Portfolio Theory and Cost-Effectiveness Analysis: A Further Discussion

AbstractObjectivesPortfolio theory has been suggested as a means to improve the risk–return characteristics of investments in health-care programs through diversification when costs and effects are uncertain. This approach is based on the assumption that the investment proportions are not subject to uncertainty and that the budget can be invested in toto in health-care programs.MethodsIn the present paper we develop an algorithm that accounts for the fact that investment proportions in health-care programs may be uncertain (due to the uncertainty associated with costs) and limited (due to the size of the programs). The initial budget allocation across programs may therefore be revised at the end of the investment period to cover the extra costs of some programs with the leftover budget of other programs in the portfolio.ResultsOnce the total budget is equivalent to or exceeds the expected costs of the programs in the portfolio, the initial budget allocation policy does not impact the risk–return characteristics of the combined portfolio, i.e., there is no benefit from diversification anymore.ConclusionThe applicability of portfolio methods to improve the risk–return characteristics of investments in health care is limited to situations where the available budget is much smaller than the expected costs of the programs to be funded

Cost-consequence analysis of remifentanil-based analgo-sedation vs. conventional analgesia and sedation for patients on mechanical ventilation in the Netherlands

Introduction: Hospitals are increasingly forced to consider the economics of technology use. We estimated the incremental cost-consequences of remifentanil-based analgo-sedation (RS) vs. conventional analgesia and sedation (CS) in patients requiring mechanical ventilation (MV) in the intensive care unit (ICU), using a modelling approach. Methods: A Markov model was developed to describe patient flow in the ICU. The hourly probabilities to move from one state to another were derived from UltiSAFE, a Dutch clinical study involving ICU patients with an expected MV-time of 2-3 days requiring analgesia and sedation. Study medication was either: CS (morphine or fentanyl combined with propofol, midazolam or lorazepam) or: RS (remifentanil, combined with propofol when required). Study drug costs were derived from the trial, whereas all other ICU costs were estimated separately in a Dutch micro-costing study. All costs were measured from the hospital perspective (price level of 2006). Patients were followed in the model for 28 days. We also studied the sub-population where weaning had started within 72 hours. Results: The average total 28-day costs were 15,626 euros with RS versus 17,100 euros with CS, meaning a difference in costs of 1474 euros (95% CI -2163, 5110). The average length-of-stay (LOS) in the ICU was 7.6 days in the RS group versus 8.5 days in the CS group (difference 1.0, 95% CI -0.7, 2.6), while the average MV time was 5.0 days for RS versus 6.0 days for CS. Similar differences were found in the subgroup analysis. Conclusions: Compared to CS, RS significantly decreases the overall costs in the ICU

Cost recommendation under uncertainty in IQWiG’s efficiency frontier framework

Background: The National Institute for Quality and Efficiency in Health Care (IQWiG) employs an efficiency frontier (EF) framework to facilitate setting maximum reimbursable prices for new interventions. Probabilistic sensitivity analysis (PSA) is used when yes/no reimbursement decisions are sought based on a fixed threshold. In the IQWiG framework, an additional layer of complexity arises as the EF itself may vary its shape in each PSA iteration, and thus the willingness-to-pay, indicated by the EF segments, may vary. Objectives: To explore the practical problems arising when, within the EF approach, maximum reimbursable prices for new interventions are sought through PSA. Methods: When the EF is varied in a PSA, cost recommendations for new interventions may be determined by the mean or the median of the distances between each intervention’s point estimate and each EF. Implications of using these metrics were explored in a simulation study based on the model used by IQWiG to assess the cost-effectiveness of 4 antidepressants. Results. Depending on the metric used, cost recommendations can be contradictory. Recommendations based on the mean can also be inconsistent. Results (median) suggested that costs of duloxetine, venlafaxine, mirtazapine, and bupropion should be decreased by €131, €29, €12, and €99, respectively. These recommendations were implemented and the analysis repeated. New results suggested keeping the costs as they were. The percentage of acceptable PSA outcomes increased 41% on average, and the uncertainty associated to the net health benefit was significantly reduced. Conclusions: The median of the distances between every intervention outcome and every EF is a good proxy for the cost recommendation that would be given should the EF be fixed. Adjusting costs according to the median increased the probability of acceptance and reduced the uncertainty around the net health benefit distribution, resulting in a reduced uncertainty for decision makers

The increasing importance of a continence nurse specialist to improve outcomes and save costs of urinary incontinence care

__Background:__ In an ageing population, it is inevitable to improve the management of care for community-dwellingelderly with incontinence. A previous study showed that implementation of the Optimum Continence ServiceSpecification (OCSS) for urinary incontinence in community-dwelling elderly with four or more chronic diseasesresults in a reduction of urinary incontinence, an improved quality of life, and lower healt

Cost-effectiveness analysis of the first-line EGFR-TKIs in patients with non-small cell lung cancer harbouring EGFR mutations

Objectives: To compare the cost-effectiveness of first-line gefitinib, erlotinib, afatinib, and osimertinib in patients with non-small cell lung cancer (NSCLC) harbouring epidermal growth factor receptor (EGFR) mutations. Methods: A systematic review and network meta-analysis (NMA) were conducted to compare the relative efficacy of gefitinib, erlotinib, afatinib, and osimertinib in EGFR-mutated NSCLC. To assess the cost-effectiveness of these treatments, a Markov model was developed from Dutch societal perspective. The model was based on the clinical studies included in the NMA. Incremental costs per life-year (LY) and per quality-adjusted life-year (QALY) gained were estimated. Deterministic and probabilistic sensitivity analyses (PSA) were conducted. Results: Total discounted per patient costs for gefitinib, erlotinib, afatinib, and osimertinib were €65,889, €64,035, €69,418, and €131,997, and mean QALYs were 1.36, 1.39, 1.52, and 2.01 per patient, respectively. Erlotinib dominated gefitinib. Afatinib versus erlotinib yielded incremental costs of €27,058/LY and €41,504/QALY gained. Osimertinib resulted in €91,726/LY and €128,343/QALY gained compared to afatinib. PSA showed that gefitinib, erlotinib, afatinib, and osimertinib had 13%, 19%, 43%, and 26% probability to be cost-effective at a threshold of €80,000/QALY. A price reduction of osimertinib of 30% is required for osimertinib to be cost-effective at a threshold of €80,000/QALY. Conclusions: Osimertinib has a better effectiveness compared to all other TKIs. However, at a Dutch threshold of €80,000/QALY, osimertinib appears not to be cost-effective

The Missing Stakeholder Group: Why Patients Should be Involved in Health Economic Modelling

Evaluations of healthcare interventions, e.g. new drugs or other new treatment strategies, commonly include a cost-effectiveness analysis (CEA) that is based on the application of health economic (HE) models. As end users, patients are important stakeholders regarding the outcomes of CEAs, yet their knowledge of HE model development and application, or their involvement therein, is absent. This paper considers possible benefits and risks of patient involvement in HE model development and application for modellers and patients. An exploratory review of the literature has been performed on stakeholder-involved modelling in various disciplines. In addition, Dutch patient experts have been interviewed about their experience in, and opinion about, the application of HE models. Patients have little to no knowledge of HE models and are seldom involved in HE model development and application. Benefits of becoming involved would include a greater understanding and possible acceptance by patients of HE model application, improved model validation, and a more direct infusion of patient expertise. Risks would include patient bias and increased costs of modelling. Patient involvement in HE modelling seems to carry several benefits as well as risks. We claim that the benefits may outweigh the risks and that patients should become involved

Ramucirumab for Treating Advanced Gastric Cancer or Gastro-Oesophageal Junction Adenocarcinoma Previously Treated with Chemotherapy

The National Institute for Health and Care Excellence (NICE) invited the company that manufactures ramucirumab (Cyramza®, Eli Lilly and Company) to submit evidence of the clinical and cost effectiveness of the drug administered alone (monotherapy) or with paclitaxel (combination therapy) for treating adults with advanced gastric cancer or gastro-oesophageal junction (GC/GOJ) adenocarcinoma that were previously treated with chemotherapy, as part of the Institute’s single technology appraisal (STA) process. Kleijnen Systematic Reviews Ltd (KSR), in collaboration with Erasmus University Rotterdam, was commissioned to act as the Evidence Review Group (ERG). This paper describes the company’s submission, the ERG review, and NICE’s subsequent decisions. Clinical effectiveness evidence for ramucirumab monotherapy (RAM), compared with best supportive care (BSC), was based on data from the REGARD trial. Clinical effectiveness evidence for ramucirumab combination therapy (RAM + PAC), compared with paclitaxel monotherapy (PAC), was based on data from the RAINBOW trial. In addition, the company undertook a network meta-analysis (NMA) to compare RAM + PAC with BSC and docetaxel. Cost-ef

Being Transparent About Brilliant Failures:An Attempt to Use Real-World Data in a Disease Model for Patients with Castration-Resistant Prostate Cancer

Background: Real-world disease models spanning multiple treatment lines can provide insight into the (cost) effectiveness of treatment sequences in clinical practice. Objective: Our objective was to explore whether a disease model based solely on real-world data (RWD) could be used to estimate the effectiveness of treatments for patients with castration-resistant prostate cancer (CRPC) that could then be suitably used in a cost-effectiveness analysis. Methods: We developed a patient-level simulation model using patient-level data from the Dutch CAPRI registry as input parameters. Time to event (TTE) and overall survival (OS) were estimated with multivariate regression models, and type of event (i.e., next treatment or death) was estimated with multivariate logistic regression models. To test internal validity, TTE and OS from the simulation model were compared with the observed outcomes in the registry. Results: Although patient characteristics and survival outcomes of the simulated data were comparable to those in the observed data (median OS 20.6 vs. 19.8 months, respectively), the disease model was less accurate in estimating differences between treatments (median OS simulated vs. observed population: 18.6 vs. 17.9 [abiraterone acetate plus prednisone], 24.0 vs. 25.0 [enzalutamide], 20.2 vs. 18.7 [docetaxel], and 20.0 vs. 23.8 months [radium-223]). Conclusions: Overall, the disease model accurately approximated the observed data in the total CRPC population. However, the disease model was unable to predict differences in survival between treatments due to unobserved differences. Therefore, the model is not suitable for cost-effectiveness analysis of CRPC treatment. Using a combination of RWD and data from randomised controlled trials to estimate treatment effectiveness may improve the model