Development of a Value Assessment Framework for Pediatric Health Technologies Using Multicriteria Decision Analysis: Expanding the Value Lens for Funding Decision Making.

OBJECTIVES: A health technology assessment (HTA) does not systematically account for the circumstances and needs of children and youth. To supplement HTA processes, we aimed to develop a child-tailored value assessment framework using a multicriteria decision analysis approach. METHODS: We constructed a multicriteria-decision-analysis-based model in multiple phases to create the Comprehensive Assessment of Technologies for Child Health (CATCH) framework. Using a modified Delphi process with stakeholders having broad disciplinary and geographic variation (N = 23), we refined previously generated criteria and developed rank-based weights. We established a criterion-pertinent scoring rubric for assessing incremental benefits of new drugs. Three clinicians independently assessed comprehension by pilotscoring 9 drugs. We then validated CATCH for 2 childhood cancer therapies through structured deliberation with an expert panel (N = 10), obtaining individual scores, consensus scores, and verbal feedback. Analyses included descriptive statistics, thematic analysis, exploratory disagreement indices, and sensitivity analysis. RESULTS: The modified Delphi process yielded 10 criteria, based on absolute importance/relevance and agreed importance (median disagreement indices = 0.34): Effectiveness, Child-specific Health-related Quality of Life, Disease Severity, Unmet Need, Therapeutic Safety, Equity, Family Impacts, Life-course Development, Rarity, and Fair Share of Life. Pilot scoring resulted in adjusted criteria definitions and more precise score-scaling guidelines. Validation panelists endorsed the framework's key modifiers of value. Modes of their individual prescores aligned closely with deliberative consensus scores. CONCLUSIONS: We iteratively developed a value assessment framework that captures dimensions of child-specific health and nonhealth gains. CATCH could improve the richness and relevance of HTA decision making for children in Canada and comparable health systems.

A Systematic Review of Methods and Practice for Integrating Maternal, Fetal, and Child Health Outcomes, and Family Spillover Effects into Cost-Utility Analyses.

BACKGROUND: Maternal-perinatal interventions delivered during pregnancy or childbirth have unique characteristics that impact the health-related quality of life (HRQoL) of the mother, fetus, and newborn child. However, maternal-perinatal cost-utility analyses (CUAs) often only consider either maternal or child health outcomes. Challenges include, but are not limited to, measuring fetal, newborn, and infant health outcomes, and assessing their impact on maternal HRQoL. It is also important to recognize the impact of maternal-perinatal health on family members' HRQoL (i.e., family spillover effects) and to incorporate these effects in maternal-perinatal CUAs. OBJECTIVE: The aim was to systematically review the methods used to include health outcomes of pregnant women, fetuses, and children and to incorporate family spillover effects in maternal-perinatal CUAs. METHODS: A literature search was conducted in Medline, Embase, EconLit, Cochrane Collection, Cumulative Index to Nursing and Allied Health Literature (CINAHL), International Network of Agencies for Health Technology Assessment (INAHTA), and the Pediatric Economic Database Evaluation (PEDE) databases from inception to 2020 to identify maternal-perinatal CUAs that included health outcomes for pregnant women, fetuses, and/or children. The search was updated to December 2022 using PEDE. Data describing how the health outcomes of mothers, fetuses, and children were measured, incorporated, and reported along with the data on family spillover effects were extracted. RESULTS: Out of 174 maternal-perinatal CUAs identified, 62 considered the health outcomes of pregnant women, and children. Among the 54 quality-adjusted life year (QALY)-based CUAs, 12 included fetal health outcomes, the impact of fetal loss on mothers' HRQoL, and the impact of neonatal demise on mothers' HRQoL. Four studies considered fetal health outcomes and the effects of fetal loss on mothers' HRQoL. One study included fetal health outcomes and the impact of neonatal demise on maternal HRQoL. Furthermore, six studies considered the impact of neonatal demise on maternal HRQoL, while four included fetal health outcomes. One study included the impact of fetal loss on maternal HRQoL. The remaining 26 only included the health outcomes of pregnant women and children. Among the eight disability-adjusted life year (DALY)-based CUAs, two measured fetal health outcomes. Out of 174 studies, only one study included family spillover effects. The most common measurement approach was to measure the health outcomes of pregnant women and children separately. Various approaches were used to assess fetal losses in terms of QALYs or DALYs and their impact on HRQoL of mothers. The most common integration approach was to sum the QALYs or DALYs for pregnant women and children. Most studies reported combined QALYs and incremental QALYs, or DALYs and incremental DALYs, at the family level for pregnant women and children. CONCLUSIONS: Approximately one-third of maternal-perinatal CUAs included the health outcomes of pregnant women, fetuses, and/or children. Future CUAs of maternal-perinatal interventions, conducted from a societal perspective, should aim to incorporate health outcomes for mothers, fetuses, and children when appropriate. The various approaches used within these CUAs highlight the need for standardized measurement and integration methods, potentially leading to rigorous and standardized inclusion practices, providing higher-quality evidence to better inform decision-makers about the costs and benefits of maternal-perinatal interventions. Health Technology Assessment agencies may consider providing guidance for interventions affecting future lives in future updates.

Paving the path for implementation of clinical genomic sequencing globally: Are we ready?

Despite the emerging evidence in recent years, successful implementation of clinical genomic sequencing (CGS) remains limited and is challenged by a range of barriers. These include a lack of standardized practices, limited economic assessments for specific indications, limited meaningful patient engagement in health policy decision-making, and the associated costs and resource demand for implementation. Although CGS is gradually becoming more available and accessible worldwide, large variations and disparities remain, and reflections on the lessons learned for successful implementation are sparse. In this commentary, members of the Global Economics and Evaluation of Clinical Genomics Sequencing Working Group (GEECS) describe the global landscape of CGS in the context of health economics and policy and propose evidence-based solutions to address existing and future barriers to CGS implementation. The topics discussed are reflected as two overarching themes: (1) system readiness for CGS and (2) evidence, assessments, and approval processes. These themes highlight the need for health economics, public health, and infrastructure and operational considerations; a robust patient- and family-centered evidence base on CGS outcomes; and a comprehensive, collaborative, interdisciplinary approach.