Newborn Screening in the United States: A Vision for Sustaining and Advancing Excellence (2025)
Chapter: 6 The Research Enterprise Relevant to Newborn Screening
6
The Research Enterprise Relevant to Newborn Screening
“Can we identify all these different assets to see if there’s a [way to have] a coordinated effort opposed to a very sequential path? . . . How can we collaborate together to have a coordinated effort?” – Newborn screening researcher
From its inception, public health newborn screening (NBS) has relied on evidence to make programmatic and policy decisions (AAP, 1967). As a public health service, decision makers must maximize public trust in newborn screening through assurances that decisions are based on solid evidence that is accurate, valid, reproducible, informative, and minimally biased (APHA, 2019; USPSTF, 2018). Virtually every aspect of public health newborn screening relies on research to generate evidence for a range of complicated questions, such as assessing which conditions to include; considering the responsible implementation of emerging technologies and updates to existing technology; navigating complex ethical and social issues; and identifying effective health service delivery practices in such areas as results communication, education and training, health outcomes, and economic evaluation. Complicating matters, most conditions considered for inclusion in newborn screening are rare and each state and territory sets its own NBS policies and practices. Thus, gathering enough standardized data to reach an acceptable evidence threshold is arduous and costly, compromising the nation’s ability to make evidence-based decisions about public health newborn screening expeditiously and soundly (Minear et al., 2022).
This chapter outlines critical categories of research needed to inform public health newborn screening; it then provides an overview of the current landscape and challenges for evidence generation. The chapter closes by discussing the need for a national plan and the research infrastructure to ensure that NBS research is strategic, systematic, coordinated, nimble, and sufficiently resourced to provide the evidence needed for public health newborn screening to adjust to a rapidly changing landscape and ensure that children and their families receive the high-quality, timely care they need.
THE IMPORTANCE OF RESEARCH TO INFORM NEWBORN SCREENING
NBS research encompasses the study of methods, technologies, policies, and outcomes related to population-based screening of newborns for health conditions shortly after birth. Such research also includes studies to better understand the full range of a condition, which can only be revealed through population-level screening. Ultimately, decision makers need answers to a wide range of questions to inform the policy and practice of public health newborn screening. In general, these questions fall into four broad categories:
- Defining conditions to guide screening, diagnosis, and treatment;
- Applying laboratory testing and emerging technologies;
- Understanding ethical, legal, and social issues; and
- Investigating public health practice, feasibility, and impact.
Defining Conditions to Guide Screening, Diagnosis, and Treatment
Newborn screening has a special obligation for ensuring that screening is based on solid evidence of net benefit as a public health program that generally operates under the assumption that early screening and treatment of a serious health condition is sufficiently urgent that a state can screen babies without parental consent (Currier, 2022; Faden et al., 1982; King and Smith, 2016). To maintain public acceptance, decisions about what and when to screen must be consistently based on solid and compelling evidence (see Chapter 3 for a discussion of ethical principles and values informing decision making in public health newborn screening).
When considering a condition nominated for newborn screening, the Advisory Committee on Heritable Disorders in Newborns and Children focuses on several questions (see Chapter 2), including those related to understanding the disease proposed to be screened. Such questions include: Is the nominated condition medically serious? Are
the condition’s case definition and spectrum well described? Can the case definition predict the phenotype or range of symptoms in newborns and children who will be identified through population-based screening? (HRSA, 2022a). Although seemingly simple questions, underlying each are many different topics that must be addressed. Consider, for example, case definition. Evidence may be available that indicates that a condition can result in death or impairment; however, this may not provide a complete picture of phenotypes that could arise for a condition in population screening (Lloyd-Puryear et al., 2019). Screening of the general population reveals a condition’s broader and complex phenotype and natural history that lays hidden in everyday clinical medicine where only the most severe and homogeneous cases are identified and aggregated.
A useful analogy is to picture screening for any given condition as an iceberg (Figure 6-1) (Last, 2014; Last and Adelaide, 2013). Individuals with the condition who present clinically comprise the tip of the iceberg; these tend to be the most severe cases or those with resources to access clinical care. This tip represents all the data and information that would be known about a condition before population-based screening. Screening will reveal the hidden cases of conditions—the portion of the iceberg located beneath the surface of the water. The submerged portion of the
NOTE: NBS = newborn screening.
iceberg is composed of cases that have evaded clinical detection because they are asymptomatic, mild, or atypical in severity, time of onset, or symptoms.
Because of this, newborn screening faces a “chicken or the egg” dilemma: how to obtain critical population-based data about the full spectrum of a condition without adding it to a mandated NBS panel. For public health newborn screening to add conditions in a manner that is ethical and evidence based, research that reveals the totality of the screening iceberg is essential because it will allow for precise characterization of prospective conditions and inform the development of more effective testing and treatment strategies. For example, if a condition has effects ranging from asymptomatic to severe, it would be important to know if the screening test or the diagnostic procedure could tell the difference, to inform treatment planning and avoid providing a risky treatment (e.g., stem cell transplant) for a child who does not actually need it (e.g., differentiating between infantile and late-onset Krabbe disease) (Guenzel et al., 2020; New York State Krabbe Disease Consortium, 2016). In the absence of population-based screening research, public health newborn screening has to grapple with these decisions in real time with real children who are left to wait and see if they develop signs or symptoms of disease (Kwon and Steiner, 2011; Timmermans and Buchbinder, 2010).
Developing Laboratory Testing and Applying Emerging Technologies
Newborn screening relies on laboratory tests. Without an accurate test that can be performed at scale in a public health laboratory, there is no newborn screening (HRSA, 2022b). Some research questions focus on developing biochemical or molecular tests for first-tier screening; some focus on second-tier screens to provide more sensitivity following an out-of-range screening result (Chen, 2012; Furnier et al., 2020). Implementing screening tests at scale also involves research to appropriately set cutoff values for what results are considered in range and out of range, among other questions that must be addressed (Chen, 2012). Each state and territorial NBS program sets its own cutoff values,1 complicating research activities across programs (Minear et al., 2022).
Beyond these essential questions, there is also ongoing research about incorporating emerging technologies into newborn screening. Chapter 5 expands on the opportunities, challenges, and considerations for responsible application of emerging technologies, with a focus on genomic sequencing, including the research landscape and outstanding
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1 See https://dshs.texas.gov/laboratory-services/programs-laboratories/newborn-screening-laboratory/newborn-screening-faqs (accessed March 20, 2025).
questions. However, genomic sequencing is not the only technology that could impact the future of public health newborn screening. Research is also investigating the utility of other platform technologies, including proteomics approaches. First-tier public health newborn screening currently uses different biochemical approaches, several of which could be consolidated by employing liquid chromatography mass tandem spectrometry (LC-MS/MS) (Gelb, 2024). LC-MS/MS permits screening for more biomarkers than flow-injection analysis tandem mass spectrometry, a common approach used currently (Gelb et al., 2022). LC-MS/MS could potentially save both time and money while continuing to screen for conditions with high specificity and sensitivity (Gelb, 2024; Gelb et al., 2022). However, this approach has a limit on the number of conditions it can detect compared to genomics-based approaches (Gelb, 2024). Beyond platform technologies, researchers are also investigating potential applications of artificial intelligence and machine learning (AI/ML) for public health newborn screening (Peng et al., 2020; Zaunseder et al., 2022; Zhou et al., 2022), which are discussed in Box 6-1.
Understanding Ethical, Legal, and Social Issues
Ethical, legal, and social issues loom large in newborn screening—including the lack of reliable evidence to inform policy and practice decisions; whether parental consent is necessary; and the cost, storage, and reuse of blood spots (Baily, 2023). Data are needed to demonstrate the magnitude of a range of benefits and harms to inform policy decisions, but weighing both to determine net benefit is not easily quantifiable (Goldenberg et al., 2016; President’s Council on Bioethics, 2008). For example, screening could identify late-onset or milder forms of a condition, potentially leading to “patients in waiting,” anxiety, and uncertainty for families (New York State Krabbe Disease Consortium, 2016; Timmermans and Buchbinder, 2010). Some treatment regimens can be quite lengthy and painful for patients and families (Ledford, 2024). Gene therapy is expensive and offered by a limited number of medical centers, and some families may not be able to access these treatments due to cost, distance, family commitments, or other barriers (Allen et al., 2023; Levins, 2024; Peterson, 2024; Vokinger et al., 2023). A treatment might prevent death, but the child may still have severe disability (Brick et al., 2020; Larcher et al., 2015; Weise et al., 2017). Long-term outcomes of treatments or harms are often unknown, at least initially (Duncan et al., 2024). Prematurely expanding screening could exacerbate health disparities for underserved groups (Sobotka and Ross, 2023). Complex research designs are needed to address these issues, and too frequently the most critical data are missing.
BOX 6-1
Areas of Research for Artificial Intelligence and Machine Learning in Newborn Screening
Artificial intelligence and machine learning (AI/ML) tools are being developed for a variety of applications in medicine and public health. AI/ML can be used to find patterns in large datasets that may not be detected through other computational methods or human expertise. Additionally, large language models (LLMs), a subset of AI, can process inputs and produce outputs in natural human language, facilitating non-expert interaction and streamlining communication in a range of contexts. Research is needed to better understand whether such AI capabilities could be applied to public health newborn screening in a manner that maximizes benefits while minimizing risks. Two potential applications are discussed briefly here.
Enhancing Screening Accuracy
Improving screening accuracy remains an important challenge for public health newborn screening. Emerging evidence indicates that supervised machine learning tools can be used to reduce false positives for metabolic disorders without changing a test’s sensitivity. However, training these tools requires large datasets, especially for detecting rare diseases, which may necessitate new infrastructure and data sharing among different research initiatives or potentially NBS programs. In addition, ensuring the effectiveness of these models would require continuous validation and monitoring.
Support Patient Communication
LLM-based tools have been developed and deployed to support patient communication and access to care. One tool, Med-PaLM 2, accurately answers medical questions, and clinicians rated its answers to be as safe as a physician’s answers. In another example, interacting with an AI chatbot for genetic counseling resulted in patient satisfaction and comprehension comparable to those for in-person services. Both examples highlight how LLMs could support NBS communication.
Although LLMs can reduce administrative burdens and help to compress information to make it more digestible, they can also produce wrong answers, perpetuate biases, and produce responses that are too general to be useful for specific patient situations. Given these strengths and weaknesses, along with important ethical considerations, LLMs are generally seen as tools to assist human experts but not replace them. Further research is needed to assess whether and how these tools can be effectively and ethically applied to newborn screening.
SOURCES: Al Hilli et al., 2023; Mak et al., 2023; Peng et al., 2020; Scharfe, 2024; Singhal et al., 2025; Thirunavukarasu et al., 2023.
Many ethical and social concerns about the practice of newborn screening are framed through normative arguments, when they could in fact be addressed empirically through research. Distinguishing the normative argument2 with empirical observations provides a more robust understanding of an issue and clarifies trade-offs to enable better-informed decision making. For example, some contend that requiring consent for newborn screening could negatively affect participation rates, particularly for underserved communities, and thus, newborn screening ought to remain an opt-out program. This concern can be addressed empirically to understand whether consent might alter participation rates, and if so, whether it could disproportionately affect certain populations. Engagement as well as survey research are essential to understand public and parental attitudes about these issues and more. Such information gaps signal a need for public health ethics research to gather evidence that informs ethical decision making in this space.
Similarly, legal epidemiology—the study of law as a factor in the cause, distribution, and prevention of disease and injury in a population—can offer valuable, empirical insights into how policies influence public health (Burris et al., 2016). For example, many people express concerns about variable outcomes between states and territories with different screening panels or different levels of funding (Susanna Haas Lyons Engagement Consulting, 2024). These “natural experiment” studies could address whether health outcomes vary between states with different screening panels, or whether funding levels influence the timeline to adoption of RUSP conditions. Legal epidemiological studies could also investigate the effects of religious or cultural exemption policies on participation rates and health outcomes in different jurisdictions. Such studies would require more robust and standardized data collection and sharing by NBS programs, as well as improved long-term follow-up infrastructure.
Investigating Public Health Practice, Feasibility, and Impact
Assessing the nationwide impact of public health newborn screening and its benefits is challenging due to limited coordinated data collection efforts (Watson et al., 2022). Directly linking public health newborn screening to long-term benefits or cost savings at the population level is particularly difficult, though some evidence is available for specific conditions (Grosse, 2015; Van Vliet and Grosse, 2021). Coordinated efforts to collect such data are needed to enable research that investigates how policies and practices affect the delivery, quality, cost, and outcomes of newborn screening as an essential public health service. Conducting
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2 Normative arguments are based on value judgments.
successful research in these areas requires multidisciplinary teams that include, but are not limited to, experts in communication, decision analysis, systems engineering, economics, and health services. Such information can inform the development of evidence-based practices and be used to ensure that newborn screening iteratively improves. Prior work includes effort toward (1) identifying how to efficiently and effectively communicate with parents about NBS results to ensure optimal screening outcomes; (2) understanding the costs and health outcomes associated with screening for a condition or adopting a technology can help decision makers make effective use of limited resources; and (3) identifying ways to streamline the delivery of services from specimen collection to results reporting (Cochran et al., 2018; Farrell et al., 2011; Grosse and Van Vliet, 2020; La Pean et al., 2013; Simon et al., 2020).
Long-term follow-up is a critical missing piece of the puzzle needed to understand the effect of newborn screening on population health outcomes (Kellar-Guenther et al., 2024; Kemper et al., 2008). Given that long-term follow-up is outside of the scope of many state and territorial-run programs (see Chapter 4), coordination among researchers, NBS programs, and clinical care may be needed to address this complicated, but important, endeavor. Long-term follow-up, its challenges, and potential paths forward are discussed later in this chapter.
See Box 6-2 for selected questions to address as part of NBS research.
THE INTERSECTION OF NBS RESEARCH AND RARE DISEASE RESEARCH
Population-based newborn screening provides an invaluable tool for understanding the genetic causes and full spectrum of symptomatology for many rare conditions. Without such an approach, only the most severe cases are identified (Figure 6-1). Screening allows for the identification of subclinical or mild forms of a condition, which is essential for understanding the range of potential outcomes, informing individual care decisions for identified patients, and advancing research on diagnosis and treatment.
NBS research and rare disease research can sometimes be conflated, but each area has unique, albeit complementary, scopes. Although NBS research can inform rare disease research, it is not limited to conditions that are rare. The scope of rare disease research extends beyond what can be learned through newborn screening (e.g., pathophysiology and therapeutic development). Rare disease research also addresses a much wider spectrum of diseases that may not be detectable at birth or have no immediate treatments available for infants.
Ultimately, NBS research and rare disease research can inform and complement each other with knowledge gained from one field driving
BOX 6-2
Selected Questions to Address as Part of NBS Research
The list of questions that could be considered when making decisions about NBS policy and practice is a long one. A list of selected questions to address as part of NBS research includes the following:
Defining Conditions to Guide Screening, Diagnosis, and Treatment
- What is the natural history of a condition(s) being considered for newborn screening, either currently or in the foreseeable future?
- What variations exist in the phenotypic expression of various conditions, and what are the resulting implications for screening or treatment decisions?
Developing Laboratory Testing and Applying Emerging Technologies
- What are the comparative advantages, costs, disadvantages between different screening methods, laboratory cutoff values, etc.?
- How well can screening and/or subsequent diagnostic confirmation strategies determine phenotypic subtypes so parents will have a better understanding of potential future health outcomes and clinicians will be able to make more informed decisions about who needs which treatment(s) and when?
(See Chapter 5 for questions related to applying genomic sequencing to public health newborn screening.)
Understanding on Ethical, Legal, and Social Issues
- What are the benefits and harms of screening?
- What is the public perception and acceptability of screening for conditions with a range of outcomes (e.g., a few children have substantial benefit, whereas others have modest, minimal, or no benefit)?
- How do parents and clinicians deal with uncertainty?
- Would a consented approach to newborn screening affect participation rates, and if so, would it do so differently across different populations?
- Would screening for an expanded set of conditions via informed consent affect opt-out newborn screening, and, if so, how?
- How do policies related to NBS practices affect health outcomes?
Investigating Public Health Practice, Feasibility, and Impact
- What are the long-term, longitudinal (5–10 years) outcomes of screening for children and families?
- What is the comparative efficacy of various surveillance strategies for conditions in which timing of treatment is unknown (or is not immediately needed until some other signs are observed)?
- What are the best strategies for helping parents coping with diagnoses and distress about future outcomes?
- How can the delivery of services within the NBS system be optimized for efficiency and quality?
- What outcomes do families experience after receiving NBS results, both short term and long term?
progress in the other. Rare disease research can advance efforts to develop therapies, expand precision medicine, provide global frameworks for classifying diseases and linking them to health information, among others. Each of these aims can support both NBS research and decision making about public health newborn screening, more broadly. Conversely, NBS research to understand the natural history of conditions can inform the development of therapeutics and NBS pilot studies can permit researchers to identify potential presymptomatic participants for clinical trials, accelerating treatment pipelines.
NBS and rare disease research efforts also have a history of working synergistically that could be further leveraged through increased coordination. For example, an infant identified as at risk for spinal muscular atrophy (SMA) through a pilot NBS study was subsequently enrolled in a presymptomatic clinical trial for a gene therapy for SMA. These coordinated efforts demonstrated the feasibility of population-wide screening and treatment effectiveness for SMA and ultimately informed its inclusion on the RUSP (Evidence-based Review Group, 2018; Kraszewski et al., 2018).
However, a distinction must be drawn between public health newborn screening and NBS or rare disease research. Routine public health newborn screening performed without explicit consent cannot be used to conduct research.
THE LANDSCAPE OF NBS RESEARCH
The current NBS research landscape generates valuable tools, technologies, discoveries, and insights for newborn screening. However, these discoveries frequently focus on a single disease, are funded and completed too late to inform programmatic and policy decision making, and are often not responsive to the immediate needs and priorities related to public health newborn screening. This reduces the effectiveness and timeliness of NBS research—especially given a funding environment in which newborn screening must compete for resources with research on more common pediatric conditions such as asthma and obesity. This section provides an overview of prior and ongoing research related to newborn screening and its effect on the field.
NBS Translational Research Network
Prior calls for increased NBS research infrastructure prompted the National Institutes of Health (NIH) to create the Newborn Screening Translational Research Network (NBSTRN). The goal of NBSTRN was to develop and share resources and infrastructure to support NBS researchers (Lloyd-Puryear et al., 2019). NBSTRN was active for 15 years
and received over $35 million in funding from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD, making it among the largest investments into NBS research by NIH).3
Major contributions by NBSTRN include data tools developed to support NBS research such as the Longitudinal Pediatric Data Resource (LPDR) and the Virtual Repository of Dried Blood Spots (VRDBS) (Chan et al., 2023; Lloyd-Puryear et al., 2019). The LPDR is a database for genomic and phenotypic information collected over the lifespan of newborns identified as at risk through screening to facilitate the understanding of genetic disease and assess the effect of early identification and treatment. Case-level, deidentified datasets from the LPDR are available for secondary research and data mining. As part of this effort, NBSTRN used a consensus-based process with clinical care experts to develop common data elements and then built those into the LPDR (Brower et al., 2021). Promoting the standardization of data elements through the LPDR is recognized as a key contribution of NBSTRN among those in the field (HRSA, 2018).
NBSTRN also created the VRDBS—a web-based tool that allows investigators to access a catalog of dried blood spots from NBS programs that may be available for use in research and NBS program development (Lloyd-Puryear et al., 2019). In addition to data tools, NBSTRN developed resources related to ethical, legal, and social issues (ELSI), including guidelines for parental permission for pilot testing NBS research and a survey to gather input on ELSI needs in NBS research (Botkin et al., 2014; Unnikumaran et al., 2024).
Although NBSTRN created several tools and shared resources, there was limited uptake by the research community and little evidence that these resources facilitated evidence generation to inform policy decisions. For example, the committee identified only two citations that used data from the LPDR to perform secondary research (Hartnett et al., 2022; Wilhelm et al., 2022). Similarly, one published study seemed to use the VRDBS to perform secondary research (on prenatal alcohol exposure) (Baldwin, 2015), and only a handful of investigators submitted protocols (Lloyd-Puryear et al., 2019). Both of these resources relied heavily on public health personnel to input data, and then, for the VRDBS, to facilitate use of the resource (Lloyd-Puryear et al., 2019), which ultimately put a strain on programs rather than adding resources to support their mission. Finally, NBSTRN was likely
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3 See https://www.usaspending.gov/award/CONT_AWD_HHSN275200800001C_7529_-NONE-_-NONE- (accessed January 17, 2025); https://www.usaspending.gov/award/CONT_AWD_75N94018C00005_7529_-NONE-_-NONE- (accessed January 17, 2025); https://www.usaspending.gov/award/CONT_AWD_HHSN275201300011C_7529_-NONE-_-NONE- (accessed January 17, 2025).
hampered from setting priorities and stimulating research because of funding constraints and limited authority to guide research.
NICHD recently terminated this initiative after performing a landscape analysis of investments in NBS research. NBSTRN-related responsibilities have been shifted to the National Center for Advancing Translational Sciences (NCATS) in the context of the Rare Disease Clinical Research Network (RDCRN).4 However, the recent request for applications for new RDCRN centers did not have a requirement for NBS-related research.5
NSIGHT and Other Large Programs
Recent advances in genome sequencing technology—including developments that have decreased cost—have attracted large-scale research investment to determine the usefulness and acceptability of genomic sequencing in newborns (Minear et al., 2022). The Newborn Sequencing in Genomic Medicine and Public Health (NSIGHT) program was a research initiative jointly funded by the National Human Genome Research Institute (NHGRI) and NICHD from 2013 to 2019, with an initial funding commitment totaling $25 million (NIH, 2022).6 Through NSIGHT, four centers investigated genomic sequencing in newborns within different contexts, including the clinical diagnosis of sick newborns in intensive care units and the screening of healthy newborns at birth. Each center used different approaches with minimal coordination and had a sequencing project, a clinical project, and an ethics project. Several major findings were published because of this investment (see Chapter 5), and many more questions were raised (Minear et al., 2022).
With the ending of NSIGHT’s funding, several large-scale research programs continue to focus on how genomic sequencing could be integrated into newborn screening and its potential ethical ramifications (see Chapter 5 for information about these ongoing projects). None of these programs rely exclusively on federal funding or a single source of support, seeking money from industry, foundations, and advocacy groups. However, a new initiative was recently announced at an NIH Council of Councils meeting: the Newborn Screening by Whole-Genome Sequencing initiative, which will be solely supported through Common Fund venture support. The initiative will disperse $5 million annually for 3 years with the goal of demonstrating the feasibility of a collaborative model for newborn screening by whole genome sequencing (Sheely, 2024).
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4 See https://grants.nih.gov/grants/guide/notice-files/NOT-HD-23-012.html (accessed January 16, 2025).
5 See https://grants.nih.gov/grants/guide/pa-files/PAR-24-206.html (accessed January 16, 2025).
6 See https://grants.nih.gov/grants/guide/rfa-files/RFA-HD-13-010.html for initial funding details (accessed January 16, 2025).
Grants, Small Business Agreements, and Contracts Awarded by NIH
NICHD has a suite of grants, small business awards, and contracts specifically addressing NBS-related research. There are currently four program announcements related to NBS research;7 however, these opportunities do not have promised funds nor are they reviewed through a dedicated study section. Few grants have been funded through these program announcements in recent years (Minear et al., 2022; NICHD, 2024). For investigator-initiated grants, the research focus is typically on a single condition and not necessarily responsive to priorities of public health newborn screening. Small business awards or small business technology transfers awarded by NIH are issued to commercial entities for projects that have the ultimate goal of commercialization; for example, such an award helped fund the development of a microfluidics platform for a panel of four lysosomal storage disorders that was eventually used by NBS programs (Millington et al., 2018). NICHD also contracts task orders to prequalified entities to pilot test conditions considered for inclusion in public health NBS panels. However, these conditions do not necessarily meet the priorities of the system; for example, task orders totaling $750,000 were issued in 2017 for a spinal muscular atrophy pilot study8 when a large pilot study had just been completed, and the condition was already under consideration for the RUSP (Cure SMA, 2017; Kraszewski et al., 2018; Minear et al., 2022).
Other Federal Research Initiatives Related to Newborn Screening
The Centers for Disease Control and Prevention (CDC), the Health Resources and Services Administration (HRSA), and the Agency for Healthcare Research and Quality (AHRQ) also support research efforts related to newborn screening (see Chapter 2). Briefly, CDC contributes to long-term follow-up efforts, screening tool validation, and population-wide pilot studies (Brosco, 2024). Although HRSA does not fund research grants per se, some of its grants support initiatives that collect data to inform the provision of this public health service, such as long-term follow-up.9 Since 2018, AHRQ has not awarded any grants that contain the term “newborn screening” in the abstract;10 however, previously funded studies have investigated cost-effectiveness and health outcomes related to newborn screening (Richardson et al., 2021). More broadly, AHRQ
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7 See https://grants.nih.gov/grants/guide/notice-files/NOT-HD-22-042.html (accessed January 16, 2025).
8 See https://www.highergov.com/vehicle/newborn-screening-pilot-studies-idiq-2276 for funding amounts (accessed January 27, 2025).
9 See https://www.hrsa.gov/grants/find-funding/HRSA-24-052 (accessed January 27, 2025).
10 See AHRQ grants by state from 2018 to the present here: https://www.ahrq.gov/funding/grant-mgmt/grants-by-state.html (accessed January 27, 2025).
supports research that may be relevant to the broader NBS ecosystem such as health IT infrastructure research and health services research related to children with medical complexity, rare diseases, care coordination, continuity of care, and developmental screening.11
CHALLENGES IN THE EVIDENCE-GENERATION PROCESS
Evidence is essential to inform federal and state or territorial decision makers and advisory bodies as they develop policy and guidance on newborn screening and its implementation. Yet the generation, interpretation, and compilation of the necessary evidence can involve inherent challenges that burden partners across the NBS ecosystem, complicate decision making, and contribute to disparities.
Funding Landscape
It is difficult to capture a complete picture of the NIH’s NBS research portfolio as funding is distributed across several institutes and centers, including NCATS, NICHD, NHGRI, the National Institute of Diabetes and Digestive and Kidney Diseases, the National Institute of Neurological Disorders and Stroke, the National Heart, Lung, and Blood Institute, and the National Institute of General Medical Sciences (Minear et al., 2022). NBS-related research is not indexed in the Research, Condition, and Disease Categorization (RCDC) system (NIH, 2024); this system is instrumental for public reporting on the totality of funding for a particular category of research and allows for accurate funding analyses and increased transparency. The RCDC system also provides opportunities for more strategic alignment and coordination of research across institutes and centers. In addition to limited coordination across NIH institutes and centers, there is limited input from the broader NBS ecosystem, including state and federal health partners, on how to best prioritize research questions and most effectively deploy available funds.
Beyond government support, funding for research related to newborn screening is heavily reliant on advocacy and, therefore, susceptible to both perpetuating and exacerbating disparities in research investment (Halley et al., 2022). Patient advocacy organizations work tirelessly to raise funds, build awareness, and promote greater research investment for their condition (Bailey, 2022). On an individual level, advocacy efforts are often deeply personal and rooted in a search for answers to save the
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11 See https://www.ahrq.gov/ncepcr/research/health-it/index.html (accessed January 10, 2025).
lives of themselves, loved ones, and/or others affected by a particular condition (Halley, 2021). However, on a systems level, the prominent role of advocacy makes rare disease research investment vulnerable to the identifiable victim effect, or the tendency to offer help to the loudest and most recognizable voices, and not necessarily those with the greatest need (Largent and Pearson, 2012).
Conditions that affect families with the social and financial capital to effectively advocate for research tend to attract the most attention and resources, whereas conditions that affect populations that are smaller, more diffuse, or historically marginalized are more likely to be left behind (Largent and Pearson, 2012). This process places undue burden on all patient communities, and particularly those that may have less resources. Directing resources based on an advocacy model does not support systematic or strategic investment to inform decision making about public health newborn screening.
Industry also plays a role in driving research. The global NBS market was valued at over $3 billion in 2024 and is expected to reach nearly $6 billion by 2032 (Towards Healthcare, 2023). This growth potential has attracted industry investment into technological advancements related to screening, including genome sequencing, in addition to developing new diagnostic tools as well as drugs and other treatments for congenital disorders. Beyond their own investments, industry also supports research initiatives, which tend to be focused on their priorities and not those of the NBS system (Bailey, 2022).
Together, this funding landscape does not promote strategic and coordinated investments to support timely, evidence-based decision making related to public health newborn screening based on the perspectives of the many partners in the NBS ecosystem. A coordinated, planned, and nimble funding strategy for NBS research is critical to ensure that research dollars generate insights that are informative, useful, and timely.
Burden on Public Health Programs
“[Pilot studies] illustrate the importance of collaborations between public health systems and external partners, and the unique and specialized contributions of each.” – NBS public health professional
The highest priority of NBS programs must be to screen infants born in their respective jurisdictions in a timely manner and connect infants identified as at risk with confirmatory diagnosis and clinical care. However, there has been an increasing reliance on programs to provide resources and generate the evidence base for inclusion of new conditions, incorporation of novel technologies, and more. Some of this is born out of necessity, as NBS programs are the only source for some data and
the specimens needed for relevant research. Researchers rely on public health programs to access deidentified blood spots to develop screening assays, determine condition prevalence, and more, including prospective population-wide pilot studies.12
As previously described, newborn screening faces a “chicken or the egg” dilemma: to be included in public health newborn screening, a condition must have a prospective population-wide pilot study, but population-wide pilot studies are best conducted by or in partnership with public health programs to yield a sufficiently large, representative sample (HRSA, 2016). For pilot studies, public health programs may be responsible for scaling a validated screening method and coordinating follow-up for any identified infants; these tasks may raise both foreseeable and unanticipated issues but generally fall within the scope of work performed by programs. However, pilot studies also require educating and recruiting participants, which is not typical for public health personnel. External collaborators are vital to conduct these activities (Kay, 2024).
Past research infrastructure has drawn on NBS program staff and resources rather than added to their arsenal. For example, NBSTRN created a VRDBS that included dried blood spots from several state programs to serve as a resource for the research community. However, NBS program personnel rather than NBSTRN staff were ultimately responsible for providing researchers with information about the required processes for material transfer agreements, assisting with specific study-related questions, and other tasks that might have been addressed by individuals outside of NBS programs (Lloyd-Puryear et al., 2019). With existing constraints on staff and resources, programs cannot shoulder demands to generate evidence and provide resources without increased funding, personnel, partnerships, and infrastructure. The legal landscape and rising public concerns around the storage and secondary reuse of dried blood spots for research continue to be difficult for both public health personnel and researchers to navigate (Lloyd-Puryear et al., 2019; Therrell et al., 2011).
Long-Term Follow-Up
“We need a national system to track patients and follow-up.” – Medical geneticist
NBS longitudinal follow-up refers to the tracking and monitoring of newborns over time. Follow-up from screening to communication of results or confirmatory testing is referred to as short-term follow-up; this responsibility sits within the purview of state- and territorial-run NBS
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12 In some jurisdictions, dried blood spots collected through newborn screening are deidentified and available for secondary research.
programs (see Chapter 4). Long-term follow-up in the context of newborn screening generally refers to the surveillance after confirmatory testing is completed. Essentially, it begins with a baby’s transition into clinical care and can continue for years to decades (Hinton et al., 2014; Kemper et al., 2008). Despite persistent calls to collect long-term follow-up information, efforts to gather such data have been limited and sporadic at best (Hoff and Hoyt, 2006). The ownership of the responsibility to collect and analyze long-term follow-up data has previously been ill defined, and this diffused accountability has limited efforts (Kellar-Guenther et al., 2024). The types of data pertinent to NBS long-term follow-up are largely beyond the purview of NBS programs or other state- or territorial-run public health programs, falling more within clinical data and large-scale public health surveillance (see Chapter 4), which given the nature of the U.S. health system provides a fragmented and disjointed dataset. However, long-term follow-up provides critical evidence on the health effects of newborn screening and the performance of NBS programs and the system at large.
To support long-term follow-up goals, an ideal strategy would include effective mechanisms for collecting, storing, and sharing data both across public health and clinical care as well as across state lines. Attributes of an ideal long-term follow-up scenario for newborn screening could include
- Harmonization and interoperability of electronic datasets: Electronic submission of data is critical to limit data silos. Robust systems for data governance, privacy, and security to ensure appropriate protections when sharing and accessing data across systems would be needed.
- Standardized NBS templates and data elements: National standards for patient, laboratory, and genomic data would enable consistency in data collection, which is particularly important when dealing with small sample sizes.
- Data support for care teams: Bidirectional links are needed between existing data systems to provide care teams with all the data they need, provide a record of family communication, and support shared case management among different providers and organizations, including NBS programs, pediatric care, primary care providers, and rare disease specialists.
- Tools for families to engage meaningfully: Patients need to understand the ways their data might be used, provide informed consent as appropriate, and access their results and records in line with the 21st Century Cures Act.13
- Strategies to ensure data quality, including mechanisms to address gaps or systemic problems.
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13 21st Century Cures Act, P.L. 114-255.
There are significant barriers to achieving such a scenario. Different NBS programs and clinical care systems employ an incredibly broad array of approaches to collect and handle NBS data, from electronic health records and portals to handwritten notes and faxes. Datasets are often siloed or inaccessible, and even when they can be shared or combined, inconsistencies in nomenclature and data formats limit interoperability and the ability to extract insights. Finally, the infrastructure required for data collection, storage, use, and sharing is costly and requires ongoing maintenance, which can pose a barrier for sustaining systems in the long run. Despite these challenges, there are opportunities to make progress toward a more cohesive system for handling and sharing long-term follow-up data related to newborn screening.
An important first step toward developing a robust national system is aligning partners to define the goals of long-term follow-up efforts. Goals could include identifying particular outcomes to track, such as survival, or particular problems to solve, such as disparities in connection to a specialist. Kellar-Guenther et al. (2024) outline three core long-term follow-up outcomes for a year after birth:
- Is the child still alive?
- Did the child have contact with a specialist?
- Did the child receive appropriate care specific to their diagnosis within 1 year?
Kellar-Guenther et al. also state that a set of minimal data elements is critical for tracking those outcomes as a foundation for understanding the effects of newborn screening within and across programs (Kellar-Guenther et al., 2024). Additional lessons on identifying key metrics and practical data-collection strategies that enable information exchange between private and public health sectors can be gleaned from previous HRSA-supported research initiatives on quality measures for long-term follow-up (HRSA, 2018; Lloyd-Puryear and Brower, 2010). Once a minimal dataset is consistently collected, efforts could be expanded to include more outcome measures or tackle additional problems.
Another critical step is to identify the key players and delineate who has the responsibility and authority to collect, store, and share what data and with whom. Given that this responsibility is outside of the scope for most state- and territorial-run NBS programs (see Chapter 4), it is important to take an expansive view of the key players and data sources involved.
An approach is needed to navigate collecting data across the decentralized NBS programs and health care systems. One approach could be to focus on improving linkages and data sharing among existing disparate systems with the aim of greater interoperability and harmonization.
Another option is to establish a more central screening registry. In either case, starting small and building upon existing resources—including using existing partnerships within and among organizations such as HRSA, CDC, the Association of Public Health Laboratories, and the Council of State and Territorial Epidemiologists, as well as existing registries14—is likely to make for a more feasible and sustainable path forward.
Many well-designed data systems exist that could provide a basis for establishing standardized definitions, templates, and data models to support consistency and interoperability among datasets relevant to longitudinal follow-up for newborn screening. The USCDI+ initiative, which supports the development of domain-specific data element lists to advance the use of interoperable data elements among federal and industry partners, could provide a framework for the NBS community to coalesce around shared data elements and harmonize data standards and taxonomies.15 In addition, Fast Healthcare Interoperability Resources, a standard for the exchange of health care data, could support linkages among disparate systems, potentially with an implementation guide specifically for newborn screening.16 Health information exchanges (HIEs) may also serve as a repository for long-term follow-up data within each state or territory. Some states have very robust HIEs; for example, the Indiana Health Information Exchange connects data from hospitals, laboratories, state-run public health programs, and other health care entities.17 Ongoing work by the Trusted Exchange Framework and Common Agreements to support standardizing formats for HIE interoperability nationally could also enable more efficient exchange of information across HIEs.18 Systems such as electronic case reporting, which automates the exchange of data between electronic health records and public health agencies, provide another useful model that could be built upon for sharing data on NBS follow-up.19
Electronic health record (EHR) vendors could collaborate with researchers and others to set up disease-specific templates and collect standardized data elements for long-term follow-up. If Epic, Oracle Cerner, and Meditech participated, it is estimated that 75 percent of hospitals in the United States would be covered (Bruce, 2023). The template could integrate quality of life or other patient-reported metrics
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14 Some conditions screened through newborn screening have robust registries coordinated by foundations. For example, 36,518 individuals participated in the Cystic Fibrosis Foundation Patient Registry in 2020 (Cromwell et al., 2023).
15 See https://www.healthit.gov/topic/interoperability/uscdi-plus (accessed March 6, 2025).
16 See https://hl7.org/fhir/ (accessed March 6, 2025).
17 See https://www.ihie.org/ (accessed March 6, 2025).
18 See https://www.healthit.gov/topic/interoperability/policy/trusted-exchange-framework-and-common-agreement-tefca (accessed March 6, 2025).
19 See https://www.cdc.gov/ecr/php/about/index.html (accessed March 6, 2025).
(Azad et al., 2016). Such IT infrastructure would avoid attrition by individuals who move across states lines, so long as they continued to be seen at a hospital using the same EHR vendor. A dashboard component embedded in the EHR that permitted easy access to—and visualization of—patient data might also encourage patient participation. This option would align with the 21st Century Cures Act, which includes measures to make research data more accessible to participants and to improve transparency.20 Combining this approach with electronic case-reporting tools could enable interaction between many components across the NBS ecosystem.
EHR dashboards have been employed by the Connecticut Department of Health in partnership with the Connecticut NBS Network to establish registries for long-term follow-up of patients identified through newborn screening. This effort may serve as a model for applying population health tools to track care delivery and quickly fill identified care gaps; preliminary results indicate this approach can lead to improvements in the percentage of visits up-to-date and condition-specific performance metrics for patients identified through newborn screening. Limitations of this approach include the need for an analyst with specialized training in EHR systems to implement and optimize the dashboard, interpret data, and identify areas for continuous improvement in clinical care. Comprehensive training for the clinical care teams is also necessary to ensure successful implementation of the dashboard and meaningful improvements in care management (Raboin et al., 2024).
Gathering information at a national level will ultimately require national coordination and the investment into a national data infrastructure. The current landscape of long-term follow-up is fractured and ad hoc: some NBS programs have begun engaging in long-term follow-up, particularly those with support from HRSA Propel and Co-Propel grants, and others have also made initial investments in this space (HRSA, 2024a,b; Kellar-Guenther et al., 2024; Raboin et al., 2024). The long-term follow-up challenge can be best addressed by thinking beyond NBS programs to include other partners in the NBS ecosystem and taking a national view of data collection and infrastructure.
Challenges Related to Rare Disease
Another tension in the evidence-generation process for newborn screening reflects inherent challenges with studying rare diseases more broadly. The rarity of these conditions makes it difficult to generate the data needed, particularly for population-level insights (Belter et al.,
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20 21st Century Cures Act, P.L. 114-255.
2024; Venugopal et al., 2024). Before population-based pilot studies are conducted, most of the data available on these conditions reflect individuals who are symptomatic or clinically affected, potentially missing those who have not developed symptoms or received a diagnosis (Lloyd-Puryear et al., 2019). It often takes large screening studies or population-wide screening to accurately estimate the prevalence of a disease in a population, but without some understanding of the prevalence it can be difficult to generate the funding and research interest required to conduct these studies (Belter et al., 2024; Venugopal et al., 2024). Since these conditions are rare, coordination across multiple sites and complex data sharing and aggregation efforts may be necessary to achieve sufficient statistical power for studies, including those to estimate prevalence in the population and within different subgroups (Belter et al., 2024; Venugopal et al., 2024).
ADDRESSING UNMET NEEDS IN NBS RESEARCH
Research is essential to provide the information required to make informed decisions about NBS policy and practice. No formal infrastructure or program currently exists to gather this information in a coordinated or expeditious fashion. There is a need for strategic, systematic, nimble, and sufficiently funded research to provide the evidence necessary for newborn screening to adjust to a rapidly changing landscape of new technologies and new treatments. Several mechanisms could be considered to advance NBS research, each of which has its own set of trade-offs.
Options to Address Research Needs Related to Newborn Screening
Substantially Increase Funding for Investigator-Initiated Research
Most NIH funding is currently dispersed to NBS-related research through investigator-initiated grants. However, investigators historically have not been incentivized to include NBS-related questions in their research as there is not a set-aside study section for grant review. Few grants have been funded through previous NBS program announcements (Minear et al., 2022; NICHD, 2024).
Increasing NIH funding for investigator-initiated grants would prompt researchers to focus on newborn screening. Grants awarded with these funds would need to be reviewed by a separate study section comprising reviewers familiar with newborn screening to allow for an accurate assessment of the overall effect and significance of the proposed research. There would almost certainly be a substantial increase in strong
research proposals given the increased amount of funding available and the opportunity to be reviewed by those who understand the importance of certain kinds of studies (e.g., natural history) to the NBS evidence base.
Establish NBS Research Centers
Research centers, or centers of excellence, are a common model employed by NIH to support and promote interdisciplinary research with a unifying focus. Centers operate independently and may collaborate but typically do not. Centers often have larger budgets than individual research projects and require increased overall investment by NIH. For example, grants to fund the recently established Autism Centers of Excellence, composed of nine centers, total an estimated $100 million, which will be distributed over a period of 5 years—with each center ultimately receiving just over $2 million per year (NICHD, 2022). Usually, centers consist of several projects supported by specialized cores that provide services to promote research. Different centers have different cores depending on the strengths of the institution (e.g., biostatistics, genomics, pathology).
This model has been employed previously to study the implications of genome sequencing with both healthy and symptomatic newborns through the NSIGHT program. Funded under a cooperative agreement, there was some effort to organize meetings involving all four centers, but, ultimately, there was little research collaboration. By working independently, centers were able to develop and investigate different approaches, and ultimately their collective research led to major findings that pushed the field forward (see Chapter 5).
Each prospective academic center would apply in partnership with an NBS public health program. Partnerships between public health NBS programs and academic institutions have already proven highly successful at expeditiously generating evidence to inform policy decisions. Several features would be needed to establish a rigorous research enterprise that does not strain the partner public health program—adding rather than detracting resources to support its mission. Appropriate staffing and training by the academic center would be necessary to avoid drawing on existing public health personnel who already have limited bandwidth. Certain agreements (e.g., business associate agreement, memorandum of understanding) would be needed to enable the recruitment of infants within the jurisdiction, to allow data sharing of protected health information with consent, and to gain access to deidentified dried blood spots as appropriate,21 among other logistical hurdles (Bailey et al., 2019).
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21 See Chapter 7 for an exploration of the issues surrounding deidentified dried blood spots in secondary research.
Preestablishing partnerships and data-sharing agreements would reduce administrative burden of both the researchers and public health professionals, and thus, ought to be required criteria for centers.
Establish a Coordinated Network of NBS Research Centers
Research networks are a model used by NIH to create a more efficient and responsive research ecosystem that can address complex research questions through increased coordination (e.g., neonatal research network) (Watterberg et al., 2022). A network of research centers could be established with each center expected to work in a coordinated and nimble fashion to address timely issues related to newborn screening. Centers would develop their own research questions and would also work together to generate evidence to address high-priority issues in the field. Centers in the network would work in partnership with NBS public health programs with appropriate safeguards to protect strained public health resources and agreements in place to reduce administrative burden, as described for the research center model. A data-coordinating center and a decision-making body (involving all the centers) would provide the central glue to facilitate coordinated and strategic research to inform policy in a timely manner.
Investigating conditions considered for screening, which tend to be rare, often requires coordination across multiple sites with complicated data sharing and aggregation efforts to achieve sufficient statistical power. Further, generating data for population-level insights to inform decisions about newborn screening also likely requires large-scale, multisite studies. A research network could facilitate such coordinated research, and a data coordination center (DCC) would be instrumental to accomplish this goal. Across the network, the DCC would ensure data quality and consistency, provide statistical support for study design, collect and manage data, analyze data, and manage centralized databases and data sharing, among other tasks. Ultimately, the DCC would ensure consistency, efficiency, and scientific rigor across participating centers and would be necessary to address the key challenges in NBS research (see Box 6-3).
The network would be guided by a steering committee to identify high-priority questions for the centers to align on gathering evidence. Reflecting the systems-level research needs of newborn screening, the committee would involve members representing different sectors, including representatives from each center, public health, the medical community, and researchers outside the centers. The steering committee would draw on federal perspectives to identify high-priority research questions that must be addressed quickly. The research network would also involve patient advocacy groups using the Coalition of Patient Advocacy Groups
BOX 6-3
Examples of NBS-Related Studies Enabled by a Coordinated Research Network
Natural history studies—Conducting natural history studies across multiple sites would ensure access to a larger pool of potential participants, enable recruitment of enough patients for statistical power, and capture a more representative patient population.
Comparison studies—Coordination across multiple sites would allow for studies comparing the outcomes of different informed consent approaches for expanded screening, or the sensitivity and specificity of different screening approaches, among other comparisons.
Expanded DNA sequencing studies—Studies that incorporate DNA-based screening across multiple sites would enable continued inclusion of representative ancestral populations in genomic databases and a fuller understanding of the implications of applying this technology to screen healthy newborns.
(PAGs) model, or similar, employed by the Rare Disease Clinical Research Network (Merkel et al., 2016). PAGs would advise researchers and facilitate bilateral communication about perspectives, needs, and interests of patients with rare disease.
Trade-Offs
Increased investment into investigator-initiated grants—with a set-aside study section for review—would provide broad access to newly infused resources into the NBS research space. This mechanism would also enable bottom-up communication of avenues for inquiry. However, investigator-initiated grants would not systematize coordination across multiple sites, which can be critical to achieve statistical power, nor would this mechanism enable investigators to quickly address questions informed by national research priorities. Therefore, greatly expanding investigator-initiated projects alone would not solve the problem of a coordinated system and would be quite slow in producing evidence to address problems for which a solution is urgently needed.
Establishing NBS research centers could stimulate research on a broad range of topics related to newborn screening and involve teams of investigators. However, without some sort of coordinating mechanism and mandate, centers tend to work independently and not necessarily in accordance with public need. Therefore, the center model would likely limit coordination and strategy to address questions in a timely manner based on national priorities.
Research networks are designed to enable investigators to coordinate and answer questions quickly with increased access to resources, but generally this occurs at the expense of a fairer allocation of available resources. This mechanism can also create an information bubble in which the same set of individuals sets priorities and allocates resources according to what they consider important without knowledge of, or maybe consideration for, the interests of the broader research community or those with lived experience.
However, there are several strategies that may prove useful to combat these potential pitfalls. Research network resources could be made available to outside investigators (this is already common, though such use is typically more expensive). A hub-and-spoke approach could be used where the research center serves as the hub that provides resources or technological support through its specialized cores to investigators at spoke institutions. Creating a multistakeholder steering committee, or having routinized avenues to gather multistakeholder input, would help avoid creating an echo chamber concerning research priorities. It would be particularly important to ensure that interests of researchers that are not part of the network are represented on the committee.
CONCLUSIONS
Conclusion 6-1: Research is critical to inform evidence-based decisions about newborn screening policies and practice. There are gaps in these essential areas: defining conditions to guide screening, diagnosis, and treatment; applying laboratory testing and emerging technologies; understanding ethical, legal, and social issues; and investigating public health practice, feasibility, and impact.
Conclusion 6-2: Linking public health newborn screening to long-term health outcomes is difficult with existing data. Coordinated efforts to collect long-term follow-up data are needed. Such data would better support research on the effect of newborn screening on population health outcomes and guide policies and practices for public health newborn screening.
Conclusion 6-3: The full breadth of investment in newborn screening research by the federal government, advocacy, and industry is difficult to assess. Indexing newborn screening in the Research, Condition, and Disease Categorization system would help clarify at least the National Institutes of Health’s portfolio of investments in newborn screening.
Conclusion 6-4: Newborn screening (NBS) research studies can strain public health resources. Gaining a population-level understanding of the rare congenital conditions included or considered for newborn screening often requires researchers to draw on resources embedded in NBS programs, including accessing dried blood spots or conducting population-wide pilot studies on the feasibility
and effectiveness of screening for the condition through newborn screening. However, sharing these resources, or embedding research within the public health sphere, burdens public health programs. Mechanisms are needed to ensure that research infrastructure does not detract from public health bandwidth.
Conclusion 6-5: More robust, coordinated newborn screening (NBS) research infrastructure would enable strategic evidence generation that is responsive to high-priority questions. Existing mechanisms to perform research and gather data to support NBS are scattered, uncoordinated, and nonstrategic. The current landscape is overly reliant on investigator-initiated research and research driven by advocacy and industry, which do not necessarily reflect systems-level needs or priorities. Further, overreliance on advocacy places undue burden on patient communities, particularly those that are ultrarare or underresourced, to drive research. There is a need to strategically prioritize questions with input from partners in the NBS ecosystem.
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