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Lowry E, Hogan MJ, Moriarty J, Harney OM, Ruijer E, Pilch M, Groarke JM, Hanlon M, Shuttleworth I. Using collective intelligence methods to improve government data infrastructures and promote the use of complex data: The example of the Northern Ireland Longitudinal Study. Health Res Policy Syst 2023; 21:134. [PMID: 38111046 PMCID: PMC10726592 DOI: 10.1186/s12961-023-01070-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 11/03/2023] [Indexed: 12/20/2023] Open
Abstract
BACKGROUND This paper discusses how collective intelligence (CI) methods can be implemented to improve government data infrastructures, not only to support understanding and primary use of complex national data but also to increase the dissemination and secondary impact of research based on these data. The case study uses the Northern Ireland Longitudinal Study (NILS), a member of the UK family of census/administrative data longitudinal studies (UKLS). METHODS A stakeholder-engaged CI approach was applied to inform the transformation of the NILS Research Support Unit (RSU) infrastructure to support researchers in their use of government data, including collaborative decision-making and better dissemination of research outputs. RESULTS We provide an overview of NILS RSU infrastructure design changes that have been implemented to date, focusing on a website redesign to meet user information requirements and the formation of better working partnerships between data users and providers within the Northern Ireland data landscape. We also discuss the key challenges faced by the design team during this project of transformation. CONCLUSION Our primary objective to improve government data infrastructure and to increase dissemination and the impact of research based on data was a complex and multifaceted challenge due to the number of stakeholders involved and their often conflicting perspectives. Results from this CI approach have been pivotal in highlighting how NILS RSU can work collaboratively with users to maximize the potential of this data, in terms of forming multidisciplinary networks to ensure the research is utilized in policy and in the literature and providing academic support and resources to attract new researchers.
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Affiliation(s)
- Estelle Lowry
- School of Natural and Built Environment, Queen's University Belfast, University Street, BT7 1NN, Belfast, Northern Ireland.
| | - Michael J Hogan
- School of Psychology, University of Galway, Galway, Ireland.
| | - John Moriarty
- School of Social Sciences, Education and Social Work, Queen's University Belfast, BT7 1NN, Belfast, Northern Ireland
| | - Owen M Harney
- School of Psychology, University of Galway, Galway, Ireland
| | | | - Monika Pilch
- School of Medicine, Trinity College Dublin, Dublin, Ireland
| | | | | | - Ian Shuttleworth
- School of Natural and Built Environment, Queen's University Belfast, University Street, BT7 1NN, Belfast, Northern Ireland
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El-Jardali F, Bou-Karroum L, Hilal N, Hammoud M, Hemadi N, Assal M, Kalach N, Harb A, Azzopardi-Muscat N, Sy TR, Novillo-Ortiz D. Knowledge management tools and mechanisms for evidence-informed decision-making in the WHO European Region: a scoping review. Health Res Policy Syst 2023; 21:113. [PMID: 37907919 PMCID: PMC10619313 DOI: 10.1186/s12961-023-01058-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Accepted: 10/07/2023] [Indexed: 11/02/2023] Open
Abstract
BACKGROUND Knowledge management (KM) emerged as a strategy to promote evidence-informed decision-making. This scoping review aims to map existing KM tools and mechanisms used to promote evidence-informed health decision-making in the WHO European Region and identify knowledge gaps. METHODS Following the Joanna Briggs Institute (JBI) guidance for conducting scoping reviews, we searched Medline, PubMed, EMBASE, the Cochrane library, and Open Grey. We conducted a descriptive analysis of the general characteristics of the included papers and conducted narrative analysis of the included studies and categorized studies according to KM type and phase. RESULTS Out of 9541 citations identified, we included 141 studies. The KM tools mostly assessed are evidence networks, surveillance tools, observatories, data platforms and registries, with most examining KM tools in high-income countries of the WHO European region. Findings suggest that KM tools can identify health problems, inform health planning and resource allocation, increase the use of evidence by policymakers and stimulate policy discussion. CONCLUSION Policymakers and funding agencies are called to support capacity-building activities, and future studies to strengthen KM in the WHO European region particularly in Eastern Europe and Central Asia. An updated over-arching strategy to coordinate KM activities in the WHO European region will be useful in these efforts.
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Affiliation(s)
- Fadi El-Jardali
- Department of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, ON, Canada
| | - Lama Bou-Karroum
- Department of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Nadeen Hilal
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Maya Hammoud
- Department of Health Management and Policy, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Nour Hemadi
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Michelle Assal
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Nour Kalach
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Aya Harb
- Knowledge to Policy Center, Faculty of Health Sciences, American University of Beirut, Beirut, Lebanon
| | - Natasha Azzopardi-Muscat
- Division of Country Health Policies and Systems, WHO Regional Office for Europe, Copenhagen, Denmark
| | - Tyrone Reden Sy
- Division of Country Health Policies and Systems, WHO Regional Office for Europe, Copenhagen, Denmark.
| | - David Novillo-Ortiz
- Division of Country Health Policies and Systems, WHO Regional Office for Europe, Copenhagen, Denmark
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Grath-Lone LM, Jay MA, Blackburn R, Gordon E, Zylbersztejn A, Wijlaars L, Gilbert R. What makes administrative data "research-ready"? A systematic review and thematic analysis of published literature. Int J Popul Data Sci 2022; 7:1718. [PMID: 35520099 PMCID: PMC9052961 DOI: 10.23889/ijpds.v6i1.1718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
Introduction Administrative data are a valuable research resource, but are under-utilised in the UK due to governance, technical and other barriers (e.g., the time and effort taken to gain secure data access). In recent years, there has been considerable government investment in making administrative data "research-ready", but there is no definition of what this term means. A common understanding of what constitutes research-ready administrative data is needed to establish clear principles and frameworks for their development and the realisation of their full research potential. Objective To define the characteristics of research-ready administrative data based on a systematic review and synthesis of existing literature. Methods On 29th June 2021, we systematically searched seven electronic databases for (1) peer-reviewed literature (2) related to research-ready administrative data (3) written in the English language. Following supplementary searches and snowball screening, we conducted a thematic analysis of the identified relevant literature. Results Overall, we screened 2,375 records and identified 38 relevant studies published between 2012 and 2021. Most related to administrative data from the UK and US and particularly to health data. The term research-ready was used inconsistently in the literature and there was some conflation with the concept of data being ready for statistical analysis. From the thematic analysis, we identified five defining characteristics of research-ready administrative data: (a) accessible, (b) broad, (c) curated, (d) documented and (e) enhanced for research purposes. Conclusions Our proposed characteristics of research-ready administrative data could act as a starting point to help data owners and researchers develop common principles and standards. In the more immediate term, the proposed characteristics are a useful framework for cataloguing existing research-ready administrative databases and relevant resources that can support their development.
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Affiliation(s)
| | - Matthew A. Jay
- Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, UK
| | - Ruth Blackburn
- Institute of Health Informatics, University College London, UK
| | - Emma Gordon
- Administrative Data Research UK, Economic & Social Research Council, UK
| | - Ania Zylbersztejn
- Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, UK
| | - Linda Wijlaars
- Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, UK
| | - Ruth Gilbert
- Institute of Health Informatics, University College London, UK
- Population, Policy and Practice Research and Teaching Department, Great Ormond Street Institute of Child Health, University College London, UK
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Taylor JA, Crowe S, Espuny Pujol F, Franklin RC, Feltbower RG, Norman LJ, Doidge J, Gould DW, Pagel C. The road to hell is paved with good intentions: the experience of applying for national data for linkage and suggestions for improvement. BMJ Open 2021; 11:e047575. [PMID: 34413101 PMCID: PMC8378388 DOI: 10.1136/bmjopen-2020-047575] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
BACKGROUND We can improve healthcare services by better understanding current provision. One way to understand this is by linking data sets from clinical and national audits, national registries and other National Health Service (NHS) encounter data. However, getting to the point of having linked national data sets is challenging. OBJECTIVE We describe our experience of the data application and linkage process for our study 'LAUNCHES QI', and the time, processes and resource requirements involved. To help others planning similar projects, we highlight challenges encountered and advice for applications in the current system as well as suggestions for system improvements. FINDINGS The study set up for LAUNCHES QI began in March 2018, and the process through to data acquisition took 2.5 years. Several challenges were encountered, including the amount of information required (often duplicate information in different formats across applications), lack of clarity on processes, resource constraints that limit an audit's capacity to fulfil requests and the unexpected amount of time required from the study team. It is incredibly difficult to estimate the resources needed ahead of time, and yet necessary to do so as early on as funding applications. Early decisions can have a significant impact during latter stages and be hard to change, yet it is difficult to get specific information at the beginning of the process. CONCLUSIONS The current system is incredibly complex, arduous and slow, stifling innovation and delaying scientific progress. NHS data can inform and improve health services and we believe there is an ethical responsibility to use it to do so. Streamlining the number of applications required for accessing data for health services research and providing clarity to data controllers could facilitate the maintenance of stringent governance, while accelerating scientific studies and progress, leading to swifter application of findings and improvements in healthcare.
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Affiliation(s)
- Julie A Taylor
- Clinical Operational Research Unit, Department of Mathematics, University College London, London, UK
| | - Sonya Crowe
- Clinical Operational Research Unit, Department of Mathematics, University College London, London, UK
| | - Ferran Espuny Pujol
- Clinical Operational Research Unit, Department of Mathematics, University College London, London, UK
| | - Rodney C Franklin
- Paediatric Cardiology Department, Royal Brompton and Harefield NHS Foundation Trust, London, UK
| | | | - Lee J Norman
- Paediatric Intensive Care Audit Network, University of Leeds, Leeds, UK
| | - James Doidge
- Intensive Care National Audit and Research Centre, London, UK
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | | | - Christina Pagel
- Clinical Operational Research Unit, Department of Mathematics, University College London, London, UK
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Dahl LT, Katz A, McGrail K, Diverty B, Ethier JF, Gavin F, McDonald JT, Paprica PA, Schull M, Walker JD, Wu J. The SPOR-Canadian Data Platform: a national initiative to facilitate data rich multi-jurisdictional research. Int J Popul Data Sci 2020; 5:1374. [PMID: 34007883 PMCID: PMC8104066 DOI: 10.23889/ijpds.v5i1.1374] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Administrative health data is recognized for its value for conducting population-based research that has contributed to numerous improvements in health. In Canada, each province and territory is responsible for administering its own publicly funded health care program, which has resulted in multiple sets of administrative health data. Challenges to using these data within each of these jurisdictions have been identified, which are further amplified when the research involves more than one jurisdiction. The benefits to conducting multi-jurisdictional studies has been recognized by the Canadian Institutes of Health Research (CIHR), which issued a call in 2017 for proposals that address the challenges. The grant led to the creation of Health Data Research Network Canada (HDRN), with a vision is to establish a distributed network that facilitates and accelerates multi-jurisdictional research in Canada. HDRN received funding for seven years that will be used to support the objectives and activities of an initiative called the Strategy for Patient-Oriented Research Canadian Data Platform (SPOR-CDP). In this paper, we describe the challenges that researchers face while using, or considering using, administrative health data to conduct multi-jurisdictional research and the various ways that the SPOR-CDP will attempt to address them. Our objective is to assist other groups facing similar challenges associated with undertaking multi-jurisdictional research.
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Affiliation(s)
- Lindsey Todd Dahl
- Manitoba Centre for Health Policy (MCHP), Rady Faculty of Health Sciences, Winnipeg, Manitoba R3E 3P5
| | - Alan Katz
- University of Manitoba, Departments of Community Health Sciences and Family Medicine; Director, Manitoba Centre for Health Policy (MCHP), Rady Faculty of Health Sciences, Winnipeg, Manitoba R3E 3P5
| | - Kimberlyn McGrail
- Centre for Health Services and Policy Research, School of Population and Public Health, Vancouver, British Columbia V6T 1Z3
| | - Brent Diverty
- Vice President, Programs Division, Canadian Institute for Health Information, Ottawa, Ontario K2A 4H6
| | - Jean-Francois Ethier
- Associate professor, GRIIS, Université de Sherbrooke, Sherbrooke, Quebec J1K 2R1; Scientist, Centre de Recherche sur le vieillissement, 1036 Rue Belvédère S, Sherbrooke, Quebec J1H 4C4
| | - Frank Gavin
- Public Advisory Council, Health Data Research Network Canada, Toronto, Ontario M4S 1M4
| | - James Ted McDonald
- Director, New Brunswick Institute for Research, Data and Training; Professor of Economics, University of New Brunswick, Fredericton, New Brunswick E3B 5A3
| | - P. Alison Paprica
- Executive Advisor and Affiliate Scientist, Institute for Clinical Evaluative Sciences (ICES), 2075 Bayview Ave, Toronto, Ontario M4N 3M5
| | - Michael Schull
- CEO, Institute for Clinical Evaluative Sciences (ICES), 2075 Bayview Ave, Toronto, Ontario M4N 3M5; Senior Scientist, Evaluative Clinical Sciences, Trauma, Emergency & Critical Care Research Program, Sunnybrook Research Institute, 2075 Bayview Ave, Toronto, Ontario M4N 3M5; Professor, University of Toronto, Institute for Health Policy Management and Evaluation, 155 College Street, Suite 425, Toronto, Ontario M5T 3M6
| | - Jennifer D Walker
- Indigenous Lead, Institute for Clinical Evaluative Sciences (ICES), 2075 Bayview Ave, Toronto, Ontario M4N 3M5; Canada Research Chair in Indigenous Health, School of Rural and Northern Health, Laurentian University, Sudbury Ontario P3E 2C6
| | - Juliana Wu
- Manager, Corporate Data Request Program, Canadian Institute for Health Information (CIHI), Toronto, Ontario M2P 2B7,
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