Time-dependent cost comparison and health economic impact analysis of second-line interventions for transplant-ineligible patients with relapsed or refractory diffuse large B cell lymphoma.

OBJECTIVES: Novel interventions (axicabtagene ciloleucel [axi-cel], lisocabtagene maraleucel [liso-cel], tafasitamab-lenalidomide [Tafa-L], polatuzumab-rituximab-bendamustine [pola-BR]) improve clinical outcomes in second-line (2 L) treatment of transplant-ineligible patients with early relapse or refractory (R/R) diffuse large B cell lymphoma (DLBCL). The costs vary depending on the respective treatment regimen and the treatment duration, difficult comparability in reimbursement decisions. The objective was to analyze the health economic impacts of novel 2 L interventions and conventional immunochemotherapies (bendamustine-rituximab [BR], rituximab-gemcitabine-oxaliplatin [R-GemOx]) from a German healthcare payer's perspective as a function of treatment duration. METHODS: An economic model was developed to compare treatment costs of 2 L interventions depending on the treatment duration. Treatment duration was measured by progression-free survival (PFS), identified based on a systematic review. Total and average costs were calculated over 5 years to evaluate incremental costs at median PFS for each intervention. RESULTS: Average costs per month at median PFS ranged from €2846 (95% CI: 5067-1641) to €40 535 (95% CI: 91180-N/A) for BR and liso-cel, respectively. Incremental costs at the lowest median PFS (R-GemOx: 5.3 months) revealed -€664, €5560, €11 817, €53 145, and €67 745 for BR, Tafa-L, pola-BR, axi-cel, and liso-cel as compared to R-GemOx, respectively. CONCLUSIONS: Analyses uncovered a variation of incremental costs of 2 L transplant-ineligible DLBCL interventions as a function of time leading to amortization of high-priced interventions.

A Causal Model for Primary Prevention of Cardiovascular Disease: The Health Economic Model for the Primary Prevention of Cardiovascular Disease.

OBJECTIVES: Our objective was to design and develop an open-source model capable of simulating interventions for primary prevention of cardiovascular disease (CVD) that incorporated the cumulative effects of risk factors (eg, cholesterol years or blood-pressure years) to enhance health economic modeling in settings which clinical trials are not possible. METHODS: We reviewed the literature to design the model structure by selecting the most important causal risk factors for CVD-low-density lipoprotein-cholesterol (LDL-C), systolic blood pressure (SBP), smoking, diabetes, and lipoprotein (a) (Lp(a))-and most common CVDs-myocardial infarction and stroke. The epidemiological basis of the model involves the simulation of risk factor trajectories, which are used to modify CVD risk via causal effect estimates derived from Mendelian randomization. LDL-C, SBP, Lp(a), and smoking all have cumulative impacts on CVD risk, which were incorporated into the health economic model. The data for the model were primarily sourced from the UK Biobank study. We calibrated the model using clinical trial data and validated the model against the observed UK Biobank data. Finally, we performed an example health economic analysis to demonstrate the utility of the model. The model is open source. RESULTS: The model performed well in all validation tests. It was able to produce interpretable and plausible (consistent with expectations of the existing literature) results from an example health economic analysis. CONCLUSIONS: We have constructed an open-source health economic model capable of incorporating the cumulative effect of LDL-C (ie, cholesterol years), SBP (SBP-years), Lp(a), and smoking on lifetime CVD risk.

Consolidated Health Economic Evaluation Reporting Standards for Interventions That Use Artificial Intelligence (CHEERS-AI).

OBJECTIVES: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed Consolidated Health Economic Evaluation Reporting Standards for Interventions that use AI (CHEERS-AI) to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner. METHODS: Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalize outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective. RESULTS: A total of 58 participants responded to survey round 1, 42, and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported. CONCLUSIONS: CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.

Estimating the Lifetime Costs and Benefits of the Incredible Years Teacher Classroom Management Intervention Using Data From 30 Months Follow-Up of the Supporting Teachers and childRen in Schools Trial.

OBJECTIVES: The Incredible Years Teacher® Classroom Management (IY-TCM) intervention is associated with short-term improvements in mental health difficulties in young people. The aim was to estimate the long-term impact and cost-effectiveness of the IY-TCM intervention compared with no intervention. METHODS: An existing health economic model (LifeSim 1.0) was used to translate short-term changes in the Strength and Difficulties Questionnaire (SDQ), based on the Supporting Teachers and childRen in Schools cluster randomized controlled trial of the IY-TCM intervention in schools, into estimated medium- and long-term effects using multiple longitudinal data sets. LifeSim 1.0 was adapted to incorporate teacher-reported SDQ and account for individual heterogeneity. Cost-effectiveness analyses were conducted using the trial-based intervention cost with subgroup analyses on deprivation, conduct scores and parental depression in the simulated baseline population. RESULTS: Regression analyses show significant predictor variables for intervention effectiveness, including deprivation and baseline SDQ. LifeSim results indicate small gains in long-term outcomes, and cost-effective analyses estimated that the IY-TCM intervention could be cost-effective, but there was a large amount of uncertainty (net monetary benefit = £10, Estimated CI = -£134, £156). Benefits and certainty of cost-effectiveness were greater for some subgroups, such as those with high conduct scores at baseline (net monetary benefit = £206, Estimated CI = £26, £318). CONCLUSIONS: IY-TCM could be cost-effective, but there was a large amount of uncertainty around costs and benefits. Greater benefits for pupils with difficulties at baseline suggest that the intervention may be more cost-effective for schools in more deprived areas with high levels of conduct problems.

IPECAD Modeling Workshop 2023 Cross Comparison Challenge on Cost-Effectiveness Models in Alzheimer's Disease.

OBJECTIVES: Decision-analytic models assessing the value of emerging Alzheimer's disease (AD) treatments are challenged by limited evidence on short-term trial outcomes and uncertainty in extrapolating long-term patient-relevant outcomes. To improve understanding and foster transparency and credibility in modeling methods, we cross-compared AD decision models in a hypothetical context of disease-modifying treatment for mild cognitive impairment (MCI) due to AD. METHODS: A benchmark scenario (US setting) was used with target population MCI due to AD and a set of synthetically generated hypothetical trial efficacy estimates. Treatment costs were excluded. Model predictions (10-year horizon) were assessed and discussed during a 2-day workshop. RESULTS: Nine modeling groups provided model predictions. Implementation of treatment effectiveness varied across models based on trial efficacy outcome selection (CDR-SB, CDR-global, MMSE, FAQ) and analysis method (observed severity transitions, change from baseline, progression hazard ratio, or calibration to these). Predicted mean time in MCI ranged from 2.6-5.2 years for control strategy, and from 0.1-1.0 years for difference between intervention and control strategies. Predicted quality-adjusted life-year gains ranged from 0.0-0.6 and incremental costs (excluding treatment costs) from -US$66,897 to US$11,896. CONCLUSIONS: Trial data can be implemented in different ways across health-economic models leading to large variation in model predictions. We recommend 1) addressing the choice of outcome measure and treatment effectiveness assumptions in sensitivity analysis, 2) a standardized reporting table for model predictions, and 3) exploring the use of registries for future AD treatments measuring long-term disease progression to reduce uncertainty of extrapolating short-term trial results by health economic models.

Validating Health Economic Models With the Probabilistic Analysis Check dashBOARD.

OBJECTIVES: Health economic (HE) models are often considered as "black boxes" because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making. This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes. METHODS: The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist. Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel. To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model's outcomes. RESULTS: PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes. CONCLUSIONS: PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models' parameters and outcomes.

New International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) Open-Source Model Framework for the Health Technology Assessment of Early Alzheimer's Disease Treatment: Development and Use Cases.

OBJECTIVES: Reimbursement decisions for new Alzheimer's disease (AD) treatments are informed by economic evaluations. An open-source model with intuitive structure for model cross-validation can support the transparency and credibility of such evaluations. We describe the new International Pharmaco-Economic Collaboration on Alzheimer's Disease (IPECAD) open-source model framework (version 2) for the health-economic evaluation of early AD treatment and use it for cross-validation and addressing uncertainty. METHODS: A cohort state-transition model using a categorized composite domain (cognition and function) was developed by replicating an existing reference model and testing it for internal validity. Then, features of existing Institute for Clinical and Economic Review (ICER) and Alzheimer's Disease Archimedes Condition-Event Simulator (AD-ACE) models assessing lecanemab treatment were implemented for model cross-validation. Additional uncertainty scenarios were performed on choice of efficacy outcome from trial, natural disease progression, treatment effect waning and stopping rules, and other methodological choices. The model is available open-source as R code, spreadsheet, and web-based version via https://github.com/ronhandels/IPECAD. RESULTS: In the IPECAD model incremental life-years, quality-adjusted life-years (QALY) gains and cost savings were 21% to 31% smaller compared with the ICER model and 36% to 56% smaller compared with the AD-ACE model. IPECAD model results were particularly sensitive to assumptions on treatment effect waning and stopping rules and choice of efficacy outcome from trial. CONCLUSIONS: We demonstrated the ability of a new IPECAD open-source model framework for researchers and decision makers to cross-validate other (Health Technology Assessment submission) models and perform additional uncertainty analyses, setting an example for open science in AD decision modeling and supporting important reimbursement decisions.

Challenges of Incorporating Life Cycle Drug Pricing in Cost-Effectiveness Models: A Review of Methods and Modeling Suggestions.

OBJECTIVES: This study aimed to conduct a review of existing methods used to incorporate life cycle drug pricing (LCDP) in cost-effectiveness analyses (CEAs), identify common methodological challenges, and suggest modeling approaches for prospectively implementing LCDP in CEA. METHODS: Two complementary searches were conducted in PubMed, combined with hand searching and reference mining, to identify English language full-text articles that explored (1) how drug prices change over time and (2) methods used to apply dynamic pricing in cost-effectiveness models (CEMs). Relevant articles were reviewed, and authors discussed the common methodological practices used in the literature and their associated challenges on prospectively implementing LCDP in CEMs. For each key challenge identified, we provide modeling suggestions to address the issue. RESULTS: We screened 1200 studies based on title and abstract; 117 were reviewed for eligibility, and 47 individual studies were included across both searches. Variations in prices over a product's life cycle are complex and multifactorial, and models applying LCDP in CEA varied in their methodology. We identified 4 key challenges to modeling LCDP in CEA, including how to model price trends before and after loss of exclusivity, how to capture the effect of price changes on future patient cohorts, and how to report results. CONCLUSION: Accurately quantifying the impact of LCDP requires careful consideration of multiple aspects pertaining to both the evolution of drug prices and how to reflect these in CEA. Although uncertainties remain, our findings can aid implementation and evaluation of LCDP in economic evaluations.

Clostridioides difficile infection, recurrence and the associated healthcare consumption in Sweden between 2006 and 2019: a population-based cohort study.

BACKGROUND: Clostridioides difficile infection (CDI) causes a major burden to individuals and society, yet the impact may vary depending on age, sex, underlying comorbidities and where CDI was acquired (hospital or community). METHODS: This Swedish nationwide population-based cohort study (2006-2019) compared all 43,150 individuals with CDI to their 355,172 matched controls (first year and entire follow-up). Negative binomial regression models compared the cumulated length of stay, number of in-hospital admissions, outpatient visits and prescriptions after the first CDI episode expressed as incidence rate ratios (IRR) and 95% confidence intervals for the entire follow-up. RESULTS: Overall, 91.6% of CDI cases were hospital acquired, and 16.8% presented with recurrence(s); 74.8%of cases were ≥ 65 years and 54.2% were women. Compared to individuals without CDI, in-hospital stay rates were 18.01 times higher after CDI (95% CI 17.40-18.63, first-year: 27.4 versus 1.6 days), 9.45 times higher in-hospital admission (95% CI 9.16-9.76, first-year: 2.6 versus 1.3 hospitalisations), 3.94 times higher outpatient visit (95% CI 3.84-4.05, first-year: 4.0 versus 1.9 visits) and 3.39 times higher dispensed prescriptions rates (95% CI 3.31-3.48, first-year: 25.5 versus 13.7 prescriptions). For all outcomes, relative risks were higher among the younger (< 65 years) than the older (≥ 65 years), and in those with fewer comorbidities, but similar between sexes. Compared to those without recurrence, individuals with recurrence particularly showed a higher rate of hospital admissions (IRR = 1.18, 95% 1.12-1.24). Compared to community-acquired CDI, those with hospital-acquired CDI presented with a higher rate of hospital admissions (IRR = 7.29, 95% CI 6.68-7.96) and a longer length of stay (IRR = 7.64, 95% CI 7.07-8.26). CONCLUSION: CDI was associated with increased health consumption in all affected patient groups. The majority of the CDI burden could be contributed to hospital-acquired CDI (~ 9/10), older patients (~ 3/4) and those with multiple comorbidities (~ 6/10 Charlson score ≥ 3), with 1/5 of the total CDI burden contributed to individuals with recurrence. Yet, relatively speaking the burden was higher among the younger and those with fewer comorbidities, compared to their peers without CDI.

Health economic evaluation of blended collaborative care for older multimorbid heart failure patients: study protocol.

BACKGROUND: Integrated care, in particular the 'Blended Collaborative Care (BCC)' strategy, may have the potential to improve health-related quality of life (HRQoL) in multimorbid patients with heart failure (HF) and psychosocial burden at no or low additional cost. The ESCAPE trial is a randomised controlled trial for the evaluation of a BCC approach in five European countries. For the economic evaluation of alongside this trial, the four main objectives were: (i) to document the costs of delivering the intervention, (ii) to assess the running costs across study sites, (iii) to evaluate short-term cost-effectiveness and cost-utility compared to providers' usual care, and (iv) to examine the budgetary implications. METHODS: The trial-based economic analyses will include cross-country cost-effectiveness and cost-utility assessments from a payer perspective. The cost-utility analysis will calculate quality-adjusted life years (QALYs) using the EQ-5D-5L and national value sets. Cost-effectiveness will include the cost per hospital admission avoided and the cost per depression-free days (DFD). Resource use will be measured from different sources, including electronic medical health records, standardised questionnaires, patient receipts and a care manager survey. Uncertainty will be addressed using bootstrapping. DISCUSSION: The various methods and approaches used for data acquisition should provide insights into the potential benefits and cost-effectiveness of a BCC intervention. Providing the economic evaluation of ESCAPE will contribute to a country-based structural and organisational planning of BCC (e.g., the number of patients that may benefit, how many care managers are needed). Improved care is expected to enhance health-related quality of life at little or no extra cost. TRIAL REGISTRATION: The study follows CHEERS2022 and is registered at the German Clinical Trials Register (DRKS00025120).

Mapping of Family Reported Outcome Measure (FROM-16) scores to EQ-5D: algorithm to calculate utility values.

OBJECTIVE: Although decision scientists and health economists encourage inclusion of family member/informal carer utility in health economic evaluation, there is a lack of suitable utility measures comparable to patient utility measures such those based on the EQ-5D. This study aims to predict EQ-5D-3L utility values from Family Reported Outcome Measure (FROM-16) scores, to allow the use of FROM-16 data in health economic evaluation when EQ-5D data is not available. METHODS: Data from 4228 family members/partners of patients recruited to an online cross-sectional study through 58 UK-based patient support groups, three research support platforms and Welsh social services departments were randomly divided five times into two groups, to derive and test a mapping model. Split-half cross-validation was employed, resulting in a total of ten multinomial logistic regression models. The Monte Carlo simulation procedure was used to generate predicted EQ-5D-3L responses, and utility scores were calculated and compared against observed values. Mean error and mean absolute error were calculated for all ten validation models. The final model algorithm was derived using the entire sample. RESULTS: The model was highly predictive, and its repeated fitting using multinomial logistic regression demonstrated a stable model. The mean differences between predicted and observed health utility estimates ranged from 0.005 to 0.029 across the ten modelling exercises, with an average overall difference of 0.015 (a 2.2% overestimate, not of clinical importance). CONCLUSIONS: The algorithm developed will enable researchers and decision scientists to calculate EQ-5D health utility estimates from FROM-16 scores, thus allowing the inclusion of the family impact of disease in health economic evaluation of medical interventions when EQ-5D data is not available.

Estimation of the maximum potential cost saving from reducing serious adverse events in hospitalized patients.

PURPOSE: The increasing use of advanced medical technologies to detect adverse events, for instance, artificial intelligence-assisted technologies, has shown promise in improving various aspects within health care but may also come with substantial expenses. Therefore, understanding the potential economic benefits can guide decision-making processes regarding implementation. We aimed to estimate the potential cost savings associated with reducing length of stay and avoiding readmissions within the framework of an artificial intelligence-assisted vital signs monitoring system. METHODS: We used data from Danish national registries and coarsened exact matching to estimate the difference in length of stay and probability of readmission among adult in-hospital patients exposed to and not exposed to serious adverse events. We used these estimates to calculate the maximum potential savings that could be achieved by early detection of adverse events to reduce length of stay and avoid readmissions. RESULTS: Patients exposed to serious adverse events during admission had 2.4 (95% CI: 2.4-2.5) additional hospital bed days and had 14% (95% CI 11%-17%) higher odds of readmissions compared with patients not exposed to such events. A base case scenario yielded maximum potential savings if one patient avoided a serious adverse event of EUR 2040 due to reduced length of stay and EUR 43 due to avoidance of readmissions caused by serious adverse events. CONCLUSION: Reductions in serious adverse events are associated with decreased healthcare costs due to reduced length of stay and avoided readmissions. Artificial intelligence-assisted vital signs monitoring systems are one potential approach to reduce serious adverse events, however, the ability of this technology to reduce adverse events remains unclear. Comprehensive prospective analyses of such systems including the intervention and implementation costs are necessary to understand their full economic impact.

Health-economic evaluation of orthogeriatric co-management for patients with pelvic or vertebral fragility fractures.

BACKGROUND: Orthogeriatric co-management (OGCM) addresses the special needs of geriatric fracture patients. Most of the research on OGCM focused on hip fractures while results concerning other severe fractures are rare. We conducted a health-economic evaluation of OGCM for pelvic and vertebral fractures. METHODS: In this retrospective cohort study, we used German health and long-term care insurance claims data and included cases of geriatric patients aged 80 years or older treated in an OGCM (OGCM group) or a non-OGCM hospital (non-OGCM group) due to pelvic or vertebral fractures in 2014-2018. We analyzed life years gained, fracture-free life years gained, healthcare costs, and cost-effectiveness within 1 year. We applied entropy balancing, weighted gamma and two-part models. We calculated incremental cost-effectiveness ratios and cost-effectiveness acceptability curves. RESULTS: We included 21,036 cases with pelvic (71.2% in the OGCM, 28.8% in the non-OGCM group) and 33,827 with vertebral fractures (72.8% OGCM, 27.2% non-OGCM group). 4.5-5.9% of the pelvic and 31.8-33.8% of the vertebral fracture cases were treated surgically. Total healthcare costs were significantly higher after treatment in OGCM compared to non-OGCM hospitals for both fracture cohorts. For both fracture cohorts, a 95% probability of cost-effectiveness was not exceeded for a willingness-to-pay of up to €150,000 per life year or €150,000 per fracture-free life year gained. CONCLUSION: We did not obtain distinct benefits of treatment in an OGCM hospital. Assigning cases to OGCM or non-OGCM group on hospital level might have underestimated the effect of OGCM as not all patients in the OGCM group have received OGCM.

Cost-effectiveness of prehabilitation of elderly frail or pre-frail patients prior to elective surgery (PRAEP-GO) versus usual care - Protocol for a health economic evaluation alongside a randomized controlled trial.

BACKGROUND: Prehabilitation aims to improve patients' functional capacity before surgery to reduce perioperative complications, promote recovery and decrease probability of disability. The planned economic evaluation is performed alongside a large German multi-centre pragmatic, two-arm parallel-group, randomized controlled trial on prehabilitation for frail elderly patients before elective surgery compared to standard care (PRAEP-GO RCT). The aim is to determine the cost-effectiveness and cost-utility of prehabilitation for frail elderly before an elective surgery. METHODS: The planned health economic evaluation comprises cost-effectiveness, and cost-utility analyses. Analyses are conducted in the German context from different perspectives including the payer perspective, i.e. the statutory health insurance, the societal perspective and the health care provider perspective. Data on outcomes and costs, are collected alongside the ongoing PRAEP-GO RCT. The trial population includes frail or pre-frail patients aged ≥70 years with planned elective surgery. The intervention consists of frailty screening (Fried phenotype), a shared decision-making conference determining modality (physiotherapy and unsupervised physical exercises, nutrition counselling, etc.) and setting (inpatient, day care, outpatient etc.) of a 3-week individual multimodal prehabilitation prior to surgery. The control group receives standard preoperative care. Costs include the intervention costs, the costs of the index hospital stay for surgery, and health care resources consumed during a 12-month follow-up. Clinical effectiveness outcomes included in the economic evaluation are the level of care dependency, the degree of disability as measured by the WHO Disability Assessment Schedule 2.0 (WHODAS 2.0), quality-adjusted life years (QALY) derived from the EQ-5D-5L and the German utility set, and complications occurring during the index hospital stay. Each adopted perspective considers different types of costs and outcomes as outlined in the protocol. All analyses will feature Intention-To-Treat analysis. To explore methodological and parametric uncertainties, we will conduct probabilistic and deterministic sensitivity analyses. Subgroup analyses will be performed as secondary analyses. DISCUSSION: The health economic evaluation will provide insights into the cost-effectiveness of prehabilitation in older frail populations, informing decision-making processes and contributing to the evidence base in this field. Potential limitation includes a highly heterogeneous trial population. TRIAL REGISTRATION: PRAEP-GO RCT: NCT04418271; economic evaluation: OSF ( https://osf.io/ecm74 ).

Cross-model validation of public health microsimulation models; comparing two models on estimated effects of a weight management intervention.

BACKGROUND: Health economic modelling indicates that referral to a behavioural weight management programme is cost saving and generates QALY gains compared with a brief intervention. The aim of this study was to conduct a cross-model validation comparing outcomes from this cost-effectiveness analysis to those of a comparator model, to understand how differences in model structure contribute to outcomes. METHODS: The outcomes produced by two models, the School for Public Health Research diabetes prevention (SPHR) and Health Checks (HC) models, were compared for three weight-management programme strategies; Weight Watchers (WW) for 12 weeks, WW for 52 weeks, and a brief intervention, and a simulated no intervention scenario. Model inputs were standardised, and iterative adjustments were made to each model to identify drivers of differences in key outcomes. RESULTS: The total QALYs estimated by the HC model were higher in all treatment groups than those estimated by the SPHR model, and there was a large difference in incremental QALYs between the models. SPHR simulated greater QALY gains for 12-week WW and 52-week WW relative to the Brief Intervention. Comparisons across socioeconomic groups found a stronger socioeconomic gradient in the SPHR model. Removing the impact of treatment on HbA1c from the SPHR model, running both models only with the conditions that the models have in common and, to a lesser extent, changing the data used to estimate risk factor trajectories, resulted in more consistent model outcomes. CONCLUSIONS: The key driver of difference between the models was the inclusion of extra evidence-based detail in SPHR on the impacts of treatments on HbA1c. The conclusions were less sensitive to the dataset used to inform the risk factor trajectories. These findings strengthen the original cost-effectiveness analyses of the weight management interventions and provide an increased understanding of what is structurally important in the models.

Electronic monitoring versus manual paper-based monitoring for hand hygiene compliance: a comprehensive health economic assessment analysis.

BACKGROUND: Monitoring hand hygiene compliance (HHC) of healthcare providers (HCPs) in healthcare facilities is critical for hand hygiene (HH) promotion. However, less is known about the cost and effectiveness of different HHC monitoring tools. In this study, we aimed to compare various health economic indicators corresponding to electronic system-based monitoring (ESM) and manual paper-based monitoring (MPM) for HHC to provide evidence-based advice for HHC monitoring measures targeted selecting. METHODS: A before and after study in 40 clinical departments with 4,524 healthcare providers was conducted from December 2022 to January 2023 (MPM implementation phase) and March 2023 to May 2023 (ESM implementation phase). The cost-effectiveness, cost-efficiency, the extent of the Hawthorne effect, and indirect cost-benefit of the two monitoring methods were compared. RESULTS: The total cost spent on ESM for the 40 departments (17,702.92 CNY) was 4,123.76 CNY lower than that of MPM (21,826.68 CNY). The HHC of MPM (80.16%) was higher than that of ESM (69.82%) (p < 0.01). In high- and medium-risk departments, the cost-effectiveness ratio of ESM (7,977.90 CNY and 13,794.60 CNY, respectively) was lower than that of MPM (9,039.61 CNY and 14,549.05 CNY, respectively). In low-risk departments, the cost-effectiveness ratio of ESM (3,910.77 CNY) was higher than that of MPM (3,899.06 CNY). Compared with ESM, the incremental cost of MPM in all departments was 4,123.76 CNY, the incremental effectiveness was 10.34%, and the incremental cost-effectiveness ratio was 39,881.62 CNY. Between the two monitoring methods, the efficiency of ESM (48.11%) in all departments was higher than that of MPM (14.20%) (p < 0.01). The cost-efficiency ratio of MPM in all departments (155,775.56 CNY) was higher than that of ESM (36,796.76 CNY). The extent of Hawthorne effect of MPM of HHC in all departments (43.99%) was higher than that of ESM (35.69%) (p < 0.01). When ESM was used as the HHC monitoring approach, the HAI rates (1.39%) in all departments were higher than that when MPM was used (1.34%) (p = 0.562). When the payment willingness was less than 40,000 CNY, the ESM method was the better option for cost-effectiveness; When the input exceeded this threshold, the MPM method was the better option for cost-effectiveness. CONCLUSIONS: ESM exhibited notable advantages over MPM in terms of cost-effectiveness, cost-efficiency, cost-benefit, and the Hawthorne effect.

Health-economic evaluation of orthogeriatric co-management for patients with forearm or humerus fractures: an analysis of insurance claims data from Germany.

Orthogeriatric co-management (OGCM) describes a collaboration of orthopedic surgeons and geriatricians for the treatment of fragility fractures in geriatric patients. While its cost-effectiveness for hip fractures has been widely investigated, research focusing on fractures of the upper extremities is lacking. Thus, we conducted a health economic evaluation of treatment in OGCM hospitals for forearm and humerus fractures.In a retrospective cohort study with nationwide health insurance claims data, we selected the first inpatient stay due to a forearm or humerus fracture in 2014-2018 either treated in hospitals that were able to offer OGCM (OGCM group) or not (non-OGCM group) and applied a 1-year follow-up. We included 31,557 cases with forearm (63.1% OGCM group) and 39,093 cases with humerus fractures (63.9% OGCM group) and balanced relevant covariates using entropy balancing. We investigated costs in different health sectors, length of stay, and cost-effectiveness regarding total cost per life year or fracture-free life year gained.In both fracture cohorts, initial hospital stay, inpatient stay, and total costs were higher in OGCM than in non-OGCM hospitals. For neither cohort nor effectiveness outcome, the probability that treatment in OGCM hospitals was cost-effective exceeded 95% for a willingness-to-pay of up to €150,000.We did not find distinct benefits of treatment in OGCM hospitals. Assigning cases to study groups on hospital-level and using life years and fracture-free life years, which might not adequately reflect the manifold ways these fractures affect the patients' health, as effectiveness outcomes, might have underestimated the effectiveness of treatment in OGCM hospitals.

Extending mechanical thrombectomy service provision to 24/7: a break-even analysis.

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.

Inclusion of phase III clinical trial costs in health economic evaluations.

INTRODUCTION: Protocol-driven trial activities contribute to the utility gain demonstrated in the phase III clinical trial of a new drug. If this utility gain cannot be distinguished from the effects of the new drug itself, protocol-driven trial costs cannot be easily dismissed for consistency reasons. This study aims to estimate the impact of including per-patient costs of phase III clinical trials on the incremental cost-effectiveness ratio (ICER). METHODS: The analysis utilized a modeling approach with secondary data from an ad-hoc literature review, considering both societal and payer perspectives. While the costs of phase III clinical trials may cancel out during the period of "normal" life-years due to the incremental cost calculation, they do not cancel out when differential early treatment termination occurs (e.g., due to differential mortality). Assuming the presence of differential mortality, per-patient phase III trial costs were calculated for the period of added life-years. These costs were then included in the ICER of a new drug, under the assumption that direct patient-related costs constitute 30-70% of the total trial costs. Capital costs were also incorporated from a societal perspective. RESULTS: Based on assumptions of $40,000 out-of-pocket expenses per patient enrolled in a phase III trial and a life expectancy gain of three months, incremental costs increased by $27,000 from a societal perspective. From a payer perspective, the estimate was $12,000. CONCLUSIONS: The costs of phase III trials are a relevant component of the ICER, and excluding it is generally not appropriate for consistency reasons. Properly considering these trial costs is essential for a comprehensive evaluation of a new drug's cost-effectiveness.

A blueprint for health technology assessment capacity building: lessons learned from Malta.

OBJECTIVES: The development and strengthening of health technology assessment (HTA) capacity on the individual and organizational level and the wider environment is relevant for cooperation on HTAs. Based on the Maltese case, we provide a blueprint for building HTA capacity. METHODS: A set of activities were developed based on Pichler et al.'s framework and the starting HTA capacity in Malta. Individual level activities focused on strengthening epidemiological and health economic skills through online and in-person training. On the organizational level, a new HTA framework was developed which was subsequently utilized in a shadow assessment. Awareness campaign activities raised awareness and support in the wider environment where HTAs are conducted and utilized. RESULTS: The time needed to build HTA capacity exceeded the planned two years accommodating the learning progress of the assessors. In addition to the planned trainings, webinars supplemented the online courses, allowing for more knowledge exchange. The advanced online course was extended over time to facilitate learning next to the assessors' daily tasks. Training sessions were added to implement the new economic evaluation framework, which was utilized in a second shadow assessment. Awareness by decision-makers was achieved with reports, posters, and an article on the current and developing HTA capacity. CONCLUSIONS: It takes time and much (hands-on) training to build skills for conducting complex assessment such as HTAs. Facilitating exchange with knowledgeable parties is crucial for succeeding as well as the buy-in of local managers motivating staff. Decision-makers need to be on-boarded for the continued success of HTA capacity building.