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. 2026 Aug 19;9(8):e2629351. doi: 10.1001/jamanetworkopen.2026.29351

Implementation Readiness for National Cancer Survivorship Care Standards

Christiane J El Khoury 1, Meera Gupta 2, Maryem Shirzadi 3, Heidi Dowst 4, Martha Mims 3, Maysa Abu-Khalaf 1,5, Hoda Badr 1,5,✉
PMCID: PMC13491111  PMID: 42616501

This Delphi survey study investigates opinions of experts in cancer survivorship care delivery on the readiness of health systems to implement the new National Standards for Cancer Survivorship Care and perceived barriers to implementation.

Key Points

Question

How ready are comprehensive cancer centers to implement the National Standards for Cancer Survivorship Care across key implementation domains?

Findings

In this real-time Delphi survey study of 25 multidisciplinary cancer survivorship care delivery experts, cancer survivorship standards were consistently rated as important and high impact, but readiness gaps were identified in formal policies, implementation consistency, and health system evaluation mechanisms.

Meaning

The findings suggest implementing survivorship standards may require defined clinical workflows, structured documentation, referral tracking, and health system metrics to support consistent delivery and evaluation.

Abstract

Importance

Cancer survivorship care is a growing public health priority, yet delivery remains variable across health systems. The National Standards for Cancer Survivorship Care provide a framework for high-quality care, but little empirical evidence exists regarding health system readiness to implement these standards in routine practice.

Objective

To assess implementation readiness for the National Standards for Cancer Survivorship Care and identify perceived barriers to implementation.

Design, Setting, and Participants

This real-time Delphi survey study was conducted from January to March 2025 at a National Cancer Institute–designated comprehensive cancer center. Participants were multidisciplinary experts involved in cancer survivorship care delivery, care coordination, and program implementation.

Main Outcomes and Measures

For each of the 10 survivorship standards, expert agreement was assessed across 6 implementation domains: importance, anticipated impact, feasibility, consistency of implementation and documentation, existence of formal organizational policies, and presence of health system evaluation mechanisms. Agreement was considered present when at least 50% of respondents selected a single response category.

Results

Of 30 experts recruited, 25 participated (19 [76%] female), for a response rate of 83%. Among the 10 standards, agreement was consistently achieved for importance (9 standards [90%]) and anticipated impact (all 10 standards). In contrast, agreement regarding the existence of formal organizational policies and health system evaluation mechanisms was limited, and respondents frequently indicated absence or uncertainty. Agreement on implementation consistency was also limited, with several standards reaching agreement that implementation was inconsistent across practitioners and settings. Standards requiring coordination across clinicians, care settings, and supportive services were generally perceived as less ready for implementation than those supported by more established workflows. Qualitative findings identified cross-cutting barriers including time constraints, workforce limitations, lack of standardized workflows, and electronic health record limitations.

Conclusions and Relevance

Experts endorsed the cancer survivorship standards as important and potentially high impact but identified substantial gaps in the organizational infrastructure needed for consistent implementation. These findings suggest that improving survivorship care will require investments in workflows, accountability structures, and evaluation systems that support routine delivery and measurement of survivorship care.

Introduction

Cancer survivorship is a major and growing public health priority in the US.1,2 As of January 1, 2022, an estimated 18.1 million individuals in the US were living with a history of cancer, with this number projected to increase to 21.6 million by 2030 and 26 million by 2040.3,4,5,6 Despite longstanding recommendations from the Institute of Medicine,1 the American Society of Clinical Oncology,7 and the National Comprehensive Cancer Network,8 survivorship care delivery remains fragmented, with substantial variation in care coordination, symptom assessment, and access to supportive services.2,7,8,9

In 2024, the National Cancer Institute, in collaboration with other agencies within the US Department of Health and Human Services, announced the National Standards for Cancer Survivorship Care.4,10 Collectively, the standards provide a national framework for assessing survivorship care quality and guide the development of survivorship programs.4,11

Although the National Standards for Cancer Survivorship Care define what survivorship care should include, less is known about how health systems can operationalize these standards. Implementation requires workflows, documentation processes, and evaluation mechanisms; lack of operational specificity may limit consistent uptake and impact.12,13 Comprehensive survivorship care also requires coordination across oncology, primary care, and supportive services that varies substantially across settings.14 As health systems begin adopting these standards, early assessments of implementation readiness may help identify operational barriers and infrastructure needs. Because many cancer programs operate within Commission on Cancer accreditation standards, which include expectations for survivorship programming and care planning, these early implementation challenges may offer useful insights for other health systems translating national standards into routine workflows.7

Expert consensus methods are well suited to this type of early operational assessment, particularly when evidence regarding implementation is still emerging and standardized performance metrics do not yet exist.15,16 The Delphi method has been widely used in health services research to assess consensus on complex, system-level constructs.17,18,19 To date, little empirical evidence exists regarding health systems’ readiness to implement the National Standards for Cancer Survivorship Care or the organizational infrastructure needed to support their implementation. In this study, we conducted a real-time Delphi assessment to evaluate implementation readiness for the National Standards for Cancer Survivorship Care.11 We assessed patterns of expert agreement across key implementation domains and the presence of organizational policies and health system evaluation. We also elicited perceived barriers to implementation. By identifying areas of convergence and divergence in expert perspectives, this study aimed to provide an early assessment of implementation readiness for the newly released National Standards for Cancer Survivorship Care and to identify areas where perceived importance diverges from the organizational infrastructure needed for consistent implementation.

Methods

Study Design

We conducted this real-time Delphi survey study15,16 from January to March 2025 to assess implementation readiness for the National Standards for Cancer Survivorship Care within a National Cancer Institute–designated comprehensive cancer center. This study was conducted as part of an administrative supplement to the Oncology–Primary Care Partnership to Improve Survivorship Care (OPTIMISE) R01 and was conducted independently of the parent trial’s intervention and outcomes.20 Participants were multidisciplinary experts involved in survivorship care delivery, care coordination, and program implementation. The study was approved by the institutional review board of Baylor College of Medicine, and all participants provided electronic informed consent. This report follows applicable elements of the American Association for Public Opinion Research (AAPOR) reporting guideline for survey studies, including sampling, recruitment, administration mode, eligibility, analytic denominators, and item-level nonresponse.21

A real-time Delphi approach was selected to characterize convergence and divergence in expert opinion. Unlike traditional Delphi methods that require multiple sequential rounds, real-time Delphi provides immediate, aggregated feedback after each response and allows participants to revise responses within a single survey administration. A single administration was used because the purpose of the study was to assess shared perceptions of implementation readiness rather than to iteratively refine estimates across multiple rounds.15,16

Expert Panel Recruitment

Panelists were recruited using purposive sampling22,23 and they were all institutional stakeholders with direct experience in survivorship care delivery, coordination, informatics support, or survivorship-focused research. Eligible participants included oncology and primary care clinicians, survivorship program staff, nurse navigators, and research personnel involved in posttreatment follow-up, management of late and long-term effects, supportive care referrals, care coordination, or evaluation of survivorship workflows within the health system. Invitations were sent by email by the study research coordinator (M.S.). Participation was voluntary, and no compensation was given. Recruitment ensured representation across multiple disciplines and professional roles involved in survivorship care. Race, included to describe the demographic characteristics and diversity of the expert panel, was self-reported by participants through the survey instrument; categories were based on survey responses and included Asian, Black, White, and other (participants who selected Middle Eastern or North African as their race).

Survey Development

The Delphi instrument was developed by the study team based on the published National Standards for Cancer Survivorship Care and relevant literature.4,10 The survey evaluated the 10 survivorship care process standards contained within the National Standards framework. To assess implementation readiness, each standard was evaluated across domains reflecting the broader policy, process, and evaluation components of the National Standards framework. The survey addressed the 10 survivorship standards, including access to survivorship programs, assessment and management of physical effects, access to specialty care for late effects, assessment and treatment of psychological effects, assessment of practical and social impacts and provision of resources, assessment of recurrence or new cancer risk and referral for surveillance, assessment of lifestyle behaviors and provision of strategies or referrals, access to supportive health services, assessment and management of financial hardship or toxicity, and survivor engagement in care planning.11

For each standard, survey items assessed 6 implementation domains developed by the study team to operationalize implementation readiness for the survivorship process standards. Domain selection was informed by the structure of the National Standards for Cancer Survivorship Care, which includes policy, process, and evaluation components, as well as by implementation science constructs relevant to organizational readiness, including perceived importance, feasibility, implementation consistency, and evaluation capacity. For each standard, survey items assessed 6 implementation domains: (1) policy existence, defined as whether formal institutional policies or processes were perceived to be in place; (2) importance, defined as the perceived importance of formal policies and processes; (3) consistency, defined as whether implementation and documentation were perceived as consistent across practitioners and care settings; (4) feasibility, defined as the perceived ability to implement the standard with current resources; (5) health system evaluation, defined as the presence of mechanisms, metrics, or benchmarks to evaluate implementation; and (6) impact, defined as the anticipated effect of implementing the standard on survivorship care delivery. Importance, consistency, feasibility, and impact were measured using 5-point Likert-type scales ranging from “strongly disagree” to “strongly agree,” while policy existence and health system evaluation were assessed using categorical response options: “yes,” “no,” or “unsure.” Each standard also included an open-ended question eliciting perceived barriers to implementation to capture contextual factors not fully represented in the structured ratings.

Delphi Procedures

The survey was administered through Surveylet (Calibrum),24 a secure web-based platform supporting real-time Delphi methods. Panelists completed the survey asynchronously through a secure electronic link. For each survivorship standard, panelists were first presented with the full text of the standard and a brief description. Because the expert panel included diverse professional roles with varying knowledge of specific policies, workflows, and evaluation mechanisms, participants first indicated whether they felt qualified to assess each standard; item-level denominators therefore varied across standards and domains.

After submitting each item response, participants viewed anonymized aggregated feedback summarizing group responses and were given the option to revise their answer during the same survey administration. Both initial and revised responses were retained within the platform. Because the objective was to characterize implementation readiness rather than develop formal recommendations, analyses focused on patterns of expert agreement. Published Delphi studies have used agreement thresholds ranging from 50% to 97%, and threshold selection is generally guided by study objectives and intended use of the findings.18,25,26,27 In this study, agreement was considered present when at least 50% of respondents selected a single response category, a threshold selected to identify areas of convergence and divergence in expert perspectives.

Statistical Analysis

We used a mixed-methods approach, integrating descriptive quantitative summaries with qualitative thematic analysis of open-ended responses.28 Quantitative analyses included frequencies and percentages for participant characteristics and for categorical items and were conducted using IBM SPSS, version 32 (IBM Corp). We synthesized results across standards in a matrix summarizing patterns of agreement across the 6 implementation domains, using participants’ final submitted responses following real-time feedback and optional revision.

Responses to open-ended questions about barriers to implementation were analyzed using descriptive content analysis.9 Responses were reviewed to identify recurrent barriers related to organizational structure, clinical workflows, staffing and resource constraints, informatics infrastructure, and broader system factors. Similar responses were grouped into higher-level barrier categories across survivorship standards while retaining examples of barriers specific to individual standards. These qualitative summaries were used to contextualize the quantitative findings and inform interpretation of implementation gaps.

Results

Of 30 experts recruited, a total of 25 completed the survey, with a response rate of 83% (Table 1). Nineteen participants (76%) were female and 6 (24%) were male. Eight respondents (32%) identified as Asian, 1 (4%) as Black, 15 (56%) as White, and 2 (8%) as other race. Participants represented a range of professional roles, including physicians (14 [56%]), clinical staff (4 [16%]), and research staff (7 [28%]). Survivorship experience was substantial, with 18 participants (72%) having 5 or more years of experience in survivorship care. Most participants held doctoral-level degrees (18 [72%]), with the remainder holding master’s (5 [20%]) or bachelor’s (2 [8%]) degrees.

Table 1. Participant Characteristics.

Characteristic Participants, No. (%) (N = 25)
Sex
Female 19 (76)
Male 6 (24)
Race
Asian 8 (32)
Black 1 (4)
White 14 (56)
Othera 2 (8)
Occupation category
Physician 14 (56)
Clinical staff 4 (16)
Research staff 7 (28)
Experience in survivorship, y
<5 7 (28)
5-10 6 (24)
11-15 5 (20)
16-20 3 (12)
>20 4 (16)
Educational level
Bachelor’s degree 2 (8)
Master’s degree 5 (20)
Doctoral degree (eg, PhD, MD, JD) 18 (72)
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a

Included participants who selected Middle Eastern or North African as their race.

Table 2 shows how patterns of agreement varied across the 6 implementation domains. Experts consistently endorsed the importance of the survivorship standards, with agreement observed for 9 of 10 standards (90%; all except access to specialty care for late effects). In contrast, agreement regarding the existence of formal policies and health system evaluation mechanisms was more limited and frequently indicated absence or uncertainty: policy existence was most clearly endorsed for standards addressing psychological effects, whereas standards related to care coordination, practical and social impacts, and late-effects specialty care reached agreement that policies did not exist. Across standards, implementation was generally perceived as feasible, with agreement observed for 5 standards (50%). In contrast, implementation consistency emerged as a notable challenge, with experts agreeing that delivery was inconsistent for care coordination, practical and social impacts, lifestyle behaviors, financial hardship, and survivor engagement in care planning. Despite these gaps, agreement that implementation would have high impact was achieved for all 10 standards, indicating broad support for strengthening survivorship practices even where current policies, implementation consistency, and evaluation mechanisms were perceived as limited.

Table 2. Response Categories Reaching the Agreement Threshold Across the 6 Implementation Domainsa.

Survivorship standardb Implementation domain
Existence Importance Consistency Feasibility HSE Impact
Facilitation of survivorship care and care coordination No Agree Disagree Agree No Agree
Assessment for physical effects and provision of treatment or referrals No agreement Agree No agreement Agree No Agree
Provision of access to specialty care for late effects No No agreement No agreement No agreement No Agree
Assessment for psychological effects and provision of treatment or referrals Yes Agree No agreement No agreement Unsure Agree
Assessment for practical and social impacts and provision of resources or referrals No Agree Disagree No agreement No Agree
Assessment for risk of recurrence or new cancers and provision of referrals No agreement Agree No agreement Agree No Agree
Assessment for lifestyle behaviors and provision of strategies or referrals No agreement Agree Disagree No agreement No Agree
Provision of access or referrals to supportive health services No agreement Agree Agree Agree Unsure Agree
Assessment for financial hardship or toxicity and provision of support Unsure Agree Disagree No agreement Unsure Agree
Engagement in the care planning process No agreement Agree Disagree Agree Unsure Agree
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Abbreviation: HSE, health system evaluation.

a

Table entries indicate the response category that reached the prespecified agreement threshold. Agreement was considered present when at least 50% of respondents selected a single response category. For Likert-type items (importance, consistency, feasibility, and impact), responses were grouped as “agree,” “unsure,” or “disagree.” For categorical items (policy existence and HSE), responses were grouped as “yes,” “unsure,” or “no.” “No agreement” indicates that no response category reached the 50% threshold.

b

Wording of the standards is adapted from the National Standards for Survivorship Care Toolkit.11

The Figure illustrates the distribution of responses across the 6 implementation domains for each survivorship standard. Consistent with the agreement findings, responses were most favorable for importance and anticipated impact, whereas responses for policy existence, implementation consistency, and health system evaluation mechanisms were more often distributed toward the “no” or “disagree” or the “unsure” categories. Overall, the figure highlights a recurring pattern in which standards were perceived as valuable but not consistently supported by the organizational infrastructure needed for routine implementation.

Figure. Component Bar Graphs Reflecting Expert Survey Responses Submitted Through the Real-Time Delphi Platform for Each Implementation Domain.

Six-panel stacked bar charts of survey responses by domain and implementation standard. Six panels labeled A through F arranged in two columns and three rows, each containing horizontal stacked bars for 10 standards. A legend at the upper right maps fill colors to response categories: very light gray for Disagree or no, light blue gray for Neutral or unsure, and dark blue gray for Agree or yes. In every panel, the horizontal axis is labeled Responses, percent, with tick marks from 0 to 100; the vertical axis lists standards and includes a left-side label Standard with a small arrow marker. Panel A title Importance. Standards listed top to bottom: Care planning, Financial toxicity, Supportive services, Lifestyle behaviors, Recurrence risk, Practical or social impacts, Psychological effects, Specialty care access, Physical effects, Care coordination, each followed by a denominator in parentheses ranging from n equals 12 to n equals 18. Bars in Panel A are predominantly dark blue gray across most standards, with larger light blue gray segments for Specialty care access and Physical effects, and smaller very light gray segments variably present. Panel B title Anticipated impact, with denominators ranging from n equals 10 to n equals 16; most bars are largely dark blue gray, with Recurrence risk and Specialty care access containing larger light blue gray portions and small very light gray portions near the left. Panel C title Feasibility, denominators from n equals 12 to n equals 17; bars contain more mixed light blue gray and very light gray segments than Panels A and B, with dark blue gray still occupying roughly half or more for several standards such as Supportive services, Recurrence risk, Physical effects, and Care coordination. Panel D title Existence of formal organizational policies, denominators from n equals 12 to n equals 18; many standards have substantial very light gray and light blue gray segments with smaller dark blue gray segments, and Specialty care access appears entirely non-dark, split between very light gray and light blue gray. Panel E title Health system evaluation mechanisms, denominators from n equals 12 to n equals 17; bars are dominated by very light gray and light blue gray with minimal dark blue gray, and several standards have no visible dark blue gray segment. Panel F title Consistency of implementation and documentation, denominators from n equals 11 to n equals 15; bars include large very light gray segments on the left, moderate light blue gray midsections, and dark blue gray segments on the right that vary by standard, with Supportive services and Recurrence risk having comparatively larger dark blue gray portions.

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Likert-type responses were collapsed into “agree,” “unsure,” and “disagree” and categorical responses into “yes,” “unsure,” and “no.” Only respondents who indicated they were qualified to assess a given standard contributed responses to that item; thus, denominators vary.

Across open-ended responses, barriers clustered into several cross-cutting themes (Table 3). The most common were limited visit time and competing clinical demands, which constrained screening, counseling, and documentation. Respondents also identified workforce and role-capacity limitations, including insufficient availability of patient navigators, social workers, mental health professionals, palliative care, and financial counselors to deliver services and follow up on identified needs. Additional barriers included lack of standardized workflows and tools (eg, survivorship-specific checklists, algorithms, and templates), electronic health record (EHR) and informatics limitations, referral access bottlenecks, and funding challenges for non–revenue-generating services such as supportive care and financial toxicity mitigation.

Table 3. Expert-Reported Barriers to Implementation of Survivorship Standardsa.

Survivorship standard Key barrier themes
Survivorship care and care coordination Lack of formal survivorship infrastructure, time and workflow burden, EHR or documentation constraints, limited workforce and implementation champions, low institutional prioritization and funding
Physical effects assessment and treatment or referrals Knowledge gaps in primary care, lack of standardized checklists and referral pathways, referral delays and staffing shortages, EHR or reporting limitations
Access to specialty care for late effects Limited specialty access and long wait times, nonstandard screening and referral triggers, fragmented coordination across oncology and specialty care, insurance and access barriers
Psychological effects assessment and treatment or referrals Mental health workforce shortages, gaps in referral follow-through, EHR and infrastructure limitations, competing clinical priorities and time constraints
Practical and social impacts, resources, or referrals Limited staffing for resource navigation, lack of standardized screening tools or workflows, time and training burden, funding constraints
Recurrence or new cancer risk assessment and referrals Lack of standardized risk protocols, EHR tracking and reminder limitations, specialty resource constraints, unclear role ownership and patient-level barriers
Lifestyle behaviors assessment and strategies or referrals Time constraints and competing demands, insufficient supportive programs or resources, unclear practitioner ownership and buy-in, need for standardized tools and leadership support
Supportive health services access or referrals EHR referral tracking limitations, limited supportive care capacity, funding or resource allocation constraints, patient navigation barriers
Financial hardship or toxicity assessment and support No universal screening workflow, EHR visibility and structured data gaps, limited financial navigation expertise or capacity, funding and structural barriers
Survivor engagement in care planning Time and documentation burden, need for dedicated team roles, limited leadership prioritization, workflow design challenges, training and education needs
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Abbreviation: EHR, electronic health record.

a

Themes were derived from descriptive content analysis of open-ended responses. Table entries summarize higher-level barrier categories identified across respondents and standards; examples provided by participants were condensed for clarity.

Discussion

In this real-time Delphi study, experts consistently endorsed the National Standards for Cancer Survivorship Care4,11 as important and likely to improve care yet did not perceive the organizational infrastructure needed to implement them consistently as being fully in place. Agreement was strongest for the standards’ importance and anticipated impact and weakest for formal policies, implementation consistency, and health system evaluation mechanisms. These findings suggest that a principal challenge in survivorship care may not be lack of agreement about what high-quality care should include but limited operational capacity to deliver and measure it reliably in routine practice. As 1 of the first empirical assessments of implementation readiness for the National Standards for Cancer Survivorship Care following their release, these findings highlight implementation challenges likely to be relevant to other health systems translating national survivorship standards into practice. The readiness gaps identified were concentrated in workflows, referral pathways, documentation, and evaluation mechanisms, suggesting barriers that may extend beyond a single institution and inform future multi-institutional implementation efforts.

Distinction between perceived value and perceived readiness is important and reflects a broader implementation problem in survivorship care.1,2,7,16,29,30 In this context, the National Standards for Cancer Survivorship Care may be most useful not only as a framework for defining high-quality survivorship care but also as a tool for identifying where health systems lack the operational infrastructure needed to deliver that care reliably. The findings suggest that readiness may depend less on whether a survivorship domain is viewed as clinically important and more on whether it has been embedded into routine care processes and standardized workflows.12,13,16

The variation across domains further suggests that survivorship implementation may be shaped by the complexity of the work required. Domains that require coordination across clinicians, care settings, and longitudinal follow-up may be especially difficult to implement without shared ownership and system-level supports.30,31 This may explain why care coordination, practical and social needs, financial hardship, and survivor engagement in care planning appeared less operationally mature, whereas psychological assessment and referral may be more readily integrated because distress screening and referral processes are already more familiar within oncology care.32,33

Other “not ready” domains, particularly financial toxicity and survivor engagement in care planning, further illustrate the distinction between perceived value and operational readiness. This is especially consequential in the context of rising cancer-related out-of-pocket costs, which continue to contribute to financial hardship, medical debt, and treatment disruption.34 Emerging evidence also suggests that even when financial toxicity screening is implemented, substantial barriers may limit follow-through, including difficulty contacting patients, limited staffing and navigation capacity, and workflow friction.35 More broadly, the low ratings for implementation consistency across several domains suggest that survivorship care may remain highly dependent on individual clinicians or local practice patterns rather than being supported by standardized systems of care.

Qualitative findings helped clarify sources of these readiness gaps. Time constraints, workforce limitations, fragmented workflows, referral bottlenecks, and informatics barriers were described across multiple standards rather than as isolated challenges within single domains. This pattern suggests that implementation of survivorship standards may depend less on adding isolated services and more on strengthening the cross-cutting infrastructure needed. One practical implication is that survivorship standards may need to be translated into explicit workflow-based processes that define who is responsible, when assessments occur, how referrals are triggered, and how care is documented and tracked.36,37 Such workflow-based implementation may reduce variation across clinicians and settings while creating measurable care processes that can be monitored over time.

Health information technology will likely be central to scalable implementation of survivorship standards.35,38,39,40 Respondents frequently identified limitations in documentation, referral tracking, and reporting capacity, suggesting that survivorship care is difficult to monitor in the absence of structured EHR tools and process indicators. Templates, decision support prompts, referral tracking systems, and automated reporting functions may help translate survivorship standards into measurable care processes.35,41 However, EHR-based strategies are unlikely to be sustainable if they primarily add documentation burden to already constrained clinical environments.41,42,43,44 Effective implementation will depend not only on integrating standards into the EHR but also on whether that integration reduces workflow friction and supports longitudinal care delivery in practice.

Limited agreement regarding formal policies and health system evaluation mechanisms suggests that survivorship care may lack clear operational ownership and governance. Importantly, the domains perceived as least ready were not those viewed as least important but those lacking formalized policies, standardized workflows, and mechanisms for monitoring implementation. This finding suggests that implementation efforts may need to focus less on increasing awareness of survivorship standards and more on establishing the organizational infrastructure required to support them. Future implementation efforts should evaluate strategies for standardizing workflows, strengthening accountability, and monitoring delivery of survivorship care across settings. Together, these approaches may help translate survivorship standards from aspirational recommendations into measurable care processes embedded within routine oncology practice.

Strengths and Limitations

This study’s strengths included use of a real-time Delphi approach that allowed efficient expert feedback and optional response revision while minimizing participant burden. The multidisciplinary panel included stakeholders involved in survivorship care delivery across diverse clinical contexts, and the mixed-methods design helped contextualize quantitative readiness findings with qualitative barriers.

This study also has limitations. First, it was conducted within a single regional survivorship care network anchored by 1 National Cancer Institute–designated comprehensive cancer center, which may limit transferability to other health systems. However, because comprehensive cancer centers often function as early adopters of survivorship programming and multidisciplinary care models, similar implementation challenges may be even more pronounced in less-resourced settings. Second, panelists were recruited through purposive sampling, which may have favored individuals more engaged in survivorship care or implementation efforts, potentially contributing to high ratings of importance and anticipated impact. Third, item-level nonresponse resulted in varying denominators across survey items, which may affect the stability of agreement classifications for some items. Fourth, the prespecified threshold of 50% or greater agreement was selected to identify areas of convergence and divergence in implementation readiness rather than to establish formal recommendations or practice guidelines; alternative thresholds may have yielded different classifications. Fifth, the study assessed perceived implementation readiness rather than directly observed organizational performance, and some survivorship activities may occur but remain inconsistently documented or difficult to evaluate within existing health system infrastructure.

Conclusions

In this real-time Delphi survey study, experts endorsed the National Standards for Cancer Survivorship Care as important but identified substantial gaps in the organizational infrastructure required for consistent implementation. These findings suggest that dissemination of standards alone is unlikely to improve survivorship care without corresponding investments in workflows, data systems, and accountability structures. Multi-institutional studies are needed to determine how survivorship standards can be implemented as scalable workflows, measurable quality indicators, and sustainable care delivery models across oncologic settings.

Supplement.

Data Sharing Statement

jamanetwopen-e2629351-s001.pdf (15.3KB, pdf)

References

  • 1.Nekhlyudov L, Mollica MA, Jacobsen PB, Mayer DK, Shulman LN, Geiger AM. Developing a quality of cancer survivorship care framework: implications for clinical care, research, and policy. J Natl Cancer Inst. 2019;111(11):1120-1130. doi: 10.1093/jnci/djz089 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Jefford M, Howell D, Li Q, et al. Improved models of care for cancer survivors. Lancet. 2022;399(10334):1551-1560. doi: 10.1016/S0140-6736(22)00306-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Riba MB, Donovan KA, Ahmed K, et al. NCCN guidelines insights: distress management, version 2.2023. J Natl Compr Canc Netw. 2023;21(5):450-457. doi: 10.6004/jnccn.2023.0026 [DOI] [PubMed] [Google Scholar]
  • 4.Mollica MA, McWhirter G, Tonorezos E, et al. ; National Cancer Survivorship Standards Subject Matter Expert Group . Developing national cancer survivorship standards to inform quality of care in the United States using a consensus approach. J Cancer Surviv. 2024;18(4):1190-1199. doi: 10.1007/s11764-024-01602-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Wagle NS, Nogueira L, Devasia TP, et al. Cancer treatment and survivorship statistics, 2025. CA Cancer J Clin. 2025;75(4):308-340. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Tonorezos E, Devasia T, Mariotto AB, et al. Prevalence of cancer survivors in the United States. J Natl Cancer Inst. 2024;116(11):1784-1790. doi: 10.1093/jnci/djae135 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Blaes AH, Adamson PC, Foxhall L, Bhatia S. Survivorship care plans and the Commission on Cancer Standards: the increasing need for better strategies to improve the outcome for survivors of cancer. JCO Oncol Pract. 2020;16(8):447-450. doi: 10.1200/JOP.19.00801 [DOI] [PubMed] [Google Scholar]
  • 8.Sanft T, Denlinger CS, Armenian S, et al. NCCN guidelines insights: survivorship, version 2.2019. J Natl Compr Canc Netw. 2019;17(7):784-794. doi: 10.6004/jnccn.2019.0034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Kunthur A, Xiang Z, Kaur H, Jewell S, Mehta P. Updates on cancer survivorship care planning. Fed Pract. 2015;32(suppl 7):64S-69S. [PMC free article] [PubMed] [Google Scholar]
  • 10.Stal J, Miller KA, Mullett TW, et al. Cancer survivorship care in the United States at facilities accredited by the Commission on Cancer. JAMA Netw Open. 2024;7(7):e2418736. doi: 10.1001/jamanetworkopen.2024.18736 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.National Cancer Institute, Office of Cancer Survivorship . National Standards for Cancer Survivorship Care Toolkit. US Department of Health and Human Services, National Institutes of Health; 2024. Accessed July 8, 2026. https://cancercontrol.cancer.gov/sites/default/files/2024-10/DCCPS_National_Cancer_Survivorship_Standards_Toolkit_508.pdf
  • 12.Birken SA, Ellis SD, Walker JS, et al. Guidelines for the use of survivorship care plans: a systematic quality appraisal using the AGREE II instrument. Implement Sci. 2015;10:63. doi: 10.1186/s13012-015-0254-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Proctor EK, Powell BJ, McMillen JC. Implementation strategies: recommendations for specifying and reporting. Implement Sci. 2013;8:139. doi: 10.1186/1748-5908-8-139 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Office of Cancer Survivorship . Division of Cancer Control & Population Sciences. Models of survivorship care. National Cancer Institute. Accessed April 8, 2026. https://cancercontrol.cancer.gov/ocs/special-focus-areas/models-of-survivorship-care
  • 15.Varndell W, Fry M, Elliott D. Applying real-time Delphi methods: development of a pain management survey in emergency nursing. BMC Nurs. 2021;20(1):149. doi: 10.1186/s12912-021-00661-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Tremblay D, Latreille J, Bilodeau K, et al. Improving the transition from oncology to primary care teams: a case for shared leadership. J Oncol Pract. 2016;12(11):1012-1019. doi: 10.1200/JOP.2016.013771 [DOI] [PubMed] [Google Scholar]
  • 17.Giroux CM, Zomahoun HTV, Boies S, et al. Assessing healthcare organisations’ readiness to implement a learning health system: protocol for questionnaire validation using a Delphi method. BMJ Open. 2025;15(8):e088720. doi: 10.1136/bmjopen-2024-088720 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Nasa P, Jain R, Juneja D. Delphi methodology in healthcare research: how to decide its appropriateness. World J Methodol. 2021;11(4):116-129. doi: 10.5662/wjm.v11.i4.116 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Parker G, Kastner M, Born K, Berta W. Development of an implementation process model: a Delphi study. BMC Health Serv Res. 2021;21(1):558. doi: 10.1186/s12913-021-06501-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Improving comprehensive care of cancer patients (OPTIMISE). ClinicalTrials.gov identifier: NCT05323409. Updated June 30, 2026. Accessed July 31, 2026. https://clinicaltrials.gov/study/NCT05323409
  • 21.American Association for Public Opinion Research . Best practices for survey research. Accessed June 1, 2026. https://aapor.org/standards-and-ethics/best-practices/
  • 22.Duan N, Bhaumik DK, Palinkas LA, Hoagwood K. Optimal design and purposeful sampling: complementary methodologies for implementation research. Adm Policy Ment Health. 2015;42(5):524-532. doi: 10.1007/s10488-014-0596-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Palinkas LA, Horwitz SM, Green CA, Wisdom JP, Duan N, Hoagwood K. Purposeful sampling for qualitative data collection and analysis in mixed method implementation research. Adm Policy Ment Health. 2015;42(5):533-544. doi: 10.1007/s10488-013-0528-y [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Surveylet: Delphi survey software. Calibrum. Accessed December 1, 2025. https://surveylet.com/
  • 25.Schifano J, Niederberger M. How Delphi studies in the health sciences find consensus: a scoping review. Syst Rev. 2025;14(1):14. doi: 10.1186/s13643-024-02738-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Diamond IR, Grant RC, Feldman BM, et al. Defining consensus: a systematic review recommends methodologic criteria for reporting of Delphi studies. J Clin Epidemiol. 2014;67(4):401-409. doi: 10.1016/j.jclinepi.2013.12.002 [DOI] [PubMed] [Google Scholar]
  • 27.Dietrich TJ, Mascarenhas VV, Cerezal L, Afonso PD, Sudoł-Szopińska I. Overview for developing Delphi-based interdisciplinary consensus statements on imaging: pros and cons. J Ultrason. 2024;24(97):1-6. doi: 10.15557/JoU.2024.0015 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Colorafi KJ, Evans B. Qualitative descriptive methods in health science research. HERD. 2016;9(4):16-25. doi: 10.1177/1937586715614171 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Chan RJ, Crawford-Williams F, Crichton M, et al. Effectiveness and implementation of models of cancer survivorship care: an overview of systematic reviews. J Cancer Surviv. 2023;17(1):197-221. doi: 10.1007/s11764-021-01128-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Tomasone JR, Brouwers MC, Vukmirovic M, et al. Interventions to improve care coordination between primary healthcare and oncology care providers: a systematic review. ESMO Open. 2016;1(5):e000077. doi: 10.1136/esmoopen-2016-000077 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Armin JS, Price SN, Ver Hoeve ES, et al. Using stakeholder engagement to build cancer survivorship care coordination capacity between primary and oncology care. Health Equity. 2025;9(1):648-656. doi: 10.1177/24731242251385402 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Mitchell AJ. Screening for cancer-related distress: when is implementation successful and when is it unsuccessful? Acta Oncol. 2013;52(2):216-224. doi: 10.3109/0284186X.2012.745949 [DOI] [PubMed] [Google Scholar]
  • 33.Brandenbarg D, Maass SWMC, Geerse OP, et al. A systematic review on the prevalence of symptoms of depression, anxiety and distress in long-term cancer survivors: implications for primary care. Eur J Cancer Care (Engl). 2019;28(3):e13086. doi: 10.1111/ecc.13086 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Zafar SY, Peppercorn JM, Schrag D, et al. The financial toxicity of cancer treatment: a pilot study assessing out-of-pocket expenses and the insured cancer patient’s experience. Oncologist. 2013;18(4):381-390. doi: 10.1634/theoncologist.2012-0279 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Morken CM, Tevaarwerk AJ, Swiecichowski AK, et al. Survivor and clinician assessment of survivorship care plans for hematopoietic stem cell transplantation patients: an engineering, primary care, and oncology collaborative for survivorship health. Biol Blood Marrow Transplant. 2019;25(6):1240-1246. doi: 10.1016/j.bbmt.2019.02.003 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Tevaarwerk AJ, Zhang X, Haine J, et al. Re-engineering survivorship care plans to support primary care needs and workflow: results from an engineering, primary care and oncology collaborative for survivorship health (EPOCH). J Cancer Educ. 2022;37(6):1654-1661. doi: 10.1007/s13187-021-02008-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Mayer DK, Taylor K, Gerstel A, Coghill A, Birken SA. Implementing survivorship care plans within an electronic health record. Oncology (Williston Park). 2015;29(12):980-982, 989. [PubMed] [Google Scholar]
  • 38.Saraceno D, Chronaki C, Cangioli G, et al. Assessment of HL7 FHIR interoperability between EHR systems and the Survivorship Passport v2.0 platform to generate treatment summaries for childhood cancer survivors in six clinics: preliminary testing results. Stud Health Technol Inform. 2024;316:1280-1284. doi: 10.3233/SHTI240646 [DOI] [PubMed] [Google Scholar]
  • 39.O’Hea E, Wu J, Dietzen L, Harralson T, Boudreaux ED. The Polaris Oncology Survivorship Transition (POST) system: a patient- and provider-driven cancer survivorship planning program. J Oncol Navig Surviv. 2016;7(10):11-24. [PMC free article] [PubMed] [Google Scholar]
  • 40.Mikles SP, Griffin AC, Chung AE. Health information technology to support cancer survivorship care planning: a systematic review. J Am Med Inform Assoc. 2021;28(10):2277-2286. doi: 10.1093/jamia/ocab134 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Apathy NC, Holmgren AJ, Cross DA. Physician EHR time and visit volume following adoption of team-based documentation support. JAMA Intern Med. 2024;184(10):1212-1221. doi: 10.1001/jamainternmed.2024.4123 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Apathy NC, Rotenstein L, Bates DW, Holmgren AJ. Documentation dynamics: note composition, burden, and physician efficiency. Health Serv Res. 2023;58(3):674-685. doi: 10.1111/1475-6773.14097 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Moy AJ, Schwartz JM, Chen R, et al. Measurement of clinical documentation burden among physicians and nurses using electronic health records: a scoping review. J Am Med Inform Assoc. 2021;28(5):998-1008. doi: 10.1093/jamia/ocaa325 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Melnick ER, Dyrbye LN, Sinsky CA, et al. The association between perceived electronic health record usability and professional burnout among US physicians. Mayo Clin Proc. 2020;95(3):476-487. doi: 10.1016/j.mayocp.2019.09.024 [DOI] [PubMed] [Google Scholar]

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