequent chuna/manual therapy sessions were marginally associated with higher costs, suggesting these rehabilitative modalities may serve as proxies for underlying health complexity during the stabilization phase. Spinal and shoulder disorders, metropolitan residence, obesity, multimorbidity, heavy inpatient and outpatient use during the first post-discharge year, and frequent TKM sessions, albeit marginally, jointly predicted the highest second-year expenditures. These findings highlight the value of early risk stratification and tightly coordinated Western-and-traditional care pathways that facilitate the shift from structural repair to functional restoration. From a policy perspective, these results suggest the need for integrated post-discharge care models and targeted financial support strategies to reduce avoidable costs and enhance equity in musculoskeletal rehabilitation.

Sustained clinical and economic impact of sleeve gastrectomy: Beyond weight loss.

The persistent increase in healthcare expenditure has become a major challenge for the sustainability of public financing worldwide. Therefore, identifying the characteristics of at-risk population and their predictability for healthcare use is crucial to inform targeted policy and interventions to curb with increasing healthcare use and expenditure. Drawing on three waves of the HILDA survey that included a 'health module', the study applied four machine learning (ML) methods-Random Forest, Gradient Boosting Decision Trees, Extreme Gradient Boosting, and multilayer perceptron neural networks and conventional logistic regression for prediction of non-emergency healthcare use (specifically primary and tertiary inpatient hospital care). Predictive performance for the classifiers was evaluated using accuracy, sensitivity, and specificity measures, and area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and Matthews Correlation Coefficient (MCC). Calibration of the models was assessed using Brier score, which measures the mean squared difference between predicted probabilities and observed outcomes with lower values indicating better calibration. Finally, Local Interpretable Model-agnostic Explanations (LIME) was conducted to explain the model's predictive behaviour, while SHAP results are provided for each wave along with a representative SHAP plot as a demonstration which uses the probability-contribution scale. Based on 47,899 observations and 741 variables, our model identified socio-economic factors (age, socio-economic status, private insurance status) and health-related variables (e.g. previous contact with healthcare service) and having a designated doctor to see when sick or for health advice were strong predictors of healthcare use. Between the different ML techniques, Gradient Boosting Decision Trees provided better prediction performance on healthcare use compared with logistic regression across all three waves. Although the standard logistic regression produced AUC of 0.69, had 71% positive predictive value (PPV), and 52% negative predictive value (NPV), with 86% sensitivity and 30% specificity, the ML models produced AUC in the range of 0.68 to 0.76, PPV of 75% to 77%, and NPVs of 61% to 63% with sensitivity ranging between 0.86 and 0.89, specificity between 0.40 and 0.44 and brier scores ranging between 0.11 and 0.28. The novelty of using ML techniques on a large, nationally representative longitudinal household survey data that covers a range of different domains provided more robust estimates on factors influencing future healthcare use (primary and inpatient elective care) which are important to inform resource allocation decisions and priority setting.

Antibiotic resistance is one of the most significant challenges of the 21st century, leading to increased global healthcare expenditure due to the necessity for more complex and expensive treatments. In response, researchers are investigating target product profiles as alternative antimicrobial sources capable of combating this prevalent issue. Medicinal plants used in traditional practices have emerged as promising candidates for developing new drug leads effective against antibiotic resistant bacteria. This study aims to evaluate the in vitro antibacterial activity of selected medicinal plants against common human pathogenic bacteria; Escherichia coli (ATCC® 25922™) and Staphylococcus aureus (ATCC® 29213™). The plant materials examined included Abelmoschus moschatus (leaves and stems), Aporosa cardiosperma (Gaertn.) Merr. (leaves and stems), Celosia argentea (leaves and flowers) and Nauclea orientalis (leaves and roots). A sequential extraction procedure using industrial solvents, methanol, ethyl acetate, nd hexane, was performed, followed by qualitative phytochemical analysis to identify secondary metabolites present in the extracts. Antimicrobial susceptibility was assessed using the EUCAST disk diffusion assay. As the main findings of the research, the methanolic crude extracts of all plants exhibited inhibitory effects on the proliferation and growth of both test microorganisms. Among all plant extracts, 400 µg/mL concentrated crude methanolic extracts of Nauclea orientalis leaves exhibited the highest zone of inhibition against Gram-negative E. coli (12.67±0.58 mm) and Gram-positive S. aureus (10.00±2.65 mm). Preliminary phytochemical screening of plant extracts was conducted using standard qualitative methods; Hager's test, foam test, alkaline reagent test, and Ferric chloride test revealed the presence of alkaloids, saponins, flavonoids, phenols, and tannins, respectively. The antibacterial activity was observed in the plant extracts may be caused by the presence of these secondary metabolites. Hence, his study emphasizes the potential of the selected medicinal plants as sources of novel antibacterial agents that can be further improved and developed for pharmaceutical applications against antibiotic resistant bacteria.

Effective nursing interventions for infection prevention and control in acute and critically ill patients with a peripherally inserted venous catheter: an umbrella review.

For financial sustainability and service-based efficiency in healthcare services, there is a need for better understanding and application of cost analysis, Break-even Point (BEP) analysis, and Cost-benefit Analysis (CBA). The present article focuses specifically on Paediatric spirometry and highlights literature and case-based evidence to show how BEP helps determine the minimum service volume required for cost recovery. Evaluating healthcare expenditures against medical benefits, pricing decisions, and investment planning is crucial from a healthcare administration perspective, and these objectives can be achieved through CBA. The present review emphasises the importance of structured financial planning to ensure high-quality, cost-effective healthcare services by integrating break-even and cost-benefit analyses.

Universal Health Coverage places strong emphasis on health insurance as a strategy to ensure need-based care without financial hardship, yet its direct impact on healthcare utilisation and expenditure remains unclear. This scoping review maps recent evidence on how insurance influences both service use and out-of-pocket expenditure (OOPE), including catastrophic health expenditure(CHE) , by examining studies published between 2018 and early 2024. Using the Population, Concept, Context (PCC) framework and PRISMA-Scr checklist, the review included only studies that reported both utilisation and expenditure outcomes within the same context. Ten eligible studies were identified. Overall, the findings indicate that enrolment in health insurance schemes generally increases healthcare utilisation, although the effect varies by type of service and is not universal across all care categories. Evidence also shows that insurance contributes to reducing OOPE, but the magnitude of this effect depends heavily on the design and generosity of the insurance scheme. In contrast, CHE does not demonstrate a clear or consistent association with insurance coverage, suggesting gaps in financial protection. These results highlight the need for policy attention to benefit package design, depth of coverage, and inclusion of diverse service types to strengthen financial risk protection across different health system settings.

Intraspinal anomalies (IA) are reported to occur in 7% to 19% of patients undergoing surgery for adolescent idiopathic scoliosis (AIS). However, these studies have not focused on IA that require neurosurgical intervention and have not assessed whether deformity characteristics predict their underlying presence. We hypothesized that specific radiographic deformity parameters would be associated with underlying IA in a population of presumed AIS patients undergoing posterior spinal fusion (PSF). A retrospective cohort study was performed over a 10-year period, identifying all patients with presumed AIS undergoing PSF who had a preoperative total spine MRI at a single, tertiary care pediatric hospital. The presence of an intraspinal anomaly was confirmed by MRI, and subsequent neurosurgical evaluation and intervention were recorded. Coronal and sagittal plane radiographic criteria were recorded, with a focus on previously identified predictive criteria. Radiographic criteria were compared against the whole population, as well as just those with thoracic deformities, seeking to identify factors associated with the presence of IA, as well as those associated with the need for neurosurgical intervention. A total of 427 patients met the inclusion criteria (mean 14.6±2.3y, 80.7% female). Of these, 33 patients (7.7%) were diagnosed with an IA: 23 syringomyelia, 14 Chiari I malformation, 4 tethered spinal cord, and 8 cerebellar tonsillar ectopia, with only 8 patients (1.9%) undergoing neurosurgical treatment. Thoracic deformities were predominant in 350 patients (81.7%), which was statistically similar for IA and AIS (84.9% vs. 83.3%). For the whole cohort, a left thoracic curve apex was significantly more likely in a patient with an underlying IA (IA: 21% vs. AIS: 6.2%; P<0.001) and was predictive on logistic regression analysis (odds ratio: 0.25, 95% CI: 0.1-0.67; P=0.003). Neurosurgical intervention was also associated with a left thoracic curve apex within the subset of thoracic-only deformities (IA: 38% vs. AIS: 6.5%, P=0.005) with a 37.5% sensitivity and 92.7% specificity. However, all patients requiring neurosurgical intervention also showed neurological symptoms, such as occipital headaches, sleep apnea, or extremity neurological symptoms. The presence of an intraspinal anomaly occurred in 33 patients (7.7%) of this presumed AIS cohort, but only 8 patients (24%) required neurosurgical intervention (1.9% of the total cohort). Only a left thoracic apex was associated with the need for neurosurgical intervention. However, all patients requiring neurosurgical intervention presented with concomitant neurological symptoms. Selective MRI screening protocols incorporating patient sex, radiographic criteria, and neurological indicators may prove sufficient in contrast to universal MRI screening in children with presumed AIS undergoing PSF while minimizing health care expenditures.

Switzerland's statutory health insurance system is compulsory, but offers consumers a choice between different deductible levels. Faced with a steady growth of healthcare expenditure (HCE), both chambers of the national parliament recently voted in favour of increasing the minimum deductible from CHF 300 to CHF 500. In this study, we use claims data from the largest Swiss health insurer to compare the per capita HCE of adults who voluntarily chose different deductible levels. Specifically, we focus on individuals with the minimum deductible (CHF 300), the proposed new minimum (CHF 500), and the maximum deductible (CHF 2500). Applying matching and regression analysis, we find an 11% and 27% reduction in HCE, respectively, of the higher deductibles. The effects are stronger for outpatient care and drugs and weaker for inpatient and long-term care. If the minimum deductible increases to CHF 500 and insurers pass through the estimated CHF 900 reduction in per capita HCE, the average consumer will benefit by CHF 772. No consumer will lose because the maximum additional copayment is capped at CHF 200.

To compare healthcare consumption and work absenteeism of individuals with and without persistent complaints after COVID-19 and determine to what extent cognitive-behavioural factors, neuropsychological functioning and depressive symptoms influence this relationship. Individuals with (n = 129) and without (n = 96) persistent fatigue (Checklist Individual Strength (CIS) fatigue ≥ 35) and difficulty concentrating (CIS concentration ≥ 18) at least 3 months (IQR 16-28months) after SARS-CoV-2 infection were included. Using the Treatment Inventory of Costs in Patients, healthcare consumption (number of visits) and work absenteeism (≥ 3weeks absent from paid work) in the past 3 months were assessed. Mediation analyses were performed to investigate whether the putative factors indeed influence the relationship between persistent complaints and work absenteeism or healthcare consumption. Individuals with persistent complaints more often visited a healthcare professional in the past 3 months (3; IQR = 0-11) than participants without persistent complaints (0; IQR = 0-2, p < 0.001). None of the putative factors was associated with healthcare consumption. Work absenteeism (n = 21/85 with paid work) and work disability (n = 27/225) were only reported by participants with persistent complaints, so no mediation analysis could be performed. Within the group with persistent symptoms, worse neuropsychological functioning (attention and executive functioning) and two illness perception subscales were associated with an increased likelihood of work absenteeism. The relationship between reporting persisting symptoms and increased healthcare consumption could not be explained by cognitive-behavioural factors, depressive symptoms or neuropsychological functioning. In participants with persistent complaints, illness perceptions and neuropsychological functioning were associated with work absenteeism.

Strengthening the audit supervision of healthcare financial expenditures and improving the performance of healthcare expenditures are critical to achieving the Healthy China strategy. This study uses data from 14 cities in Hunan Province from 2013 to 2022 and employs the DEA-Malmquist analysis method to analyze the existing problems and institutional incentives for healthcare financial expenditures in Hunan Province on the basis of estimating the performance of healthcare financial expenditures in each city. The results show that the overall performance level of healthcare financial expenditure in Hunan Province is low, and the efficiency of healthcare expenditure is trending downward. The majority of cities are in the state of increasing scale efficiency of healthcare expenditure, with insufficient scale of inputs. The main reason for the decline in efficiency is the low technological progress change index. The fundamental reasons are the shortcomings of the healthcare financial expenditure system, insufficient binding force, and inadequate supervision. Based on this, the article explores the audit mechanism of changes in expenditure performance, and then proposes specific ways for the audit to promote the improvement of healthcare financial expenditure performance, in order to give full play to the supervision and guarantee role of the audit in promoting healthcare financial expenditure performance.

Development and validation of a machine learning model for frailty screening using claims data in Japan: the Longevity Improvement & Fair Evidence Study.

Does healthcare expenditure matter equally for all mental disorders? An international approach employing dynamic panel data methods.

Mental health conditions impose substantial economic burdens on healthcare systems globally, with growing evidence indicating disproportionate impacts on household-level out-of-pocket (OOP) expenditures. Despite Australia's universal healthcare system, the financial burden of mental health conditions on households remains underexplored. To examine the longitudinal relationship between mental health status and OOP healthcare expenditures among Australian adults, and assess how education and income moderate this relationship. We analyzed 17 waves (2006-2022) of the Household, Income and Labour Dynamics in Australia (HILDA) survey, encompassing 57,647 person-year observations from 3,391 unique individuals. Mental health was measured using the Mental Health Inventory-5 (MHI-5) scale and newly proposed expanded MHI-9 scales. We employed fixed-effects panel regression models and instrumental variable analysis to address unobserved heterogeneity. A one-unit decrease in MHI-5 score is associated with 0.18-0.25% increase in inflation-adjusted OOP healthcare expenditure, equivalent to AU$2.10-$3.00 per unit decline, with a 10-point decline in MHI-5 costing households an additional AU$21-$30. Instrumental variable estimates revealed larger causal effects of 0.80-1.00%. Individuals with good mental health and higher education demonstrated expenditure patterns consistent with Grossman's health capital theory, while those with poor mental health showed disrupted relationships between education and healthcare spending. Urban residents faced 11.00% higher inflation-adjusted OOP costs than the rural residents. Mental health deterioration significantly increases household healthcare expenditure burdens in Australia. Traditional health economics theories apply primarily to individuals with good mental health, indicating the need for targeted rather than universal policy approaches.

Economic Benefits of T-cell-depleting Induction in Deceased Donor Kidney Transplant Recipients.

Chronic kidney disease (CKD) is a globally pervasive and insidious health crisis, frequently escaping detection until its advanced stages, which critically narrows the window for effective treatment and drastically worsens patient prognosis. Crucially, early and precise diagnosis is the key to enhancing patient outcomes and significantly cutting healthcare expenditures. While machine learning (ML) models offer remarkable potential for predicting CKD, their clinical adoption is hampered by the need for centralized datasets, which inevitably triggers major concerns regarding patient privacy and data security. Federated learning (FL) directly tackles this privacy dilemma by allowing multiple institutions to collaboratively train a global model without ever sharing their raw, sensitive patient data. Nevertheless, standard FL approaches, such as federated averaging (FedAvg), are known to suffer from poor performance and sluggish convergence, especially when dealing with the heterogeneous (non-IID) data distributions typical of real-world clinical environments. To overcome these performance bottlenecks, we introduce the Mayfly-based federated learning (MBFL) framework that embeds the Mayfly optimization algorithm (MOA) into the FL aggregation process. MBFL fundamentally improves both the convergence speed and the overall robustness of the global model across diverse data sources. We conducted a rigorous comparative trial using public CKD datasets, benchmarking the performance of MBFL against the foundational FedAvg and two other leading metaheuristic FL variants: Federated Particle Swarm Optimization (FedPSO) and Federated Sand Cat Swarm Optimization (FedSCSO). The results mark a definitive paradigm shift: MBFL achieved a remarkable classification accuracy of 99.2%, decisively outperforming all comparison algorithms. This unprecedented performance confirms MBFL as a performance leader in both data-independent (IID) and non-independent (non-IID) distributed scenarios. Ultimately, MBFL offers a streamlined, efficient, and collaborative new standard for CKD detection, far surpassing the capabilities of current models.

ABSTRACTBackgroundStatins are one of the most widely used therapeutic classes and have significantly contributed to health care expenditures with reported variability between countries and regions. We aim to identify the economic implications of different statin prescription patterns in the central region of Portugal.MethodsA retrospective longitudinal study of statin consumption between 2010 and 2022 in the central region, with data obtained from the national administrative claim database. Prescription and expenditure (retail price) were analysed at the municipality level. A score was created for the quartile position (1 = first to 4 = fourth) of each municipality in the distributions of consumption and expenditure for each year. An overall score was created for the study period by aggregating yearly scores. A four-quadrant analysis with the overall scores of cost/DDD and DDD/1000inhabitants/day (DID) was conducted. Bivariate and multivariate analyses were performed.ResultsStatin consumption increased from 64 DDD/1000inhabitants/day (DID) to 149 DID, while cost/DDD and cost/inhabitant decreased from 0.77 € to 0.26 € and from 17.84 € to 13.99 €, respectively. Prescription pattern of high-intensity statins increased from 26% to 74% of the DDD consumed. A four-quadrant plot revealed discrepancies between the municipalities. These discrepancies were associated with the percentage of pitavastatin in DDD (F = 4.604; p = 0.005), and the percentage of statins monotherapy in DDD (F = 5.201; p = 0.003). Generalising the characteristics of high-level consumption and expenditure municipalities to the entire region would result in a 39.7% increase in expenditure but a 20.8% increase in patients. Prescription of statins per municipality correlated with the prescription of antidepressants (R = 0.643; p < 0.001) in the bivariate analysis, and in the multivariate analysis (p < 0.001; B = 0.580; 95%CI = 0.416:0.744).ConclusionDifferences in prescribing patterns resulted in very different proportions of patients treated and expenses associated with the consumption of these lipid-lowering agents. Further analysis should be carried out to understand the financial implications of prescribing new (patent-protected) medicines in Portugal.

The smoking initiation age may influence risks for chronic diseases and their progression toward multi-morbidity and mortality. However, evidence on the long-term associations of initiating smoking in childhood (< 10 years) with transitions among cardiometabolic conditions remains limited, particularly across countries with varying socio-economic contexts. We aimed to examine the associations of early smoking initiation with the risk and longitudinal progression of heart problems, diabetes, and mortality in older adults. We further explored the associations of daily smoking intensity, and current smoking status with these health outcomes. In this multi-national, prospective cohort study, we used data from three nationally representative longitudinal aging cohorts across three countries from 2010 to 2020: the Health and Retirement Study (HRS, 2010-2020), the China Health and Retirement Longitudinal Study (CHARLS, 2011-2020), and the Mexican Health and Aging Study (MHAS, 2012-2018). We included adults aged ≥ 50 years without heart problems, diabetes, or all-cause mortality at baseline. Participants were categorized based on smoking initiation age. Cox proportional hazards models were used to assess associations between smoking initiation age, incident heart problems, diabetes, and all-cause mortality, by adjusting different covariates. Multi-state models explored the associations of smoking initiation age with different transitions from baseline to individual diseases and their co-morbidity. Among 21,018 eligible older adults, 2,447 participants developed heart problems, 3,078 developed diabetes, and 1,165 reported all-cause mortality. Compared with smoking initiation age ≥ 10, initiating smoking before age 10 was consistently associated with increased risks of heart problems across HRS (adjusted hazard ratio [aHR] 1.52, 95% CI 1.04-2.21), CHARLS (aHR = 1.43, 1.04-1.96), and MHAS (aHR = 1.45, 1.12-1.88). Childhood smoking initiation significantly associated with diabetes (aHR = 1.54, 1.13-2.10) and mortality risk (aHR = 2.27, 1.12-4.63) in the HRS cohort. Multi-state models showed that childhood smoking initiation (age < 10) significantly associated with transition risks from baseline to heart problems in all cohorts. Significant association of smoking initiation age < 10 with risk of direct transitions from baseline to cardiometabolic multi-morbidity (co-occurrence of heart problems and diabetes) was found in CHARLS (aHR = 1.71, 1.12-2.61). Smoking cessation was associated with a reduced risk compared to current smokers; however, the impact of smoking intensity on health outcomes varies across cohorts from different countries. Initiating smoking in early childhood (before age 10) significantly associate with long-term risks of heart disease, diabetes, and premature mortality for older adults, and influences the progression toward cardiometabolic multi-morbidity. Our findings highlight the importance of targeting younger children, beyond current adolescent-focused tobacco intervention strategies. We also emphasize the necessity for early-life smoking prevention, which could substantially reduce the future burden of chronic diseases and associated healthcare expenditures globally. In addition, promoting smoking cessation at any stage of life, particularly among current smokers, remains critical, as quitting smoking can meaningfully lower health risks and improve long-term outcomes.

Impact of Demographic and Socio-Economic Factors on Households Out-of-Pocket Healthcare Expenditures: A Case of Trans-Nzoia County, Kenya

BACKGROUNDAcute cholangitis (AC) is characterized by infection and inflammation of the biliary tree, often resulting from acute biliary obstruction.AIMTo evaluate outcomes of endoscopic retrograde cholangiopancreatography (ERCP) and laparoscopic common bile duct exploration (LCBDE) in the management of AC, focusing on timing, complications, and hospital resource utilization.METHODSBetween 2016 and 2021, a total of 31817 patients were included, with 30330 (95.3%) undergoing ERCP and 1487 (4.67%) undergoing LCBDE.RESULTSERCP patients were older (mean age 64.5 years vs 59.7 years; P < 0.001) with higher Medicare use (56.1% vs 48.1%) compared to LCBDE patients. LCBDE patients had more elective admissions (19.6% vs 11.7%; P < 0.001) and were treated more often in non-teaching hospitals (P < 0.001). Complication rates differed significantly: LCBDE patients had higher respiratory failure (3.34% vs 2.34%; P = 0.026) and bile duct perforation (1.55% vs 0.64%; P = 0.026), while ERCP patients had higher rates of pancreatitis (P < 0.001) and jaundice (P = 0.002). Late ERCP was associated with higher rates of septic shock (1.23%), respiratory failure (3.80%), and bile duct perforation (0.93%) compared to earlier timing. Patients undergoing late ERCP also had longer hospital stays and higher costs (P < 0.001). LCBDE patients experienced significantly longer hospital stays (mean 8.92 days vs 4.89 days) and higher costs, particularly in late interventions (P < 0.001).CONCLUSIONERCP remains the preferred intervention for AC, with earlier procedures resulting in better outcomes and lower resource utilization. LCBDE, while less common, is associated with longer hospital stays and higher costs, particularly when performed late. Optimizing timing for both ERCP and LCBDE is critical to improving patient outcomes and reducing healthcare expenditures.