Partnership Model for Academic Health Science Systems to Address the Continuum from Discovery to Care, at Scale

2012 ◽  
pp. 6-17
Author(s):  
David Fish ◽  
Cyril Chantler ◽  
Ajay K. Kakkar ◽  
Richard Trembath ◽  
John Tooke
Keyword(s):  
Health Science ◽  
Academic Health ◽  
Partnership Model ◽  
The Continuum

scholarly journals Leading the spread and adoption of innovation at scale: an Academic Health Science Network’s perspective

BMJ Leader ◽  
2020 ◽  
pp. leader-2020-000252
Author(s):  
Andrew Walker ◽  
Catherine Dale ◽  
Natasha Curran ◽  
Annette Boaz ◽  
Michael V Hurley
Keyword(s):  
Complex Adaptive Systems ◽  
Adaptive Systems ◽  
Knowledge Exchange ◽  
Social Process ◽  
Health Science ◽  
Academic Health ◽  
Academic Networks ◽  
Adoption Of Innovation ◽  
Complex Adaptive ◽  
Operational Issues

BackgroundThere is virtually no limit to the number of innovations being developed, tested and piloted at any one time to improve the quality and safety of care. The perennial problem is spreading innovations that are proven to be effective on a smaller scale or under controlled conditions. Much of the literature on spread refers to the important role played by external agencies in supporting the spread of innovations.Academic Health Science Networks and the spread of innovationExternal agencies can provide additional capacity and capabilities to adopter organisations, such as technical expertise, resources and tools to assist with operational issues. In England, the National Health Service (NHS) established 15 Academic Health Science Networks (AHSNs) to help accelerate the spread and adoption of innovation in healthcare. However, formal clinical-academic networks (such as AHSNs) themselves will not deliver positive, tangible outcomes on the ground (ie, evidence-based innovations embedded at scale across a system). This begs the question of how do AHSNs practically go about achieving this change successfully? We provide an AHSN’s perspective on how we conceptualise and undertake our work in leading implementation of innovation at scale.An AHSN's perspectiveOur approach is a collaborative process of widening understanding of the innovation and its implementation. At its core, the implementation and spread of innovation into practice is a collective social process. Healthcare comprises complex adaptive systems, where contexts need to be negotiated for implementation to be successful. As AHSNs, we aim to lead this negotiation through facilitating knowledge exchange and production across the system to mobilise the resources and collective action necessary for achieving spread.

Enabling the success of academic health science centres in Australia: where is the leadership?

2014 ◽  
Vol 201 (11) ◽  
pp. 636-638 ◽  
Author(s):  
David E Theile ◽  
Ian A Scott ◽  
Jennifer H Martin ◽  
Areti Gavrilidis
Keyword(s):  
Health Science ◽  
Academic Health ◽  
Science Centres

scholarly journals Burnout among faculty physicians in an academic health science centre

2011 ◽  
Vol 16 (7) ◽  
pp. 409-413 ◽  
Author(s):  
James Gardner Wright ◽  
Nicole Khetani ◽  
Derek Stephens
Keyword(s):  
Health Science ◽  
Academic Health ◽  
Science Centre ◽  
Academic Health Science Centre

England gets five academic health science centres to compete on global stage

BMJ ◽  
2009 ◽  
Vol 338 (mar11 1) ◽  
pp. b1005-b1005 ◽  
Author(s):  
Z. Kmietowicz
Keyword(s):  
Health Science ◽  
Academic Health ◽  
Science Centres

scholarly journals Research IT maturity models for academic health centers: Early development and initial evaluation

1900 ◽  
Vol 2 (5) ◽  
pp. 289-294 ◽  
Author(s):  
Boyd M. Knosp ◽  
William K. Barnett ◽  
Nicholas R. Anderson ◽  
Peter J. Embi
Keyword(s):  
Model Development ◽  
Data Access ◽  
Health Science ◽  
Health Centers ◽  
Academic Health Centers ◽  
Maturity Model ◽  
Maturity Models ◽  
Academic Health ◽  
It Systems ◽  
Technological Advances

AbstractThis paper proposes the creation and application of maturity models to guide institutional strategic investment in research informatics and information technology (research IT) and to provide the ability to measure readiness for clinical and research infrastructure as well as sustainability of expertise. Conducting effective and efficient research in health science increasingly relies upon robust research IT systems and capabilities. Academic health centers are increasing investments in health IT systems to address operational pressures, including rapidly growing data, technological advances, and increasing security and regulatory challenges associated with data access requirements. Current approaches for planning and investment in research IT infrastructure vary across institutions and lack comparable guidance for evaluating investments, resulting in inconsistent approaches to research IT implementation across peer academic health centers as well as uncertainty in linking research IT investments to institutional goals. Maturity models address these issues through coupling the assessment of current organizational state with readiness for deployment of potential research IT investment, which can inform leadership strategy. Pilot work in maturity model development has ranged from using them as a catalyst for engaging medical school IT leaders in planning at a single institution to developing initial maturity indices that have been applied and refined across peer medical schools.

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