Multimorbidity healthcare expenditure in Belgium: a 4-year analysis (COMORB study).

BACKGROUND: The complex management of health needs in multimorbid patients, alongside limited cost data, presents challenges in developing cost-effective patient-care pathways. We estimated the costs of managing 171 dyads and 969 triads in Belgium, taking into account the influence of morbidity interactions on costs. METHODS: We followed a retrospective longitudinal study design, using the linked Belgian Health Interview Survey 2018 and the administrative claim database 2017-2020 hosted by the Intermutualistic Agency. We included people aged 15 and older, who had complete profiles (N = 9753). Applying a system costing perspective, the average annual direct cost per person per dyad/triad was presented in 2022 Euro and comprised mainly direct medical costs. We developed mixed models to analyse the impact of single chronic conditions, dyads and triads on healthcare costs, considering two-/three-way interactions within dyads/triads, key cost determinants and clustering at the household level. RESULTS: People with multimorbidity constituted nearly half of the study population and their total healthcare cost constituted around three quarters of the healthcare cost of the study population. The most common dyad, arthropathies + dorsopathies, with a 14% prevalence rate, accounted for 11% of the total national health expenditure. The most frequent triad, arthropathies + dorsopathies + hypertension, with a 5% prevalence rate, contributed 5%. The average annual direct costs per person with dyad and triad were €3515 (95% CI 3093-3937) and €4592 (95% CI 3920-5264), respectively. Dyads and triads associated with cancer, diabetes, chronic fatigue, and genitourinary problems incurred the highest costs. In most cases, the cost associated with multimorbidity was lower or not substantially different from the combined cost of the same conditions observed in separate patients. CONCLUSION: Prevalent morbidity combinations, rather than high-cost ones, made a greater contribution to total national health expenditure. Our study contributes to the sparse evidence on this topic globally and in Europe, with the aim of improving cost-effective care for patients with diverse needs.

Cost-effectiveness of encorafenib with binimetinib in unresectable or metastatic BRAF-mutant melanoma.

OBJECTIVE: The objective of this study was to determine the cost-effectiveness of encorafenib with binimetinib (EncoBini) as compared to other targeted double combination therapies, namely dabrafenib with trametinib (DabraTrame) and vemurafenib with cobimetinib (VemuCobi), for the treatment of BRAF V600-mutant unresectable or metastatic melanoma (MM) from the French payer perspective. METHODS: A partitioned survival model was developed considering a lifetime horizon. The model structure simulated the clinical pathway of patients with BRAF V600-mutant MM. Clinical effectiveness and safety inputs were sourced from the COLUMBUS trial, a network meta-analysis and published literature. Costs, resource use, and the quality of life inputs were obtained from the literature and appropriate French sources. RESULTS: Over a lifetime horizon, EncoBini was associated, on average, with reduced costs and increased quality adjusted life years (QALYs), dominating both targeted double combination therapies. For a willingness-to-pay threshold of €90,000 per QALY, the probability of EncoBini being cost-effective against either comparator remained above 80%. The most influential model parameters were the hazard ratios for the overall survival of EncoBini vs DabraTrame and VemuCobi, the pre- and post-progression utility values, as well as treatment dosages and the relative dose intensity of all interventions. CONCLUSION: EncoBini is associated with reduced costs and increased QALYs, dominating other targeted double combination therapies (DabraTrame, VemuCobi) for patients with BRAF V600-mutant MM in France. EncoBini is a highly cost-effective intervention in MM.

Costs of multimorbidity: a systematic review and meta-analyses.

BACKGROUND: Multimorbidity is a rising global phenomenon, placing strains on countries' population health and finances. This systematic review provides insight into the costs of multimorbidity through addressing the following primary and secondary research questions: What evidence exists on the costs of multimorbidity? How do costs of specific disease combinations vary across countries? How do multimorbidity costs vary across disease combinations? What "cost ingredients" are most commonly included in these multimorbidity studies? METHODS: We conducted a systematic review (PROSPERO: CRD42020204871) of studies published from January 2010 to January 2022, which reported on costs associated with combinations of at least two specified conditions. Systematic string-based searches were conducted in MEDLINE, The Cochrane Library, SCOPUS, Global Health, Web of Science, and Business Source Complete. We explored the association between costs of multimorbidity and country Gross Domestic Product (GDP) per capita using a linear mixed model with random intercept. Annual mean direct medical costs per capita were pooled in fixed-effects meta-analyses for each of the frequently reported dyads. Costs are reported in 2021 International Dollars (I$). RESULTS: Fifty-nine studies were included in the review, the majority of which were from high-income countries, particularly the United States. (1) Reported annual costs of multimorbidity per person ranged from I$800 to I$150,000, depending on disease combination, country, cost ingredients, and other study characteristics. (2) Our results further demonstrated that increased country GDP per capita was associated with higher costs of multimorbidity. (3) Meta-analyses of 15 studies showed that on average, dyads which featured Hypertension were among the least expensive to manage, with the most expensive dyads being Respiratory and Mental Health condition (I$36,840), Diabetes and Heart/vascular condition (I$37,090), and Cancer and Mental Health condition in the first year after cancer diagnosis (I$85,820). (4) Most studies reported only direct medical costs, such as costs of hospitalization, outpatient care, emergency care, and drugs. CONCLUSIONS: Multimorbidity imposes a large economic burden on both the health system and society, most notably for patients with cancer and mental health condition in the first year after cancer diagnosis. Whether the cost of a disease combination is more or less than the additive costs of the component diseases needs to be further explored. Multimorbidity costing studies typically consider only a limited number of disease combinations, and few have been conducted in low- and middle-income countries and Europe. Rigorous and standardized methods of data collection and costing for multimorbidity should be developed to provide more comprehensive and comparable evidence for the costs of multimorbidity.

TB morbidity estimates overlook the contribution of post-TB disability: evidence from urban Malawi.

INTRODUCTION: Despite growing evidence of the long-term impact of tuberculosis (TB) on quality of life, Global Burden of Disease (GBD) estimates of TB-related disability-adjusted life years (DALYs) do not include post-TB morbidity, and evaluations of TB interventions typically assume treated patients return to pre-TB health. Using primary data, we estimate years of life lost due to disability (YLDs), years of life lost due to premature mortality (YLL) and DALYs associated with post-TB cardiorespiratory morbidity in a low-income country. METHODS: Adults aged ≥15 years who had successfully completed treatment for drug-sensitive pulmonary TB in Blantyre, Malawi (February 2016-April 2017) were followed-up for 3 years with 6-monthly and 12-monthly study visits. In this secondary analysis, St George's Respiratory Questionnaire data were used to match patients to GBD cardiorespiratory health states and corresponding disability weights (DWs) at each visit. YLDs were calculated for the study period and estimated for remaining lifespan using Malawian life table life expectancies. YLL were estimated using study mortality data and aspirational life expectancies, and post-TB DALYs derived. Data were disaggregated by HIV status and gender. RESULTS: At treatment completion, 222/403 (55.1%) participants met criteria for a cardiorespiratory DW, decreasing to 15.6% after 3 years, at which point two-thirds of the disability burden was experienced by women. Over 90% of projected lifetime-YLD were concentrated within the most severely affected 20% of survivors. Mean DWs in the 3 years post-treatment were 0.041 (HIV-) and 0.025 (HIV+), and beyond 3 years estimated as 0.025 (HIV-) and 0.010 (HIV+), compared with GBD DWs of 0.408 (HIV+) and 0.333 (HIV-) during active disease. Our results imply that the majority of TB-related morbidity occurs post-treatment. CONCLUSION: TB-related DALYs are greatly underestimated by overlooking post-TB disability. The total disability burden of TB is likely undervalued by both GBD estimates and economic evaluations of interventions, particularly those aimed at early diagnosis and prevention.

Digital interventions in mental health: evidence syntheses and economic modelling.

BACKGROUND: Economic evaluations provide evidence on whether or not digital interventions offer value for money, based on their costs and outcomes relative to the costs and outcomes of alternatives. OBJECTIVES: (1) Evaluate and summarise published economic studies about digital interventions across different technologies, therapies, comparators and mental health conditions; (2) synthesise clinical evidence about digital interventions for an exemplar mental health condition; (3) construct an economic model for the same exemplar mental health condition using the previously synthesised clinical evidence; and (4) consult with stakeholders about how they understand and assess the value of digital interventions. METHODS: We completed four work packages: (1) a systematic review and quality assessment of economic studies about digital interventions; (2) a systematic review and network meta-analysis of randomised controlled trials on digital interventions for generalised anxiety disorder; (3) an economic model and value-of-information analysis on digital interventions for generalised anxiety disorder; and (4) a series of knowledge exchange face-to-face and digital seminars with stakeholders. RESULTS: In work package 1, we reviewed 76 economic evaluations: 11 economic models and 65 within-trial analyses. Although the results of the studies are not directly comparable because they used different methods, the overall picture suggests that digital interventions are likely to be cost-effective, compared with no intervention and non-therapeutic controls, whereas the value of digital interventions compared with face-to-face therapy or printed manuals is unclear. In work package 2, we carried out two network meta-analyses of 20 randomised controlled trials of digital interventions for generalised anxiety disorder with a total of 2350 participants. The results were used to inform our economic model, but when considered on their own they were inconclusive because of the very wide confidence intervals. In work package 3, our decision-analytic model found that digital interventions for generalised anxiety disorder were associated with lower net monetary benefit than medication and face-to-face therapy, but greater net monetary benefit than non-therapeutic controls and no intervention. Value for money was driven by clinical outcomes rather than by intervention costs, and a value-of-information analysis suggested that uncertainty in the treatment effect had the greatest value (£12.9B). In work package 4, stakeholders identified several areas of benefits and costs of digital interventions that are important to them, including safety, sustainability and reducing waiting times. Four factors may influence their decisions to use digital interventions, other than costs and outcomes: increasing patient choice, reaching underserved populations, enabling continuous care and accepting the 'inevitability of going digital'. LIMITATIONS: There was substantial uncertainty around effect estimates of digital interventions compared with alternatives. This uncertainty was driven by the small number of studies informing most comparisons, the small samples in some of these studies and the studies' high risk of bias. CONCLUSIONS: Digital interventions may offer good value for money as an alternative to 'doing nothing' or 'doing something non-therapeutic' (e.g. monitoring or having a general discussion), but their added value compared with medication, face-to-face therapy and printed manuals is uncertain. Clinical outcomes rather than intervention costs drive 'value for money'. FUTURE WORK: There is a need to develop digital interventions that are more effective, rather than just cheaper, than their alternatives. STUDY REGISTRATION: This study is registered as PROSPERO CRD42018105837. FUNDING: This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 26, No. 1. See the NIHR Journals Library website for further project information.

Digital interventions are activities accessed via technology platforms (e.g. computers, smartphones and virtual reality) that can improve users' mental health and reduce addiction problems. To assess whether or not digital interventions offer 'value for money', we needed to compare their costs and outcomes with the costs and outcomes of alternatives, such as face-to-face therapy and medication. This was done through economic evaluations. This project consisted of four work packages. In work package 1, we reviewed 76 published economic evaluations of digital interventions for different mental health and addiction problems. We could not directly compare their results because of differences in the methods that were used, but the overall picture suggested that digital interventions could offer good value for money as an alternative to 'doing nothing' or simply monitoring someone or giving them general information. The picture was unclear when digital interventions were compared with face-to-face therapy. In work package 2, we pooled research studies that evaluated the outcomes of digital interventions in reducing anxiety and worry; the results were inconclusive because we were uncertain about the differences in outcomes between digital interventions and alternatives. In work package 3, an economic model suggested that value for money in digital interventions is driven by how good they are and not by how much they cost. In work package 4, we presented our methods and results to service users, mental health professionals and researchers who wanted to know more about the value of digital interventions for specific groups (e.g. children and older adults) and for outcomes other than reducing symptoms (e.g. reducing waiting times for treatment and improving attendance for therapy). Finally, the stakeholders highlighted four factors that may influence their decisions to use digital interventions, other than costs and outcomes: increasing choice, reaching underserved populations, enabling continuous care and accepting the 'inevitability of going digital'.

Classifying information-sharing methods.

BACKGROUND: Sparse relative effectiveness evidence is a frequent problem in Health Technology Assessment (HTA). Where evidence directly pertaining to the decision problem is sparse, it may be feasible to expand the evidence-base to include studies that relate to the decision problem only indirectly: for instance, when there is no evidence on a comparator, evidence on other treatments of the same molecular class could be used; similarly, a decision on children may borrow-strength from evidence on adults. Usually, in HTA, such indirect evidence is either included by ignoring any differences ('lumping') or not included at all ('splitting'). However, a range of more sophisticated methods exists, primarily in the biostatistics literature. The objective of this study is to identify and classify the breadth of the available information-sharing methods. METHODS: Forwards and backwards citation-mining techniques were used on a set of seminal papers on the topic of information-sharing. Papers were included if they specified (network) meta-analytic methods for combining information from distinct populations, interventions, outcomes or study-designs. RESULTS: Overall, 89 papers were included. A plethora of evidence synthesis methods have been used for information-sharing. Most papers (n=79) described methods that shared information on relative treatment effects. Amongst these, there was a strong emphasis on methods for information-sharing across multiple outcomes (n=42) and treatments (n=25), with fewer papers focusing on study-designs (n=23) or populations (n=8). We categorise and discuss the methods under four 'core' relationships of information-sharing: functional, exchangeability-based, prior-based and multivariate relationships, and explain the assumptions made within each of these core approaches. CONCLUSIONS: This study highlights the range of information-sharing methods available. These methods often impose more moderate assumptions than lumping or splitting. Hence, the degree of information-sharing that they impose could potentially be considered more appropriate. Our identification of four 'core' methods of information-sharing allows for an improved understanding of the assumptions underpinning the different methods. Further research is required to understand how the methods differ in terms of the strength of sharing they impose and the implications of this for health care decisions.