https://orcid.org/0000-0001-9816-4617
Figures
Abstract
Background
Research funding is a crucial driver of healthcare innovation and improved patient outcomes. However, the peer-review process utilised during funding allocation is often subjective, inconsistent, and prone to reviewer biases, leading to inefficiencies in selecting high-impact projects. This study aimed to develop an objective, transparent, and structured scoring system to improve research funding decisions.
Methods
A mixed-methods approach was used, incorporating a scoping review, surveys, Delphi methodology, and the analytic hierarchy process (AHP). The scoping review identified funding criteria used by national and international agencies. A survey of researchers and decision-makers at the Royal Hospital in Muscat, Oman, gathered insights into funding priorities. Experts refined and validated criteria using the Delphi method, while weighted importance to each criterion as per the AHP was assigned through pairwise comparisons.
Results
The study identified 10 key criteria for funding decisions: scientific merit, ethical standards, novelty and innovation, significance and strategic alignment, feasibility, impact and knowledge transfer, budget and cost-efficiency, team expertise and collaboration, sustainability, and partnerships in funding. Based on AHP weighting, the final model prioritised Ethical Standards (21.7%), Scientific Merit (19.1%), and Novelty and Innovation (16.7%) as the highest-weighted criteria, together accounting for more than half of the overall decision weight.
Conclusion
The proposed scoring model provides a structured, evidence-based framework to enhance research funding decisions by enhancing consistency and transparency during peer review. It ensures alignment with institutional and national research priorities, while the inclusion of impact, feasibility, and sustainability criteria reflects a shift towards funding research that yields tangible societal and healthcare benefits. Future studies should evaluate implementation of the model in real-world settings and explore the role of artificial intelligence-driven decision-support tools to further refine research funding processes.
Citation: Al Harthi H, Al Nabhani M, Al Sabei S, A-Amri A, Al Hinaai S, AlDhuhli S (2026) A peer-review decision support tool for research funding decision-making using the analytic hierarchy process. PLoS One 21(8): e0350938. https://doi.org/10.1371/journal.pone.0350938
Editor: Chih-Cheng Lin, National Kaohsiung University of Science and Technology, TAIWAN
Received: April 23, 2025; Accepted: May 19, 2026; Published: August 12, 2026
Copyright: © 2026 Al Harthi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting information files. Raw survey responses collected via Google Forms can be shared by the authors upon reasonable request.
Funding: The author(s) received no specific funding for this work.
Competing interests: No authors have competing interests.
Abbreviations: AHP, Analytic Hierarchy Process; AI, Artificial Intelligence; PI, Principal Investigator; R&D, Research and Development; SROI, Social Return on Investment; TRC, The Research Council (Oman); SQU, Sultan Qaboos University; NIH, National Institutes of Health; RIMA, Southern African Research and Innovation Management Association
Introduction
Efforts to strengthen evidence-based healthcare practice and decision-making have driven increased investment in research funding. However, this investment is only effective if it translates into meaningful impact and value [1]. To maximise research benefits, every stage of knowledge development plays a crucial role in ensuring efficiency, minimising waste, and enhancing impact, including funding decisions [1,2]. The effectiveness of health research is further shaped by the complexity of medical issues, the extended timeline required for basic science to yield clinical applications, and socioeconomic and political factors influencing funding priorities [3]. Additionally, the allocation of limited funds complicates the process. While peer review remains the standard for funding decisions, it often lacks precision and is subject to numerous challenges [4].
Despite these challenges, peer review in funding decision-making can be improved through innovative approaches. Streamlining review processes [5], leveraging technology [6], incorporating public participation [7], and establishing effective feedback mechanisms [8] can allow funding organisations to enhance the quality and efficiency of their decision-making processes. These improvements are essential to ensuring that research funding is allocated effectively, ultimately advancing scientific knowledge and improving health outcomes.
A major issue of the current peer-review system is ambiguity and inconsistency in applying evaluation criteria. Variations among funding agencies and individual reviewers lead to misalignment between applicant expectations and reviewer priorities [9,10]. The process often fails to capture the multifaceted nature of research quality, focusing narrowly on intrinsic research excellence while overlooking ethical considerations and societal relevance, which may disadvantage interdisciplinary and innovative proposals [10,11]. Reviewer biases, influenced by background and institutional affiliations, further distort evaluations, often favouring established researchers over emerging scientists [9,12]. Additionally, the lack of transparency in applying criteria and providing feedback undermines accountability and trust in the process [8]. The predictive validity of peer review is also debatable, as reviewer scores do not consistently correlate with the future impact of funded research [13,14]. Addressing these issues is crucial to improving the fairness and effectiveness of research funding decisions.
To reduce subjectivity in research proposal evaluation and enhance the selection of high-impact projects, a more robust scoring system is needed. This study aimed to develop a unified scoring framework to improve the peer-review process for research funding allocation at the Royal Hospital, a tertiary care facility in Muscat, Oman. By increasing transparency and ensuring consistent scoring among peer reviewers, the proposed system benefits both funders and researchers, ultimately supporting more equitable and effective research funding.
This study applies a structured multi-criteria decision-making approach based on the Analytic Hierarchy Process (AHP), informed by expert input, to develop a transparent and adaptable research funding decision-support tool. The methodological innovation lies in translating qualitative expert judgments into a quantitative, policy-relevant scoring framework tailored to institutional and national research priorities. The resulting model identified ethical standards, scientific merit, and innovation as dominant funding criteria and demonstrated stable prioritization under alternative weighting scenarios.
Methods
Research design and setting
This mixed-methods study was conducted at the Royal Hospital, a tertiary care facility serving the Omani population and providing specialised healthcare. The hospital also plays a key role in national medical education, training, and research. Between 2019 and 2024, healthcare providers at the hospital contributed to more than 743 published works [15].
Data collection
The study comprised three main phases (Fig 1), using a mixed-methods approach that included a scoping review, surveys, Delphi methodology, and the analytic hierarchy process (AHP). The scoping review identified initial funding criteria, which informed a stakeholder survey to capture local priorities. These were refined through Delphi consensus, with AHP used to assign weights. Each phase built on the previous one, with outputs iteratively informing the next to refine and validate the criteria.
Phase I: Scoping review and survey.
A scoping review was conducted to identify criteria used by major national and international agencies. The criteria were consolidated into overarching themes. Subsequently, all staff with research experience or who were involved in funding decisions were invited to participate in an online survey to identify and evaluate funding criteria. No exclusion criteria were applied. Survey links were disseminated via research focal points in all hospital departments, official hospital messaging groups, and the in-hospital communication system. The survey remained open for two weeks from 20th October 2024.
The survey comprised three sections. The first included an open-ended question inviting participants to propose key funding criteria. In the second section, participants were asked to review a structured list of criteria to prompt reflection and stimulate further input. The third section was an open-ended question asking participants to reflect on challenges in the peer-review process to inform criteria development and address practical barriers to improve funding decisions. Responses to the open-ended questions were analysed thematically through a systematic process: coding meaningful units, grouping codes into themes, and refining themes for consistency and relevance.
Phase II: Expert rating and initial validation.
On 4th November 2024, a panel of 15 experts in healthcare, academia, and policy fields was convened to evaluate the preliminary criteria. Experts were purposively selected based on their dual roles as researchers involved in reviewing and scoring funding applications and/or as senior decision-makers responsible for research management, budget allocation, and sector strategy. Each criterion was rated for suitability on a 5-point Likert scale from 1 (strongly disagree) to 5 (strongly agree). Criteria with a median rating below 3 were eliminated. Experts also provided qualitative feedback to refine existing or propose additional criteria.
Subsequently, on 14th November 2024, face-to-face interviews were conducted with three senior decision-makers with extensive research experience to develop the first draft of the final list of criteria. These interviews provided deeper insights into each criterion, highlighting their relevance in funding decisions, practical considerations that could impact the model’s weighting, and opportunities to merge overlapping criteria, improving the coherence of the final model. The revised criteria were then re-evaluated on 17th November 2024 in a second round by the expert panel, who rated the relevance of each criterion on a 5-point Likert scale from 1 (not relevant) to 5 (highly relevant) and provided further feedback. The final list of criteria was developed based on this iterative process.
Phase III: Weighting and validation.
The AHP, a structured decision-making approach that quantifies subjective judgments, was applied to prioritize 10 predefined criteria for research funding decisions. Pairwise comparisons were used to generate weightings for each criterion based on relative importance [16,17]. Two formats were adopted. First, during an in-person workshop at the Royal Hospital in late November 2024, four members of the hospital’s Research Committee completed comparisons using the Saaty scale (1–9) [18], which captures the relative importance of one criterion over another. Second, a panel of three additional experts in clinical research, health strategy, and funding evaluation—who had participated in earlier study phases—were provided the AHP matrix during site visits and later submitted their responses via email within three days.
In both groups, each participant completed a reciprocal comparison matrix. Normalised weights were calculated by averaging values across rows, followed by a group average to represent consensus priorities. Consistency ratio was used to assess judgment reliability, with values below 0.10 indicating acceptable consistency. While several raters met this threshold, others showed moderate to high inconsistency; however, all inputs were retained to preserve diversity of perspectives, with the group averaging process mitigating individual variation. This participatory, multi-source approach enhanced the transparency, fairness, and policy relevance of the final weighted criteria.
Sensitivity analysis was conducted to assess the robustness of the prioritisation framework to plausible variations in stakeholder weighting preferences. One-way sensitivity analyses were performed by independently varying the relative weight of each criterion within a policy-relevant range while maintaining the overall hierarchical structure and total weight at 100%, and examining resulting changes in ranking. In addition, a multi-criterion scenario analysis was conducted to simulate an alternative policy emphasis through proportional redistribution of weights. Ranking stability across scenarios was interpreted as an indicator of model robustness.
Results
Phase I: Scoping review
Thematic analysis was conducted of research funding priorities at three national institutions—the Ministry of Health, Ministry of Higher Education, Research and Innovation, and Sultan Qaboos University—and seven international institutions—the National Institutes of Health, UK Research and Innovation, the Australian Government Department of Health, the Southern African Research and Innovation Management Association, the Canadian Institutes of Health Research, the European Commission, and the Health Research Council of New Zealand.
Table 1 synthesises findings from the literature and institutional funding guidelines detailed in Appendix I and illustrates the consistency of core evaluation domains across funding contexts, which informed the theme construction in the proposed framework.
By reviewing and comparing criteria, common focus areas were identified and subsequently grouped into 17 categories.
Key categories included Novelty and Originality, assessing the introduction of new ideas and the proposal’s differentiation from prior work, ensuring that projects are genuinely innovative; Literature Review and Background, evaluating whether the proposal effectively justifies the research gap, grounding the research question in a comprehensive review of existing studies; and Clarity and Coherence, ensuring well-defined objectives and clear communication of the research approach, a crucial aspect for understanding the proposal’s goals and methodologies.
Significance and Impact covered the broader contributions of the research, considering the project’s potential contribution to scientific, societal, or economic spheres. Methodology and Feasibility assessed the study design’s robustness, ensuring that the approach, timeline, and budget were realistic and achievable. Qualifications and Expertise of the Research Team evaluated the investigators’ relevant experience and capacity to execute the project successfully, while Research Environment and Resources encompassed institutional support, infrastructure, and available facilities. Interdisciplinary and Collaborative Approach recognised the value of cross-disciplinary partnerships, particularly in tackling complex research questions, while Alignment with National or Institutional Priorities determined whether the proposal addressed key strategic objectives, a critical factor in funding decisions.
Furthermore, Public Awareness and Knowledge Transfer and Research Capacity-Building emphasised the project’s outreach, skill development, and infrastructure enhancement. Various other categories, such as Budget Justification and Cost-Efficiency, Data Management and Ethical Standards, and Sustainability and Long-term Benefits, assessed the practical and ethical dimensions of the project, ensuring responsible resource use and potential for lasting impact. Other categories identified during the scoping review included Outcome Maximisation and Project Timeline and Management, both of which examine the project’s potential to produce impactful results and manage operations efficiently.
Phase I: Survey
A total of 96 respondents completed the survey, of which 37.5% were researchers, 24.0% were decision-makers, and 12.5% held both roles. Most of the criteria identified by survey respondents aligned closely with the thematic categories established during the initial scoping review. Frequently mentioned areas such as Innovation and Novelty, Feasibility, Team Expertise, and Alignment with Institutional Priorities reaffirmed the relevance and comprehensiveness of the original framework. This convergence suggests that the foundational themes derived from national and international sources were reflective of stakeholder perspectives.
Nonetheless, the survey also revealed additional considerations not previously captured. These included Impact and Relevance, with a focus on the alignment of research with emerging healthcare challenges and the specific needs of the local context. Respondents also highlighted Resource Allocation, emphasising the importance of balancing budget size with justification and anticipated outcomes. Operational Readiness was another emergent theme, reflecting the need for clearly defined implementation plans, realistic timelines, and risk mitigation strategies. These newly identified elements were incorporated to refine and strengthen the thematic framework. Their inclusion enhanced the applicability of the criteria by integrating frontline insights and ensuring the final set of themes reflected both established priorities and practical, context-specific considerations relevant to research funding decisions.
Respondents acknowledged challenges in balancing innovation with Feasibility and Resource Allocation. Resource limitations were cited as a significant constraint, forcing decision-makers to make difficult trade-offs between equally promising projects. Concerns were also raised about Bias Mitigation in Decision-Making, particularly regarding potential favouritism towards familiar researchers or conventional topics.
Phase II: Expert rating
In round 1 of the panel, 13 out of 15 experts participated. Their feedback included insightful suggestions on incorporating additional criteria for funding decision-making, highlighting the importance of essential factors like practical impact, stakeholder engagement, and research outcome relevance (Table 2).
A key theme was scalability and replicability, with one participant noting, “Funding should favour projects that can be scaled up or replicated by other researchers, as these efforts contribute to lasting impact and greater dissemination of knowledge.” Another recurring theme was potential societal and economic benefits and applications, particularly for publicly funded projects. One respondent explained, “Projects that demonstrate a potential to benefit society or the economy may be prioritised, especially if aligned with public welfare goals.”
Other highlighted themes included collaborative funding support, with some respondents highlighting the role of international partnerships in augmenting research funding. One participant noted, “If the study will be conducted in Oman and internationally, sometimes the participating international university also funds part of the budget.” Several experts suggested incorporating criteria to assess the transferability of research findings. As one participant remarked, “It may be beneficial to consider adding criteria that assess the transferability of research findings into tangible products, programmes, or initiatives.” Stakeholder and end-user involvement was also highlighted, with one respondent stating, “Including end-users, beneficiaries, or key stakeholders in the planning or design phases enhances the likelihood of practical applications and strengthens societal impact.”
Other suggestions included ensuring context and sociopolitical sensitivity, considering commercialisation potential, and evaluating research maturity for clinical trials. As one respondent pointed out, “The maturity of the research and if it will lead to clinical trials is a key factor in determining its impact on healthcare interventions”.
Qualitative interviews with the three strategic-level decision-makers reinforced the importance of social return on investment (SROI) to evaluate communal benefits, such as improved public health, patient outcomes, and healthcare efficiency, despite challenges in quantification and delayed impact realisation. Innovation was identified as a catalyst for economic growth, with various suggestions proposed, including fostering transdisciplinary collaboration, rewarding diverse teams, and promoting early-career researchers to drive creativity. Experts also stressed the need for collaborative funding through partnerships with external stakeholders, including those in the private sector, to enhance research applicability and ensure a balance between high-risk, high-reward projects and conventional studies.
Sustainability and scalability were also deemed essential, prioritising research with enduring and adaptable benefits across diverse settings. Additionally, experts advocated balancing research and development (R&D)-intensive projects with process improvement initiatives to enhance patient care. Finally, aligning research with local healthcare priorities while maintaining global relevance was viewed as critical for fostering meaningful innovation.
Phase II: Initial validation
Nine out of 15 experts participated in round 2 of the panel. The evaluation criteria for research proposals were finalised after incorporating expert ratings, averaging scores, and integrating feedback to merge and clarify overlapping categories (Table 3). This process resulted in a final list of 10 criteria.
The most highly prioritised criteria were Ethical Standards and Scientific Merit (combined average score: 4.78), highlighting the importance of methodological rigour, ethical integrity, and risk-benefit analyses, and Novelty and Innovation (4.78), stressing originality, filling critical knowledge gaps, and scalability. Significance and Strategic Alignment (4.56) and Feasibility and Risk Mitigation (4.56) were also highly prioritised, ensuring projects are both impactful and realistically executable.
Impact and Knowledge Transfer (4.67) focused on the dissemination and the societal and practical benefits of research findings, while Budget and Cost-Efficiency (4.56) underscored the need for financial justification, prudent spending, and appropriate resource allocation. Team Expertise and Collaboration (4.30) assessed the research team’s capability to execute the project successfully across relevant disciplines. Sustainability (3.89) and Partnerships in Funding (3.40) addressed long-term viability and external resource contributions.
Phase III: Weighting and validation
The AHP results prioritized 10 evaluation criteria based on ratings from seven experts. The highest-weighted criterion was Scientific Merit (20.16%), indicating it was considered the most critical factor in assessing proposals. This was followed closely by Ethical Standards (19.21%) and Novelty and Innovation (14.34%), underscoring the importance of methodological soundness and forward-thinking approaches. Significance and Alignment (10.10%) and Team Expertise and Collaboration (8.39%) also received notable weights, suggesting their perceived influence in the overall impact of the proposal. Other criteria such as Feasibility and Risk Mitigation (7.27%), Impact and Knowledge Transfer (7.00%), and Budget and Cost Efficiency (6.24%) were moderately prioritized. Sustainability (4.14%) and Partnerships in Funding (3.17%) received the lowest weights, suggesting they were considered less critical in this context.
Each expert provided pairwise comparisons, which were synthesised to generate individual weights and a group consensus score of 0.84586, indicating strong agreement among raters (Table 4). The hierarchical structure of the AHP model effectively captured the relative importance of each criterion in the decision-making framework. This hierarchy not only organises the decision criteria logically but also supports transparent, quantifiable comparisons, reinforcing the credibility of the final prioritisation (Fig 2).
Sensitivity analysis: Innovation-focused weighting scenario
This scenario simulated a funding context that places greater emphasis on innovative research while preserving the overall decision structure. The adjusted criterion weights under this scenario are presented in Table 5.
In this scenario, the weight assigned to Novelty and Innovation was increased from 16.7% to 20.0%, with proportional reductions applied to the remaining criteria to maintain a total weight of 100%. Comparison of the adjusted and original rankings showed no rank reversal among the top criteria. Ethical Standards and Scientific Merit remained the highest-weighted domains, and the overall hierarchical ordering was preserved.
The limited magnitude of change and absence of structural rank shifts indicate that the prioritization framework is robust to plausible strategic reweighting. This suggests that the model can accommodate shifts in funding emphasis without destabilizing its core decision logic.
Discussion
This study developed a scoring model to enhance the peer-review process for research funding allocation in healthcare institutions. By establishing 10 key criteria, the model supports transparent, consistent, and impact-driven decision-making, ensuring that resources are directed towards proposals that are not only innovative and scientifically robust but also ethically sound and strategically relevant. Given the challenges of limited funding, diverse evaluation standards, and the need to balance innovation with feasibility, this model integrates expert insights to address these complexities and improve research funding practices.
The identified criteria, which span societal impact, innovation, sustainability, and collaborative funding, reflect a broader perspective on research impact, extending beyond conventional academic metrics. This aligns with growing calls for comprehensive, outcome-focused evaluation frameworks for research that prioritises both local healthcare needs and contributions to global knowledge. The following discussion explores how the model’s key components align with contemporary research funding practices, offer a balanced approach to funding high-impact projects, and provide a foundation for fostering a sustainable, innovation-driven healthcare research culture.
Refining the peer-review process
Our findings align with existing literature on the limitations and potential refinements of peer-review systems in research funding. Guthrie et al. highlight the inherent uncertainties and biases of traditional peer-review processes, including cognitive biases, cronyism, and the challenge of predicting research impact based on bibliometric indicators [19]. These insights reinforce the need for alternative approaches, such as confidence ratings and portfolio-based assessments, to refine peer-review practices and enhance fairness and effectiveness. The researchers advocate for leveraging technological advancements and exploring alternative methodologies like lotteries to complement traditional peer-review processes [19]. Our proposed scoring model aligns with this direction, balancing subjectivity with transparency to refine decision-making.
Predefined selection criteria have been widely recognised for their role in promoting transparency and prioritising impactful research. Tuffaha et al. emphasise the importance of criteria such as societal and economic benefits, stakeholder engagement, and alignment with institutional priorities [20]. These elements ensure that funding decisions address pressing real-world healthcare challenges while avoiding redundancy. However, other concepts like cost-effectiveness and systematic reviews are often underutilised in funding decisions, suggesting areas for improvement that could further strengthen the comprehensiveness of our model.
Evaluating broader impacts and social return on investment
Incorporating SROI as a key evaluation criterion ensures that funding decisions account for long-term societal benefits beyond traditional academic outputs. While publication counts and citation metrics remain dominant, SROI provides a more holistic perspective by considering broader advantages, such as improvements in public health, patient outcomes, and healthcare system efficiency. However, measuring these benefits remains challenging, mainly due to the difficulty quantifying these social impacts within the confines of traditional research frameworks. Moreover, societal benefits often unfold over extended periods of time, making them difficult to assess at the proposal stage.
Despite these complexities, integrating SROI into funding decisions can help prioritise research with tangible public benefits. This approach aligns with recent calls to expand the criteria for assessing research impact, shifting toward models that evaluate both academic contributions and their real-world applications [21]. By embedding SROI within structured scoring frameworks, research institutions can enhance their ability to allocate funds effectively while maximising societal value.
Innovation as economic catalyst
The global shift toward a knowledge-based economy underscores the importance of fostering innovation in research funding [22]. Our model prioritises transdisciplinary collaboration, recognising that innovation flourishes in diverse, multidisciplinary teams rather than through the efforts of a single principal investigator. Evaluating proposals based on collective expertise rather than individual credentials encourages participation from early-career researchers and facilitates cross-disciplinary idea exchange, strengthening the research ecosystem.
Studies indicate that deep-level diversity in culturally varied teams enhances creativity and innovation, particularly in interdependent tasks requiring collaborative problem-solving [23]. By valuing team-based approaches, our model promotes inclusivity, nurtures creativity, and ensures that innovative ideas receive the necessary support to progress from conceptualisation to implementation.
Collaborative funding and risk mitigation
High-impact research often entails financial and operational risks, necessitating collaborative funding strategies to distribute these burdens. Our model incorporates partnerships with external stakeholders, including private-sector entities, to enhance research applicability and financial resilience. Literature on collaborative funding highlights its role in risk mitigation and accelerating the translation of research into practical applications [24].
Engaging industry partners not only expands funding opportunities but also strengthens pathways for commercialisation, fostering a balanced research environment where high-risk, high-reward projects can coexist with more conventional studies. This balanced approach supports a diverse research portfolio, ensuring a sustainable and adaptive innovation ecosystem.
Sustainability and scalability
Sustainability is a fundamental consideration in healthcare research, where long-term impact is as crucial as immediate outcomes. Our model prioritises projects that demonstrate sustainability, ensuring that funded research not only addresses immediate healthcare and societal needs but also possesses the potential to be expanded effectively across different settings. This aligns with the increasing emphasis in funding literature on sustainable research practices that extend beyond individual projects to influence broader healthcare systems [25].
By supporting proposals with the potential for enduring, scalable benefits, our model maximises SROI and reinforces a resilient research culture that prioritises long-term knowledge advancement. Scalability not only extends the reach and relevance of research outcomes but also enhances healthcare systems’ ability to adapt to emerging challenges.
Balancing research and development with process improvement
While technological advancements remain a core focus of many funding models, our approach acknowledges the equal importance of research aimed at improving healthcare processes. Process-oriented research has been shown to enhance patient care and system efficiency, contributing significantly to healthcare outcomes without necessarily resulting in new technologies [26]. By accommodating both R&D-intensive projects and process-driven improvements, our model ensures a well-rounded funding strategy that strengthens the healthcare sector’s resilience and adaptability.
Context sensitivity and global relevance
Ensuring that funded research aligns with local healthcare priorities while maintaining global relevance enhances both the applicability and impact of research outcomes. Context sensitivity has been identified as a key factor in increasing the likelihood of research generating direct benefits [27]. Our model encourages projects that address pressing national healthcare challenges while contributing to the global knowledge base, fostering innovation that serves both Oman and the international community.
By integrating structured evaluation criteria, this study contributes to ongoing efforts to refine research funding mechanisms. Implementing such models enhances funding equity, promotes impactful research, and ensures that resources are allocated towards projects with the greatest potential for societal and scientific benefit.
Plans for model implementation
A phased implementation approach will be adopted to ensure the effective integration of the proposed scoring model. An initial pilot testing phase will be conducted at the Royal Hospital to compare the model’s effectiveness against traditional peer-review methods, followed by structured reviewer training to standardise evaluation practices. The model will then be embedded into the hospital’s funding framework through an online platform facilitating systematic scoring and proposal evaluation.
To promote broader adoption, national and international cross-institutional collaborations will be encouraged, aligning the model with best practices in research funding. Additionally, AI-artificial intelligence (AI)-driven decision-support tools will be integrated to optimise the process, enabling automated initial screenings, predictive impact assessments based on historical data, and bias detection in peer reviews. Natural language processing algorithms will further enhance objectivity, reducing reviewer fatigue while improving transparency.
A systematic review and update process will be established to ensure the model’s long-term relevance and effectiveness. Annual stakeholder evaluations, data-driven assessments of funded project outcomes, and adaptive learning mechanisms using AI analytics will refine selection criteria based on emerging research trends. Benchmarking against international funding frameworks will facilitate continuous improvement and alignment with best practices. Expanding the model’s application beyond the Royal Hospital and leveraging digital tools will be key priorities in enhancing research funding fairness, efficiency, and impact. By adopting these measures, healthcare institutions can maximise research investments, fostering meaningful medical innovation and advancing patient care.
This study has several limitations. First, although expert input was obtained from diverse professional backgrounds, the weighting process was conducted within a single institutional context, which may limit the generalisability of the findings to other funding environments. Second, while structured methods such as the Delphi technique and the Analytic Hierarchy Process were used to enhance transparency and consistency, the prioritisation framework remains dependent on expert judgment. Third, the sensitivity analysis focused on assessing rank stability under alternative weighting scenarios rather than full numerical recomputation of AHP matrices. Finally, the study did not evaluate the long-term impact of implementing the proposed tool in real-world funding decisions, and future research should assess its performance through longitudinal application.
Conclusion
This study developed a structured and transparent scoring model to improve the peer-review process for research funding allocation in healthcare institutions. The final framework comprised ten weighted criteria, with ethical standards (21.7%), scientific merit (19.1%), and novelty and innovation (16.7%) emerging as the most influential. These findings demonstrate the utility of a structured, transparent approach to improving consistency and accountability in research funding decisions.
By incorporating expert insights, stakeholder feedback, and a systematic weighting approach using AHP, the model addresses key challenges such as subjectivity, inconsistency, and bias in funding decisions. The findings underscore the importance of ethical standards, scientific merit, and innovation in prioritising research proposals, ensuring that resources are directed towards high-impact projects with meaningful contributions to scientific advancement and healthcare improvement. Implementing this model has the potential to enhance the fairness and efficiency of research funding processes, fostering a culture of evidence-based decision-making in healthcare research funding allocation.
Supporting information
S1 Appendix. Appendix 1: Final list of criteria determined for a peer-review decision support tool for research funding.
https://doi.org/10.1371/journal.pone.0350938.s001
(DOCX)
Acknowledgments
The authors sincerely thank relevant stakeholders at the Royal Hospital and experts from the Planning and Studies Directorate and Research Centre, Ministry of Higher Education, Research and Innovation, for their valuable input. Special appreciation is extended to Dr. Ahmed Al Mandhari, Undersecretary of Planning and Research, Ministry of Health; Professor Salam Al Kindi, Department of Haematology, College of Medicine and Health Sciences, Sultan Qaboos University; Dr. Sharifa Al Harthi, Decision Making Support Unit; Dr. Fahad Al Zadjali, Department of Biochemistry, College of Medicine and Health Sciences, Sultan Qaboos University; and Dr. Sultana Al Sabahi, Directorate of Research and Studies, Ministry of Health. The authors also acknowledge the use of ChatGPT (OpenAI) and Grammarly for language enhancement.
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