Conceptual Framework Model Research Articles

Health impact of borders: general reflections and a case study from the Polish–German border

Background and objectivePolitical, economic, communicative and cultural borders still limit the accessibility of acute healthcare services for patients so that they frequently have to accept longer distances to travel to the next provider within their own country. In this paper, we analyze the impact of borders and opening of borders on acute medical care in hospitals and on patients in border regions.MethodsWe develop a conceptual framework model of cross-border healthcare and apply it to the Polish–German border area. The model combines the distance decay effect, a catchment area analysis, economies of scale and the learning curve.ResultsBorders have a major impact on acute medical care in hospitals and on patients. Setting of new borders will reduce the accessibility of health facilities for patients or require the establishment of new hospitals. Reopening borders might induce a vicious circle leading to the insolvency of a hospital which might result in poorer health for some patients.ConclusionStrong effort should be invested to overcome political and cultural borders to improve the health of the population in border regions. Similarly, increased cross-border acute healthcare must be seen in the context of rural health and the special situation of small rural hospitals in rural peripheral areas.

Tourist walkability and sustainable community-based tourism: conceptual framework and strategic model

PurposeThis paper aims to determine the significance of tourist walkability on three community-based tourism sustainability indicators, namely, the economic, social and environmental benefits and costs impacting community’s quality of life through the lens of the triple bottom line approach with the institutional theory.Design/methodology/approachThis study views institutions as either enabling or restricting the sustainable community-based tourism because institutions influence resource integration and value assessment by the beneficiary. Moreover, institutions also lead the co-creation of sustainable community-based tourism among various stakeholders. Drawing on this conceptualisation, the notion of sustainable community-based tourism is filtered through the lens of institutional theory. Thus, this work approaches sustainable community-based tourism as a dynamic process of co-creating a tourist destination formed by different actors’ and institutions within the ecosystem of the tourist destination. Meanwhile, the triple bottom line benefits and costs experienced by the overall community would produce net effects on the residents’ perceptions of sustainable tourism.FindingsThis paper classifies both tangible and intangible costs and benefits because of tourist walkability and its triple bottom line trade-offs experienced by tourists and residents. This paper penetrates new grounds by reviewing the triple bottom line impacts of tourist walkability on residents’ quality of life. Government policies as mediating variable and national culture and individual personalities of tourists and residents as moderating variables were discussed. A conceptual framework named Tourist Walkability Sustainable Tourism Impact on Residents (TWSTIR) is proposed. Finally, a Sustainable Community-based Tourism Strategic (SCBTS) model which is based on the two dimensions of intensity of tourist walkability and residents’ quality of life is proposed.Research limitations/implicationsResearch limitations may include a lack of assessment on political, technological and legal issues, and therefore, future research is warranted in these three areas. Some emotions and attitudes of the residents may not be captured since the Gross National Index (Gross National Happiness) may have its inherent blind spots.Practical implicationsThis paper would be of interest to the scholarly world, as its original idea and concluding research agenda are burrowing into a new sub-field of tourism research. In view of growth and degrowth of sustaining community-based tourism, the SCBTS model is presented to provide directions for tourism policymakers and entrepreneurs to formulate and implement appropriate strategy for the tourist walkability activity per se and investment in the accompanying infrastructure.Social implicationsThis paper also presents the sacrifices and inequities in the communities and the relevance of government policies, national culture and individual personalities of tourists and residents, in which the attention of tourism policymakers and the communities that thrive on the travel and tourism industry should not be neglected.Originality/valueThe idea and discussion of this paper is original. This paper burrows into a new sub-field of tourism research. Tourist walkability needs more attention from the scholars, as this tourist activity can have positive and negative effects on residents’ quality of life. The TWSTIR framework is developed to discuss the relationships of tourist walkability, triple bottom line concept and residents’ quality of life within the sustainable community-based tourism scope. The SCBTS model is presented for tourism policymakers and entrepreneurs to perform appropriate strategy for the tourist walkability activity and investment in the accompanying infrastructure.

Evaluation of the positive impacts of e-customs implementations on foreign trade by fuzzy AHP method

This study aims to evaluate the positive impacts of e-customs implementations on international trade and rank these impacts hierarchically according to their importance weights. For this purpose, Fuzzy Analytical Hierarchy Process (AHP) method was applied to analyze the importance weights of each impact. Data were collected from the experts by conducting a survey prepared following the study's research method. Questionnaire forms were structured within the conceptual model framework created in line with the literature review and expert decisions. Questionnaires were sent via e-mail to the experts and fully completed seven of them were included in the analysis. Results of the study demonstrate that the Time criterion has the highest impact on e-customs implementations among the main criteria. Besides, the first three important impacts of e-customs implementations among the sub-criteria are ease of transactions, reduced bureaucracy, and faster transactions. The findings obtained from this study are supposed to contribute to the studies concerning e-customs applications.

Developing a Conceptual Framework Model for Effective Perishable Food Cold-Supply-Chain Management Based on Structured Literature Review

This paper reviews the literature on perishable food cold-chain management (FCCM) in order to assess its current state, pinpoint its knowledge gaps, and suggest a framework for addressing the issues faced by this industry. This work examines 103 academic articles on the topic of the perishable food supply chain published in various journals between 2001 and 2022. Research publications were selected from two reputed databases—Scopus and Web of Science. The study finds that the current trend in FCCM is toward sustainable FCCM, which offers financial, ecological, and social benefits. However, sustainable FCC practices are more common in wealthy nations but are still lacking in developing countries. High lead times, costs, waste, order returns, complaints, and dissatisfied consumers are the results of a fragmented market and the associated proliferation of chain intermediates. The authors have also developed a conceptual framework based on the findings that illustrates the interconnected nature of the food cold-chain facilities, collaboration among food cold-chain (FCC) stakeholders, concern among FCC stakeholders, economic enhancement, fulfilment of FCC stakeholders’ responsibilities, and overall functioning of the FCC. This study may be helpful to FCC professionals, food regulators, government authorities, and researchers because it gives a concise picture of the state of research in the field.

A conceptual modelling framework for assessment multiple soil degradation: A case study in the region of Šumadija and Western Serbia

Soil degradation is a global problem and researchers are facing the challenge of assessing the scale, trends, and consequences of contributing processes. With this in mind, this study implemented the new concept of multiple soil degradation indices (MSDI) for the first time in the region of Šumadija and Western Serbia (SWS). This concept enables the simultaneous integration of several environmental components that can act separately or synergistically and offers concrete answers and information on the state and distribution of physical (PSDI), chemical (CSDI) and biological (BSDI) soil degradation. Using several different geospatial-modelled approaches, results indicated that physical degradation was the greatest contributor to soil degradation in the SWS region with an impact of 55%, followed by chemical degradation at 16%, while biological degradation only had a 6% impact. The dominant indicator of physical degradation was the vegetation cover management factor with an impact of approximately 58%, while for chemical degradation it was soil organic matter, with a relative impact of almost 49%. Total microflora and total number of fungi were the most significant biological indicators with an average impact of approximately 43%. In addition, this study indicated that about 59% of the region is currently degraded, with about 44% of it classified as moderately degraded. The results of this study offer new insights into the geospatial dynamics of interactive degradation processes in Serbia and can form the basis for strengthening scientific, expert, and political support when implementing international and national policies concerned with protecting soil from degradation.

Using Pop-GUIDE to Assess the Applicability of MCnest for Relative Risk of Pesticides to Hummingbirds

Hummingbirds are charismatic fauna that provide important pollination services, including in the continental US, where 15 species regularly breed. Compared to other birds in North America, hummingbirds (family Trochilidae) have a unique exposure route to pesticides because they forage on nectar. Therefore, hummingbirds may be exposed to systemic pesticides borne in nectar. They also may be particularly vulnerable to pesticide exposure due to their small size and extreme metabolic demands. We review relevant factors including hummingbird life history, nectar residue uptake, and avian bioenergetic considerations with the goal of clearly identifying and articulating the specific modeling challenges that must be overcome to develop and/or adapt existing modeling approaches. To help evaluate these factors, we developed a dataset for ruby-throated hummingbirds (Archilochus colubris) and other avian species potentially exposed to pesticides. We used the systemic neonicotinoid pesticide imidacloprid as an illustration and compared results to five other common current use pesticides. We use the structure of Pop-GUIDE to provide a conceptual modeling framework for implementation of MCnest and to compile parameter values and relevant algorithms to predict the effects of pesticide exposure on avian pollinators. Conservative screening assessments suggest the potential for adverse effects from imidacloprid, as do more refined assessments, though many important limitations and uncertainties remain. Our review found many areas in which current USEPA avian models must be improved in order to conduct a full higher-tier risk assessment for avian pollinators exposed to neonicotinoid insecticides, including addition of models suitable for soil and seed treatments within the MCnest environment, ability to include empirical residue data in both nectar and invertebrates rather than relying on existing nomograms, expansion of MCnest to a full annual cycle, and increased representation of spatial heterogeneity. Although this work focuses on hummingbirds, the methods and recommendations may apply more widely to other vertebrate pollinators.

Artificial Intelligence and Groups: Effects of Attitudes and Discretion on Collaboration

We theorize about human-team collaboration with AI by drawing upon research in groups and teams, social psychology, information systems, engineering, and beyond. Based on our review, we focus on two main issues in the teams and AI arena. The first is whether the team generally views AI positively or negatively. The second is whether the decision to use AI is left up to the team members (voluntary use of AI) or mandated by top management or other policy-setters in the organization. These two aspects guide our creation of a team-level conceptual framework modeling how AI introduced as a mandated addition to the team can have asymmetric effects on collaboration level depending on the team’s attitudes about AI. When AI is viewed positively by the team, the effect of mandatory use suppresses collaboration in the team. But when a team has negative attitudes toward AI, mandatory use elevates team collaboration. Our model emphasizes the need for managing team attitudes and discretion strategies and promoting new research directions regarding AI’s implications for teamwork.

Barriers and facilitators to maintaining a high level of polypharmacy adherence in people living with HIV: A scoping review.

Objectives: With the prolongation of life span and increasing incidence of comorbidities, polypharmacy has become a challenge for people living with HIV/AIDS (PLWH). This review aimed to identify barriers and facilitators to maintaining a high level of polypharmacy adherence in people living with HIV/AIDS. Methods: Nine electronic databases were searched for studies from 1996 to October 2021. Studies were included if they were conducted with adults living with HIV/AIDS and reported barriers and facilitators to maintaining a high level of polypharmacy adherence. This review presents a conceptual framework model to help understand the barriers and facilitators. Results: Twenty-nine studies were included. The majority of publications were observational studies. Eighty specific factors were identified and further divided into five categories, including individual factors, treatment-related factors, condition-related factors, healthcare provider-related factors, and socioeconomic factors, based on the multidimensional adherence model (MAM). Conclusion: Eighty factors associated with polypharmacy adherence among people living with HIV/AIDS were identified and grouped into five major categories. Healthcare providers can make decisions based on the five categories of relevant factors described in this paper when developing interventions to enhance polypharmacy adherence. It is recommended that medications be evaluated separately and that an overall medication evaluation be conducted at the same time to prevent inappropriate polypharmacy use.

Developing an Inpatient Relationship Centered Communication Curriculum (I-RCCC) rounding framework for surgical teams

BackgroundMorning rounds by an acute care surgery (ACS) service at a level one trauma center are uniquely demanding, given the fast pace, high acuity, and increased patient volume. These demands notwithstanding, communication remains integral to the success of surgical teams. Yet there are limited published curricula that address trauma inpatient communication needs. Observations at our institution confirmed that the surgical team lacked a shared mental model for communication. We hypothesized that creating a relationship-centered rounding conceptual framework model would enhance the provider-patient experience.Study designA mixed-methods approach was used for this study. A multi-pronged needs assessment was conducted. Provider communion items for Press Ganey and Hospital Consumer Assessment of Healthcare Providers and Systems (HCAHPS) surveys were used to measure patients’ expressed needs. Faculty with experience in relationship-centered communication observed morning rounds and documented demonstrated behaviors. A five-hour workshop was designed based on the identified needs. A pre-and post-course Assessment and course evaluation were conducted. Provider-related patient satisfaction items were measured six months before the course and six months after the workshop.ResultsNeeds assessment revealed a lack of a shared communication framework and a lack of leadership skills for senior trauma residents. Barriers included: time constraints, patient load, and interruptions during rounds. The curriculum was very well received. The self-reflected behaviors that demonstrated the most dramatic change between the pre and post-workshop surveys were: I listened without interrupting; I spoke clearly and at a moderate pace; I repeated key points; and I checked that the patient understood. All these changed from being performed by 50% of respondents “about half of the time” to 100% of them “always”. Press Ganey top box likelihood to recommend (LTR) and provider-related top box items showed a trend towards improvement after implementing the training with a percentage difference of up to 20%.ConclusionThe Inpatient Relationship Centered Communication Curriculum (I-RCCC) targeting senior residents and Nurse Practitioners (NP) was feasible, practical, and well-received by participants. There was a trend of an increase in LTRs and provider-specific patient satisfaction items. This curriculum will be refined based on the study results and potentially scalable to other surgical specialties.

SHAPING MILLENNIALS’ ATTITUDES TOWARDS LUXURY BRANDS IN INTERNATIONAL CITIES: THE CASE OF ABU DHABI

This study aims to investigate the impact of two intrinsic motives (perceived self-identity and perceived self- status) and two other extrinsic motives (celebrities and social media presence) on millennials' attitudes towards luxury brands; ultimately reflecting on their buying intention. Illustrated through a conceptual framework model, results reveal that intrinsic motives strongly influence millennials' attitudes while extrinsic motives slightly influence their attitudes towards luxury brands; both resulting in molding millennials' buying intention correspondingly.

Developing Privacy Incident Responses to Combat Information Warfare

Violations of privacy harm real people, and as nation-state actors grow their information warfare capabilities, civilians suffer these harms as part of coordinated and targeted actions on objectives. When privacy harms manifest, they allow threat actors to injure data subjects by weaponizing their information to harm individuals, communities, and societies. These attacks injure civilians as the confidence of legitimate authorities, institutions, and defences is eroded, and consequences may impact national security. Distinct from cybersecurity, privacy depends upon confidentiality, integrity, and availability but encompasses a unique set of concerns. Whereas security incident response has an established practice and research history, approaches to privacy incident response, such as unauthorized disclosure, are not well researched or documented in academic literature in the unique context of privacy. By mapping privacy harm to techniques and tactics, a cohesive framework emerges to distinguish tailored mitigation strategies for each. This paper proposes a conceptual model and classification framework for privacy-related harms, tactics, techniques, and mitigation strategies to address sophisticated privacy threat actors. Using this model and framework, contingency planners can develop privacy incident response strategies to defend against the privacy harms of information warfare.

Our Healthy Community Conceptual Framework and Intervention Model for Health Promotion and Disease Prevention in Municipalities.

This paper introduces the conceptual framework and intervention model of Our Healthy Community (OHC), a new, coordinated, and integrated approach towards health promotion and disease prevention in municipalities. The model is inspired by systems-based approaches and employs a supersetting approach for engaging stakeholders across sectors in the development and implementation of interventions to increase health and well-being among citizens. The conceptual model includes a combination of a bottom-up approach emphasizing involvement of citizens and other community-based stakeholders combined with a top-down approach emphasizing political, legal, administrative, and technical support from a variety of councils and departments in local municipality government. The model operates bidirectionally: (1) by pushing political and administrative processes to promote the establishment of conducive structural environments for making healthy choices, and (2) by involving citizens and professional stakeholders at all levels in co-creating processes of shaping their own community and municipality. An operational intervention model was further developed by the OHC project while working with the OHC in two Danish municipalities. The operational intervention model of OHC comprises three main phases and key actions to be implemented at the levels of local government and community: (1) Local government: Situational analysis, dialogue, and political priorities; (2) Community: Thematic co-creation among professional stakeholders; and (3) Target area: Intervention development and implementation. The OHC model will provide municipalities with new tools to improve the citizens' health and well-being with available resources. Health promotion and disease prevention interventions are developed, implemented, and anchored in the local community by citizens and local stakeholders at municipal and local community levels using collaboration and partnerships as leverage points.

Factors Influencing Green Innovation Adoption and Its Impact on the Sustainability Performance of Small- and Medium-Sized Enterprises in Saudi Arabia

Due to the growing worries of communities and governments about the depletion of natural resources and environmental contamination, green innovation (GI) is currently receiving much attention on a global scale. This study intends to investigate how Green Innovation Adoption (GIA) influences Sustainable Performance (SNP) in Saudi Arabia’s small- and medium-sized enterprises (SMEs) based on primary research. A conceptual framework model is developed to better comprehend the relationships of Government Support (GS), External Partnership and Cooperation (EPC), Rules and Regulatory Factors (RR), Market and Customer Factors (MC), Organization and Human Factors (OH), Green Innovation Strategy (GIS), and Technology Factors (TF) with GIA. The evaluation of hypotheses is performed using the Partial Least-Squares Structural Equation Modeling (PLS-SEM) method. The study’s findings are obtained using the SPSS 24.0 and AMOS 24.0 software programs. The results of this study reveal that GS, EPC, RR, MC, OH, and TF all have a positive impact on GIA. Furthermore, it has been noted that GIA has a positive impact on the economic, social, and environmental performance of SMEs in the Kingdom of Saudi Arabia. In accordance with the findings, corporate units that use GI would produce more acceptable eco-friendly and long-term performance.

Cash Waqf Linked Sukuk Through Securities Crowdfunding in Indonesia

Islamic charitable innovations have evolved to give rise to the integration between Sukuk and cash waqf called Cash Waqf Linked Sukuk (CWLS). The integration of these two things is promising when combined, considering that Sukuk has long been named a commercial sharia instrument that aims to raise funds, while cash waqf as a sharia social instrument has played a philanthropic role. As for Indonesia, The cash waqf combined with Sukuk has become a new fiscal instrument because it has advantages in addition to contributing to development, furthermore, the returns obtained are reused into waqf money for socio-economic projects and funds invested be returned at maturity. As a legal research, this article uses qualitative analysis with statutory approaches and conceptual approaches. This article intends to introduce a new conceptual framework model innovation between CWLS and fintech types of Islamic securities crowdfunding. This innovation is for no reason considering that the use of fintech types of Islamic securities crowdfunding makes CWLS more popular and more flexible so that the funds raised are expected to be larger and can reach the broader community for the construction of more massive socio-economic projects. Furthermore, this article provides an overview of the proposed innovations in achieving the goals of maqasid al-shariah, regulations, and opportunities and challenges to be implemented in Indonesia.

From Business Objectives to Analytics and Machine Learning Solutions: A Framework for Conceptual Modeling

Analytical methods and machine learning are progressively being incorporated into all kinds of information systems. Despite the excitement around these technologies, contemporary firms nonetheless have trouble utilizing them to fully use their data and solve the company's challenges. Businesses must deal with a variety of challenges while developing business analytics and machine learning solutions, including requirements elicitation, design, development, and implementation. Although conceptual modelling and requirements engineering approaches to the process are important and relevant, little study has been done in this area. In this paper a conceptual modelling framework for business analytics and machine learning solutions that is shown and evaluated. The framework consists of instantiations, meta-models, techniques, design patterns and catalogues, rules, and recommendations. It is made up of three modelling perspectives that each reflect a distinct aspect of a solution or the perspective of a different role in the creation of such systems. Through the capture of stakeholders, strategic goals, choices, questions, and necessary insights, the Business View aids in the elicitation of business analytical needs. The Analytics Design View, which largely focuses on machine learning solutions, aids in the design of the solution by collecting algorithms, metrics, and quality criteria.

A conceptual framework for modelling the role of livestock systems in sustainable diets and a sustainable planet

The role of livestock in sustainable food systems and sustainable diets is a complex issue. It should be assessed in terms of its impacts on environmental, economic, and social sustainability, as well as the levels of animal performance, the human food supply, and the human food production system. However, such nuanced analyses are made difficult by the lack of multi-metric, multi-domain modelling frameworks and a lack of data on regional variation in livestock production. This paper proposes a conceptual biophysical modelling framework that could be used as a pathway to address existing methodology gaps and improve sustainability analyses across multiple levels. Realising this modelling framework requires clear, transparent, and enforceable frameworks for multi-scale sustainability assessments, as well as long-term investment into region-specific data collection, particularly from under-represented regions. To ensure representativeness and broader utility, this framework must also be able to model variation in both production systems and consumer dietary patterns, and the feedback loops between producer/consumer decisions and on-farm production. Beyond the level of science, this will also require concerted effort by the various actors in the livestock and food-chain sectors such as governmental bodies, the food production industry and local communities. Once realised, this framework could be used to assess trade-offs between potential food-system changes and to ensure that decisions are being made from a big picture, net-benefit perspective, while exploring methods for building flexible, diverse food systems that are sustainable across multiple scales.

Graph models for engineering design: Model encoding, and fidelity evaluation based on dataset and other sources of knowledge

Abstract Automatically extracting knowledge from small datasets with a valid causal ordering is a challenge for current state-of-the-art methods in machine learning. Extracting other type of knowledge is important but challenging for multiple engineering fields where data are scarce and difficult to collect. This research aims to address this problem by presenting a machine learning-based modeling framework leveraging the knowledge available in fundamental units of the variables recorded from data samples, to develop parsimonious, explainable, and graph-based simulation models during the early design stages. The developed approach is exemplified using an engineering design case study of a spherical body moving in a fluid. For the system of interest, two types of intricated models are generated by (1) using an automated selection of variables from datasets and (2) combining the automated extraction with supplementary knowledge about functions and dimensional homogeneity associated with the variables of the system. The effect of design, data, model, and simulation specifications on model fidelity are investigated. The study discusses the interrelationships between fidelity levels, variables, functions, and the available knowledge. The research contributes to the development of a fidelity measurement theory by presenting the premises of a standardized, modeling approach for transforming data into measurable level of fidelities for the produced models. This research shows that structured model building with a focus on model fidelity can support early design reasoning and decision making using for example the dimensional analysis conceptual modeling (DACM) framework.

Circular Economy Models in Industry: Developing a Conceptual Framework

One of the trends in sustainable economic development is the transition to circular business models, which aim to optimize goods and material flows by taking into account their cyclical nature at all production stages. Adapting circular business models to mining and mineral processing operations can serve as an impetus for mining companies to upgrade and move to a new level of technological sophistication. This article attempts to develop a conceptual framework for circular business models factoring in the nature of production chains in coal mining, power generation, and metal production to reduce production costs, expand the product range, improve sustainable development indicators, and deliver growth in company value. This article is based on desk studies that were aimed at analyzing the efficiency of circular models, organizing data on experience in rational resource use in the mining industry, and transforming basic circular models into adapted ones for the environment in which coal companies operate. This study developed a conceptual framework of options for the implementation and evaluation of circular business models using an interdisciplinary approach and taking into account the specific features of coal companies and the principle of a resource being valuable throughout its whole life cycle. The proposed conceptual framework of circular business models can be used by Russian coal companies to design corporate strategies and long-term development plans.

A Conceptual Modeling Framework to Measure the Effectiveness using ML in Business Analytics

The purpose of this article is to introduce price analytics as a tool for business. Improving outcomes using supervised machine learning for find solutions to the challenges of determining appropriate pricing for a variety of goods and shopping for goods at the best possible price. Important and necessary important to do research on business analytics many factors, dimensions, and methods for enhancing productivity of business processes, managerial effectiveness, and decision making to get an edge in the market. The use of Machine Learning in the workplace can improve results in allowing us to make prompt, informed judgments based on the data we've stored knowledge. Methods such as supervised learning are used to achievement in business, both qualitatively and quantitatively, by the entrepreneur. In this step, we accomplish this after determining the optimal pricing and distributing it. Instantly update the costs of anything in stock. Because of this, it's possible that the operational effectiveness and efficiency by the highest possible profit, the rate of all of the bookkeeping work and determining the best possible pricing to reach the goal set by the business owners. To summarize, it may be argued that Because of the incredibly competitive corporate environment, cutting-edge scientific research is needed. In particular machine learning technologies with the rise of supervised learning, data mining methods, and corporate optimization of prices in a corporate setting using analytics essential, number one, must-have, etc. Machine learning with an instructor is called supervised learning. By entering the system's recommendations on what to do and what not to do the right values for the variables to get the expected outcome. Some of the many facets of in the corporate world, including domains, orientations, and methodologies..

PD24 Robust Real-World Evidence Generation In Comparative Effects Studies – NICE’s Methods Guidance

IntroductionRecent reviews have shown that many real-world evidence (RWE) studies suffer from avoidable methodological flaws. Meanwhile, the National Institute for Health and Care Excellence (NICE) is seeing an increase in RWE submissions in Health Technology Appraisals and is keen to support the use of this evidence. However, limited guidance exists for the development and assessment of RWE, risking both missed opportunities for unbiased evidence generation and inconsistent decision making based on that evidence. As part of its RWE framework, NICE has developed methods guidance to provide clear expectations for the conduct and reporting of non-randomized comparative effects studies using real world data.MethodsA conceptual model and draft framework were developed based on established international best practices in RWE and observational research. This was refined with focused literature searches, for example, on the use of external control arm studies. We then engaged with external stakeholders to incorporate their feedback and develop case studies. A reporting template was developed and tested on multiple use cases.Results & ConclusionsThe guidance stresses the central importance of a target trial approach to study design, e.g., adopting an active comparator, new user design, where possible. Target trial emulation is a useful tool to improve the quality and transparency of RWE studies, helping to overcome selection and confounding biases. Various other study design and analytical approaches are outlined for addressing confounding bias and biases due to missing data, measurement error, or misclassification, which are common challenges in RWE. Alongside traditional approaches to sensitivity analysis, the framework promotes quantitative bias analyses which includes a range of methods to assess and communicate the potential impact of remaining bias to study findings by quantifying the direction, magnitude, and uncertainty of bias. A reporting template, based on common methodological pitfalls, is provided to help evidence developers consider key areas of bias in their work and to inform reviewers of any approaches used to investigate or resolve these.