Prioritization Process Research Articles

Growing Inwards: Densification and Ecosystem Services in Comprehensive Plans from Three Municipalities in Southern Sweden

This article analyses how urban densification, primarily in relation to ecosystem services, is addressed in comprehensive plans from three cities in southernmost Sweden: Malmö, Lund and Helsingborg. The aim was to investigate and problematise how the comprehensive plans articulate and negotiate how to build dense cities while preserving and enhancing ecosystem services. A qualitative content analysis was performed on the comprehensive plans in use during the study period. The comprehensive plans were all ambitiously formulated. However, three recurrent issues were found. Planners struggled to address the issue of scale: Ecosystem services in the city were addressed when planning for densification, while ecosystem services for the city were either omitted or mentioned in the passing. The timeframe in relation to sustainable urban development was also not clarified. Most importantly, there were profound unclarities regarding priorities. Densification was suggested to provide all positive qualities simultaneously, including enhancing and supporting ecosystem services, which is, from a systems viewpoint, not possible. We suggest that when planning for sustainable cities, based on best available research, politicians should bring the prioritisation process to the fore, to clarify and address how to plan for dense, healthy cities with functioning ecosystem services in a more holistic manner.

The Value of Better Vehicle Occupancy Estimates for Project Prioritization

Transportation projects are increasingly evaluated based on how they improve person throughput, which requires knowing the passenger car occupancy. Yet obtaining occupancies is labor intensive, leading agencies to rely on statewide values. How useful are locality-specific vehicle occupancies? A case study of 38 candidate Virginia highway investments showed an occupancy change of .15 randomly applied to one-half of the projects affects 24% to 42% of project rankings if locality-specific occupancies are used. Occupancy is not the only data element affecting project prioritization, but it is an underlooked one. The study showed that an occupancy uncertainty of .15 is equivalent to an uncertainty of 3.90% in the discount rate or 13.2% in assigned traffic volume. As these investments had a mean value of $17 M, this study demonstrated that when project prioritization metrics are based on person throughput, city-or county-specific occupancies are an integral component of a data-driven prioritization process.

Prioritization of vegetable-borne biological hazards in Argentina using a multicriteria decision analysis tool.

Vegetables, especially those eaten raw, have been implicated in several foodborne disease outbreaks. Since multiple vegetable matrices and hazards are involved, risk managers have to prioritize those with the greatest impact on public health to design control strategies. In this study, a scientific-based risk ranking of foodborne pathogens transmitted by leafy green vegetables in Argentina was performed. The prioritization process included hazard identification, evaluation criteria identification and definition, criteria weighting, expert survey design and selection and call for experts, hazard score calculation, hazard ranking and variation coefficient, and result analysis. Regression tree analysis determined four risk clusters: high (Cryptosporidum spp., Toxoplasma gondii, Norovirus), moderate (Giardia spp., Listeria spp., Shigella sonnei), low (Shiga toxin-producing Escherichia coli, Ascaris spp., Entamoeba histolytica, Salmonella spp., Rotavirus, Enterovirus) and very low (Campylobacter jejuni, hepatitis A virus and Yersinia pseudotuberculosis). Diseases caused by Norovirus, Cryptosporidium spp. and T. gondii do not require mandatory notification. Neither viruses nor parasites are included as microbiological criteria for foodstuff. The lack of outbreak studies did not allow to accurately identify vegetables as a source of Norovirus disease. Information on listeriosis cases or outbreaks due to vegetable consumption was not available. Shigella spp. was the main responsible for bacterial diarrhea, but it has not been epidemiologically associated with vegetable consumption. The quality of the available information for all hazards studied was very low and low. The implementation of good practice guidelines throughout the entire vegetable production chain could prevent the presence of the identified hazards. The current study allowed the identification of vacancy areas and could help reinforce the need for performing epidemiological studies on foodborne diseases potentially associated with vegetable consumption in Argentina.

Problem Analysis in Sub-Assembly Department Using Empathize Design Thinking and Failure Mode Effects Analysis: A Case Study of PT X

PT X is a company that engages in the production of large vehicles, particularly buses. The company currently has a sub-assembly department responsible for providing support materials used in the production process. Within the sub-assembly department, there are several constraints that affect the ongoing production process. These hindrances can lead to various losses for the company. Therefore, a study is being conducted to identify and understand the obstacles present in the sub-assembly department. The problem identification process employs the empathize stage of design thinking, aiming to determine the importance of each problem. To achieve this, a ranking system known as Failure Mode Effects and Analysis is being utilized. The results indicate the existence of six problems within the sub-assembly department. Following the prioritization process, it was determined that the primary issue revolves around inadequate administrative procedures. Based on these findings, an evaluation is planned for the company, specifically focusing on the sub-assembly department. The objective is to promptly address these problems and prevent any significant impacts on the company. This abstract emphasizes the importance of identifying departmental issues and prioritizing immediate solutions.

The reproducibility crisis meets stock assessment science: Sources of inadvertent bias in the stock assessment prioritization and review process

The broader scientific community is struggling with a reproducibility crisis brought on by numerous factors, including “p-hacking” or selective reporting that may increase the rate of false positives or generate misleading effect size estimates from meta-analyses. This results when multiple modeling approaches or statistical tests may be brought to bear on the same problem, and there are pressures or rewards for finding “significant” results. Fisheries science is unlikely to be immune to this problem, with numerous opportunities for bias to inadvertently enter into the process through the prioritization of stocks for assessment, decisions about competing model approaches or data treatments within complex assessment models, and decisions about whether to adopt assessments for management after they are reviewed. I present a simple simulation model of a system where many assessments are performed each management cycle for a multi-stock fishery, and show how asymmetric selection of assessments for extra scrutiny or re-assessment within a cycle can turn a process generating unbiased advice on fishing limits into one that is biased high. I show similar results when sequential assessments receive extra scrutiny if they show large proportional decreases in catch limits compared to a prior assessment for the same stock, especially if there are only small changes in true stock size or status over the interval between assessments. The level of bias introduced by a plausible level of asymmetric scrutiny is unlikely to fundamentally undermine scientific advice, but may be sufficient to compromise the nominal “overfishing probabilities” used in a common framework for accommodating uncertainty, and introduce a level of bias comparable to the difference between buffers corresponding to commonly-applied levels of risk tolerance.

Non-tariff measures: a methodology for the quantification of bilateral trade effects of policy measures at a product level

ABSTRACT Trade negotiators are confronted with the policy challenge of determining which non-tariff measures (NTMs) and products to focus on, particularly in the agriculture and food sectors, which face a prevalence of NTMs. Quantitative advice on the trade effects of different measures can inform one aspect of a negotiator’s multifaceted prioritization process. Despite well-established methods for the quantification of trade policies at an aggregate bilateral trade level, the product-level literature suffers from a general misapplication of economic theory, leaving much of it divergent from microeconomic foundations. Furthermore, the literature generally makes compromises that inhibit the ability to draw useful insight on importer-specific policy variables like NTMs. In light of this gap in the literature, we propose an approach that leads to a proof-of-concept quantification methodology for bilateral product-level analysis, fulfiling a need in the body politic to defensibly identify trade effects of NTMs at a bilateral and product level. International grains markets are used as an example to demonstrate the proof-of-concept.

Improving Software Requirements Prioritization through the Lens of Constraint Satisfaction

Requirements prioritization is a critical activity during the early software development process, which produces a set of key requirements to implement. The prioritization process offers a parity among the requirements based on multiple characteristics, including end-users’ preferences, cost to implement, and technical dependencies. This paper presents an interactive method to requirements prioritization that leverages the pairwise comparisons and a constraint solver. Our method employs an interactive accumulation of knowledge from the requirements analyst when the relative priority among the requirements cannot be determined based on the existing knowledge from the requirements documents. The final ranking of the requirements is produced via the constraint solver and interactive pairwise comparisons. We evaluate the proposed method using the requirements from a real healthcare project. The proposed prioritization method relying on a constraint solver outperforms state-of-the-art interactive prioritization methods in terms of effectiveness and robustness to analyst’s errors.

Input data resolution affects the conservation prioritization outcome of spatially sparse biodiversity features.

Detailed spatial data are an essential part of land use planning and decision-making. Their spatial resolution sets limitations to their use, as coarse datasets are not suitable for detecting small-scale phenomena. In this study, we explored the effects of spatial resolution on the ecological outcome of a conservation prioritization process in Zonation software. Our study area was in Evo, southern Finland, covering a mosaic of managed and conserved forests. We produced the feature layers describing the forest characteristics using high-resolution remote sensing datasets, object-based mapping methods, and forest site type data. We found that increasing the resolution above the 16 m baseline resolution resulted in substantial errors. The conservation errors were the highest for rare features related to European Aspen, whereas the common features related to dominant tree species could benefit from the growth of cell size. We conclude that adequate spatial resolution is a prerequisite for efficient conservation prioritization, and that the size and spatial distribution of the features affect the resolution requirements.

Is access to adjuvant treatments prioritized over therapies for metastatic cancer? The Israeli experience.

e18599 Background: The Israeli National Insurance Law determines a uniform benefits package ('the Health Basket') for all residents. A public committee advises each year on which new medications should be added to the Health Basket, subject to the fixed annum budget allocated by the government for this purpose. The clinical benefit of the proposed health technologies is the committee's prime consideration; however, the committee also considers the professional medical societies' prioritizations, the expected budget impact, and other social and ethical aspects. Towards the annual discussions for 2023, 63 new indications for 41 cancer drugs were proposed for the annual update. Of those, 8 were for novel neo-adjuvant/ adjuvant indications, all given high priority ranks by the Israeli Oncologists Society based on the significant disease-free survival (DFS) figures from the phase III clinical trials. Varying the adjuvant treatment practice patterns based solely on DFS figures without available overall survival (OS) data has been in much debate recently between global key opinion leaders. We, therefore, aimed to evaluate whether the Israeli decision-makers have de-facto accepted the attitude of prioritizing budgets for adjuvant/neo-adjuvant therapies as the Israeli Oncologists Society recommended. Methods: We collected data on all cancer therapies proposed for inclusion in the 2023 Health Basket update; drug name, indication, treatment setting (curative intent vs. metastatic disease therapy), ESMO-MCBS grade, and whether or not accepted for reimbursement. All data were extracted from the official Israeli Ministry of Health website publications and press releases. Results: 20% of the allocated budget for updating the National Health basket for 2023 was provided to treat solid tumor cancers. 7 out of the 8 candidate therapies in the neo-adjuvant/adjuvant settings received reimbursement approval (88%) vs. 11 out of 55 therapies for advanced/ metastatic stages of disease (20%). 13 of the 16 candidate metastatic disease therapies that had a high ESMO-MCBS score (4 or 5) were not approved for reimbursement in the 2023 annual committee discussions. Conclusions: Our retrospective evaluation of the Israeli reimbursement prioritization process reveals that decision-makers have accepted the approach of prioritizing potentially curative adjuvant therapies over treatments for patients with incurable cancer. In an era of prosperity of adjuvant therapies in a range of tumor types, concerns might arise regarding restrictions on access to novel therapies for metastatic cancer, even those with proven benefits of significantly improving patients' OS and quality of life. Future analysis should determine the impact of this trend adopted by decision-makers in Israel on disease progression and overall survival in the real-world setting.

The first positive evidence that training improves triage decisions in Greece: evidence from emergency nurses at an Academic Tertiary Care Emergency Department

BackgroundTriage refers to the process of patient prioritisation in the emergency department (ED). This is based on the severity of the patient’s illness and is performed by emergency nurses (ENs). This has a pivotal role in ensuring patient safety and in ensuring that the ED operates smoothly – so continuous and accurate training are essential. As Emergency Nursing has been formally established in Greece since 2019, it is of the uppermost importance that all Greek ENs should be trained in the use of a standardised triage system. The present study aimed to evaluate the effect of triage training of ENs in the use of the Swiss Triage System (STS) after an intervention of one week.MethodsThe effect of triage training was studied experimentally by comparing performance before and one week after training. A sample of thirty-six ENs from the University Department of Emergency Medicine at AHEPA University Hospital took part. The role of training in triage by the STS was assessed by completing the same self-administered questionnaire before and after a 45-minute e-learning program (presentation video of STS but with simulation scenarios) which was available during the period of a week. The post-training test was taken 2 weeks later, after the training process.ResultsThe most promising finding was that there was a significant improvement in the number of correct answers after the training in triage (p<0.001). A significant improvement was also detected (p<0.001) in the questions that tested vigilance in providing safe health services by ENs, whereas there was no significant association between the number of correct answers and years of emergency experience or level of education, - either before or after the intervention.ConclusionsTriage training seems to successfully improve effective and efficient triage. To the best of our knowledge, this is the first study that has demonstrated that triage training has a significant positive impact on triage performance by ENs in Greece. It is planned to support these findings by real time studies in an ED.

Meaningful coproduction with clinicians: establishing a practice-based research network with physiotherapists in regional Australia

BackgroundThe disconnect between research and clinical practice leads to research evidence that is often not useful for clinical practice. Practice-based research networks are collaborations between researchers and clinicians aimed at coproducing more useful research. Such networks are rare in the physiotherapy field. We aimed to describe (i) clinicians’ motivations behind, and enablers to, participating in a network, (ii) the process of network establishment and (iii) research priorities for a practice-based network of physiotherapists in the Hunter Region of New South Wales (NSW), Australia that supports research coproduction.MethodsWe describe the methods and outcomes of the three steps we used to establish the network. Step 1 involved consultation with local opinion leaders and a formative evaluation to understand clinicians’ motivations behind, and enablers to, participating in a network. Step 2 involved establishment activities to generate a founding membership group and codesign a governance model. Step 3 involved mapping clinical problems through a workshop guided by systems thinking theory with local stakeholders and prioritizing research areas.ResultsThrough formative evaluation focus groups, we generated five key motivating themes and three key enablers for physiotherapists’ involvement in the network. Establishment activities led to a founding membership group (n = 29, 67% from private practice clinics), a network vision and mission statement, and a joint governance group (9/13 [70%] are private practice clinicians). Our problem-mapping and prioritization process led to three clinically relevant priority research areas with the potential for significant change in practice and patient outcomes.ConclusionsClinicians are motivated to break down traditional siloed research generation and collaborate with researchers to solve a wide array of issues with the delivery of care. Practice-based research networks have promise for both researchers and clinicians in the common goal of improving patient outcomes.

Development of acompetence catalogue for physicians in training for curriculum creation with respect to delivery room training

Anesthesiologic expertise is used at various points in the delivery room. The natural turnover of professionals requires continuous education and training for patient care. In afirst survey among consultants and trainees, the desire for adelivery room-specific anesthesiologic curriculum has emerged. In order to enable acurriculum with decreasing supervision, acompetence-oriented catalogue is used in many medical fields. The gain in competence develops gradually. The participation of practitioners should be obligatory to avoid adifferentiation between theory and practice. The structural framework of curriculum development by Kern etal. provides the learning objective analysis after further evaluation. In the sense of specific learning objective definition, the present study aims to describe the competences for anesthetists in the delivery room. An expert group (active in the anesthesiology delivery room environment) developed aset of items via atwo-step online Delphi survey. The experts were recruited from the German Society for Anesthesiology and Intensive Care Medicine (DGAI). We evaluated the resulting parameters for relevance and validity in alarger collective. Lastly, we used factorial analyses to identify factors that could be used to group items into relevant scales. In total, 201participants took part in the final validation survey. During the prioritization process of Delphi analyses, competencies such as neonatal care were not followed up. Not all items developed are exclusively delivery room-related, such as managing a difficult airway. Other items are specific to the environment of obstetrics. One example is integration of spinal anesthesia into the obstetric context. Some items are exclusively related to the delivery room, such as in-house standards of care in obstetrics as abasic skill. After validation, acompetence catalogue with 8scales with atotal of 44 competence items resulted (Kayser-Meyer-Olkin criterion 0.88). Acatalogue of relevant learning objectives for anesthetists in training could be developed. It specifies the generally required content of anesthesiologic training in Germany. Specific patient groups, such as patients with congenital heart defects, are not mapped. Competencies that could also be learned outside the delivery room, should be learned before the rotation. This enables the focus on the delivery room items, especially for those to be trained who do not work in ahospital with obstetrics. The catalogue needs to be revised for completeness for its own working environment. Particularly in hospitals that do not have apediatrician available, neonatal care becomes significant. Didactic methods, such as entrustable professional activities, have to be tested and evaluated. These enable competence-based learning with decreasing supervision and reflect the reality in hospitals. As not every clinic can provide the necessary resources for this anationwide provision of documents would be helpful.

Enhancing Requirements Change Request Categorization and Prioritization in Agile Software Development Using Analytic Hierarchy Process (AHP)

Software development now relies heavily on agile methods, which call for the efficient administration and prioritization of change requests. In order to improve requirement prioritization using the Analytic Hierarchy Process (AHP) in Agile methods, this study article presents a new framework for classifying software requirements into Small Change Requests (SCRs) and Large Change Requests (LCRs). The paper examines the difficulties associated with requirement prioritization and categorization in Agile settings and offers a methodical system for dividing change requests into categories based on complexity, impact, and timeline. In order to provide a thorough grasp of the project scope and objectives, the framework considers both functional and non-functional needs. A case study containing several Agile software development projects is used to evaluate the performance of the suggested categorization and prioritization model. According to the findings, the combination of SCR and LCR categorization with AHP enables more effective teamwork and greater matching of development goals with partner objectives. The research also shows that the suggested framework's integration into the Agile development process results in a more efficient decision-making process, less time wasted on talks, and improved resource distribution. The model aids in risk mitigation by allowing a methodical and quantifiable approach to requirement prioritization. These risks are related to quick changes in project scope and changing client requirements. By presenting a fresh framework for requirement categorization and prioritization, this study adds to the current discussion on successful requirement management in Agile methods. Agile software development projects become more effective and adaptable overall thanks to the incorporation of AHP, which guarantees a more methodical and objective prioritization process. This study has the potential to greatly improve the administration of shifting needs and user expectations in Agile settings by offering a structured method to classify and rank change requests.

What values drive communities’ nutrition priorities in a resource constrained urban area in South Africa?

BackgroundVoices of under-resourced communities are recognised as important yet are often unheard in decisions about healthcare resource allocation. Deliberative public engagement can serve as an effective mechanism for involving communities in establishing nutrition priorities. This study sought to identify the priorities of community members of a South African township, Soweto, and describe the underlying values driving their prioritisation process, to improve nutrition in the first 1000 days of life.MethodsWe engaged 54 community members (28 men and 26 women aged > 18 years) from Soweto. We conducted seven group discussions to determine how to allocate limited resources for prioritising nutrition interventions. We used a modified public engagement tool: CHAT (Choosing All Together) which presented 14 nutrition intervention options and their respective costs. Participants deliberated and collectively determined their nutritional priorities. Choices were captured quantitatively, while group discussions were audio-recorded. A thematic analysis was undertaken to identify the reasons and values associated with the selected priorities.ResultsAll groups demonstrated a preference to allocate scarce resources towards three priority interventions—school breakfast provisioning, six-months paid maternity leave, and improved food safety. All but one group selected community gardens and clubs, and five groups prioritised decreasing the price of healthy food and receiving job search assistance. Participants’ allocative decisions were guided by several values implicit in their choices, such as fairness and equity, efficiency, social justice, financial resilience, relational solidarity, and human development, with a strong focus on children. Priority interventions were deemed critical to supporting children’s optimal development and well-being, interrupting the intergenerational cycle of poverty and poor human development in the community.ConclusionOur study demonstrates how public engagement can facilitate the incorporation of community values and programmatic preferences into nutrition priority setting, enabling a responsive approach to local community needs, especially in resource constrained contexts. Findings could guide policy makers to facilitate more appropriate decisions and to improve nutrition in the first 1000 days of life.

A fuzzy decision-making approach for testing activity prioritisation and its application in an engine company

Prioritising testing activities is essential for new product development to identify the most valuable tests and distinguish the critical ones from the trivial ones. Most research solves this prioritisation problem based on the high risks identified in Failure Mode and Effect Analysis (FMEA). However, an empirical case study on a UK-based engine manufacturer highlights that the aim of testing is not only to detect technical failures but also to validate customer requirements. Based on the findings identified from the empirical study, this paper proposes a systematic approach for testing activity prioritisation, where fuzzy relational decision matrices are established to link customer requirements, technical objectives and testing activities. An XOR Best–Worst Method (BWM) and an extended simple additive weighting (SAW) method are developed to calculate the weights of customer requirements and score the testing activities. The approach also handles two uncertainty scenarios during the prioritisation process, i.e. the subjective judgements of choosing from options and the linguistic vagueness of the decisions. The application in a case from the engine manufacturing company illustrates the methodological improvement in the prioritisation process. The proposed method ranks the testing activities, which suggests an order of effort distribution for the test plan.

Fuzzy Logic and Decision Making Applied to Customer Service Optimization

In the literature, the Information Technology Infrastructure Library (ITIL) methodology recommends determining the priority of incident resolution based on the impact and urgency of interactions. The RFID model, based on the parameters of Recency, Frequency, Importance and Duration in the resolution of incidents, provides an individual assessment and a clustering of customers based on these factors. We can improve the traditional concept of waiting queues for customer service management by using a procedure that adds to the evaluation provided by RFID such additional factors as Impact, Urgency and Emotional character of each interaction. If we also include aspects such as Waiting Time and Contact Center Workload, we have a procedure that allows prioritizing interactions between the customer and the Contact Center dynamically and in real time. In this paper we propose to apply a model of unification of heterogeneous information in 2-tuple linguistic evaluations, to obtain a global evaluation of each interaction by applying the Analytic Hierarchy Process (AHP), and in this way be able to have a dynamic process of prioritization of interactions.

The APPD Longitudinal Educational Assessment Research Network's First Decade.

In 2009, the Association of Pediatric Program Directors (APPD) Longitudinal Educational Assessment Research Network (LEARN), a national educational research network, was formed. We report on evaluation of the network after 10 years of operation by reviewing program context, input, processes, and products to measure its progress in performing educational research that advances training of future pediatricians. Historical changes in medical education shaped the initial development of the network. APPD LEARN now includes 74% (148 of 201) of US Pediatric residency programs and has recently incorporated a network of Pediatric subspecialty fellowship programs. At the time of this evaluation, APPD LEARN had approved 19 member-initiated studies and 14 interorganizational studies, resulting in 23 peer-reviewed publications, numerous presentations, and 7 archived sharable data sets. Most publications focused on how and when interventions work rather than whether they work, had high scores for reporting rigor, and included organizational and objective performance outcomes. Member program representatives had positive perceptions of APPD LEARN's success, with most highly valuing participation in research that impacts training, access to expertise, and the ability to make authorship contributions for presentations and publication. Areas for development and improvement identified in the evaluation include adopting a formal research prioritization process, infrastructure changes to support educational research that includes patient data, and expanding educational outreach within and outside the network. APPD LEARN and similar networks contribute to high-rigor research in pediatric education that can lead to improvements in training and thereby the health care of children.

National priority setting partnership using a Delphi consensus process to develop neonatal research questions suitable for practice-changing randomised trials in the UK

BackgroundThe provision of neonatal care is variable and commonly lacks adequate evidence base; strategic development of methodologically robust clinical trials is needed to improve outcomes and maximise research resources. Historically,...

Machine-Learning-Enhanced Blockchain Consensus With Transaction Prioritization for Smart Cities

In the given technology-driven era, smart cities are the next frontier of technology, and these smart cities aim to improve the quality of people’s lives. In this article, we introduce such future Internet of Things (IoT)-based smart cities that leverage blockchain technology. Particularly, when there are multiple parties involved, blockchain helps in improving the security and transparency of the system in an efficient manner. However, if a current fee-based or first-come–first-serve-based processing is used, emergency events may get delayed and even threaten people’s lives. Thus, there is a need for transaction prioritization based on the priority of information and a dynamic block creation mechanism for efficient data recording and faster event response. Also, our system focuses on the consortium blockchain maintained by a group of members working across different organizations to provide more efficiency. The leader election procedure in such a consortium blockchain becomes more important for the transaction prioritization process to take place honestly. Hence, in our proposed consensus protocol, we deploy a machine-learning (ML) algorithm to achieve efficient leader election, based on which a novel dynamic block creation algorithm is designed. Also, to ensure the honest block generation behavior of the leader, a peer-prediction-based verification mechanism is proposed. Both security analysis and simulation experiments are carried out to demonstrate the robustness, accuracy, and efficiency of our proposed scheme.

Improving prioritization processes for clinical practice guidelines: new methods and an evaluation from the National Heart Foundation of Australia

BackgroundReleasing timely and relevant clinical guidelines is challenging for organizations globally. Priority-setting is crucial, as guideline development is resource-intensive. Our aim, as a national organization responsible for developing cardiovascular clinical guidelines, was to develop a method for generating and prioritizing topics for future clinical guideline development in areas where guidance was most needed.MethodsSeveral novel processes were developed, adopted and evaluated, including (1) initial public consultation for health professionals and the general public to generate topics; (2) thematic and qualitative analysis, according to the International Classification of Diseases (ICD-11), to aggregate topics; (3) adapting a criteria-based matrix tool to prioritize topics; (4) achieving consensus through a modified-nominal group technique and voting on priorities; and (5) process evaluation via survey of end-users. The latter comprised the organization’s Expert Committee of 12 members with expertise across cardiology and public health, including two citizen representatives.ResultsTopics (n = 405; reduced to n = 278 when duplicates removed) were identified from public consultation responses (n = 107 respondents). Thematic analysis synthesized 127 topics that were then categorized into 37 themes using ICD-11 codes. Exclusion criteria were applied (n = 32 themes omitted), resulting in five short-listed topics: (1) congenital heart disease, (2) valvular heart disease, (3) hypercholesterolaemia, (4) hypertension and (5) ischaemic heart diseases and diseases of the coronary artery. The Expert Committee applied the prioritization matrix to all five short-listed topics during a consensus meeting and voted to prioritize topics. Unanimous consensus was reached for the topic voted the highest priority: ischaemic heart disease and diseases of the coronary arteries, resulting in the decision to update the organization’s 2016 clinical guidelines for acute coronary syndromes. Evaluation indicated that initial public consultation was highly valued by the Expert Committee, and the matrix tool was easy to use and improved transparency in priority-setting.ConclusionDeveloping a multistage, systematic process, incorporating public consultation and an international classification system led to improved transparency in our clinical guideline priority-setting processes and that topics chosen would have the greatest impact on health outcomes. These methods are potentially applicable to other national and international organizations responsible for developing clinical guidelines.