scholarly journals Chief Information Officer team evolution in university hospitals: interaction of the three ‘C’s (CIO, CCIO, CRIO)

2018 ◽  
Vol 25 (2) ◽  
pp. 88-91 ◽  
Author(s):  
Shankar Sridharan ◽  
Ward Priestman ◽  
Neil J. Sebire
Keyword(s):  
Routine Data ◽  
Clinical Information ◽  
Chief Information Officer ◽  
Research Data ◽  
Leadership Role ◽  
University Hospitals ◽  
Data Governance ◽  
Research Information ◽  
Distinct Component ◽  
Published Evidence

BackgroundThe Chief Information Officer (CIO) and Chief Clinical Information Officer (CCIO) are now established senior roles in hospital practice. With increasing emphasis on optimising use of routine health data for secondary purposes and research, additional skills are required as part of the senior information officer team, particularly in academic health care institutions.ObjectiveTo present the role of the Chief Research Information Officer (CRIO), as an emerging, and important, component of the senior information team.MethodWe review recent publications describing the composition of the senior information team, including CIO and CCIO roles, and discuss the development of the CRIO as a distinct component of the team, based on the published evidence and our experience.ResultsThe CRIO is emerging as an additional senior role in academic healthcare institutions, whose roles include leadership of the informatics strategy and optimisation of routine data collection systems for research data use, in addition to important aspects of research data governance. Such individuals should be senior clinicians with experience in informatics, in addition to having established research expertise and knowledge of research processes, governance and academic networks.ConclusionsThe CRIO is emerging as a distinct senior information leadership role in conjunction with the already established positions of CCIO and CIO, who together, can provide optimal oversight of digital activities across the organisation.

scholarly journals An Exploratory Study of Research Data Governance in the U.S.

2020 ◽  
Vol 4 (1) ◽  
pp. 122-142
Author(s):  
Inna Kouper ◽  
Anjanette H Raymond ◽  
Stacey Giroux
Keyword(s):  
Decision Making ◽  
Exploratory Study ◽  
Research Data ◽  
Science And Society ◽  
Data Governance ◽  
Knowledge Commons ◽  
Multiple Voices ◽  
The Us ◽  
The Commons ◽  
The U.S

AbstractMaking decisions regarding data and the overall credibility of research constitutes research data governance. In this paper, we present results of an exploratory study of the stakeholders of research data governance. The study was conducted among individuals who work in academic and research institutions in the US, with the goal of understanding what entities are perceived as making decisions regarding data and who researchers believe should be responsible for governing research data. Our results show that there is considerable diversity and complexity across stakeholders, both in terms of who they are and their ideas about data governance. To account for this diversity, we propose to frame research data governance in the context of polycentric governance of a knowledge commons. We argue that approaching research data from the commons perspective will allow for a governance framework that can balance the goals of science and society, allow us to shift the discussion toward protection from enclosure and knowledge resilience, and help to ensure that multiple voices are included in all levels of decision-making.

scholarly journals Representation of Slovak Research Information (A Case Study)

Information ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 137
Author(s):  
Danica Zendulková ◽  
Boris Rysuľa ◽  
Andrea Putalová
Keyword(s):  
Social Sciences ◽  
National Level ◽  
Research Data ◽  
Research Information ◽  
Social Sciences And Humanities ◽  
Central Register ◽  
The World ◽  
Mutual Relations ◽  
Analytical Tools ◽  
The Eu

In the light of the increasing importance of the societal impact of research, this article attempts to address the question as to how social sciences and humanities (SSH) research outputs from 2019 are represented in Slovak research portfolios in comparison with those of the EU-28 and the world. The data used for the analysis originate from the R&D SK CRIS and bibliographic Central Register of Publication Activities (CREPČ) national databases, and WoS Core Collection/InCites. The research data were appropriate for the analysis at the time they were structured, on the national level; of high quality and consistency; and covering as many components as possible and in mutual relations. The data resources should enable the research outputs to be assigned to research categories. The analysis prompts the conclusion that social sciences and humanities research outputs in Slovakia in 2019 are appropriately represented and in general show an increasing trend. This can be documented by the proportion represented by the SSH research projects and other entities involved in the overall Slovak research outputs, and even the higher ratio of SSH research publications in comparison with the EU-28 and the world. Recommendations of a technical character include research data management, data quality, and the integration of individual systems and available analytical tools.

scholarly journals Benchmarking experience to improve paediatric healthcare: listening to the voices of families from two European Children’s University Hospitals

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ilaria Corazza ◽  
Kendall Jamieson Gilmore ◽  
Francesca Menegazzo ◽  
Valts Abols
Keyword(s):  
Children And Adolescents ◽  
Quality Care ◽  
University Hospital ◽  
Free Text ◽  
University Hospitals ◽  
Post Discharge ◽  
Important Indicator ◽  
Published Evidence ◽  
Patient Reported ◽  
Electronic Administration

Abstract Background Patient Reported Experience Measures (PREMs) are recognized as an important indicator of high quality care and person-centeredness. PREMs are increasingly adopted for paediatric care, but there is little published evidence on how to administer, collect, and report paediatric PREMs at scale. Methods This paper describes the development of a PREMs questionnaire and administration system for the Meyer Children’s University Hospital in Florence (Meyer) and the Children’s Clinical University Hospital in Riga (CCUH). The system continuously recruits participants into the electronic administration model, with surveys completed by caregivers or adolescents at their convenience, post-discharge. We analyse 1661 responses from Meyer and 6585 from CCUH, collected from 1st December 2018 to 21st January 2020. Quantitative and qualitative experience analyses are included, using Pearson chi-square tests, Fisher’s exact tests and narrative evidence from free text responses. Results The large populations reached in both countries suggest the continuous, digital collection of paediatric PREMs described is feasible for collecting paediatric PREMs at scale. Overall response rates were 59% in Meyer and 45% in CCUH. There was very low variation in mean scores between the hospitals, with greater clustering of Likert scores around the mean in CCUH and a wider spread in Meyer for a number of items. The significant majority of responses represent the carers’ point of view or the perspective of children and adolescents expressed through proxy reporting by carers. Conclusions Very similar reported scores may reflect broadly shared preferences among children, adolescents and carers in the two countries, and the ability of both hospitals in this study to meet their expectations. The model has several interesting features: inclusion of a narrative element; electronic administration and completion after discharge from hospital, with high completion rates and easy data management; access for staff and researchers through an online platform, with real time analysis and visualization; dual implementation in two sites in different settings, with comparison and shared learning. These bring new opportunities for the utilization of PREMs for more person-centered and better quality care, although further research is needed in order to access direct reporting by children and adolescents.

scholarly journals Agreement between routine and research measurement of infant height and weight

2014 ◽  
Vol 100 (1) ◽  
pp. 24-29 ◽  
Author(s):  
M Bryant ◽  
G Santorelli ◽  
L Fairley ◽  
E S Petherick ◽  
R Bhopal ◽  
...  
Keyword(s):  
Routine Data ◽  
Research Data ◽  
Data Sources ◽  
School Age ◽  
Methodological Issues ◽  
Limits Of Agreement ◽  
Born In Bradford ◽  
Health Visitors ◽  
Health And Illness ◽  
Routine Infant

In many countries, routine data relating to growth of infants are collected as a means of tracking health and illness up to school age. These have potential to be used in research. For health monitoring and research, data should be accurate and reliable. This study aimed to determine the agreement between length/height and weight measurements from routine infant records and researcher-collected data.MethodsHeight/length and weight at ages 6, 12 and 24 months from the longitudinal UK birth cohort (born in Bradford; n=836–1280) were compared with routine data collected by health visitors within 2 months of the research data (n=104–573 for different comparisons). Data were age adjusted and compared using Bland Altman plots.ResultsThere was agreement between data sources, albeit weaker for height than for weight. Routine data tended to underestimate length/height at 6 months (0.5 cm (95% CI −4.0 to 4.9)) and overestimate it at 12 (−0.3 cm (95% CI −0.5 to 4.0)) and 24 months (0.3 cm (95% CI −4.0 to 3.4)). Routine data slightly overestimated weight at all three ages (range −0.04 kg (95% CI −1.2 to 0.9) to −0.04 (95% CI −0.7 to 0.6)). Limits of agreement were wide, particularly for height. Differences were generally random, although routine data tended to underestimate length in taller infants and underestimate weight in lighter infants.ConclusionsRoutine data can provide an accurate and feasible method of data collection for research, though wide limits of agreement between data sources may be observed. Differences could be due to methodological issues; but may relate to variability in clinical practice. Continued provision of appropriate training and assessment is essential for health professionals responsible for collecting routine data.

scholarly journals Symposium: Distributed Networks of Federated Secure Research Data Environments – Enabling Analytics Across Multiple Platforms

2020 ◽  
Vol 5 (5) ◽  
Author(s):  
Matthias Schneider
Keyword(s):  
Population Data ◽  
Data Access ◽  
Distributed Networks ◽  
Research Data ◽  
Data Governance ◽  
Virtual Database ◽  
South Wales ◽  
Challenges And Opportunities ◽  
Storage Location ◽  
Time Required

IntroductionUsers of linked data require access to an increasing number of heterogeneous datasets from diverse domains, often held in different secure research data environments, especially for multi-jurisdictional projects. Under the traditional model of data access, projects are required to transfer and harmonise the necessary datasets in one central location before analysis can be undertaken, increasing the time required for data acquisition and preparation. Objectives and ApproachIn a federated data environment, analysts query distributed datasets held in a network of multiple secure data environments via a central virtual database, without requiring the data to move. Instead, the data is analysed as close as possible to its storage location, minimising the amount of data transfers and giving data custodians more control over their data. This symposium explores the challenges and opportunities of establishing and operating a distributed network of federated secure research data environments. Leading organisations operating data platforms in various jurisdictions present for 15 minutes each the current capabilities of their platforms, the landscape of data environments in their jurisdictions and potential approaches to key questions such as: Harmonising/federating data sources Data security Data governance Discoverability/metadata Performance The audience is the then invited to participate in discussing the topic for the remaining 30 minutes. The following individuals have been approached to represent their organisations in this symposium: Professor David Ford, Swansea University: UK Secure eResearch Platform (UK SErP) Charles Victor, Institute for Clinical Evaluative Sciences (ICES): ICES Data & Analytic Virtual Environment (IDAVE) Professor Louisa Jorm, Centre for Big Data Research in Health, University of New South Wales: E-Research Institutional Cloud Architecture (ERICA) Professor Kimberlyn McGrail, Population Data BC: Secure Research Environment (SRE) Results / Conclusion / ImplicationsThis symposium will help formulate requirements for and barriers to distributed networks of federated secure research data environments, and create a foundation for data analytics across multiple platforms.

Implementing an Emergency Department Information System

2014 ◽  
Vol 6 (1) ◽  
pp. 17-30
Author(s):  
Paraskevas Vezyridis ◽  
Stephen Timmons
Keyword(s):  
Emergency Department ◽  
Information System ◽  
Information And Communication Technologies ◽  
Clinical Information System ◽  
Clinical Information ◽  
Actor Network Theory ◽  
Linear Process ◽  
University Hospitals ◽  
Structured Interviews ◽  
Healthcare Settings

Information and communication technologies (ICT) are increasingly used in healthcare settings. Despite their technical robustness, their implementation has not always been straightforward. This is a case study of the implementation of a clinical information system for patient registration and tracking in the busy emergency department (ED) of a large English NHS University Hospitals Trust. By adopting an Actor-Network Theory (ANT) approach, the authors explore the complex intertwining of people and machines in the local setting as they negotiate the success of the project. Based on the analysis of 30 semi-structured interviews with clinical and administrative staff and, of relevant policy and project documentation, the authors demonstrate how the technologically-mediated transformation of healthcare practices is not a fixed and linear process, but the interplay of various fluctuating, performative and co-constitutive technical and social factors.

scholarly journals Quality of Open Research Data: Values, Convergences and Governance

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 175 ◽  
Author(s):  
Tibor Koltay
Keyword(s):  
Big Data ◽  
Data Quality ◽  
Academic Research ◽  
Research Data ◽  
Data Governance ◽  
Quality Of Data ◽  
Open Research ◽  
Research Environments

This paper focuses on the characteristics of research data quality, and aims to cover the most important issues related to it, giving particular attention to its attributes and to data governance. The corporate word’s considerable interest in the quality of data is obvious in several thoughts and issues reported in business-related publications, even if there are apparent differences between values and approaches to data in corporate and in academic (research) environments. The paper also takes into consideration that addressing data quality would be unimaginable without considering big data.

scholarly journals Joint Imaging Platform for Federated Clinical Data Analytics

2020 ◽  
pp. 1027-1038
Author(s):  
Jonas Scherer ◽  
Marco Nolden ◽  
Jens Kleesiek ◽  
Jasmin Metzger ◽  
Klaus Kades ◽  
...  
Keyword(s):  
Data Analytics ◽  
Large Scale ◽  
Image Data ◽  
Clinical Information ◽  
Quality Data ◽  
Imaging Data ◽  
University Hospitals ◽  
High Quality Data ◽  
Interactive Analysis ◽  
Legal Constraints

PURPOSE Image analysis is one of the most promising applications of artificial intelligence (AI) in health care, potentially improving prediction, diagnosis, and treatment of diseases. Although scientific advances in this area critically depend on the accessibility of large-volume and high-quality data, sharing data between institutions faces various ethical and legal constraints as well as organizational and technical obstacles. METHODS The Joint Imaging Platform (JIP) of the German Cancer Consortium (DKTK) addresses these issues by providing federated data analysis technology in a secure and compliant way. Using the JIP, medical image data remain in the originator institutions, but analysis and AI algorithms are shared and jointly used. Common standards and interfaces to local systems ensure permanent data sovereignty of participating institutions. RESULTS The JIP is established in the radiology and nuclear medicine departments of 10 university hospitals in Germany (DKTK partner sites). In multiple complementary use cases, we show that the platform fulfills all relevant requirements to serve as a foundation for multicenter medical imaging trials and research on large cohorts, including the harmonization and integration of data, interactive analysis, automatic analysis, federated machine learning, and extensibility and maintenance processes, which are elementary for the sustainability of such a platform. CONCLUSION The results demonstrate the feasibility of using the JIP as a federated data analytics platform in heterogeneous clinical information technology and software landscapes, solving an important bottleneck for the application of AI to large-scale clinical imaging data.

scholarly journals Research Data in Current Research Information Systems

2017 ◽  
Vol 106 ◽  
pp. 305-320 ◽  
Author(s):  
Joachim Schöpfel ◽  
Hélène Prost ◽  
Violane Rebouillat
Keyword(s):  
Information Systems ◽  
Research Data ◽  
Research Information
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