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Lane C, Nathan N, Wiggers J, Hall A, Shoesmith A, Bauman A, Groombridge D, Sutherland R, Wolfenden L. Learning Health System to rapidly improve the implementation of a school physical activity policy. Implement Sci Commun 2024; 5:85. [PMID: 39085972 PMCID: PMC11292924 DOI: 10.1186/s43058-024-00619-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 07/13/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Learning Health Systems (LHS) - characterised by cycles of evidence generation and application - are increasingly recognised for their potential to improve public health interventions and optimise health impacts; however there is little evidence of their application in the context of public health practice. Here, we describe how an Australian public health unit applied a LHS approach to successfully improve a model of support for implementation of a school-based physical activity policy. METHODS This body of work was undertaken in the context of a strong research-practice partnership. Core LHS capabilities included: i) partnerships and stakeholder engagement; ii) workforce development and learning health communities; iii) multi-disciplinary scientific expertise; iv) practice data collection and management system; v) evidence surveillance and synthesis; and vi) governance and organisational processes of decision making. Three cycles of data generation and application were used. Within each cycle, randomised controlled trials conducted in NSW primary schools were used to generate data on the support model's effectiveness for improving schools' implementation of a government physical activity policy, its delivery costs, and process measures such as adoption and acceptability. Each type of data were analysed independently, synthesised, and then presented to a multi-disciplinary team of researchers and practitioners, in consult with stakeholders, leading to collaborative decisions for incremental improvements to the support model. RESULTS Cycle 1 tested the first version of the support model (composed of five implementation strategies targeting identified barriers of policy implementation) and showed the model's feasibility and efficacy for improving schools' policy implementation. Data-informed changes were made to enhance impact, including the addition of three implementation strategies to address outstanding barriers. Cycle 2 (now, testing a package of eight implementation strategies) established the model's effectiveness and cost-effectiveness for improving school's policy implementation. Data-informed changes were made to reduce delivery costs, specifically adapting the costliest strategies to reduce in-person contact from external support personnel. Cycle 3 showed that the adaptations minimised the relative cost of delivery without adversely impacting on the effect. CONCLUSIONS Through this process, we identified an effective, cost-effective, acceptable and scalable policy implementation support model for service delivery. This provides important information to inform or support LHS approaches for other agencies seeking to optimise the health impact of evidence-based interventions.
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Affiliation(s)
- Cassandra Lane
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia.
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia.
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia.
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia.
| | - Nicole Nathan
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia
| | - John Wiggers
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia
| | - Alix Hall
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia
| | - Adam Shoesmith
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia
| | - Adrian Bauman
- School of Public Health, University of Sydney, Sydney, NSW, Australia
| | - Daniel Groombridge
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
| | - Rachel Sutherland
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia
| | - Luke Wolfenden
- School of Medicine and Public Health, The University of Newcastle, 1 University Drive Callaghan, Newcastle, NSW, Australia
- Hunter New England Population Health, Hunter New England Area Health Service, Newcastle , NSW, Australia
- National Centre of Implementation Science, The University of Newcastle, Newcastle, NSW, Australia
- Hunter Medical Research Institute, New Lambton Heights, Newcastle, NSW, Australia
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Weaver SJ, Breslau ES, Russell LE, Zhang A, Sharma R, Bass EB, Marsteller JA, Snyder C. Health-care organization characteristics in cancer care delivery: an integrated conceptual framework with content validation. J Natl Cancer Inst 2024; 116:800-811. [PMID: 38419574 DOI: 10.1093/jnci/djae048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Revised: 02/01/2024] [Accepted: 02/20/2024] [Indexed: 03/02/2024] Open
Abstract
Context can influence cancer-related outcomes. For example, health-care organization characteristics, including ownership, leadership, and culture, can affect care access, communication, and patient outcomes. Health-care organization characteristics and other contextual factors can also influence whether and how clinical discoveries reduce cancer incidence, morbidity, and mortality. Importantly, policy, market, and technology changes are transforming health-care organization design, culture, and operations across the cancer continuum. Consequently, research is essential to examine when, for whom, and how organizational characteristics influence person-level, organization-level, and population-level cancer outcomes. Understanding organizational characteristics-the structures, processes, and other features of entities involved in health care delivery-and their dynamics is an important yet understudied area of care delivery research across the cancer continuum. Research incorporating organizational characteristics is critical to address health inequities, test care delivery models, adapt interventions, and strengthen implementation. The field lacks conceptual grounding, however, to help researchers identify germane organizational characteristics. We propose a framework identifying organizational characteristics relevant for cancer care delivery research based on conceptual work in health services, organizational behavior, and management science and refined using a systematic review and key informant input. The proposed framework is a tool for organizing existing research and enhancing future cancer care delivery research. Following a 2012 Journal of the National Cancer Institute monograph, this work complements National Cancer Institute efforts to stimulate research addressing the relationship between cancer outcomes and contextual factors at the patient, provider, team, delivery organization, community, and health policy levels.
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Affiliation(s)
- Sallie J Weaver
- Health Systems and Interventions Research Branch, Healthcare Delivery Research Program, Division of Cancer Control & Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Erica S Breslau
- Health Systems and Interventions Research Branch, Healthcare Delivery Research Program, Division of Cancer Control & Population Sciences, National Cancer Institute, Rockville, MD, USA
| | - Lauren E Russell
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Allen Zhang
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ritu Sharma
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Eric B Bass
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jill A Marsteller
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | - Claire Snyder
- Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
- Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Johns Hopkins Sidney Kimmel Comprehensive Cancer Center, Baltimore, MD, USA
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Kim B, Guyer M, Keshavan M. Using implementation science to operate as a learning health system to improve outcomes in early psychosis. Early Interv Psychiatry 2024; 18:374-380. [PMID: 38527863 DOI: 10.1111/eip.13496] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 09/23/2023] [Accepted: 01/24/2024] [Indexed: 03/27/2024]
Abstract
AIM Early interventions are well understood to improve psychosis outcomes, but their successful implementation remains limited. This article introduces a three-step roadmap for advancing the implementation of evidence-based practices to operate as a learning health system, which can be applied to early interventions for psychosis and is intended for an audience that is relatively new to systematic approaches to implementation. METHODS The roadmap is grounded in implementation science, which specializes in methods to promote routine use of evidence-based innovations. The roadmap draws on learning health system principles that call for commitment of leadership, application of evidence, examination of care experiences, and study of health outcomes. Examples are discussed for each roadmap step, emphasizing both data- and stakeholder-related considerations applicable throughout the roadmap. CONCLUSIONS Early psychosis care is a promising topic through which to discuss the critical need to move evidence into practice. Despite remarkable advances in early psychosis interventions, population-level impact of those interventions is yet to be realized. By providing an introduction to how implementation science principles can be operationalized in a learning health system and sharing examples from early psychosis care, this article prompts inclusion of a wider audience in essential discourse on the role that implementation science can play for moving evidence into practice for other realms of psychiatric care as well. To this end, the proposed roadmap can serve as a conceptual guiding template and framework through which various psychiatric services can methodically pursue timely implementation of evidence-based interventions for higher quality care and improved outcomes.
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Affiliation(s)
- Bo Kim
- Center for Healthcare Organization and Implementation Research, VA Boston Healthcare System, Boston, Massachusetts, USA
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
| | - Margaret Guyer
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Massachusetts Department of Mental Health, Boston, Massachusetts, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
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Kasaai B, Thompson E, Glazier RH, McMahon M. Enrichment of core competencies to maximize health system impact: An analysis of an embedded research training program. Learn Health Syst 2024; 8:e10399. [PMID: 38633024 PMCID: PMC11019376 DOI: 10.1002/lrh2.10399] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Revised: 09/26/2023] [Accepted: 10/05/2023] [Indexed: 04/19/2024] Open
Abstract
Introduction The Health System Impact (HSI) Fellowship is an embedded research training program that aims to prepare doctoral trainees and postdoctoral fellows for stronger career readiness and greater impact as emerging leaders within and beyond the academy, including in learning health systems (LHS). The program supports fellows to develop 10 leadership and research competencies that comprise the Enriched Core Competency Framework in Health Services and Policy Research through a combination of experiential learning, mentorship, and professional development training. This study tracks competency development of HSI fellows over time and examines fellows' perspectives on which program design elements support their competency development. Methods A competency assessment tool developed for the program was independently completed by 95 postdoctoral and 36 doctoral fellows (self-assessments) and their respective 203 dyad (academic and health system) supervisors in the 2017 to 2019 program cohorts, who independently rated the strength of fellows' 10 competencies at baseline and several points thereafter. Competency strength ratings were analyzed to understand change over time and differences in ratings across groups (between fellows' sex, supervisor type, and supervisor vs. fellow). Program design element ratings were examined to understand perspectives on their contribution toward fellows' competency development. Results Fellows' competency strength significantly improved in all 10 domains over time, based on independent assessments by the fellows and their dyad supervisors. Supervisors tended to rate the fellows' competency strength higher than the fellows did. Differences in competency ratings between male and female fellows (self-assessments) and between academic and health system supervisors were either negligble or not significant. Fellows identified all nine program design elements as enriching their competency development. Conclusion The HSI Fellowship provides an opportunity for fellows to develop the full suite of enriched core competencies and to prepare a cadre of emerging leaders with the skills and experience to contribute to the advancement of LHS.
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Affiliation(s)
- Bahar Kasaai
- CIHR Institute of Health Services and Policy Research (IHSPR)TorontoOntarioCanada
| | - Erin Thompson
- CIHR Institute of Health Services and Policy Research (IHSPR)TorontoOntarioCanada
| | - Richard H Glazier
- CIHR Institute of Health Services and Policy Research (IHSPR)TorontoOntarioCanada
- Institute for Clinical Evaluative Sciences (ICES)TorontoOntarioCanada
- MAP Centre for Urban Health SolutionsSt. Michael's HospitalTorontoOntarioCanada
- Family and Community MedicineUniversity of TorontoTorontoOntarioCanada
| | - Meghan McMahon
- CIHR Institute of Health Services and Policy Research (IHSPR)TorontoOntarioCanada
- Institute of Health Policy, Management and EvaluationUniversity of TorontoTorontoOntarioCanada
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Smith CL, Fisher G, Dharmayani PNA, Wijekulasuriya S, Ellis LA, Spanos S, Dammery G, Zurynski Y, Braithwaite J. Progress with the Learning Health System 2.0: a rapid review of Learning Health Systems' responses to pandemics and climate change. BMC Med 2024; 22:131. [PMID: 38519952 PMCID: PMC10960489 DOI: 10.1186/s12916-024-03345-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 01/23/2024] [Indexed: 03/25/2024] Open
Abstract
BACKGROUND Pandemics and climate change each challenge health systems through increasing numbers and new types of patients. To adapt to these challenges, leading health systems have embraced a Learning Health System (LHS) approach, aiming to increase the efficiency with which data is translated into actionable knowledge. This rapid review sought to determine how these health systems have used LHS frameworks to both address the challenges posed by the COVID-19 pandemic and climate change, and to prepare for future disturbances, and thus transition towards the LHS2.0. METHODS Three databases (Embase, Scopus, and PubMed) were searched for peer-reviewed literature published in English in the five years to March 2023. Publications were included if they described a real-world LHS's response to one or more of the following: the COVID-19 pandemic, future pandemics, current climate events, future climate change events. Data were extracted and thematically analyzed using the five dimensions of the Institute of Medicine/Zurynski-Braithwaite's LHS framework: Science and Informatics, Patient-Clinician Partnerships, Continuous Learning Culture, Incentives, and Structure and Governance. RESULTS The search yielded 182 unique publications, four of which reported on LHSs and climate change. Backward citation tracking yielded 13 additional pandemic-related publications. None of the climate change-related papers met the inclusion criteria. Thirty-two publications were included after full-text review. Most were case studies (n = 12, 38%), narrative descriptions (n = 9, 28%) or empirical studies (n = 9, 28%). Science and Informatics (n = 31, 97%), Continuous Learning Culture (n = 26, 81%), Structure and Governance (n = 23, 72%) were the most frequently discussed LHS dimensions. Incentives (n = 21, 66%) and Patient-Clinician Partnerships (n = 18, 56%) received less attention. Twenty-nine papers (91%) discussed benefits or opportunities created by pandemics to furthering the development of an LHS, compared to 22 papers (69%) that discussed challenges. CONCLUSIONS An LHS 2.0 approach appears well-suited to responding to the rapidly changing and uncertain conditions of a pandemic, and, by extension, to preparing health systems for the effects of climate change. LHSs that embrace a continuous learning culture can inform patient care, public policy, and public messaging, and those that wisely use IT systems for decision-making can more readily enact surveillance systems for future pandemics and climate change-related events. TRIAL REGISTRATION PROSPERO pre-registration: CRD42023408896.
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Affiliation(s)
- Carolynn L Smith
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia.
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia.
| | - Georgia Fisher
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Putu Novi Arfirsta Dharmayani
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Shalini Wijekulasuriya
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Louise A Ellis
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Samantha Spanos
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Genevieve Dammery
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Yvonne Zurynski
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
| | - Jeffrey Braithwaite
- Centre for Healthcare Resilience and Implementation Science, Australian Institute of Health Innovation, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
- NHMRC Partnership Centre for Health System Sustainability, Macquarie University, 75 Talavera Road, North Ryde 2113, Sydney, Australia
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McDonald PL, Foley TJ, Verheij R, Braithwaite J, Rubin J, Harwood K, Phillips J, Gilman S, van der Wees PJ. Data to knowledge to improvement: creating the learning health system. BMJ 2024; 384:e076175. [PMID: 38272498 PMCID: PMC10809034 DOI: 10.1136/bmj-2023-076175] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2024]
Affiliation(s)
| | - Tom J Foley
- Newcastle University, Newcastle upon Tyne, UK
- University College Dublin, Dublin, Ireland
- Health Service Executive, Donegal, Ireland
| | - Robert Verheij
- Netherlands Institute of Health Services Research (NIVEL), Utrecht, Netherlands
- Tranzo, Department of Social and Behavioural Sciences, Tilburg University, Tilburg, Netherlands
- Dutch National Healthcare Institute, Diemen, Netherlands
| | | | | | | | - Jessica Phillips
- Translational Health Sciences, Department of Clinical Research and Leadership, George Washington University, Washington, DC, USA
| | - Sarah Gilman
- Translational Health Sciences, Department of Clinical Research and Leadership, George Washington University, Washington, DC, USA
| | - Philip J van der Wees
- George Washington University, Washington, DC, USA
- Radboud University Medical Center, Nijmegen, Netherlands
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Donnelly C, Janssen A, Shah K, Harnett P, Vinod S, Shaw TJ. Qualitative study of international key informants' perspectives on the current and future state of healthcare quality measurement and feedback. BMJ Open 2023; 13:e073697. [PMID: 37286326 DOI: 10.1136/bmjopen-2023-073697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 06/09/2023] Open
Abstract
OBJECTIVES The aim of this study is to explore the current and future state of quality measurement and feedback and identify factors influencing measurement feedback systems, including the barriers and enablers to their effective design, implementation, use and translation into quality improvement. DESIGN This qualitative study used semistructured interviews with key informants. A deductive framework analysis was conducted to code transcripts to the Theoretical Domains Framework (TDF). An inductive analysis was used to produce subthemes and belief statements within each TDF domain. SETTING All interviews were conducted by videoconference and audio-recorded. PARTICIPANTS Key informants were purposively sampled experts in quality measurement and feedback, including clinical (n=5), government (n=5), research (n=4) and health service leaders (n=3) from Australia (n=7), the USA (n=4), the UK (n=2), Canada (n=2) and Sweden (n=2). RESULTS A total of 17 key informants participated in the study. The interview length ranged from 48 to 66 min. 12 theoretical domains populated by 38 subthemes were identified as relevant to measurement feedback systems. The most populous domains included environmental context and resources, memory, attention and decision-making, and social influences. The most populous subthemes included 'quality improvement culture', 'financial and human resource support' and 'patient-centred measurement'. There were minimal conflicting beliefs outside of 'data quality and completeness'. Conflicting beliefs in these subthemes were predominantly between government and clinical leaders. CONCLUSIONS Multiple factors were found to influence measurement feedback systems and future considerations are presented within this manuscript. The barriers and enablers that impact these systems are complex. While there are some clear modifiable factors in the design of measurement and feedback processes, influential factors described by key informants were largely socioenvironmental. Evidence-based design and implementation, coupled with a deeper understanding of the implementation context, may lead to enhanced quality measurement feedback systems and ultimately improved care delivery and patient outcomes.
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Affiliation(s)
- Candice Donnelly
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Anna Janssen
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Kavisha Shah
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
| | - Paul Harnett
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
- The Crown Princess Mary Cancer Centre, Western Sydney Local Health District, Westmead, New South Wales, Australia
| | - Shalini Vinod
- Liverpool Cancer Therapy Centre, South Western Sydney Local Health District, Liverpool, New South Wales, Australia
- South Western Sydney Clinical School, University of New South Wales, Liverpool, New South Wales, Australia
| | - Tim J Shaw
- Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia
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