Title: Health Economic Evaluations of Genomic Newborn Screening: Approaches by studies within the International Consortium on Newborn Sequencing

Hadley Stevens Smith

PhD, MPSA

1,2✉ Emailhadley.smith@hpchi.harvard.edu

Martin Vu 3

Tamara Dangouloff 4

Camille Schubert 5

Camille Level 6

Ramesh Lamsal 1

Kurt D. Christensen 1,2

Zornitza Stark 7,8,9

Ilias Goranitis 7,10

Matthew Aujla 11

Thomas Westover 12

Amy Ponte 13

Nidhi Shah 14

Laurent Servais 4,15

Miranda Bailey 16

Tara A. Lavelle 17

Scott D. Grosse 18

Sarah Norris 19

ICoNS Economics Subcommittee 1

James Buchanan 3,20

1 Precision Medicine Translational Research (PROMoTeR) Center Harvard Pilgrim Health Care Institute Boston MA USA

2 Harvard Medical School Boston MA USA

3 Health Economics and Policy Research Unit, Centre for Evaluation and Methods Wolfson Institute of Population Health, Queen Mary University of London London UK

4 Neuromuscular Reference Center, Department of Pediatrics University Hospital Liège & University of Liège Liège Belgium

5 Adelaide Health Technology Assessment (AHTA), School of Public Health University of Adelaide Adelaide Australia

6 Centre de Génétique, FHU TRANSLAD CHU Dijon Bourgogne Dijon France

7 Australian Genomics, Murdoch Children’s Research Institute Melbourne Australia

8 Victorian Clinical Genetics Services Murdoch Children’s Research Institute Melbourne Australia

9 Department of Paediatrics University of Melbourne Melbourne Australia

10 Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health University of Melbourne Melbourne Australia

11 FirstSteps Greece

12 Maternal Fetal Medicine and Perinatal Genetics Capital Health Trenton NJ USA

13 Global Medical Rare Disorders, Scientific Affairs and Diagnostics Sanofi, Cambridge MA USA

14 Dartmouth Health Children’s Lebanon NH USA

15 MDUK Oxford Neuromuscular Centre & NIHR Oxford Biomedical Research Centre University of Oxford Oxford UK

16 Rocket Pharmaceuticals Cranbury NJ USA

17 Center for the Evaluation of Value and Risk and Health, Institute for Clinical Research and Health Policy Studies Tufts Medical Center Boston MA USA

18 Department of Pediatrics University of Minnesota Medical School Minneapolis MN USA

19 Leeder Centre for Health Policy, Economics and Data, Sydney School of Public Health University of Sydney Sydney Australia

20 Barts Biomedical Research Centre National Institute for Health Research, Queen Mary University of London London UK

Authors: Hadley Stevens Smith,^1,2 Martin Vu,³ Tamara Dangouloff,⁴ Camille Schubert,⁵ Camille Level,⁶ Ramesh Lamsal,¹ Kurt D. Christensen,^1,2 Zornitza Stark,^7,8,9 Ilias Goranitis,^7,10 Matthew Aujla,¹¹ Thomas Westover,¹² Amy Ponte,¹³ Nidhi Shah,¹⁴ Laurent Servais,^4,15 Miranda Bailey,¹⁶ Tara A. Lavelle,¹⁷ Scott D. Grosse,¹⁸ Sarah Norris,¹⁹ ICoNS Economics Subcommittee, James Buchanan^3,20

Affiliations:

1. Precision Medicine Translational Research (PROMoTeR) Center, Harvard Pilgrim Health Care Institute, Boston, MA, USA

2. Harvard Medical School, Boston, MA, USA

3. Health Economics and Policy Research Unit, Centre for Evaluation and Methods, Wolfson Institute of Population Health, Queen Mary University of London, London, UK

4. Neuromuscular Reference Center, Department of Pediatrics, University Hospital Liège & University of Liège, Liège, Belgium

5. Adelaide Health Technology Assessment (AHTA), School of Public Health, University of Adelaide, Adelaide, Australia

6. Centre de Génétique, FHU TRANSLAD, CHU Dijon Bourgogne, Dijon, France

7. Australian Genomics, Murdoch Children’s Research Institute, Melbourne, Australia

8. Victorian Clinical Genetics Services, Murdoch Children’s Research Institute, Melbourne, Australia

9. Department of Paediatrics, University of Melbourne, Melbourne, Australia

10. Economics of Genomics and Precision Medicine Unit, Centre for Health Policy, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia

11. FirstSteps, Greece

12. Maternal Fetal Medicine and Perinatal Genetics, Capital Health, Trenton, NJ, USA

13. Global Medical Rare Disorders, Scientific Affairs and Diagnostics, Sanofi, Cambridge, MA, USA

14. Dartmouth Health Children’s, Lebanon, NH, USA

15. MDUK Oxford Neuromuscular Centre & NIHR Oxford Biomedical Research Centre, University of Oxford, Oxford, UK

16. Rocket Pharmaceuticals, Cranbury, NJ, USA

17. Center for the Evaluation of Value and Risk and Health, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA

18. Department of Pediatrics, University of Minnesota Medical School, Minneapolis, MN, USA

19. Leeder Centre for Health Policy, Economics and Data, Sydney School of Public Health, University of Sydney, Sydney, Australia

20. National Institute for Health Research, Barts Biomedical Research Centre, Queen Mary University of London, London, UK

Correspondence:

Hadley Stevens Smith, PhD, MPSA

hadley.smith@hpchi.harvard.edu

Abstract

Affordability and value-for-money are key factors that will inform decisions about implementation of genomic newborn screening (gNBS) as a population-based program. Given the methodological and data-related challenges to evaluating health and economic outcomes of gNBS, there is a need for discussion and knowledge sharing amongst investigators responsible for conducting such evaluations. The International Consortium on Newborn Sequencing (ICoNS) includes academic and commercial gNBS pilot and implementation programs, and the ICoNS Economics Subcommittee assembles health economists who are involved in the evaluation of these programs. This paper summarizes the reported approaches taken by gNBS researchers to assess the health, psychosocial, and economic outcomes of gNBS and provides recommendations for reporting of gNBS economic evaluations developed by an international working group of health economists. We surveyed 12 ICoNS-affiliated project investigators involved in the design of health economics and outcomes evaluation protocols, the results of which were supplemented through ICoNS Economics Subcommittee discussion.

Investigators reported making economic evaluation methodological design choices that reflect both the gNBS study design and adaptation to local policy questions and stakeholder input. Investigators reported plans to conduct cost-effectiveness analyses (n = 7, 58%) and/or cost-utility analyses (n = 5, 42%). Recommendations for reporting gNBS economic evaluations include aspects of genetic condition identification, screening and follow-up care pathways, and health and cost outcomes. Going forward, making transparent study design choices and sharing lessons learned could advance understanding of outcomes in a methodologically complex context and inform researchers planning to design similar studies in the future.

Key words:

newborn screening

genomic sequencing

economic evaluation

outcome assessment

Introduction

Incorporating genomic sequencing technologies into newborn population-based screening programs holds promise to improve child health (1, 2). Genomic newborn screening (gNBS) aims to predict genetic risk at birth and identify conditions that are treatable or otherwise actionable in childhood, enabling early intervention. Complementary to biochemical assays, gNBS increases the number of conditions for which early initiation of disease surveillance and therapeutic intervention would be possible (3, 4), with the potential to prevent diagnostic delays, slow disease progression, and facilitate access to targeted treatments (1).

The first randomized controlled trial (RCT) of genomic sequencing as a complement to standard newborn screening, the BabySeq Project, began in the United States in 2015. The trial provided initial evidence on the impact of gNBS on medical (5), psychosocial (6), and economic outcomes (7). Interest in gNBS has since expanded globally, with more than 60 research studies and commercial programs now assessing the feasibility and outcomes of gNBS implementation (8). The International Consortium on Newborn Sequencing (ICoNS) emerged in 2022 from efforts to share learnings across projects and has grown to include more than 700 members from over 50 countries. A key goal of the consortium is to facilitate harmonization of data collection approaches and data sharing, where feasible, to expand the evidence base on gNBS implementation outcomes.

Health economic evidence generated through existing gNBS pilot and implementation studies can inform gNBS adoption decisions (9). Beyond parental acceptability, the affordability and value-for-money of gNBS programs will be critical for their sustainable implementation in public health or clinical care (10). There is an opportunity cost associated with gNBS implementation given the finite nature of healthcare resources and the potential impact of gNBS on existing service delivery and longer-term health outcomes. Economic evaluations that compare the health outcomes and associated costs of gNBS with those of an appropriate comparator, such as traditional newborn screening or clinical case detection, will provide useful information to decision-makers (11). However, generating definitive evidence on the value of gNBS is difficult because gNBS projects differ widely in gene selection for analysis and reporting (8), parental information provision and consent procedures, data management, and evaluation of clinical, psychosocial, and economic outcomes. Decision-making processes regarding screening programs and clinical genomic medicine interventions also vary across jurisdictions (12). Evidence generation approaches will need to be tailored to local health system contexts, although harmonization of primary data collection efforts across programs may benefit broader health economic modeling efforts.

In the absence of standard practices for outcome measurement and economic evaluation in the context of gNBS, the experiences and intent of ongoing projects represent a valuable learning opportunity for the field. Development of standards for reporting methods and results of gNBS economic evaluations can increase transparency and the ability to leverage knowledge across jurisdictions to better inform gNBS translation into health systems. This paper summarizes the approaches to economic evaluation of gNBS that ICoNS member projects are employing and describes methods used to collect infant health and parent-reported experience and outcome data. Additionally, we present recommendations for reporting gNBS economic evaluations developed by an international working group of health economists.

Methods

The Economics Subcommittee of ICoNS was established in 2024 to develop a community of practice and facilitate the exchange of ideas and lessons learned amongst health economists involved in gNBS projects around the world. As part of subcommittee activities, subcommittee members (the authors) aimed to catalogue the approaches to economic evaluation of gNBS applied by these projects. To that end, we designed a survey to collect information on plans for the collection and analysis of outcome and cost data in each project. The survey was iteratively developed by two study team members with expertise in health economic evaluation of genomic medicine interventions (HSS, JB) and included items in five domains: 1) Planned health economic analyses; 2) Health, healthcare, and cost outcomes; 3) Psychosocial outcomes; 4) Methodological approach to economic evaluation; 5) Project timeline.

We constructed a sample frame by identifying key individuals who had specialized understanding of the methods for economic evaluation and/or survey design within ICoNS-affiliated projects. Among the 25 ICoNS-affiliated research projects in August 2024, 15 projects in which health economists were currently or potentially engaged in the research were identified by two subcommittee co-leads (JB, HSS) via conversations with key project personnel, and email contact information was collected for these individuals. We distributed links to the online survey, which was programmed in REDCap, to these key individuals and to the Economics Subcommittee member mailing list.

Survey responses were summarized using descriptive statistics and presented for discussion during subcommittee meetings, which took place regularly via webconference, and at the ICoNS annual conference in October 2024. Project representatives provided regular project updates and additional details regarding their survey responses as part of subcommittee discussions to add context and richness.

Given the various approaches to data collection and economic evaluation design that were reported on the survey and discussed, we identified a need for reporting guidance to facilitate clear communication of study methods and results. In addition to the established reporting standards for economic evaluations of healthcare interventions (13), specific elements relevant to gNBS were identified through structured discussion in a subcommittee meeting. A final set of reporting recommendations was refined through discussion and written feedback. Data analysis was conducted in Stata 17.

This research was approved by the Harvard Pilgrim Health Care Institutional Review Board (2183967).

Results

The survey was open for responses between August and October 2024. We received responses from representatives of 12 ICoNS member projects (80% response rate), which represented 48% of all ICoNS active projects in August 2024. Table 1 provides an overview of included projects. These include national government-funded initiatives in several countries (Greece, England (14)), member projects of the Genomic Screening Consortium for Australian Newborns (GenSCAN) consortium in Australia (BabyScreen+ (15), gEnomics4newborns, NewbornslnSA) (16), and independent research efforts in Belgium (4), France, and the US (3, 17–19).

Table 1

Global newborn genomic sequencing studies included in this study
Project Name	Country	Study Design	Planned Enrollment	Sequencing Type	Project Status	Planned Health Economic Analysis	Primary research goal related to economic evaluation
BabyDetect	Belgium	Prospective observational pilot study	7,000	Panel	Complete	Yes	Evaluate the costs of implementing a gNBS program and demonstrate its economic impact
BabyScreen+	Australia	Prospective implementation pilot study	1,000	GS	Complete	Yes	Explore public preferences for the value and implementation of gNBS and evaluate its cost-effectiveness relative to current newborn bloodspot screening
BabySeq	United States	Randomized controlled trial	500	GS	Ongoing	Yes	Understand the health and cost impact of genomic sequencing as a screening tool for all infants
BeginNGS	United States	Prospective observational pilot study	10,000 to 100,000	GS/ES	Ongoing	Yes	Model-based economic evaluation of gNBS using study results and a literature-based comparator
Early Check	United States	Prospective observational pilot study	10,000	GS/ES	Ongoing	Unsure	N/A
FirstSteps	Greece	Prospective observational pilot study	101,000	GS/ES	Ongoing	Yes	Model-based health economic evaluation
Generation Study	England	Prospective observational pilot study	100,000	GS	Ongoing	Yes	Estimate the costs and benefits of gNBS alongside current newborn bloodspot screening
gEnomics4newborns	Australia	Multi-modal research (interviews, equity-informed economic modelling, choice experiment, deliberative methods) to explore legal, ethical, equity, and economic implications of gNBS	N/A	N/A (no sequencing is being conducted as part of this study)	N/A	Yes	Investigate how ethics, equity effectiveness and economic aspects of using genomics in newborn screening should be assessed
GUARDIAN (ESLI proposal)	United States	Prospective observational pilot study	100,000	GS	Expected	Yes	Assess the total upfront costs associated with gNBS and traditional NBS using a microcosting approach; Assess the economic value of gNBS compared with NBS using a model-based economic evaluation
NewbornslnSA	Australia	Prospective observational pilot study	1,000	GS	Ongoing	Yes	Compare preliminary estimates of cost-effectiveness across targeted and non-targeted GS screening approaches.
PERIGENOMED	France	Prospective observational pilot study	20,000	GS	Expected	Yes	Not specified
New Jersey Task Force	United States	Prospective observational pilot study	Not specified	Not specified	Not specified	Unsure	N/A
GS, Genome Sequencing; ES, Exome Sequencing; Panel, Targeted Gene Panel Sequencing; ELSI, ethical, legal, social implications N/A, not applicable

Health economic analyses are currently planned for 10 (83%) projects, and a health economic evaluation protocol is reported to be in place for four (40%) projects. Support for conducting a health economic analysis is included in the budget of eight (67%) projects. Primary outcomes data are being collected in all but one project, gEnomics4newborns, which aims to develop health technology assessment tools and is not enrolling participants.

Formative research

Most projects employed formal stakeholder engagement approaches to inform the design of their data collection and analysis plans, as is required in some jurisdictions by decision makers involved in gNBS adoption and implementation into public health programs. For example, the Generation Study engaged with members of the UK National Screening Committee to identify key research questions and an evaluation framework during the Generation Study design between 2022–2023. The Generation Study also conducted a scoping study and worked with a Patient and Public Involvement Advisory Group to define its evaluation scope (14). Findings from this formative research were supplemented by document review and observation of recruitment and consent processes to inform bespoke questions and selection of validated outcome measures.

The BabySeq Project in the US is currently in its second iteration, recruiting participants from geographically diverse locations across the US with the goal of enrolling participants who have been underrepresented in genomics research (17). Semi-structured interviews were conducted with parents of children from underrepresented groups to inform aspects of study design and facilitate research participation (20). In addition to investigators’ experience with the previous iteration of the trial, a Community Advisory Board provided input on study materials, including survey instruments, and helped shape endpoint selection and measurement approaches (17). The GUARDIAN study in the US plans to collect qualitative and survey data from a range of stakeholder groups throughout the study, including pediatric providers, state newborn screening staff, geneticists, and parents of newborns offered participation in GUARDIAN, to explore the clinical, ethical, legal and economic issues related to gNBS. An expert advisory panel will advise on the study questions to address and data collection instrument development. Panel members will also assist in formulating options and recommendations for the future implementation of gNBS.

The BabyScreen + and NewbornsInSA projects in Australia conducted formative work to inform the study design including focus groups and key informant interviews (21–23). In addition, the BabyScreen + project conducted a discrete choice experiment study aimed at understanding public preferences for the value and implementation of gNBS (24). The study provided insights into the Australian public’s views and priorities about the types of conditions included in gNBS, as well as views and priorities about service delivery (24). The gEnomics4newborns study in Australia has also undertaken formative qualitative work with parents/carers of children with rare diseases identified via genetic testing, as well as healthcare professionals, scientists and policy makers involved in newborn screening regarding their views on gNBS (25). They have formed a Citizens Jury with members of the general public to understand their perspectives on gNBS. These studies have been overseen by an Expert Reference Group and a Consumer Advisory Group. The findings from both studies have been used to inform the attributes for a best-worst scaling study.

The Baby Detect program in Belgium conducted surveys to assess parental acceptability, knowledge, and trust in gNBS among both participants and non-participants. Semi-structured interviews with parents and healthcare professionals were also conducted after informational sessions during pregnancy to explore optimal ways to communicate about gNBS and support informed decision-making, with findings used to refine recruitment strategies, study materials, and implementation procedures.

Health, healthcare, and cost outcomes

As reported by project representatives, the primary clinical effectiveness endpoints across projects include the number of newborns with at least one reportable variant detected (n = 5, 42%) and the number of newborns with health care management changes (n = 4, 33%). Other projects are either conducting a cost analysis only (n = 1) or do not have a primary clinical effectiveness endpoint within their present evaluation (n = 2). Projects are collecting primary data on multiple health, healthcare, and cost outcomes; data collection time points are summarized in Table 2 and instruments are summarized in Table 3.

Table 2

Health, healthcare, and cost outcomes collected in newborn genomic sequencing studies (n = 12)
Outcome	n (%); Study names and data collection time points by data source
Outcome	Administrative Records	Electronic Health Records	Parent Surveys	Clinician Surveys	Other
Infant health-related quality of life	1 (8) New Jersey Task Force^d	1 (8) New Jersey Task Force^d	5 (42) BabySeq^a,c,d; BabyDetect^e; FirstSteps^d,e; Generation Study^a,d; PERIGENOMED^d,e;	1 (8) FristSteps^d,e	1 (8) Generation Study: Data for a control population of newborns not undergoing sequencing will be sourced from the literature and combined with prospectively collected data for newborns undergoing sequencing.
Parent health-related quality of life	0 (0)	0 (0)	5 (42) BabySeq^a,c,d; BabyDetect^e; PERIGENOMED^d; Generation Study^a,d; NewbornsInSA^a,d	0 (0)	1 (8) Generation Study: Data for a control population of parents whose newborn is not undergoing sequencing will be sourced from the literature and combined with prospectively collected data for newborns undergoing sequencing.
Actions recommended based on genomic sequencing results	4 (33) BabyDetect^e; Early Check^d,e; FristSteps^d,e; New Jersey Task Force^d	4 (33) BabyScreen + ^d,e; FristSteps^d,e; GUARDIAN (ESLI proposal)^d; NewbornsInSA^d	3 (25) BabySeq^d; Early Check^d,e NewbornsInSA^d;	4 (33) BabyDetect^e; FirstSteps^d,e; Generation Study^d; NewbornsInSA^d	3 (25) BabySeq: Chart notes from study-affiliated genetic counselor disclosure sessions sent to newborn's healthcare provider. BeginNGS: Expert panel uses Delphi method to assess treatment initiation likelihood and benefits for disorders with similar treatments and outcomes. Generation Study: Bespoke clinician survey questions post-testing.
Follow-through on recommended actions	3 (25) FristSteps^d,e; Early Check^d; New Jersey Task Force^d	4 (33) BabyScreen + ^d; BabySeq^d; FirstSteps^d,e; New Jersey Task Force^d	1 (8) BabySeq^d	1 (8) FirstSteps^d,e	0 (0)
Infant health care utilization	2 (17) BabyDetect^e; FirstSeps^d,e	6 (50) BabyScreen+; BabySeq^a,c,d; FirstSteps^d,e; Generation Study^c,d; PERIGENOMED^d,e; NewbornsInSA^d	2 (17) BabySeq^d; GUARDIAN (ESLI proposal)^f	2 (17) BabySeq^a,c,d; GUARDIAN (ESLI proposal)^f	2 (17) Generation Study: Secondary care resource use by the newborn (hospital episode statistics) will be linked to their clinical/genetic records. GUARDAIN (ESLI proposal): Cross sectional survey data and interviews to retrospectively estimate what resources are used from the time from blood spot collection to the return of genomic NBS results.
Health care costs	3 (25) BabyDetect^e; NewbornsInSA^d; PERIGENOMED^d,e	3 (25) BabyScreen + ^d,e; BabySeq^a,c,d; PERIGENOMED^d,e	2 (17) BabySeq^a,c,d; NewbornsInSA^d	0 (0)	2 (17) Generation Study: National Reference Cost database. BabyScreen+: data on infants diagnosed with the same conditions using standard approaches will be sourced from the literature and local databases
Personal costs for parents and infants (e.g., out-of-pocket health care costs)	0 (0)	1 (8) BabySeq^a,c,d	3 (25) BabySeq^a,c,d; BabyDetect^e; Generation Study^d; NewbornsInSA^d,e	0 (0)	0 (0)
^a At the time of consent for the study; ^b Prior to birth; ^c After birth, but before return of sequencing results; ^d After the return of sequencing results; ^e Long-term follow-up; ^f Other

Table 3

Data collection approach and instruments for health, healthcare, and cost outcomes in newborn genomic sequencing studies (n = 12)
Outcome, n (%)	Data Collection Instrument/Approach	n	Studies
Infant health-related quality of life, 6 (50)	EQ-TIPS	2	BabySeq; Generation Study
	HUI 2/3	1	BabyDetect
	PedsQL	3	BabyDetect; PERIGENOMED; FirstSteps^a
Parent health-related quality of life, 4 (33)	EQ-5D-3L	1	BabySeq
	EQ-5D-5L	1	Generation Study
	PedsQL-Family Impact Module	2	BabyDetect, Generation Study
	SF-12	1	PERIGENOMED
Actions recommended based on genomic sequencing results, 8 (67)	Bespoke items/case report forms	5	BabyDetect; BabySeq; Early Check; FirstSteps; NewsbornInSA
	C-GUIDE	2	Generation Study, BabyScreen+
	Not specified	1	New Jersey Task Force
Follow-through on recommended actions, 4 (33)	Bespoke items/case report forms	2	BabySeq; FirstSteps
Follow-through on recommended actions, 4 (33)	Not specified	2	Early Check; New Jersey Task Force
Infant health care utilization, 8 (67)	Bespoke items/case report forms	4	BabyDetect; BabySeq; FirstSteps, NewbornsInSA
Infant health care utilization, 8 (67)	Not specified	4	PERIGENOMED; Early Check; GUARDAIN (ESLI proposal); BabyScreen+
Health care costs, 6 (50)	Bespoke items	2	BabyDetect; BabySeq; NewsbornInSA
	National reference cost database	1	Generation Study
	Not specified	2	BabyScreen+; PERIGENOMED
Personal costs for parents and infants (e.g., out-of-pocket health care costs), 4 (33)	Bespoke items (e.g., out-of-pocket expenses for healthcare visits, services, equipment and therapies, employment and productivity costs, childcare and schooling costs, and family)	4	BabySeq; BabyDetect; Generation Study; NewbornsInSA
^a modified version of instrument used C-GUIDE, Clinician-reported Genetic testing Utility InDEx; EQ-TIPS, EuroQol Toddler and Infant Populations; HUI, Health Utilities Index; PedsQL Family Impact Module, Pediatric Quality of Life Inventory Family Impact Module; EQ-5D, EQ 5-Dimension Questionnaire; EQ-3D, EQ 3-Dimension Questionnaire; SF-12, 12-Item Short Form Health Survey

Parent surveys serve as important data collection tools in all projects that are enrolling newborns. Projects are collecting data on infant health-related quality of life (HRQoL) (n = 6, 50%) and parent HRQoL (n = 4, 33%) using various instruments.(26–31) These data were judged by respondents to be important to understand the impact of specific rare diseases for which screening is taking place, which will enable comparisons between individuals diagnosed following screening with those diagnosed through standard clinical case detection. Parent and clinician surveys are also being used to collect data on actions recommended based on gNBS results (32), follow-through on recommended actions, and personal/family health care costs (e.g., out-of-pocket costs).

Because most projects are conducting observational studies, most outcomes data is focused on gNBS follow-up. As part of its RCT design, the BabySeq Project is also collecting parent-reported outcomes data at baseline. The Generation Study evaluation is collecting HRQoL data for mothers at baseline, and for mothers and for their newborns immediately following result return and at 12 month follow up. NewbornsInSA review medical records and conduct follow-up surveys to ask both clinicians and parents about expected future actions, noting these will be used as exploratory data. To estimate the value of gNBS outcomes, BabyScreen + collected information on participant’s willingness-to-pay for gNBS using contingent valuation and it further conducted a discrete choice experiment with the Australian public (24).

Most projects will analyze health care utilization and associated costs after the return of screening results using data obtained through administrative records and parent surveys. In addition, the Generation Study is conducting a micro-costing analysis of gNBS and existing newborn bloodspot screening using a time-driven activity-based approach. Data is being collected via interviews with clinical and research staff, direct site observations and reviews of standard operating procedures and other relevant study documents. Secondary healthcare resource use data is also being collected and costed for all 100,000 newborns in the Generation Study, from birth onwards. The GUARDIAN study also plans a micro-costing study using a similar approach.

Psychosocial outcomes

Projects are collecting parent-reported experience and outcome data on several psychosocial measures to identify the impact of gNBS on parents and families, as well as their perceptions of the utility of gNBS. Instruments used to assess psychosocial experiences and outcomes are presented in Table 4. The rationale for including these measures is related to the need to identify broader impacts of gNBS on parent and child well-being, and associated parent attitudes, evidence of which may be considered as part of implementation and funding decisions. For example, in NewbornsInSA, it was considered important to understand the impact on the whole screened population, not just individuals who are identified to have a condition. This is critical to acceptability, and therefore uptake, of the program, and clarity regarding the overall benefit-harm ratio of gNBS programs. Both considerations may impact estimates of cost-effectiveness, given that there are sunk infrastructure and program costs to consider, and that small psychosocial impacts felt by large numbers in screening populations may be significant when compared with any health impact among a small number of diagnosed individuals.

Table 4

Psychosocial measures administered in genomic newborn sequencing studies (n = 12)
Psychosocial Outcome	n (%)	Project(s)	Instrument(s) used to assess outcomes
Collecting psychosocial outcomes as primary data
Yes	8 (58)	BabyScreen+, BabySeq, BabyDetect, Early Check, FirstSteps, Generation Study, PERIGENOMED, NewbornsinSA
No	2 (17)	BeginNGS, New Jersey Task Force
Types of psychosocial outcomes
Parental anxiety	7 (58)	BabyScreen+, BabySeq^a,c,d, Early Check^d, FirstSteps^d,e, Generation Study^a,d, PERIGENOMED^d,e, NewbornsInSA^a,d	Customized version of Moore’s Outcomes-mapped questionnaire, GAD-7, HADS, STAI-6, PHQ-2, GAD-2, PHQ-9
Parental depression	5 (42)	BabyScreen+, BabySeq^a,c,d, Early Check^d, PERIGENOMEDe, NewbornsInSA ^a,d	PHQ-8, HADS, CES-D, PHQ-2, GAD-2, PHQ-9, EPDS-9
Parental stress	4 (33)	BabySeq^a,c,d, BabyDetect^e, FirstSteps^d,e, PERIGENOMED^d,e	Customized version of Moore’s Outcomes-mapped questionnaire, PSI/-4SF, PSS
Parental feelings about test results	5 (42)	BabySeq ^a,c,d, Early Check^e, FirstSteps^d,e, PERIGENOMED^d,e, NewbornsInSA ^a,d	Customized version of Moore’s Outcomes-mapped questionnaire, FACToR, PUGS, customized application of HBM
Perceived vulnerability of the child	3 (25)	BabySeq^d, FirstSteps^d,e, Generation Study^d	Customized version of Moore’s Outcomes-mapped questionnaire, VBS
Personal or perceived utility of genomic sequencing	6 (50)	BabySeq^a,c,d, Early Check^e, FirstSteps^d,e, Generation Study^d, PERIGENOMED^d, NewbornsInSA^a,d	GENE-U, Parent PrU, customized application of HBM
Parental relationship satisfaction	2 (17)	BabySeq^a,c,d, FirstSteps^d	KMS
Parental blame and/or guilt	2 (17)	BabySeq^a,c,d, PERIGENOMED ^d,e	Bespoke items
Other	3 (25)	BabyScreen+, Generation Study^d, NewbornsInSA^a,d	PedsQL Family Impact Module, MIBS, Decisional conflict scale, Decisional regret scale, willingness-to-pay, customized application of HBM
^a At the time of consent for the study; ^b Prior to birth; ^c After birth, but before return of sequencing results; ^d After the return of sequencing results; ^e Long-term follow-up; ^f Other CESD: Center for Epidemiologic Studies Depression Scale, EPDS-9: Edinburgh Postnatal Depression Scale 9, FACToR: Feelings About Genomic Testing Results, GAD-2: Generalized Anxiety Disorder 2, GAD-7: Generalized Anxiety Disorder 7, GENE-U: GENEtic Utility Scale, HADS: Hospital Anxiety and Depression Scale, HBM: Health Belief Model, KMS: Kansas Marital Satisfaction Scale, MIBS: Mother-to-Infant Bonding Scale, PedsQL: Pediatric Quality of Life Inventory Family Impact Module, PHQ-2: Patient Health Questionnaire 2, PHQ-9: Patient Health Questionnaire 9, Parent PrU: Parent Personal Utility Scale, PSI: Parenting Stress Index, PSS: Parental Stress Scale (PSS), PUGS: Perceptions of Uncertainties in Genome Sequencing, STAI-6: State-Trait Anxiety Inventory – 6 item, VBS: Vulnerable Baby Scale

Parental mental health will be assessed, including anxiety (n = 7, 58%) (33–35), depression (n = 5, 42%) (36–38), blame and guilt (n = 2, 17%). Measures of parents’ perceptions of and relationship with their child and partner, including parental stress (n = 4, 33%) (39, 40), perceived vulnerability of the child (n = 3, 25%) (41), mother-to-infant bonding (n = 1, 8%) (42), and marital relationship satisfaction (n = 2, 17%) will also be collected (43). Additionally, studies will examine genomics-specific outcomes, such as parental feelings about test results, uncertainty, and the personal or perceived utility of genomic sequencing (n = 6, 50%) (44–47). Some studies also include survey items to assess families’ perspectives, such as items to assess family thoughts around the benefit-harm of gNBS. For example, NewbornsInSA is assessing decision regret, as well as ways in which parents’ health beliefs and family and social structures influence their decision to participate or not and satisfaction.

Economic evaluation design

A range of economic evaluation approaches will be used across the projects, with six studies planning to undertake more than one type of analysis. Several studies will conduct a cost-effectiveness analysis (n = 7, 58%) and/or cost-utility analysis (n = 5, 42%), alone or alongside a cost analysis (n = 5, 42%). Some studies also plan a cost-consequence analysis (n = 2, 17%) and a cost-benefit analysis (n = 2, 17%).

Studies that plan a cost-effectiveness analysis will use as the primary effectiveness endpoint the number of newborns with at least one reportable variant detected (n = 3, 43%), or the number of newborns with health care management changes (n = 4, 57%). Most studies will use primary data generated within the study (n = 7, 58%), and five (42%) studies will include a model-based economic evaluation. Two (18%) studies will use the study data to inform parameter values for their health economic simulation model.

Most studies (n = 8, 67%) will use a control group in their economic evaluation. The BabySeq Project was the only RCT, with the control arm for its economic evaluation sourced from within the trial. The planned analysis in The BabySeq Project includes a comparison of costs by randomization arm (gNBS vs family history review only) and gNBS result status (monogenic disease risk identified vs not).

Other studies intend to use historical controls (n = 4, 33%), comparator data from the literature (n = 5, 42%), or data collected from control parents (n = 1, 11%). Common sources of historical data will include routinely collected hospital administrative or insurance data.

The BabyDetect project will collect data from 100 control parents: 50 parents of healthy children and 50 parents of children with a pathology that is not part of the BabyDetect program. In PERIGENOMED, an external control group will be created by linking the French National Data Bank on Rare Diseases with data on healthcare consumption from the French National Health Insurance (Système National de Données de Santé). In the Generation Study, data for newborns not undergoing sequencing (costs, health care utilization, outcomes) will be extracted from the literature. NewbornsInSA will employ a hierarchical approach to modelling comparators, depending on final conditions identified and case numbers with data available: 1) historical controls if available (within 10 years); 2) literature cases; and 3) clinical opinion regarding hypothetical cases modelled, as required.

Most studies will use existing literature to supplement primary data collection. Studies using model-based approaches to health economic evaluation will use published data to derive at least some input values for models. For example, the gEnomics4newborns study will use literature to inform the model structure, to select appropriate health-related utility weights (to derive quality-adjusted life years), to estimate likely incidence of the conditions of interest, to estimate likely uptake rates of screening, and to estimate the effectiveness of specific management pathways. In the BeginNGS study, it was reported that literature may also be used to understand and inform the disease course of a patient who is diagnosed and treated later vs a patient in the study who was identified and may receive an intervention earlier (19).

Recommendations for reporting economic evaluations of gNBS

Through subcommittee discussion, an initial list of elements to report in gNBS economic evaluations was generated. These items were intended to facilitate transparent discussion and comparisons across studies and advance evidence base development. The final list contains 24 elements (Fig. 1) that address aspects of the genetic basis of the screened conditions, diagnostic testing and follow-up care, and health, psychosocial, and cost outcomes. These items complement existing good practice reporting standards for economic evaluations (13), which are not fit-for-purpose for evaluations of screening programs. Moreover, some items included on standard reporting checklists may be less clear-cut in the context of gNBS, such as whether psychosocial impacts of gNBS on parents should be included when taking a healthcare system perspective. Additionally, early publication of study protocols and the development of formal health economic analysis plans is encouraged.

Fig. 1

Recommended reporting elements in economic evaluations of genomic newborn screening programs

Discussion

We have described the landscape of data collection efforts to support health economic evaluation, as well as the design of such evaluations, across ICoNS-affiliated gNBS projects around the world.

This work identified substantial variation in approaches to evaluating health and cost impacts, which reflects variation in overall gNBS study design and requirements of local decision-makers. While projects are collecting primary data on a similar set of constructs, there are many distinct instruments are being used to assess these constructs. Primary data on actions being prompted by gNBS results, follow-through on those actions, and associated costs are being collected using bespoke instruments that were developed for the context of specific projects. These findings suggest general agreement regarding which outcomes are important to measure but no one best way to measure them. In instances where the same instrument is used in multiple projects, pooling data may inform health economic modeling efforts, which is particularly important given the low expected screen-positive rate for individual rare conditions. Projects are collecting primary outcome data during relatively short study periods. Decision makers will need longer term projections of the impacts of gNBS throughout childhood and over the full life course, which increases uncertainty and highlights the importance of supplementing program-derived evidence with continued real-world evidence generation.

There remains a need to generate economic evidence in a broader screening context to inform the potential implementation of gNBS. Methodological and data-related challenges to genomic sequencing economic evaluations are well-recognized (11, 48), and they persist despite the development of theoretical frameworks to guide health economists (49). The cost-effectiveness of genomic sequencing varies substantially depending on the clinical context and setting (e.g., diagnostics, screening, infection surveillance), indication for testing (e.g., cancer, rare disease), availability and cost of clinical interventions for a diagnosed condition, and patient population in which it is used (50). While there is a growing evidence base on the cost-effectiveness of genomic sequencing in a diagnostic context, economic evaluations of population-based genomic screening have predominantly focused on screening for a limited set of actionable conditions in newborns and adults. Due to the rarity of conditions detectable through gNBS, incremental cost-effectiveness ratios (i.e., the incremental cost divided by the incremental effect of gNBS compared with traditional newborn screening or clinical case detection) are likely to be much higher than those typically accepted as cost-effective by decision-makers due to the exceedingly small denominator. Modeling multiple conditions simultaneously is possible, but criteria for condition grouping (e.g., by natural history or intervention type) remain unclear.

Additionally, whether and how to consider psychosocial impacts remains in question. While data on psychosocial outcomes may point toward an impact on health-related quality of life or well-being, they are not necessarily transformable into a preference-based health state utility estimate. Some psychosocial data collection focuses on understanding impacts on the family system broadly using instruments commonly used across condition areas. Projects are also generating data on genetics-specific instruments that are more recently developed and have not yet been used in gNBS evaluations. Availability of relatively new measures of parental perceived utility of genomic sequencing, such as the GENE-U (46), and clinician-reported utility, such as the C-GUIDE (32), may lead to greater standardization of measurement of these outcomes in the future.

Scientific, clinical, and epidemiological factors and societal norms and policy frameworks vary across jurisdictions and will shape decision priorities (10, 12). The value and cost-effectiveness of gNBS will vary depending upon several factors, including the set of screened conditions, the population prevalence of screened conditions, and the availability of other screening programs (e.g., carrier and standard newborn screening) and effective clinical management strategies for screened conditions. It will be difficult to demonstrate that gNBS is cost-effective for conditions (or genetic variants) where there is no actionable intervention pathway or no evidence of effectiveness of a particular treatment in newborns. The benefit of screening depends on the health gains achievable though available treatments; high screening costs matter less if benefits are substantial. The monetary value placed on knowing the screening results may also vary across populations.

The number of gNBS programs has grown rapidly over a short period of time. Our study is limited in that new projects that were established since our data collection are not represented. However, the regular meetings of the ICoNS Economics Subcommittee provide opportunities for perspectives from researchers affiliated with new projects to be reflected. Many programs were already launched at the time of our initial data collection efforts, which limited the ability to harmonize instruments for primary data collection. While data collection approaches and analytic methods differ to meet study and policy context-specific requirements, efforts to ensure consistency in reporting of approaches and findings can facilitate learning and harmonization.

This article contributes to an emerging evidence base on gNBS economic evaluation methods by providing timely insight into the approaches taken by an initial set of gNBS programs, which can potentially guide the design of future studies, as well as reporting recommendations to facilitate learning and data sharing. While complete harmonization in methods may not be feasible given contextual differences, increasing alignment in key areas such as reporting could strengthen the overall evidence base for gNBS. Further research should examine the health care payer data requirements across jurisdictions and considerations for sustainability of gNBS programs outside of funded research. Future work will articulate the value proposition of gNBS across conditions and jurisdictions, leading to development of guidance to ensure that studies evaluating gNBS are undertaken in a way that generates robust evidence on all relevant aspects of value.

Data availability statement:

Data are available within the published article.

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Author contributions:

HSS drafted the manuscript. HSS and JB designed the data collection instrument. All authors critically reviewed and edited the manuscript. Participants provided informed consent for the survey research study using standard online survey procedures.

Funding:

No funding was received to support this study.

Ethical approval:

This study was approved by the Harvard Pilgrim Health Care Institute Institutional Review Board.

Competing interests:

HSS reports consulting income from Illumina, Inc. unrelated to this work. MV received a PhD (independent) scholarship from Illumina under the University of Melbourne/Illumina partnership. JB reports travel funding from Illumina, Inc. and consulting income from Genomics England. AP is an employee of Sanofi and may hold stock/stock options in the company. MB is an employee of Rocket Pharmaceuticals and may hold stock/stock options in the company. TD has given lectures sponsored by Biogen and Roche. LS gave consultancy to Illumina, Sanofi, LaCaer and is non-remunerated member of the board of directors of Thameus. TW is a past consultant to Illumina, Labcorp, Sequenom, Natera, myriad, Billion to one, Coalition to advance prenatal screening

Yes