project research methodology pdf

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Introducing research methodology : a beginner's guide to doing a research project

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Project Management Methods, Methodologies, and Frameworks: An Exploration for Study Guild for Project Management Practitioners of Ghana

2019, Project Management Scientific Journal

Project management is driven by cost minimization, on-time project delivery, quality project deliverables, and stakeholder satisfaction. As a result, the demand for increased project management effectiveness in the early phase of the project process to enhance the project success rates and decrease project failure rates is increasing among project professionals. The purpose of this quantitative, correlational study was to evaluate the relationship between project management effectiveness and project success based upon responses from a sample comprised of 110 project managers from the Project Management Institute Consulting Community of Practice (PMI-CCoP). The study, which was informed by the scientific management and strategic management theory, used 2 existing valid and reliable survey instruments, the Project Management Effectiveness Construct and the Project Success Assessment Questionnaire, to collect the data. Pearson product-moment correlation coefficient was used to evaluate the correlation between project management effectiveness and project success. Statistically significant (p < .001) and strong positive correlations (Pearson's r ranging from 0.51 to 0.72) were found between both measures of project management effectiveness and all four measures of project success. This study provides strong evidence that among project managers who are members of the PMI-CCoP, greater project management effectiveness is correlated with greater project success. From a positive social change perspective, these findings may help to advance project management knowledge. The results also may assist organizational leaders to achieve greater project success through improvements in project management. 1.0 INTRODUCTION Projects can be brought to a successful end in various ways. But the best and most popular project management methodologies, methods, and frameworks are always changing. New concepts appear all the time. An entire string of methods, tools, and techniques lies behind all successful projects. In fact, as a project management practitioner, you'll probably get to use more than just one of these during your life. However, project management methods, methodologies, and frameworks are not just for project managers. The entire project team must understand their usage, purpose, and basic terms. This will ensure that the whole process will go smoothly regardless of your choice. Remember that no project or team is the same. A methodology or framework that worked for someone else might not be the right one for you. That's why it's best to test how you can use them for your own projects. We created this extensive guide for beginners to help you pick the project management methods, methodologies, and frameworks that will fit all your needs according to your industry and project objectives. In the last part of the article we mentioned some methods, methodologies, frameworks, guides, and other approaches that are sometimes debated in a project management context but are incorrectly labeled as project management methodologies. We also reached out to a couple of project management experts to offer you a practitioner's opinion on them. 2.0 LITERATURE REVIEW The difference between methodologies, frameworks, and methods has always been a highly-debated subject, even in fields like Research and Architecture. To help you understand these terms, let's first have a look at the following definitions: Method: The Merriam-Webster Dictionary defines a method as "a procedure or process for attaining an object: such as a systematic procedure, technique, or mode of inquiry employed by or proper to a particular discipline or a systematic plan followed in presenting material for instruction". In other words, a method refers to a single action, tool, technique, process, or way of doing something. Methodology: Looking again at the Merriam-Webster Dictionary for consistency, a methodology is "a body of methods, rules, and postulates employed by a discipline; a particular procedure or set of procedures". Essentially, a methodology is a collection of methods,

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Firend Al. Rasch

One common and essential characteristic of a project, is that it is a temporary endeavor, to achieve certain outcomes (deliverables) and to help achieve organizational/stakeholders’ objectives, with defined beginning and end. Methodologies applied in projects, tends to directly influence the efficiency and effectiveness of project outcomes. Consequently, affecting the cost, quality, scope, time and outcomes. Mistakes happens regardless of the methodology applied. The first rule in project management is that “Nothing goes as you plan” (Firend, Al. R., 2019). Methodology is defined as “strictly defined combination of logically related practices, methods, and processes that determine how best to plan, develop, control and deliver a project throughout the continuous implementation processes until successful completion and termination.” (MyManagementGuide). There are numerous definitions of methodology in project management. However, there is a shared fundamental principle across all definitions. That is, methodology in project management helps project managers direct the project, and keep it in track. Methodology help organizations to achieve outcomes that aligned with strategic objectives. This is especially true when considering that projects are expensive, changing and time consuming in nature.

Annals of "Spiru Haret". Economic Series

Ungureanu Paul Adrian

Undoubtedly, a methodology properly defined and strictly followed for project management provides a firm guarantee that the work will be done on time, in budget and according to specifications. A project management methodology in simple terms is a “must-have” to avoid failure and reduce risks, because is one of the critical success factors, such basic skills of the management team. This is the simple way to guide the team through the design and execution phases, processes and tasks throughout the life cycle of project management. Project management methodology is a strictly defined combination on practices regarding logic, methods and processes that determine how best to plan, develop and control a project along the continuous process of its implementation and successful completion. In project management there are various approaches and methods that can be used in different types of project management. All types of project methodologies can be divided into traditional and modern app...

Hazem Abdulla

This study assessed the impact of project management methodologies (PMMs) on project success in the oil and gas industry in the Kingdom of Bahrain. It also explored the different project methodologies used along with their strengths and weaknesses. Quantitative approach with the support of qualitative interviews was used to achieve the objectives of this research. A total of 95 survey responses were received and 17 interviews were conducted. Projects in the oil and gas industry are more about safety than speed, and hence, the use of comprehensive methodologies and applying the relevant methodology elements are important for oil and gas projects. Furthermore, the companies in the oil and gas industry in Bahrain have to pay more attention to their project management methodologies and get it evolved and improved over time to achieve higher project success rates.

Project Management

Waelxaah Dan Nyongesa

Previously project management methods progressed a less intricate representatives comprising of smaller and more effortlessly controlled projects. Nonetheless, the modern world project is vast and complex and significantly entail more significant risk. Generally, large and complex projects include several delivery units, vendors, and subcontractors where the delivery of these activities demand an effective management and control approach.

Pamela McClinton

International Journal of Information Technology Project Management

David Ackah (PhD)

The project management domain includes many well-defined methodologies such as the Project Management Body of Knowledge: PMBoK (Project Management Institute, 2008). On the other hand, project failures rate is quite high (Woolridge, Hale, Hale, & Sharpe, 2009). An interesting question is: Does using these methods improve project performances? This paper reports on a study that was performed to investigate the added value of using a project management methodology versus an intuitive managing approach. The results indicate that the project performances improved by using a systematic approach.

Christina Chin

Journal of Project Management Practice

Zulkiflee Abdul Samad

The project management discipline has been developed worldwide through the practice and theories implemented in various types of projects. Prominent organizational bodies have outlined ways to practice project management. This study aims to highlight the differences between standards, guides and methods developed by these bodies and to evaluate their contribution to the project management profession. The differences were discussed through four aspects: approach, life cycle, procurement and stakeholders. Interpretation of the goals and objectives, transparency, accountability and ethics require further deliberation.

Journal of engineering, project, and production management

Dr. Mukhtar AL-Hashimi

Mohamed Osama

Dr Mohamed Osama

Construction projects in Egypt are categorized with high uncertainties. Coping with change in construction projects is such a big challenge that a project manager could face in managing a project. Change is something evitable specially when addressed from the owners’ side. In this certain situation and the dynamic environment of construction projects, flexibility and elasticity are needed to tackle change. The aim of this thesis is to develop a methodology to react to change easily. Agile project management is introduced to the construction sector in Egypt, as it has proven its success in the IT industry all over the world. Triangulation of different methods where used to gather data about agile project management. More specifically, interviews with experts from the field, a questionnaire to get respondents opinions about integrating agile methods to the construction projects and finally developing a medium sized project with the agile practice to test out the findings all together. Agile can be determined to react to change efficiently and effectively in construction projects with some amendments to cope with the characteristics of this enormous field. In conclusion, agile methods are a catalyst for changes in construction projects in the dynamic environment of Egypt, with expanding the methodology in alliance to cope with construction management features. Agile project management works is shorter cycles than traditional project management besides more creative and dependent teams. Client involvement in managing a project is one of the major factors that speeds up a project. Applying agile methodologies will decrease time, cost and escalate customer satisfaction in the construction field in the Egyptian economy.

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When learning how to write a research proposal, it is important to start with a detailed plan that outlines the objectives, methodology, and significance of a research project. A research proposal is a crucial document for securing funding, gaining approval from academic committees, or outlining a structured plan for personal research endeavours. Crafting a compelling research proposal requires a clear understanding of the subject matter, a well-defined research question, and a meticulous approach to planning and presenting your research. This article will explore how to write a winning research proposal and how to navigate the challenges associated with it.

Understanding the Components of a Research Proposal

A well-structured research proposal typically includes several key components. Each section serves a specific purpose and contributes to the overall coherence and persuasiveness of the proposal.

The title of your research proposal should be concise, descriptive, and indicative of the main research question or hypothesis. A well-crafted title captures the essence of the study and draws the reader’s attention.

2. Abstract

The abstract is a brief summary of the research proposal, usually no more than 250 words. It should provide an overview of the research problem, objectives, methodology, and potential implications. The abstract should be clear and succinct, giving readers a quick understanding of what the proposal entails.

3. Introduction

The introduction sets the stage for your research by providing background information on the topic, outlining the research problem, and stating the research objectives. This section should:

• Introduce the topic: Provide context and explain why the topic is important.
• State the research problem: Clearly define the issue or gap in knowledge that your research aims to address.
• Outline the research objectives: Specify the aims of your research and the questions you intend to answer.

4. Literature Review

The literature review demonstrates your understanding of the existing research on your topic. This section should:

• Summarise relevant studies: Discuss key findings from previous research that relate to your topic.
• Identify gaps: Highlight areas where further research is needed.
• Justify your research: Explain how your study will contribute to the existing body of knowledge.

5. Research Methodology

The methodology section outlines the research design and the methods you will use to collect and analyse data. This section should include:

• Research design: Describe whether your study is qualitative, quantitative, or mixed-methods.
• Data collection methods: Detail how you will gather data (e.g., surveys, interviews, experiments).
• Data analysis methods: Explain how you will analyse the data (e.g., statistical analysis, thematic analysis).
• Ethical considerations: Address any ethical issues related to your research and how you will handle them.

6. Research Plan and Timeline

Provide a detailed plan of the research activities and a timeline for completing each phase of the project. This section should demonstrate that your research is feasible within the given timeframe.

7. Budget (if applicable)

If you are seeking funding, include a budget that outlines the estimated costs of your research. Be specific about how funds will be allocated (e.g., equipment, travel, participant incentives).

8. Expected Outcomes and Impact

Discuss the potential outcomes of your research and its significance. Explain how your findings could contribute to the field, inform policy, or have practical applications.

9. References

List all the sources you cited in your proposal. Use a consistent and appropriate citation style (e.g., APA, MLA, Chicago).

Tips for Writing a Strong Research Proposal

Be clear and concise.

Use clear and straightforward language. Avoid jargon and complex sentences that might confuse readers. Aim for clarity and precision in explaining your research.

Stay Focused

Ensure that your proposal remains focused on the research question and objectives. Avoid including irrelevant information that does not contribute to the understanding of your proposed study.

Demonstrate Feasibility

Provide a realistic assessment of what can be achieved within the given timeframe and resources. Be honest about the scope of your research and any potential limitations.

Edit and Proofread

Your proposal must be clear, concise, and logically organised, following all rules of grammar, spelling, punctuation, and referencing. Adhere to the specific format and style required by your funding source or institution. Proofread your proposal multiple times, ideally with the help of a colleague or mentor, to identify and correct any mistakes or inconsistencies. Enhance the proposal’s structure, flow, and language to improve its overall quality. Ensure your proposal is compelling, engaging, and professionally presented.

Writing a research proposal is a critical step in the research process. It requires careful planning, a thorough understanding of the topic, and a clear presentation of your research plan. By following the structure outlined in this guide and paying attention to detail, you can craft a compelling research proposal that effectively communicates your ideas and secures the necessary support for your research.

At Unicaf , we offer comprehensive courses and resources to help you develop your research skills and succeed in your academic and professional endeavours. Explore our programmes today and take the next step in your research journey.

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Journal Article Reporting Standards (JARS)

APA Style Journal Article Reporting Standards offer guidance on what information should be included in all manuscript sections for quantitative, qualitative, and mixed methods research and include how to best discuss race, ethnicity, and culture.

Introducing Journal Article Reporting Standards for Race, Ethnicity, and Culture (JARS–REC)

JARS–REC were created to develop best practices related to the manner in which race, ethnicity, and culture are discussed within scientific manuscripts in psychological science.

Quantitative research

Use JARS–Quant when you collect your study data in numerical form or report them through statistical analyses.

Qualitative research

Use JARS–Qual when you collect your study data in the form of natural language and expression.

Mixed methods research

Use JARS–Mixed when your study combines both quantitative and qualitative methods.

Race, ethnicity, culture

Use JARS–REC for all studies for guidance on how to discuss race, ethnicity, and culture.

What are APA Style JARS?

APA Style Journal Article Reporting Standards (APA Style Jars ) are a set of standards designed for journal authors, reviewers, and editors to enhance scientific rigor in peer-reviewed journal articles. Educators and students can use APA Style JARS as teaching and learning tools for conducting high quality research and determining what information to report in scholarly papers.

The standards include information on what should be included in all manuscript sections for:

• Quantitative research ( Jars –Quant)
• Qualitative research ( Jars –Qual)
• Mixed methods research ( Jars –Mixed)

Additionally, the APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture ( Jars – Rec ) provide guidance on how to discuss race, ethnicity, and culture in scientific manuscripts. Jars – Rec should be applied to all research, whether it is quantitative, qualitative, or mixed methods.

• Race, Ethnicity, and Culture ( Jars – Rec )

Using these standards will make your research clearer and more accurate as well as more transparent for readers. For quantitative research, using the standards will increase the reproducibility of science. For qualitative research, using the standards will increase the methodological integrity of research.

Jars –Quant should be used in research where findings are reported numerically (quantitative research). Jars –Qual should be used in research where findings are reported using nonnumerical descriptive data (qualitative research). Jars –Mixed should be applied to research that includes both quantitative and qualitative research (mixed methods research). JARS–REC should be applied to all research, whether it is quantitative, qualitative, or mixed methods.

For more information on APA Style JARS:

• Read Editorial: Journal Article Reporting Standards
• View an infographic (PDF, 453KB) to learn about the benefits of JARS and how they are relevant to you
• Listen to a podcast with Drs. Harris Cooper and David Frost discussing JARS and implications for research in psychology

Many aspects of research methodology warrant a close look, and journal editors can promote better methods if we encourage authors to take responsibility to report their work in clear, understandable ways. —Nelson Cowan, Editor, Journal of Experimental Psychology: General

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This video describes and discusses the updated APA Style Journal Article Reporting Standards.

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• History of APA’s journal article reporting standards
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• JARS-Quant Decision Flowchart (PDF, 98KB)
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From the APA Style blog

Introducing APA Style Journal Article Reporting Standards for Race, Ethnicity, and Culture

These standards are for all authors, reviewers, and editors seeking to improve manuscript quality by encouraging more racially and ethnically conscious and culturally responsive journal reporting standards for empirical studies in psychological science.

APA Style JARS for high school students

In this post, we provide an overview of APA Style JARS and resources that can be shared with high school students who want to learn more about effective communication in scholarly research.

Happy 2022, APA Stylers!

This blog post is dedicated to our awesome APA Style users. You can use the many resources on our website to help you master APA Style and improve your scholarly writing.

APA Style JARS on the EQUATOR Network

The APA Style Journal Article Reporting Standards (APA Style JARS) have been added to the EQUATOR Network. The network aims to promote accuracy and quality in reporting of research.

APA Style JARS: Resources for instructors and students

APA Style Journal Article Reporting Standards (APA Style JARS) are a set of guidelines for papers reporting quantitative, qualitative, and mixed methods research that can be used by instructors, students, and all others reading and writing research papers.

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Speaker 1: In this video, we're going to unpack the sometimes slippery topic of narrative analysis. We'll explain what it is, consider its strengths and weaknesses, and look at when and when not to use this analysis method. By the end of the video, you'll have a clear overview of narrative analysis so that you can make well-informed decisions for your research project. By the way, if you're currently working on a dissertation, thesis, or research project, be sure to grab our free dissertation templates to help fast-track your write-up. These tried and tested templates provide a detailed roadmap to guide you through each chapter section by section. If that sounds helpful, you can find the link in the description below. So what exactly is a narrative analysis? Well, simply put, narrative analysis is a qualitative analysis method focused on interpreting individual human experiences and motivations by looking closely at the stories, the narratives, people tell in a particular context. Narrative analysis can draw on various sources, including interviews, monologues, written stories, or even recordings. In other words, it can be used on both primary and secondary data to provide evidence from the experiences described. Now that's all quite conceptual, so let's look at an example of how narrative analysis could be used in practice. Let's say you're interested in researching the beliefs of a particular author on popular culture. In that case, you might identify the characters, the plotlines, symbols, and motifs used in the stories that they write. You could then use narrative analysis to analyze these factors in combination and against the backdrop of the relevant context. This would allow you to interpret the underlying meanings and implications in their writing, and to pick apart what these reveal about the beliefs of the author. In other words, you'd look to understand the views and beliefs of the author by analyzing the narratives that run through their work. Generally speaking, there are two approaches that one can take to narrative analysis. Specifically, an inductive approach or a deductive approach. The approach you take, inductive or deductive, will have a significant impact on how you interpret your data and the conclusions you can draw from it. So it's important that you understand the difference between these two approaches. First up is the inductive approach to narrative analysis. This approach takes a bottom-up view, allowing the data to speak for itself without the influence of any preconceived notions. With the inductive approach, you begin by looking at the data and deriving patterns and themes as opposed to viewing the data through the lens of pre-existing hypotheses, theories, or frameworks. In other words, the analysis is led by the data. For example, with an inductive approach, you might notice patterns or themes in the way an author presents their characters or develops their plot. You'd then observe these patterns, develop an interpretation of what they might reveal within the context of the story, and draw conclusions in relation to your research aims. Contrasted to this is the deductive approach. With this approach, you begin by using existing theories or frameworks that a narrative can be tested against. Here, the analysis adopts particular theoretical assumptions and or provides hypotheses and then looks for evidence in a story that will either verify or disprove them. For example, your analysis might begin with a theory that wealthy authors only tell stories to garner the sympathy of their readers. Taking a deductive approach, you might then look at the narratives of wealthy authors for evidence that will substantiate or refute your theory. You would then draw conclusions about the accuracy of the theory and suggest explanations for why that might be the case. So to recap, a narrative analysis can be undertaken using either an inductive approach, where you're letting the data speak for itself and taking a more exploratory view, or you can take a deductive approach, where you're testing your data against an existing theory and assessing its accuracy. In other words, you're taking a more confirmatory view. Now that we've covered what narrative analysis is, it's important to discuss the strengths and weaknesses of this analysis method so that you can make the right choices in your research project. A primary strength of narrative analysis is the rich insight it can generate by uncovering the underlying meanings and interpretations of individual human experiences. The focus on an individual's narrative highlights the nuances and complexities of their personal experience, revealing details that might be missed or considered insignificant by other analysis methods. This makes it especially useful for those of you who are researching topics related to psychology, sociology, ideology, or cultural studies. Another strength of narrative analysis is the range of topics it can be used for, as well as the data formats it can be applied to. As an analysis method, it can be used on a wide range of data sources, including written texts, interviews, monologues, and recordings. This ability to apply narrative analysis to both primary and secondary data makes it a very flexible analysis method. All that said, just like all analysis methods, narrative analysis has its weaknesses, and it's important to understand these so that you can make informed decisions for your research project. The first drawback of narrative analysis is the problem of subjectivity and interpretation. In other words, a disadvantage of the focus on stories and their details is that they're open to being understood differently depending on who's reading them. This means that a strong understanding of the author's cultural context is crucial to developing your interpretation of the data. At the same time, it's important that you remember At the same time, it's important that you remain open-minded in how you interpret your data and avoid making any assumptions. It's a tricky balance, I know. A second weakness of narrative analysis is the issue of Since narrative analysis depends almost entirely on a subjective narrative and your interpretation, the findings and conclusions can't usually be generalized or empirically verified. Although some conclusions can be drawn about the cultural context, they're still based on what will almost always be anecdotal data and therefore wouldn't necessarily be suitable for the basis of a theory, for example. Last but not least, the focus on long-form data means that narrative analysis can be very time-consuming. Not only will you need to invest a significant amount of time to become well-versed with the data itself, but you'll also need to be well-informed regarding the author's cultural context. Ideally, you should also familiarize yourself with other interpretations of the narrative to ensure that you have a holistic view. So, if you're going to undertake narrative analysis, make sure that you allocate a generous amount of time to work through the data. If you're enjoying this video so far, please help us out by hitting that like button. You can also subscribe for loads of plain language, actionable advice. If you're new to research, check out our free dissertation writing course, which covers everything you need to get started on your research project. As always, links down in the description. Okay, so now that we've unpacked the basics of narrative analysis, as well as its strengths and weaknesses, let's have a look at when you should use it. So basically, when exactly is narrative analysis an appropriate method? As a qualitative method focused on analyzing and interpreting narratives, describing human experiences, narrative analysis is usually most appropriate for research topics that are focused on social, personal, cultural, or even ideological events or phenomena, and how they're understood at an individual level. For example, if you were interested in understanding the experiences and beliefs of individuals suffering social marginalization, you could use narrative analysis to look at the narratives and stories told by people in marginalized groups to identify patterns, symbols, or motifs that shed light on how they rationalize their experiences. In this example, narrative analysis presents a good natural fit, as it's focused on analyzing people's stories to understand their views and beliefs at an individual level. Conversely, if your research was geared towards understanding broader themes and patterns regarding an event or a phenomena, analysis methods such as content analysis or thematic analysis may be better suited. Well, depending on your research aim, of course. If you're interested in learning more about those methods, we've got videos covering them as well. Links are in the description below. All right, we've covered a lot of ground in this video, so let's do a quick recap. Narrative analysis is a qualitative method focused on interpreting human experience in the form of stories or narratives. We've discussed two approaches to narrative analysis, the inductive approach, where your interpretations and conclusions are drawn exclusively from observations within the data, and the deductive approach, where your selected narrative or stories are tested against pre-existing theories, frameworks, or hypotheses. Like all analysis methods, narrative analysis has a particular set of strengths and weaknesses. Based on those, narrative analysis is generally most appropriate for research that's focused on interpreting individual human experiences as expressed in detailed long-form accounts. If you got value from this video, please hit that like button to help more students find this content. For more videos, check out the Grad Coach channel, and make sure you subscribe for plain language, actionable tips and advice regarding all things research-related. Also, if you're looking for one-on-one support with your dissertation, your thesis, or your research project, be sure to check out our private coaching service, You can learn more about that, and book a free initial consultation at gradcoach.com.

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Title: transfusion: predict the next token and diffuse images with one multi-modal model.

Abstract: We introduce Transfusion, a recipe for training a multi-modal model over discrete and continuous data. Transfusion combines the language modeling loss function (next token prediction) with diffusion to train a single transformer over mixed-modality sequences. We pretrain multiple Transfusion models up to 7B parameters from scratch on a mixture of text and image data, establishing scaling laws with respect to a variety of uni- and cross-modal benchmarks. Our experiments show that Transfusion scales significantly better than quantizing images and training a language model over discrete image tokens. By introducing modality-specific encoding and decoding layers, we can further improve the performance of Transfusion models, and even compress each image to just 16 patches. We further demonstrate that scaling our Transfusion recipe to 7B parameters and 2T multi-modal tokens produces a model that can generate images and text on a par with similar scale diffusion models and language models, reaping the benefits of both worlds.

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• Higher proceduralist stroke thrombectomy volume is associated with reduced inpatient mortality
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• http://orcid.org/0000-0002-2854-649X Andrew B Koo 1 ,
• Daniela Renedo 1 ,
• John Ney 2 ,
• http://orcid.org/0000-0003-3357-4134 Abdelaziz Amllay 1 ,
• Matthew Kanzler 1 ,
• Sasha Stogniy 1 ,
• http://orcid.org/0000-0003-2601-8850 Ali M Alawieh 3 ,
• Nanthiya Sujijantarat 1 ,
• http://orcid.org/0000-0002-5147-1377 Joseph Antonios 1 ,
• http://orcid.org/0000-0001-8909-9761 Sami Al Kasab 4 ,
• http://orcid.org/0000-0001-9223-6640 Ajay Malhotra 5 ,
• Ryan Hebert 1 ,
• http://orcid.org/0000-0003-3234-9541 Charles Matouk 1 ,
• http://orcid.org/0000-0001-8178-8597 Adam de Havenon 6
• 1 Department of Neurosurgery , Yale School of Medicine , New Haven , Connecticut , USA
• 2 Department of Neurology , Department of Veteran's Affairs , West Haven , Connecticut , USA
• 3 Department of Neurosurgery , Emory University , Atlanta , Georgia , USA
• 4 Department of Neurology and Neurosurgery , Medical University of South Carolina , Charleston , South Carolina , USA
• 5 Department of Radiology and Biomedical Imaging , Yale University School of Medicine , New Haven , Connecticut , USA
• 6 Department of Neurology, Yale Center for Brain and Mind Health , Yale School of Medicine , New Haven , Connecticut , USA
• Correspondence to Dr Adam de Havenon; adam.dehavenon{at}yale.edu

Background The aim of this study was to determine the impact of endovascular thrombectomy (EVT) proceduralist volume on in-hospital mortality in acute ischemic stroke (AIS) patients.

Methods We performed a retrospective cohort study using the 2020 Florida State Inpatient Database, including adult patients who had a diagnosis of AIS and underwent EVT during the same admission. The primary study outcome was in-hospital death. We used Youden’s Index to define an optimal threshold for number of EVTs/year/provider. Based on this cut-point, the cohort was dichotomized into low and high proceduralist volume groups. We fit logistic regression models to mortality in the full cohort, both as univariate analyses and after adjusting for covariates.

Results Among 3143 AIS patients who underwent EVT, 1907 patients across 59 hospitals and 106 providers met our inclusion criteria. Among the providers, the median number of EVTs performed was 13.5 (IQR 7–25). The optimal cut-point was 17 EVTs. Demographics and comorbidities were similar between the cohorts. The high volume strata had a lower rate of in-hospital mortality (low volume 11.0% vs high volume 7.2%, P=0.005). After adjusting for potential confounders, high proceduralist volume remained significantly associated with lower odds of in-hospital death (OR 0.52, 95% CI 0.36 to 0.76, P=0.001). The difference in absolute risk of death was 4.8% (P=0.005).

Conclusions We found that high proceduralist volume, defined by ≥18 EVTs/year, was associated with reduced in-hospital morality. Further research is necessary to understand the effects of proceduralist experience and benchmarks for technical proficiency in stroke care.

• Thrombectomy

Data availability statement

Data are available upon reasonable request. The data are available from the Healthcare Cost and Utilization Project under the auspices of the Agency for Healthcare Research and Quality, or by the authors upon reasonable request.

https://doi.org/10.1136/jnis-2024-022021

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Contributors All authors significantly contributed to this manuscript. Concept and design: AK, SK, AM, RH, CM, and ADH. Data acquisition: AK, JN, and ADH. Data analysis and interpretation: AK and ADH. Drafting the first manuscript: AK, DR, AA, MK, and SS. Revision of the manuscript for important intellectual content: DR, AA, NS, and JA. Guarantor of study: ADH. Approval of final manuscript version for submission: all authors.

Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

Competing interests None declared.

Provenance and peer review Not commissioned; externally peer reviewed.

Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

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