Place of living at end-of-life according to cause of death: a comparative analysis of all decedents 70 years or older in 2009-2013 in Finland and Norway.

BACKGROUND: Time at home at end-of-life is perceived as valuable to individuals. Increasing home care is therefore often a political goal. Yet, little is known about where individuals live towards their end-of-life. Our aim was to describe where individuals reside their last 6 months of life in Finland and Norway, and how this differed by cause of death, sex, age, marital status, and income. METHODS: We used individual-leveled national registry data on all decedents aged >70 years in 2009-2013 to describe the number of days individuals spent at home, in hospital, in long-term care (LTC) and short-term care (STC) facilities. We described the place of residence for all and by causes of death: cancer, diseases of the circulatory system, disease in the respiratory system, and mental and behavioral disorders (primarily dementia). We analyzed how age, marital status (indicating informal care), and income associated with place of residence. Analyses were stratified by sex and country. RESULTS: During the last 6 months of life, decedents in Finland (n=186,017) and Norway (n=159,756) spent similar amounts of days in hospital (8 and 11 days) and in STC facilities (15 and 13 days). Finnish decedents spent more days at home (96 vs. 84 days) and fewer days in LTC facilities (64 vs. 80 days). Living arrangement differed similarly by cause of death in the two countries, e.g., decedents from cancer and mental and behavioral disorders spent 123 [113] vs. 29 [21] days at home in Finland (Norway). In both countries, for all causes of death, lower age and marital status were associated with more days at home, for both males and females. While those with higher income spent more days at home in Norway, the opposite was found in Finland. CONCLUSIONS: Older individual's living arrangements in the last 6 months of life were similar in Finland and Norway but differed by cause of death. Younger individuals and those with access to informal care spent more days at home, compared to their counterparts. With aging populations, more individuals will likely need LTC at their end of life. Policies should align with these needs when developing future health care services.

Healthcare use and costs in the last six months of life by level of care and cause of death.

BACKGROUND: Existing knowledge on healthcare use and costs in the last months of life is often limited to one patient group (i.e., cancer patients) and one level of healthcare (i.e., secondary care). Consequently, decision-makers lack knowledge in order to make informed decisions about the allocation of healthcare resources for all patients. Our aim is to elaborate the understanding of resource use and costs in the last six months of life by describing healthcare use and costs for all causes of death and by all levels of formal care. METHOD: Using five national registers, we gained access to patient-level data for all individuals who died in Norway between 2009 and 2013. We described healthcare use and costs for all levels of formal care-namely primary, secondary, and home- and community-based care -in the last six months of life, both in total and differentiated across three time periods (6-4 months, 3-2 months, and 1-month before death). Our analysis covers all causes of death categorized in ten ICD-10 categories. RESULTS: During their last six months of life, individuals used an average of healthcare resources equivalent to €46,000, ranging from €32,000 (Injuries) to €64,000 (Diseases of the nervous system and sense organs). In terms of care level, 63% of healthcare resources were used in home- and community-based care (i.e., in-home nursing, practical assistance, or nursing home care), 35% in secondary care (mostly hospital care), and 2% in primary care (i.e., general practitioners). The amount and level of care varied by cause of death and by time to death. The proportion of home- and community-based care which individuals received during their last six months of life varied from 38% for cancer patients to 92% for individuals dying with mental diseases. The shorter the time to death, the more resources were needed: nearly 40% of all end-of-life healthcare costs were expended in the last month of life across all causes of death. The composition of care also differed depending on age. Individuals aged 80 years and older used more home- and community-based care (77%) than individuals dying at younger ages (40%) and less secondary care (old: 21% versus young: 57%). CONCLUSIONS: Our analysis provides valuable evidence on how much healthcare individuals receive in their last six months of life and the associated costs, broken down by level of care and cause of death. Healthcare use and costs varied considerably by cause of death, but were generally higher the closer a person was to death. Our findings enable decision-makers to make more informed resource-allocation decisions and healthcare planners to better anticipate future healthcare needs.

Is Risk-Stratifying Patients with Colorectal Cancer Using a Deep Learning-Based Prognostic Biomarker Cost-Effective?

OBJECTIVES: Accurate risk stratification of patients with stage II and III colorectal cancer (CRC) prior to treatment selection enables limited health resources to be efficiently allocated to patients who are likely to benefit from adjuvant chemotherapy. We aimed to investigate the cost-effectiveness of a recently developed deep learning-based prognostic method, Histotyping, from the perspective of the Norwegian healthcare system. METHODS: Two partitioned survival models were developed to assess the cost-effectiveness of Histotyping for two treatment cohorts: patients with CRC stage II and III. For each of the two cohorts, Histotyping was used for risk stratification to assign adjuvant chemotherapy and was compared with the standard of care (SOC) (adjuvant chemotherapy to all patients). Health outcomes measured in the model were quality-adjusted life years (QALYs) and life years (LYs) gained. Deterministic and probabilistic sensitivity analyses were performed to determine the impact of uncertainty. Scenario analyses were performed to assess the impact of the parameters with the greatest uncertainty. RESULTS: Risk-stratifying patients with CRC stage II and III using Histotyping was dominant (less costly and more effective) compared to SOC. In patients with CRC stage II, the net monetary benefit of Histotyping was 270,934 Norwegian kroners (NOK) (year of valuation is 2021), and the net health benefit of Histotyping was 0.99. In stage III, the net monetary benefit of Histotyping was 195,419 NOK, and the net health benefit of Histotyping was 0.71. CONCLUSIONS:  Risk-stratifying patients with CRC using Histotyping prior to the administration of adjuvant chemotherapy is likely to be a cost-effective strategy in Norway.

The socioeconomic impact of cancer on patients and their relatives: Organisation of European Cancer Institutes task force consensus recommendations on conceptual framework, taxonomy, and research directions.

Loss of income and out-of-pocket expenditures are important causes of financial hardship in many patients with cancer, even in high-income countries. The far-reaching consequences extend beyond the patients themselves to their relatives, including caregivers and dependents. European research to date has been limited and is hampered by the absence of a coherent theoretical framework and by heterogeneous methods and terminology. To address these shortages, a task force initiated by the Organisation of European Cancer Institutes (OECI) produced 25 recommendations, including a comprehensive definition of socioeconomic impact from the perspective of patients and their relatives, a conceptual framework, and a consistent taxonomy linked to the framework. The OECI task force consensus statement highlights directions for future research with a view towards policy relevance. Beyond descriptive studies into the dimension of the problem, individual severity and predictors of vulnerability should be explored. It is anticipated that the consensus recommendations will facilitate and enhance future research efforts into the socioeconomic impact of cancer and cancer care, providing a crucial reference point for the development and validation of patient-reported outcome instruments aimed at measuring its broader effects.

Impacts of a health literacy-informed intervention in people with chronic obstructive pulmonary disease (COPD) on hospitalization, health literacy, self-management, quality of life, and health costs - A randomized controlled trial.

OBJECTIVE: To compare the effect of motivational interviewing (MI) and tailored health literacy (HL) follow-up with usual care on hospitalization, costs, HL, self-management, Quality of life (QOL), and psychological stress in people with chronic obstructive pulmonary disease (COPD). METHODS: A RCT was undertaken in Norway between March 2018-December 2020 (n = 127). The control group (CG, n = 63) received usual care. The intervention group (IG, n = 64) received tailored HL follow-up from MI-trained COPD nurses with home visits for eight weeks and phone calls for four months after hospitalization. Primary outcomes were hospitalization at eight weeks, six months, and one year from baseline. The trial was registered with ClinicalTrials.gov (NCT03216603) and analysed per protocol. RESULTS: Compared with the IG, the CG had 2.8 higher odds (95% CI [1.3 to 5.8]) of hospitalization and higher hospital health costs (MD=€ -6230, 95% CI [-6510 to -5951]) and lower QALYs (MD=0.1, 95% CI [0.10 to 0.11]) that gives an ICER = - 62,300. The IG reported higher QOL, self-management, and HL (p = 0.02- to <0.01). CONCLUSION: MI-trained COPD nurses using tailored HL follow-up is cost-effective, reduces hospitalization, and increases QOL, HL, and self-care in COPD. PRACTICE IMPLICATION: Tailored HL follow-up is beneficial for individuals with COPD and the healthcare system.

Healthcare utilization and costs associated with autologous haematopoietic stem cell transplantation in Norwegian patients with relapsing remitting multiple sclerosis.

Multiple sclerosis (MS) patients experience long-term deterioration of neurological function, reduced quality of life, long-lasting treatment cycles, and an increased risk of early workability loss imposing an economic burden to society. Autologous haematopoietic stem cell transplantation (AHSCT) has shown promising treatment effects for relapsing remitting MS (RRMS). This study employs a micro-costing approach to estimate healthcare utilization and costs associated with AHSCT in Norwegian RRMS patients. Patient-level data were extracted from medical journals of 30 RRMS patients receiving AHSCT treatment at Haukeland University Hospital in the period from January 2015 to January 2018. The time horizon for the analysis was from the pretransplant screening until one year after AHSCT. A correlation was found between patient body weight and total healthcare cost. The average total healthcare cost of AHSCT for RRMS patients was estimated to EUR 66 304 (95% CI: EUR 63 598 - EUR 69 010) including costs associated with the pre-AHSCT period, AHSCT treatment phases and one-year follow-up. The majority of the costs, EUR 64 329, occurred during the treatment phase and within the first 100 days after AHSCT. The results indicate that long-term healthcare cost savings may be achieved using AHSCT in selected patients with aggressive RRMS. This is due to the high costs of most used disease modifying treatments. Further research including long-term clinical data is needed to determine the cost-effectiveness of this treatment.

Implementation of advance care planning in the routine care for acutely admitted patients in geriatric units: protocol for a cluster randomized controlled trial.

BACKGROUND: Acutely ill and frail older adults and their next of kin are often poorly involved in treatment and care decisions. This may lead to either over- or undertreatment and unnecessary burdens. The aim of this project is to improve user involvement and health services for frail older adults living at home, and their relatives, by implementing advance care planning (ACP) in selected hospital wards, and to evaluate the clinical and the implementation interventions. METHODS: This is a cluster randomized trial with 12 hospital units. The intervention arm receives implementation support for 18 months; control units receive the same support afterwards. The ACP intervention consists of 1. Clinical intervention: ACP; 2. Implementation interventions: Implementation team, ACP coordinator, network meetings, training and supervision for health care personnel, documentation tools and other resources, and fidelity measurements with tailored feedback; 3. Implementation strategies: leadership commitment, whole ward approach and responsive evaluation. Fidelity will be measured three times in the intervention arm and twice in the control arm. Here, the primary outcome is the difference in fidelity changes between the arms. We will also include 420 geriatric patients with one close relative and an attending clinician in a triadic sub-study. Here, the primary outcomes are quality of communication and decision-making when approaching the end of life as perceived by patients and next of kin, and congruence between the patient's preferences for information and involvement and the clinician's perceptions of the same. For patients we will also collect clinical data and health register data. Additionally, all clinical staff in both arms will be invited to answer a questionnaire before and during the implementation period. To explore barriers and facilitators and further explore the significance of ACP, qualitative interviews will be performed in the intervention units with patients, next of kin, health care personnel and implementation teams, and with other stakeholders up to national level. Lastly, we will evaluate resource utilization, costs and health outcomes in a cost-effectiveness analysis. DISCUSSION: The project may contribute to improved implementation of ACP as well as valuable knowledge and methodological developments in the scientific fields of ACP, health service research and implementation science. TRIAL REGISTRATION: ClinicalTrials.gov Identifier NCT05681585. Registered 03.01.23.

Longer-term quality of care, effectiveness, and cost-effectiveness of implementing a model of care for osteoarthritis: A cluster-randomized controlled trial.

OBJECTIVE: To assess the quality of care, effectiveness, and cost-effectiveness over 12 months after implementing a structured model of care for hip and knee osteoarthritis (OA) in primary healthcare as compared to usual care. DESIGN: In this pragmatic cluster-randomized, controlled trial with a stepped-wedge cohort design, we recruited 40 general practitioners (GPs), 37 physiotherapists (PTs), and 393 patients with symptomatic hip or knee OA from six municipalities (clusters) in Norway. The model included the delivery of a 3-hour patient education and 8-12 weeks individually tailored exercise programs, and interactive workshops for GPs and PTs. At 12 months, the patient-reported quality of care was assessed by the OsteoArthritis Quality Indicator questionnaire (16 items, pass rate 0-100%, 100%=best). Costs were obtained from patient-reported and national register data. Cost-effectiveness at the healthcare perspective was evaluated using incremental net monetary benefit (INMB). RESULTS: Of 393 patients, 109 were recruited during the control periods (control group) and 284 were recruited during interventions periods (intervention group). At 12 months the intervention group reported statistically significant higher quality of care compared to the control group (59% vs. 40%; mean difference: 17.6 (95% confidence interval [CI] 11.1, 24.0)). Cost-effectiveness analyses showed that the model of care resulted in quality-adjusted life-years gained and cost-savings compared to usual care with mean INMB €2020 (95% CI 611, 3492) over 12 months. CONCLUSIONS: This study showed that implementing the model of care for OA in primary healthcare, improved quality of care and showed cost-effectiveness over 12 months compared to usual care. TRIAL REGISTRATION NUMBER: ClinicalTrials.gov NCT02333656.

A Guide to an Iterative Approach to Model-Based Decision Making in Health and Medicine: An Iterative Decision-Making Framework.

Decision makers frequently face decisions about optimal resource allocation. A model-based economic evaluation can be used to guide decision makers in their choices by systematically evaluating the magnitude of expected health effects and costs of decision options and by making trade-offs explicit. We provide a guide to an iterative approach to the medical decision-making process by following a coherent framework, and outline the overarching iterative steps of model-based decision making. We systematized the framework by performing three steps. First, we compiled the existing guidelines provided by the ISPOR-SMDM Modeling Good Research Practices Task Force, and the ISPOR Value of Information Task Force. Second, we identified other previous work related to frameworks and guidelines for model-based decision analyses through a literature search in PubMed. Third, we assessed the role of the evidence and iterative process in decision making and formalized key steps in a model-based decision-making framework. We provide guidance on an iterative approach to medical decision making by applying the compiled iterative model-based decision-making framework. The framework formally combines the decision problem conceptualization (Part I), the model conceptualization and development (Part II), and the process of model-based decision analysis (Part III). Following the overarching steps of the framework ensures compliance to the principles of evidence-based medicine and regular updates of the evidence, given that value of information analysis represents an essential component of model-based decision analysis in the framework. Following the provided guide and the steps outlined in the framework can help inform various health care decisions, and therefore it has the potential to improve decision making.

Production losses from morbidity and mortality by disease, age and sex in Norway.

AIM: The inclusion of production losses in health care priority setting is extensively debated. However, few studies allow for a comparison of these losses across relevant clinical and demographic categories. Our objective was to provide comprehensive estimates of Norwegian production losses from morbidity and mortality by age, sex and disease category. METHODS: National registries, tax records, labour force surveys, household and population statistics and data from the Global Burden of Disease were combined to estimate production losses for 12 disease categories, 38 age and sex groups and four causes of production loss. The production losses were estimated via lost wages in accordance with a human capital approach for 2019. RESULTS: The main causes of production losses in 2019 were mental and substance use disorders, totalling NOK121.6bn (32.7% of total production losses). This was followed by musculoskeletal disorders, neurological disorders, injuries, and neoplasms, which accounted for 25.2%, 7.4%, 7.4% and 6.5% of total production losses, respectively. Production losses due to sick leave, disability insurance and work assessment allowance were higher for females than for males, whereas production losses due to premature mortality were higher for males. The latter was related to neoplasms, cardiovascular disease and injuries. Across age categories, non-fatal conditions with a high prevalence among working populations caused the largest production losses. CONCLUSIONS: The inclusion of production losses in health care priority debates in Norway could result in an emphasis on chronic diseases that occur among younger populations at the expense of fatal diseases among older age groups.

General-Purpose Methods for Simulating Survival Data for Expected Value of Sample Information Calculations.

BACKGROUND: Expected value of sample information (EVSI) quantifies the expected value to a decision maker of reducing uncertainty by collecting additional data. EVSI calculations require simulating plausible data sets, typically achieved by evaluating quantile functions at random uniform numbers using standard inverse transform sampling (ITS). This is straightforward when closed-form expressions for the quantile function are available, such as for standard parametric survival models, but these are often unavailable when assuming treatment effect waning and for flexible survival models. In these circumstances, the standard ITS method could be implemented by numerically evaluating the quantile functions at each iteration in a probabilistic analysis, but this greatly increases the computational burden. Thus, our study aims to develop general-purpose methods that standardize and reduce the computational burden of the EVSI data-simulation step for survival data. METHODS: We developed a discrete sampling method and an interpolated ITS method for simulating survival data from a probabilistic sample of survival probabilities over discrete time units. We compared the general-purpose and standard ITS methods using an illustrative partitioned survival model with and without adjustment for treatment effect waning. RESULTS: The discrete sampling and interpolated ITS methods agree closely with the standard ITS method, with the added benefit of a greatly reduced computational cost in the scenario with adjustment for treatment effect waning. CONCLUSIONS: We present general-purpose methods for simulating survival data from a probabilistic sample of survival probabilities that greatly reduce the computational burden of the EVSI data-simulation step when we assume treatment effect waning or use flexible survival models. The implementation of our data-simulation methods is identical across all possible survival models and can easily be automated from standard probabilistic decision analyses. HIGHLIGHTS: Expected value of sample information (EVSI) quantifies the expected value to a decision maker of reducing uncertainty through a given data collection exercise, such as a randomized clinical trial. In this article, we address the problem of computing EVSI when we assume treatment effect waning or use flexible survival models, by developing general-purpose methods that standardize and reduce the computational burden of the EVSI data-generation step for survival data.We developed 2 methods for simulating survival data from a probabilistic sample of survival probabilities over discrete time units, a discrete sampling method and an interpolated inverse transform sampling method, which can be combined with a recently proposed nonparametric EVSI method to accurately estimate EVSI for collecting survival data.Our general-purpose data-simulation methods greatly reduce the computational burden of the EVSI data-simulation step when we assume treatment effect waning or use flexible survival models. The implementation of our data-simulation methods is identical across all possible survival models and can therefore easily be automated from standard probabilistic decision analyses.

A cost-effectiveness analysis of risk-based intervention for prevention of cardiovascular diseases in IraPEN program: A modeling study.

Background: IraPEN, a program developed in Iran based on the World Health Organization (WHO) package of essential noncommunicable (PEN) disease interventions for primary healthcare, was launched in 2015. Preventive interventions for cardiovascular diseases (CVDs) are based on the level of risk calculated using the WHO CVD risk chart. Objective: The main objective of this study was to measure the potential cost-effectiveness (CE) of IraPEN preventive actions for CVD in comparison with the status quo. Methods: A CE analysis from a healthcare perspective was conducted. Markov models were employed for individuals with and without diabetes separately. Based on the WHO CVD risk chart, four index cohorts were constructed as low (<10%), moderate (10%-19%), high (20%-29%), and very high risk (≥30%). Life years (LY) gained and quality-adjusted life years (QALY) were used as the outcome measures. Results: The intervention yields an incremental cost-effectiveness ratio (ICER) of $804, $551, and -$44 per QALY for moderate, high, and very high CVD risk in groups without diabetes, respectively. These groups gained 0.69, 0.96, and 1.45 LY, respectively, from the intervention. The results demonstrated an ICER of $711, $630, -$42, and -$71 for low, moderate, high, and very high-risk groups with diabetes, respectively, while they gained 0.46, 1.2, 2.04, and 2.29 years from the intervention. Conclusion: The IraPEN program was highly cost-effective for all CVD risk groups in the individuals without diabetes except the low-risk group. The intervention was cost-effective for all patients with diabetes regardless of their CVD risk. The results demonstrated that the IraPEN program can likely provide substantial health benefits to Iranian individuals and cost savings to the national healthcare provider.

Value of an Integrated Home Dialysis Model in the United Kingdom: A Cost-Effectiveness Analysis.

OBJECTIVES: This study aimed to determine the lifetime cost-effectiveness of increasing home hemodialysis as a treatment option for patients experiencing peritoneal dialysis technique failure compared with the current standard of care. METHODS: A Markov model was developed to assess the lifetime costs, quality-adjusted life-years, and cost-effectiveness of increasing the usage an integrated home dialysis model compared with the current patient pathways in the United Kingdom. A secondary analysis was conducted including only the cost difference in treatments, minimizing the impact of the high cost of dialysis during life-years gained. Sensitivity and scenario analyses were performed, including analyses from a societal rather than a National Health Service perspective. RESULTS: The base-case probabilistic analysis was associated with incremental costs of £3413 and a quality-adjusted life-year of 0.09, resulting in an incremental cost-effectiveness ratio of £36 341. The secondary analysis found the integrated home dialysis model to be dominant. Conclusions on cost-effectiveness did not change under the societal perspective in either analysis. CONCLUSIONS: The base-case analysis found that an integrated home dialysis model compared with current patient pathways is likely not cost-effective. These results were primarily driven by the high baseline costs of dialysis during life-years gained by patients receiving home hemodialysis. When excluding baseline dialysis-related treatment costs, the integrated home dialysis model was dominant. New strategies in kidney care patient pathway management should be explored because, under the assumption that dialysis should be funded, the results provide cost-effectiveness evidence for an integrated home dialysis model.

Health related quality of life, service utilization and costs for patients with Huntington's disease in Norway.

BACKGROUND: Huntington's disease (HD) is a progressive genetic neurodegenerative disease accompanied by mental and neurocognitive disabilities, which requires long-term and comprehensive treatment and care. Information on the health and economic burden of HD is scarce, but essential for conducting health economic analyses, in light of the prospect of new therapies for HD. In this study, we aim to identify values for Health-Related Quality of Life (HRQoL), describe service utilization and costs, and their associations with clinical and socio-demographic variables across all phases of HD. METHODS: A cross-sectional study including 86 patients across all phases of HD. Values of HRQoL were calculated based on EQ-5D-3L index scores. Additionally, health care and societal costs were estimated based on service utilization collected using the Client Service Receipt Inventory (CSRI) and data from the patients' interviews. Total societal costs included costs of primary and secondary health care services, informal care and productivity loss of the patients. Multiple regression analyses were used to investigate associations between socio-demographic and clinical variables on HRQoL and costs. RESULTS: HRQoL values declined, while total costs increased across disease severity. Total six-month healthcare costs and total societal costs were € 18,538 and € 66,789 respectively. Healthcare and societal costs doubled from early to middle phase, and tripled from middle to advanced disease phase. Main six-month cost components for the three disease phases were informal care costs (€ 30,605) accounting for approximately half the total societal costs, and costs due to production loss (€ 18,907) being slightly higher than the total healthcare costs. Disease severity and gender were found to have the strongest effect on both values of HRQoL and costs. CONCLUSIONS: Reported values of HRQoL and costs including costs for production loss may be used in modelling the cost-effectiveness of treatment for HD. Our results highlight the crucial role the informal caregivers play in the care provided to HD patients in all disease phases. Future research should focus on the estimation of productivity loss among informal caregivers.

Care pathways at end-of-life for cancer decedents: registry based analyses of the living situation, healthcare utilization and costs for all cancer decedents in Norway in 2009-2013 during their last 6 months of life.

BACKGROUND: Research on end-of-life care is often fragmented, focusing on one level of healthcare or on a particular patient subgroup. Our aim was to describe the complete care pathways of all cancer decedents in Norway during the last six months of life. METHODS: We used six national registries linked at patient level and including all cancer decedents in Norway between 2009-2013 to describe patient use of secondary, primary-, and home- and community-based care. We described patient's car pathway, including patients living situation, healthcare utilization, and costs. We then estimated how cancer type, individual and sociodemographic characteristics, and access to informal care influenced the care pathways. Regression models were used depending on the outcome, i.e., negative binomial (for healthcare utilization) and generalized linear models (for healthcare costs). RESULTS: In total, 52,926 patients were included who died of lung (16%), colorectal (12%), prostate (9%), breast (6%), cervical (1%) or other (56%) cancers. On average, patients spent 123 days at home, 24 days in hospital, 16 days in short-term care and 24 days in long-term care during their last 6 months of life. Healthcare utilization increased towards end-of-life. Total costs were high (on average, NOK 379,801). 60% of the total costs were in the secondary care setting, 3% in the primary care setting, and 37% in the home- and community-based care setting. Age (total cost-range NOK 361,363-418,618) and marital status (total cost-range NOK354,100-411,047) were stronger determining factors of care pathway than cancer type (total cost-range NOK341,318- 392,655). When patients died of cancer types requiring higher amounts of secondary care (e.g., cervical cancer), there was a corresponding lower utilization of primary, and home- and community-based care, and vice versa. CONCLUSION: Cancer patient's care pathways at end-of-life are more strongly associated with age and access to informal care than underlying type of cancer. More care in one care setting (e.g., the secondary care) is associated with less care in other settings (primary- and home- and community based care setting) as demonstrated by the substitution between the different levels of care in this study. Care at end-of-life should therefore not be evaluated in one healthcare level alone since this might bias results and lead to suboptimal priorities.

Cost-effectiveness of molecularly matched off-label therapies for end-stage cancer - the MetAction precision medicine study.

BACKGROUND: Precision cancer medicine (PCM), frequently used for the expensive and often modestly efficacious off-label treatment with medications matched to the tumour genome of end-stage cancer, challenges healthcare resources. We compared the health effects, costs and cost-effectiveness of our MetAction PCM study with corresponding data from comparator populations given best supportive care (BSC) in two external randomised controlled trials. METHODS: We designed three partitioned survival models to evaluate the healthcare costs and quality-adjusted life years (QALYs) as the main outcomes. Cost-effectiveness was calculated as the incremental cost-effectiveness ratio (ICER) of PCM relative to BSC with an annual willingness-to-pay (WTP) threshold of EUR 56,384 (NOK 605,000). One-way and probabilistic sensitivity analyses addressed uncertainty. RESULTS: We estimated total healthcare costs (relating to next-generation sequencing (NGS) equipment and personnel wages, molecularly matched medications to the patients with an actionable tumour target and follow-up of the responding patients) and the health outcomes for the MetAction patients versus costs (relating to estimated hospital admission) and outcomes for the BSC cases. The ICERs for incremental QALYs were twice or more as high as the WTP threshold and relatively insensitive to cost decrease of the NGS procedures, while reduction of medication prices would contribute significantly towards a cost-effective PCM strategy. CONCLUSIONS: The models suggested that the high ICERs of PCM were driven by costs of the NGS diagnostics and molecularly matched medications, with a likelihood for the strategy to be cost-effective defying WTP constraints. Reducing drug expenses to half the list price would likely result in an ICER at the WTP threshold. This can be an incentive for a public-private partnership for sharing drug costs in PCM, exemplified by ongoing European initiatives. CLINICALTRIALS.GOV, IDENTIFIER: NCT02142036.