BACKGROUND: The global economic cost of cancer and the costs of ongoing care for survivors are increasing. Little is known about factors affecting hospitalisations and related costs for the growing number of cancer survivors. Our aim was to identify associated factors of cancer survivors admitted to hospital in the public system and their costs from a health services perspective.
METHODS: A population-based, retrospective, data linkage study was conducted in Queensland (COS-Q), Australia, including individuals diagnosed with a first primary cancer who incurred healthcare costs between 2013 and 2016. Generalised linear models were fitted to explore associations between socio-demographic (age, sex, country of birth, marital status, occupation, geographic remoteness category and socio-economic index) and clinical (cancer type, year of/time since diagnosis, vital status and care type) factors with mean annual hospital costs and mean episode costs.
RESULTS: Of the cohort (N = 230,380) 48.5% (n = 111,820) incurred hospitalisations in the public system (n = 682,483 admissions). Hospital costs were highest for individuals who died during the costing period (cost ratio \'CR\': 1.79, p < 0.001) or living in very remote or remote location (CR: 1.71 and CR: 1.36, p < 0.001) or aged 0-24 years (CR: 1.63, p < 0.001). Episode costs were highest for individuals in rehabilitation or palliative care (CR: 2.94 and CR: 2.34, p < 0.001), or very remote location (CR: 2.10, p < 0.001). Higher contributors to overall hospital costs were \'diseases and disorders of the digestive system\' (AU$661 m, 21% of admissions) and \'neoplastic disorders\' (AU$554 m, 20% of admissions).
CONCLUSIONS: We identified a range of factors associated with hospitalisation and higher hospital costs for cancer survivors, and our results clearly demonstrate very high public health costs of hospitalisation. There is a lack of obvious means to reduce these costs in the short or medium term which emphasises an increasing economic imperative to improving cancer prevention and investments in home- or community-based patient support services.

UNASSIGNED: Trauma-related injuries are the leading cause of death and disability in the active population, with devastating economic, health, and social consequences for nations. TThis study aimed to assess the economic burden of injuries in Iran.
UNASSIGNED: In this study, the economic impact of trauma in Iran in 2019 was estimated using a prevalence-based approach. The prevalence was estimated based on available statistics in Iran and the GBD website. Direct medical expenditures were calculated using a top-down approach. The cost of lost production due to injuries and premature death was also estimated using the DALY value. Microsoft Excel 2019 and Stata software version 13.0 were used for the analysis.
UNASSIGNED: In Iran, approximately 16,500,000 individuals were estimated to have sustained injuries in a single year. The average direct medical expenses for each trauma patient were around $226. Fractures contributed to 39% of the financial impact of trauma. The overall economic burden of trauma in Iran was calculated to be $10,214,403,423. Approximately 66% of this economic burden was attributed to lost productivity and premature death resulting from trauma, while direct medical costs made up 34%.
UNASSIGNED: The economic burden of trauma in Iran is expected to significantly rise in the future. It may be necessary to enhance awareness of injury-related mortality and disability, improve therapies, and expand evidence-based interventions to reduce the economic impact of injuries.

BACKGROUND: Pulmonary tuberculosis (PTB) is a prevalent chronic disease associated with a significant economic burden on patients. Using machine learning to predict hospitalization costs can allocate medical resources effectively and optimize the cost structure rationally, so as to control the hospitalization costs of patients better.
METHODS: This research analyzed data (2020-2022) from a Kashgar pulmonary hospital\'s information system, involving 9570 eligible PTB patients. SPSS 26.0 was used for multiple regression analysis, while Python 3.7 was used for random forest regression (RFR) and MLP. The training set included data from 2020 and 2021, while the test set included data from 2022. The models predicted seven various costs related to PTB patients, including diagnostic cost, medical service cost, material cost, treatment cost, drug cost, other cost, and total hospitalization cost. The model\'s predictive performance was evaluated using R-square (R2), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) metrics.
RESULTS: Among the 9570 PTB patients included in the study, the median and quartile of total hospitalization cost were 13,150.45 (9891.34, 19,648.48) yuan. Nine factors, including age, marital status, admission condition, length of hospital stay, initial treatment, presence of other diseases, transfer, drug resistance, and admission department, significantly influenced hospitalization costs for PTB patients. Overall, MLP demonstrated superior performance in most cost predictions, outperforming RFR and multiple regression; The performance of RFR is between MLP and multiple regression; The predictive performance of multiple regression is the lowest, but it shows the best results for Other costs.
CONCLUSIONS: The MLP can effectively leverage patient information and accurately predict various hospitalization costs, achieving a rationalized structure of hospitalization costs by adjusting higher-cost inpatient items and balancing different cost categories. The insights of this predictive model also hold relevance for research in other medical conditions.

Given recent congressional interest in codifying price transparency regulations, it is important to understand the extent to which newly available price transparency data capture true underlying procedure-level prices. To that end, we compared the prices for maternity services negotiated between a large payer and 26 hospitals in Mississippi across 2 separate price transparency data sources: payer and hospital. The degree of file overlap is low, with only 16.3% of hospital-billing code observations appearing in both data sources. However, for the observations that overlap, pricing concordance is high: Corresponding prices have a correlation coefficient of 0.975, 77.4% match to the penny, and 84.4% are within 10%. Exact price matching rates are greater than 90% for 3 of the 4 service lines included in this study. Taken together, these results suggest that although administrative misalignment exists between payers and hospitals, there is a measure of signal amid the price transparency noise.

Background As the population ages, surgical intervention for degenerative spine conditions is increasing, and this causes a commiserate increase in healthcare expenditures associated with these procedures. Little research has been done on the effect of early-week versus later-week surgeries on patient outcomes, cost, and length of stay (LOS) in patients undergoing lumbar fusion surgery. The purpose of this study is to compare LOS, patient outcomes, and hospital costs between patients having surgery early in the week and later in the week. Methods A retrospective review of 771 patients undergoing a one-, two-, or three-level lumbar fusion from December 2020 to December 2023 at a single institution was performed. Demographics, surgical details, postoperative outcomes and cost were compared between patients who had surgery on Monday, Tuesday, and Wednesday, to those having surgery Thursday or Friday. Univariate and multivariate analyses were performed to compare the groups. Results There were no differences in age, sex, BMI, race, American Society of Anesthesiology (ASA) scores, Charlson Comorbidity Index (CCI) scores, number of operative levels or inpatient/outpatient status between early- and late-week surgeries. Postoperatively the only significant difference was cost, late-week surgeries were, on average, $3,697 more expensive than early-week surgeries ($26,506 vs. $22,809; p<0.001). On multivariate analysis late-week surgeries were 2.47 times more likely to have a non-home discharge (OR: 2.47, 95% CI: 1.24 to 4.95; p=0.010) and 2.19 times more likely to have a 30-day readmission (OR: 2.19, 95% CI:1.01 to 4.74; p=0.044) Additionally, late-week surgeries were $2,041.55 (β:2,041.55, 95% CI: 804.72 to 3,278.38; p=0.001) more expensive than early-week surgeries. Conclusions At our institution, patients undergoing one- to three-level lumbar fusion surgery on Thursday or Friday had a higher risk of non-home discharge, 30-day readmission, and incurred higher cost than those having early-week surgery. Further research is needed to elucidate the reasons for these findings and to evaluate interventions aimed at improving outcomes for patients undergoing surgery later in the week.

BACKGROUND: The Value-Based Health Care (VBHC) model of care provides insights into patient characteristics, outcomes, and costs of care delivery that help clinicians counsel patients. This study compares the allocation and value of curative oncological treatment in frail and fit older patients with esophageal cancer in a dedicated VBHC pathway.
METHODS: Data was collected from patients with primary esophageal cancer without distant metastases, aged 70 years or older, and treated at a Dutch tertiary care hospital between 2015 and 2019. Geriatric assessment (GA) was performed. Outcomes included treatment discontinuation, mortality, quality of life (QoL), and physical functioning over a one-year period. Direct hospital costs were estimated using activity-based costing.
RESULTS: In this study, 89 patients were included with mean age 75 years. Of 56 patients completing GA, 19 were classified as frail and 37 as fit. For frail patients, the treatment plan was chemoradiotherapy and surgery (CRT&S) in 68% (13/19) and definitive chemoradiotherapy (dCRT) in 32% (6/19); for fit patients, CRT&S in 84% (31/37) and dCRT in 16% (6/37). Frail patients discontinued chemotherapy more often than fit patients (26% (5/19) vs 11% (4/37), p = 0.03) and reported lower QoL after six months (mean 0.58 [standard deviation (SD) 0.35] vs 0.88 [0.25], p < 0.05). After one year, 11% of frail and 30% of fit patients reported no decline in physical functioning and QoL and survived. Frail and fit patients had comparable mean direct hospital costs (€24 K [SD €13 K] vs €23 K [SD €8 K], p = 0.82).
CONCLUSIONS: The value of curative oncological treatment was lower for frail than for fit patients because of slightly worse outcomes and comparable costs. The utility of the VBHC model of care depends on the availability of sufficient data. Real-world evidence in VBHC can be used to inform treatment decisions and optimization in future patients by sharing results and monitoring performance over time.
BACKGROUND: The study was retrospectively registered at the Netherlands Trial Register (NTR), trial number NL8107 (date of registration: 22-10-2019).

Robotic surgery has been increasingly adopted in various surgical fields, but the cost-effectiveness of this technology remains controversial due to its high cost and limited improvements in clinical outcomes. This study aims to explore the health economic implications of robotic pancreatic surgery, to investigate its impact on hospitalization costs and consumption of various medical resources. Data of patients who underwent pancreatic surgery at our institution were collected and divided into robotic and traditional groups. Statistical analyses of hospitalization costs, length of stay, costs across different service categories, and subgroup cost analyses based on age, BMI class, and procedure received were performed using t tests and linear regression. Although the total hospitalization cost for the robotic group was significantly higher than that for the traditional group, there was a notable reduction in the cost of medical consumables. The reduction was more prominent among elderly patients, obese patients, and those undergoing pancreaticoduodenectomy, which could be attributed to the technological advantages of the robotic surgery platform that largely facilitate blood control, tissue protection, and suturing. The study concluded that despite higher overall costs, robotic pancreatic surgery offers significant savings in medical consumables, particularly benefiting certain patient subgroups. The findings provide valuable insights into the economic viability of robotic surgery, supporting its adoption from a health economics perspective.

OBJECTIVE: Current policy responses to COVID-19 disruption and care backlogs suggest potential changes to the location and structure of hospital healthcare supply. However, few studies investigating the cost effects of hospital reorganisation consider changes in the mix of outputs or test for the existence of economies of scope in hospital healthcare. Attempts to create dedicated hubs to address healthcare demand backlogs could have unintended adverse cost effects where these are provided outside existing hospital arrangements. To evaluate this, we investigate the existence and size of economies of scope in English hospital healthcare.
METHODS: We use cost and activity data from the English NHS, linked to aggregated staff wage information and information taken from hospital financial statements. Cost and activity data was obtained from NHS England\'s Costing Publications. Wage data was extracted from the NHS\'s Electronic Staff Record via the NHS England Workforce Statistics Team, and published hospital financial accounts were aggregated and linked together at the organisation level.
RESULTS: General Surgery exhibited positive economies of scope when provided alongside other healthcare, as to a lesser extent did General Medicine and Obstetric/Gynaecology healthcare. There was little evidence for economies of scope in Diagnostic and Pathology services, Orthopaedics, or Emergency Care. Few (2/28) output cross-products (cost complementarities) were statistically significant, but Baumol\'s wider definition of scope economies demonstrates that scope economies are present in some specialties.
CONCLUSIONS: Policymakers seeking to maximise the amount of healthcare provided and minimise the costs of doing so may wish to consider retaining General Surgery, General Medicine and Obstetric/Gynaecology healthcare supply alongside the provision of other clinical specialties. There is limited evidence that reconfiguring supply by centralizing other specialty groups into fewer providers would increase costs.

BACKGROUND: Coronary heart disease (CHD) is the most prevalent type of cardiovascular disease in Iran. This study aims to investigate the estimation and determinants of direct hospitalisation cost for patients with CHD in Iranian hospitals.
METHODS: We identified patients with CHD in Iran in 2019-2020. Data were gathered from the Iran Health Insurance Organisation information systems and the Ministry of Health and Medical Education. This was a cross-sectional prevalence-based study. Generalised linear models were used to find the determinants of hospitalisation cost for patients with CHD. A total of 86 834 patients suffering from CHD were studied.
RESULTS: Mean hospitalisation cost per CHD patient was US$382.90±US$500.72 while the mean daily hospitalisation cost per CHD patient was US$89.71±US$89.99. In-hospital mortality of CHD was 2.52%. Hospitalisation accommodation and medications had the highest share of hospitalisation costs (25.59% and 22.63%, respectively). Men spent 1.12 (95% CI 1.11 to 1.13) times more on hospitalisation costs compared with women, and individuals aged 60 to 69 had hospitalisation costs 1.04 (95% CI 1.02 to 1.06) times higher than those in the 0-49 age range. Patients insured by the Iranian Fund have significantly higher costs 1.17 (95% CI 1.14 to 1.19) than the Rural fund. Hospitalisation costs for patients with CHD who received surgery and angiography were significantly 2.36 (95% CI 2.30 to 2.43) times higher than for patients who did not undergo surgery and angiography.
CONCLUSIONS: Applying CHD prevention strategies for men and the middle-aged population (50-70 years) is strongly recommended. Prudent use and prescribing of medications will be helpful to reduce hospitalisation cost.

BACKGROUND: Comprehensive stroke centres across England have developed investment proposals, showing the estimated increases in mechanical thrombectomy (MT) treatment volume that would justify extending the standard hours to a 24/7 service provision. These investment proposals have been developed taking a financial accounting perspective, that is by considering the financial revenues from tariff income. However, given the pressure put on local health authorities to provide value for money services, an affordability question emerges. That is, at what additional MT treatment volume the additional treatment costs are offset by the additional health economic benefits, that is quality-adjusted life years (QALYs) and societal cost savings, generated by administering MT compared to standard care.
METHODS: A break-even analysis was conducted to identify the additional MT treatment volume required. The incremental hospital-related costs associated with the 24/7 MT extension were estimated using information and parameters from four relevant business cases. The additional societal cost savings and health benefits were estimated by adapting a previously developed Markov chain-based model.
RESULTS: The additional hospital-related annual costs for extending MT to a 24/7 service were estimated at a mean of £3,756,818 (range £1,847,387 to £5,092,788). On average, 750 (range 246 to 1,571) additional eligible stroke patients are required to be treated with MT yearly for the proposed 24/7 service extension to be affordable from a health economic perspective. Overall, the additional facility and equipment costs associated with the 24/7 extension would affect this estimate by 20%.
CONCLUSIONS: These findings support the ongoing debate regarding the optimal levels of MT treatment required for a 24/7 extension and respective changes in hospital organisational activities. They also highlight a need for a regional-level coordination between local authorities and hospital administrations to ensure equity provision in that stroke patients can benefit from MT and that the optimal MT treatment volume is reached. Future studies should contemplate reproducing the presented analysis for different health service provision settings and decision making contexts.