16 results on '"Khan, Nushrat"'
Search Results
2. Research data sharing, reuse, and metrics : adoption and challenges across disciplines and repositories
- Author
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Khan, Nushrat and Thelwall, Mike
- Subjects
data sharing ,data reuse ,data repositories ,research data - Abstract
Data sharing is widely believed to be beneficial to science and is now supported by digitization and new online infrastructures for sharing datasets. Nevertheless, differences in research cultures and the sporadic development of data repositories, support services, guidelines, and policies have resulted in uneven data sharing and reuse practices. An overall understanding of the current situation is therefore needed to identify gaps and next steps. In response, using two case studies and two surveys, this dissertation explores the current landscape and identifies challenges within data sharing and reuse practices. The results demonstrate how present systems and policies could be modified to support and encourage these activities. The researcher survey found that the type and format of data produced, as well as systematic data sharing varied between disciplines, with Physical Sciences and Earth and Planetary Sciences leading and Business and Economics, Engineering, and Medicine lagging in some respects. Surveys and observations were frequently produced in most fields, with samples and simulations being common in science and engineering and qualitative data being more prevalent in the social sciences, business, and humanities. Researchers who had prior data reuse experience shared data more frequently (56.8%, n=1,004) than those who only used their primary data for research (32.6%, n=396). The biodiversity case study and surveys show that secondary data are valuable for many purposes, but most struggle to find datasets to reuse. Data citations can incentivize data sharing, although a lack of appropriate data citations and reliable technologies make it difficult to efficiently track them. In biodiversity, where the sharing and reuse of open data via mature infrastructures is common, citing secondary datasets in references or data access statements has been increasing (48%, n=99). However, users simultaneously exploiting many data subsets in this field complicate the situation. This thesis makes recommendations for handling large numbers of biodiversity data subsets to attribute citations accurately. It also suggests further enhancements for the article-dataset linking service, Scholexplorer, to automatically capture such links. Based on responses from data repository managers, this research further identifies nine objectives for future repository systems. Specifically, 30% (n=34) of the surveyed managers would like integration and interoperability between data and systems, 19% (n=22) want better research data management tools, 16% (n=18) want tools that allow computation without downloading datasets, and 16% (n=18) want automated systems. It also makes 23 recommendations in three categories to support data sharing and promote further data reuse including 1) improved access and usability of data, as well as formal data citations; 2) improved search systems with suggested new features; and 3) cultural and policy-related issues around awareness and acceptance, incentives, collaboration, guidelines, and documentation. Finally, based on researcher feedback, this study proposes an alternative scoring model that combines a dataset quality score and a data reuse indicator that can be incorporated in academic evaluation systems. The outcomes from this research will help funders, policymakers and technology developers prioritize areas of improvement to incentivize data sharing and support data reuse with easily discoverable and usable data.
- Published
- 2021
3. Identifying Data Sharing and Reuse with Scholix: Potentials and Limitations
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Khan, Nushrat, Pink, Catherine J., and Thelwall, Mike
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- 2020
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4. Development and Pilot Implementation of Neotree, a Digital Quality Improvement Tool Designed to Improve Newborn Care and Survival in 3 Hospitals in Malawi and Zimbabwe: Cost Analysis Study
- Author
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Haghparast-Bidgoli, Hassan, primary, Hull-Bailey, Tim, additional, Nkhoma, Deliwe, additional, Chiyaka, Tarisai, additional, Wilson, Emma, additional, Fitzgerald, Felicity, additional, Chimhini, Gwendoline, additional, Khan, Nushrat, additional, Gannon, Hannah, additional, Batura, Rekha, additional, Cortina-Borja, Mario, additional, Larsson, Leyla, additional, Chiume, Msandeni, additional, Sassoon, Yali, additional, Chimhuya, Simbarashe, additional, and Heys, Michelle, additional
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- 2023
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5. In Hospital Mortality and Short-Term Outcomes of Acute Ischemic Stroke Patients Contracting SARS CoV-2 Infection: Experience from a Dedicated Stroke Unit in Bangladesh
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Hasan, ATM Hasibul, primary, Das, Subir Chandra, additional, Islam, Muhammad Sougatul, additional, Mansur, Mohaimen, additional, Khan, Nushrat, additional, and Chowdhury, Mohammad Shah Jahirul Hoque, additional
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- 2023
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6. The Use of Digital Health Interventions for Cardiometabolic Diseases Among South Asian and Black Minority Ethnic Groups: Realist Review
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Goswami, Aumeya, primary, Poole, Lydia, additional, Thorlu-Bangura, Zareen, additional, Khan, Nushrat, additional, Hanif, Wasim, additional, Khunti, Kamlesh, additional, Gill, Paramjit, additional, Sajid, Madiha, additional, Blandford, Ann, additional, Stevenson, Fiona, additional, Banerjee, Amitava, additional, and Ramasawmy, Mel, additional
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- 2023
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7. Software development process of Neotree - a data capture and decision support system to improve newborn healthcare in low-resource settings
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Khan, Nushrat, primary, Crehan, Caroline, additional, Hull-Bailey, Tim, additional, Normand, Charles, additional, Larsson, Leyla, additional, Nkhoma, Deliwe, additional, Chiyaka, Tarisai, additional, Fitzgerald, Felicity, additional, Kesler, Erin, additional, Gannon, Hannah, additional, Kostkova, Patty, additional, Wilson, Emma, additional, Giaccone, Matteo, additional, Krige, Danie, additional, Baradza, Morris, additional, Silksmith, Daniel, additional, Neal, Samuel, additional, Chimhuya, Simbarashe, additional, Chiume, Msandeni, additional, Sassoon, Yali, additional, and Heys, Michelle, additional
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- 2022
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8. Protocol for an intervention development and pilot implementation evaluation study of an e-health solution to improve newborn care quality and survival in two low-resource settings, Malawi and Zimbabwe: Neotree
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Wilson, Emma, primary, Gannon, Hannah, additional, Chimhini, Gwendoline, additional, Fitzgerald, Felicity, additional, Khan, Nushrat, additional, Lorencatto, Fabiana, additional, Kesler, Erin, additional, Nkhoma, Deliwe, additional, Chiyaka, Tarisai, additional, Haghparast-Bidgoli, Hassan, additional, Lakhanpaul, Monica, additional, Cortina Borja, Mario, additional, Stevenson, Alexander G., additional, Crehan, Caroline, additional, Sassoon, Yali, additional, Hull-Bailey, Tim, additional, Curtis, Kristina, additional, Chiume, Msandeni, additional, Chimhuya, Simbarashe, additional, and Heys, Michelle, additional
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- 2022
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9. Work, Research Data and Play:The RDM Adventure Game
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Ball, Alex, Simango, Samuel, Khan, Nushrat, Bray, George, and McCutcheon , Valerie
- Subjects
Educational games ,Research support ,Pedagogy ,Games-based learning ,Researcher training ,Researcher skills - Abstract
The Research Data Management Adventure is interactive fiction that takes the player through the life cycle of a project, highlighting how decisions about research data can have far-reaching consequences. We explain how the game was developed, highlight some key features, and discuss researchers’ reactions to it.
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- 2022
10. Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree.
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Heys, Michelle, Kesler, Erin, Sassoon, Yali, Wilson, Emma, Fitzgerald, Felicity, Gannon, Hannah, Hull‐Bailey, Tim, Chimhini, Gwendoline, Khan, Nushrat, Cortina‐Borja, Mario, Nkhoma, Deliwe, Chiyaka, Tarisai, Stevenson, Alex, Crehan, Caroline, Chiume, Msandeni Esther, and Chimhuya, Simbarashe
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HEALTH facilities ,NEWBORN infants ,MEDICAL personnel ,COVID-19 ,NEONATAL nursing ,INSTRUCTIONAL systems ,NEONATAL mortality - Abstract
Introduction: Improving peri‐ and postnatal facility‐based care in low‐resource settings (LRS) could save over 6000 babies' lives per day. Most of the annual 2.4 million neonatal deaths and 2 million stillbirths occur in healthcare facilities in LRS and are preventable through the implementation of cost‐effective, simple, evidence‐based interventions. However, their implementation is challenging in healthcare systems where one in four babies admitted to neonatal units die. In high‐resource settings healthcare systems strengthening is increasingly delivered via learning healthcare systems to optimise care quality, but this approach is rare in LRS. Methods: Since 2014 we have worked in Bangladesh, Malawi, Zimbabwe, and the UK to co‐develop and pilot the Neotree system: an android application with accompanying data visualisation, linkage, and export. Its low‐cost hardware and state‐of‐the‐art software are used to support healthcare professionals to improve postnatal care at the bedside and to provide insights into population health trends. Here we summarise the formative conceptualisation, development, and preliminary implementation experience of the Neotree. Results: Data thus far from ~18 000 babies, 400 healthcare professionals in four hospitals (two in Zimbabwe, two in Malawi) show high acceptability, feasibility, usability, and improvements in healthcare professionals' ability to deliver newborn care. The data also highlight gaps in knowledge in newborn care and quality improvement. Implementation has been resilient and informative during external crises, for example, coronavirus disease 2019 (COVID‐19) pandemic. We have demonstrated evidence of improvements in clinical care and use of data for Quality Improvement (QI) projects. Conclusion: Human‐centred digital development of a QI system for newborn care has demonstrated the potential of a sustainable learning healthcare system to improve newborn care and outcomes in LRS. Pilot implementation evaluation is ongoing in three of the four aforementioned hospitals (two in Zimbabwe and one in Malawi) and a larger scale clinical cost effectiveness trial is planned. [ABSTRACT FROM AUTHOR]
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- 2023
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11. Is data reuse worth tracking? A survey of data repositories on current practices and challenges
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Khan, Nushrat, Thelwall, Mike, and Kousha, Kayvan
- Abstract
With scientific communities and funders pushing to share research data, it is important to examine whether and how these data are reused. This paper reports the results of a survey (n=152 responses so far) of data repositories (the previous largest similar study had 73 responses). The goal is to understand current practices for using technical frameworks and data services, interest in tracking data reuse, what types of metrics are currently being tracked and exposed, and the challenges and priorities of repositories. Among the respondents, 46% are collecting discipline-specific data and 35% are institution-based data repositories. Dspace, Eprint, Fedora, Figshare for institutions, and Dataverse were all used, largely by institutional repositories. Astonishingly, 50% had developed in-house systems and most are discipline specific. Only 27% of the repositories reported tracking data reuse but a further 53% are interested in doing so. Similarly, whereas 56% mentioned citation counts as ���extremely useful��� in understanding reuse, 35% are currently tracking them and 23% are exposing citation counts in their repositories. Amongst those who are currently tracking data reuse, 24% are institutional and the remaining 76% are discipline-specific or another type of repository. However, the number of institutional and disciplinary repositories is almost equal for those who are interested in tracking. This suggests that institutional repositories need evidence of impact but often lack the infrastructure to deliver it. A lack of human resources (55%), user engagement (50%) and infrastructure funding (43%) were the top three challenges mentioned by different types of repositories.
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- 2021
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12. Is useful research data usually shared? An investigation of genome-wide association study summary statistics
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Thelwall, Mike, primary, Munafò, Marcus, additional, Mas-Bleda, Amalia, additional, Stuart, Emma, additional, Makita, Meiko, additional, Weigert, Verena, additional, Keene, Chris, additional, Khan, Nushrat, additional, Drax, Katie, additional, and Kousha, Kayvan, additional
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- 2020
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13. Polyherbal Formulation Concept for Synergic Action: A Review
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Karole, Sarita, primary, Shrivastava, Sarika, primary, Thomas, Shefali, primary, Soni, Bhawana, primary, Khan, Shifa, primary, Dubey, Julekha, primary, Dubey, Shashi P., primary, Khan, Nushrat, primary, and Jain, Deepak Kumar, primary
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- 2019
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14. Development and Implementation of Digital Diagnostic Algorithms for Neonatal Units in Zimbabwe and Malawi: Development and Usability Study.
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Gannon H, Larsson L, Chimhuya S, Mangiza M, Wilson E, Kesler E, Chimhini G, Fitzgerald F, Zailani G, Crehan C, Khan N, Hull-Bailey T, Sassoon Y, Baradza M, Heys M, and Chiume M
- Abstract
Background: Despite an increase in hospital-based deliveries, neonatal mortality remains high in low-resource settings. Due to limited laboratory diagnostics, there is significant reliance on clinical findings to inform diagnoses. Accurate, evidence-based identification and management of neonatal conditions could improve outcomes by standardizing care. This could be achieved through digital clinical decision support (CDS) tools. Neotree is a digital, quality improvement platform that incorporates CDS, aiming to improve neonatal care in low-resource health care facilities. Before this study, first-phase CDS development included developing and implementing neonatal resuscitation algorithms, creating initial versions of CDS to address a range of neonatal conditions, and a Delphi study to review key algorithms., Objective: This second-phase study aims to codevelop and implement neonatal digital CDS algorithms in Malawi and Zimbabwe., Methods: Overall, 11 diagnosis-specific web-based workshops with Zimbabwean, Malawian, and UK neonatal experts were conducted (August 2021 to April 2022) encompassing the following: (1) review of available evidence, (2) review of country-specific guidelines (Essential Medicines List and Standard Treatment Guidelinesfor Zimbabwe and Care of the Infant and Newborn, Malawi), and (3) identification of uncertainties within the literature for future studies. After agreement of clinical content, the algorithms were programmed into a test script, tested with the respective hospital's health care professionals (HCPs), and refined according to their feedback. Once finalized, the algorithms were programmed into the Neotree software and implemented at the tertiary-level implementation sites: Sally Mugabe Central Hospital in Zimbabwe and Kamuzu Central Hospital in Malawi, in December 2021 and May 2022, respectively. In Zimbabwe, usability was evaluated through 2 usability workshops and usability questionnaires: Post-Study System Usability Questionnaire (PSSUQ) and System Usability Scale (SUS)., Results: Overall, 11 evidence-based diagnostic and management algorithms were tailored to local resource availability. These refined algorithms were then integrated into Neotree. Where national management guidelines differed, country-specific guidelines were created. In total, 9 HCPs attended the usability workshops and completed the SUS, among whom 8 (89%) completed the PSSUQ. Both usability scores (SUS mean score 75.8 out of 100 [higher score is better]; PSSUQ overall score 2.28 out of 7 [lower score is better]) demonstrated high usability of the CDS function but highlighted issues around technical complexity, which continue to be addressed iteratively., Conclusions: This study describes the successful development and implementation of the only known neonatal CDS system, incorporated within a bedside data capture system with the ability to deliver up-to-date management guidelines, tailored to local resource availability. This study highlighted the importance of collaborative participatory design. Further implementation evaluation is planned to guide and inform the development of health system and program strategies to support newborn HCPs, with the ultimate goal of reducing preventable neonatal morbidity and mortality in low-resource settings., (©Hannah Gannon, Leyla Larsson, Simbarashe Chimhuya, Marcia Mangiza, Emma Wilson, Erin Kesler, Gwendoline Chimhini, Felicity Fitzgerald, Gloria Zailani, Caroline Crehan, Nushrat Khan, Tim Hull-Bailey, Yali Sassoon, Morris Baradza, Michelle Heys, Msandeni Chiume. Originally published in JMIR Formative Research (https://formative.jmir.org), 26.01.2024.)
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- 2024
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15. Prevalence and risk factors of stroke in Bangladesh: A nationwide population-based survey.
- Author
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Mondal MBA, Hasan ATMH, Khan N, and Mohammad QD
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Background: A paucity of high-quality epidemiological survey on stroke in Bangladesh emphasizes the need for a drastic effort at the national level to study the burden of stroke in Bangladesh. Therefore, this community survey was conducted with to estimate the prevalence of stroke and its associated common risk factors among Bangladeshi population., Methods: This was a population-based cross-sectional study, carried out in 8 administrative divisions and 64 districts to estimate the prevalence of stroke throughout the country. The study adopted a two-stage cluster random sampling approach. The calculated sample size was 25,287. A semi-structured questionnaire was used to identify suspected stroke patients who were subsequently confirmed by consultant neurologists., Result: In the first stage, a total number of 25,287 respondents were interviewed throughout the country. Interviewers identified 561 respondents as suspected stroke through the Questionnaire for Verifying Stroke Free Status (QVSFS) system in 64 districts. Of the 25,287 respondents 13,878 (54.9%) were male and 11,409 (45.1%) were female. Mean age was 39.9 years. In the second stage, all suspected stroke cases (561) were further examined by neurologists and finally 288 patients were confirmed as stroke which provided a prevalence of 11.39 per 1000 population. The highest stroke prevalence (14.71 per thousand) were found in Mymensingh division and lowest (7.62 per thousand) found in Rajshahi division. The stroke prevalence varied in different age groups. It was 30.10 per thousand in the age group of >60 years and 4.60 in the age group below 40 years. The prevalence of stroke among male was twice that of female (13.62 versus 8.68 per thousand). The prevalence was slightly higher in rural areas (11.85 versus 11.07). About 50.4% respondents had some idea about stroke.Out of a total of 288 cases, 79.7% (213) patients had an ischemic stroke, 15.7% (42) had hemorrhagic, and 4.6% (12) were diagnosed as subarachnoid hemorrhage. The majority of the stroke patients had hypertension (79.2%), followed by dyslipidemia (38.9%), tobacco use in any form (37.2%), diabetes (28.8%), ischemic heart disease (20.1%)., Conclusion: We have found a stroke prevalence of 11.39 per 1000 population, the highest being in the Mymensingh division. The prevalence was much higher in the elderly and male population. More than three fourth had an ischemic stroke. Hypertension, dyslipidemia, tobacco use, diabetes, ischemic heart disease are the most common risk factors observed among stroke patients., Competing Interests: None., (© 2022 Published by Elsevier B.V.)
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- 2022
- Full Text
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16. Development and implementation experience of a learning healthcare system for facility based newborn care in low resource settings: The Neotree.
- Author
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Heys M, Kesler E, Sassoon Y, Wilson E, Fitzgerald F, Gannon H, Hull-Bailey T, Chimhini G, Khan N, Cortina-Borja M, Nkhoma D, Chiyaka T, Stevenson A, Crehan C, Chiume ME, and Chimhuya S
- Abstract
Introduction: Improving peri- and postnatal facility-based care in low-resource settings (LRS) could save over 6000 babies' lives per day. Most of the annual 2.4 million neonatal deaths and 2 million stillbirths occur in healthcare facilities in LRS and are preventable through the implementation of cost-effective, simple, evidence-based interventions. However, their implementation is challenging in healthcare systems where one in four babies admitted to neonatal units die. In high-resource settings healthcare systems strengthening is increasingly delivered via learning healthcare systems to optimise care quality, but this approach is rare in LRS., Methods: Since 2014 we have worked in Bangladesh, Malawi, Zimbabwe, and the UK to co-develop and pilot the Neotree system: an android application with accompanying data visualisation, linkage, and export. Its low-cost hardware and state-of-the-art software are used to support healthcare professionals to improve postnatal care at the bedside and to provide insights into population health trends. Here we summarise the formative conceptualisation, development, and preliminary implementation experience of the Neotree., Results: Data thus far from ~18 000 babies, 400 healthcare professionals in four hospitals (two in Zimbabwe, two in Malawi) show high acceptability, feasibility, usability, and improvements in healthcare professionals' ability to deliver newborn care. The data also highlight gaps in knowledge in newborn care and quality improvement. Implementation has been resilient and informative during external crises, for example, coronavirus disease 2019 (COVID-19) pandemic. We have demonstrated evidence of improvements in clinical care and use of data for Quality Improvement (QI) projects., Conclusion: Human-centred digital development of a QI system for newborn care has demonstrated the potential of a sustainable learning healthcare system to improve newborn care and outcomes in LRS. Pilot implementation evaluation is ongoing in three of the four aforementioned hospitals (two in Zimbabwe and one in Malawi) and a larger scale clinical cost effectiveness trial is planned., Competing Interests: Michelle Heys and Felicity Fitzgerald are both trustees of the Neotree charity (www.neotree.org) but receive no financial payment from this role. Caroline Crehan was a trustee of the Neotree charity (stepped down in 2018) and received no financial payment for this role. There are no other conflicts of interest to declare from any other co‐author., (© 2022 The Authors. Learning Health Systems published by Wiley Periodicals LLC on behalf of University of Michigan.)
- Published
- 2022
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