Topics

Lifestyle factors — smoking, alcohol consumption, inadequate dietary levels of fruit and vegetables — are major risk factors for chronic medical conditions.1 The importance of clinicians encouraging people to modify their lifestyles is emphasised in many guidelines.2 A study that included 4716 American adults found that patient‐reported lifestyle advice from their doctors was associated with corresponding behavioural changes (weight reduction, increased physical activity).3 How often Australian general practitioners provide their patients with lifestyle advice and whether such advice is effective are unknown.

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Institute for Evidence‐Based Healthcare, Bond University, Gold Coast, QLD

Correspondence: lalbarqo@bond.edu.au

Open access:

Open access publishing facilitated by Bond University, as part of the Wiley ‐ Bond University agreement via the Council of Australian University Librarians.

Data sharing:

The data we analysed for this report are publicly available.

Acknowledgements:

This study was supported by a National Health and Medical Research Council Investigator Grant (2008379). The funder played no role in the planning, writing, or publication of this study.

Competing interests:

No relevant disclosures.

1. GBD 2019 Risk Factors Collaborators. Global burden of 87 risk factors in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019. Lancet 2020; 396: 1223‐1249.
2. US Preventive Services Task Force; Mangione CM, Barry MJ, Nicholson WK, et al. Behavioral counseling interventions to promote a healthy diet and physical activity for cardiovascular disease prevention in adults without cardiovascular disease risk factors: US Preventive Services Task Force recommendation statement. JAMA 2022; 328: 367‐374.
3. Williams AR, Wilson‐Genderson M, Thomson MD. A cross‐sectional analysis of associations between lifestyle advice and behavior changes in patients with hypertension or diabetes: NHANES 2015–2018. Prev Med 2021; 145: 106426.
4. Australian Bureau of Statistics. Data items. In: National Health Survey: first results methodology, 2020–21. 21 Mar 2022. https://www.abs.gov.au/methodologies/national‐health‐survey‐methodology/2020‐21 (viewed Oct 2023).
5. Henry JA, Jebb SA, Aveyard P, et al. Lifestyle advice for hypertension or diabetes: trend analysis from 2002 to 2017 in England. Br J Gen Pract 2022; 72: e269‐e275.
6. Albarqouni L, Montori V, Jørgensen KJ, et al. Applying the time needed to treat to NICE guidelines on lifestyle interventions. BMJ Evid Based Med 2023; 28: 354‐355.

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Symptomatic cancer diagnosis in general practice: a critical perspective of current guidelines and risk assessment tools

Brent Venning and Jon D Emery

Med J Aust || doi: 10.5694/mja2.52287
Published online: 6 May 2024

Topics

Neoplasms

General medicine

On 2 November 2023, Cancer Australia unveiled the Australian Cancer Plan, emphasising a strategic commitment to “maximising cancer prevention and early detection”.1,2 This initiative holds particular significance for general practice, as most cancer diagnoses originate from symptomatic presentations to primary care, even when screening programs are available.3 For context, full‐time general practitioners on average diagnose up to 12 non‐cutaneous cancers annually, but they see patients consulting with symptoms associated with cancer almost daily.3,4

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Centre for Cancer Research, University of Melbourne, Melbourne, VIC

Correspondence: brent.venning@unimelb.edu.au

Open access:

Open access publishing facilitated by The University of Melbourne, as part of the Wiley ‐ The University of Melbourne agreement via the Council of Australian University Librarians.

Acknowledgements:

Brent Venning is supported by the Melbourne Academic Centre for Health (MACH) through the MACH‐Track program and by a University of Melbourne Research Training Program Scholarship. Jon Emery is supported by a National Health and Medical Research Council Investigator Grant (APP1195302) and is an Associate Director of the CanTest Collaborative (funded by Cancer Research UK, C8640/A23385).

Competing interests:

No relevant disclosures.

1. Cancer Australia. Australian Cancer Plan [website]. Canberra: Commonwealth of Australia, 2021. https://www.canceraustralia.gov.au/australian‐cancer‐plan (viewed Nov 2023).
2. Chaji D, Boltong A, Der Vartanian C, et al. Setting the policy agenda for cancer control reform: Australia's first national cancer control plan. Med J Aust 2023; 219: 451‐454. https://www.mja.com.au/journal/2023/219/10/setting‐policy‐agenda‐cancer‐control‐reform‐australias‐first‐national‐cancer
3. Emery JD. The challenges of early diagnosis of cancer in general practice. Med J Aust 2015; 203: 391‐393. https://www.mja.com.au/journal/2015/203/10/challenges‐early‐diagnosis‐cancer‐general‐practice
4. Hamilton W. Cancer diagnosis in primary care. Br J Gen Pract 2010; 60: 121‐128.
5. Rubin G, Berendsen A, Crawford SM, et al. The expanding role of primary care in cancer control. Lancet Oncol 2015; 16: 1231‐1272.
6. Koo MM, Hamilton W, Walter FM, et al. Symptom signatures and diagnostic timeliness in cancer patients: a review of current evidence. Neoplasia 2018; 20: 165‐174.
7. Stapley S, Peters TJ, Neal RD, et al. The risk of pancreatic cancer in symptomatic patients in primary care: a large case‐control study using electronic records. Br J Cancer 2012; 106: 1940‐1944.
8. Jensen H, Tørring ML, Olesen F, et al. Cancer suspicion in general practice, urgent referral and time to diagnosis: a population‐based GP survey and registry study. BMC Cancer 2014; 14: 636.
9. McGarvey N, Gitlin M, Fadli E, Chung KC. Increased healthcare costs by later stage cancer diagnosis. BMC Health Serv Res 2022; 22: 1155.
10. Emery JD, Shaw K, Williams B, et al. The role of primary care in early detection and follow‐up of cancer. Nat Rev Clin Oncol 2014; 11: 38‐48.
11. Renzi C, Kaushal A, Emery J, et al. Comorbid chronic diseases and cancer diagnosis: disease‐specific effects and underlying mechanisms. Nat Rev Clin Oncol 2019; 16: 746‐761.
12. Brownlee S, Chalkidou K, Doust J, et al. Evidence for overuse of medical services around the world. Lancet 2017; 390: 156‐168.
13. Lyratzopoulos G, Vedsted P, Singh H. Understanding missed opportunities for more timely diagnosis of cancer in symptomatic patients after presentation. Br J Cancer 2015; 112 (Suppl): S84‐S91.
14. Banks J, Hollinghurst S, Bigwood L, et al. Preferences for cancer investigation: a vignette‐based study of primary‐care attendees. Lancet Oncol 2014; 15: 232‐240.
15. Venning B, Pearce A, Lourenco RDA, et al. Patient preferences for investigating cancer‐related symptoms in australian general practice: a discrete choice experiment. Br J Gen Pract 2024; https://doi.org/10.3399/BJGP.2023.0583 [Epub ahead of print].
16. Cancer Australia. Optimal Care Pathways. Canberra: Commonwealth of Australia, 2024. https://www.canceraustralia.gov.au/optimal‐cancer‐care‐pathways (viewed Apr 2024).
17. Cancer Australia. Optimal Care Pathways: for general practitioners and primary care staff — I‐PACED (Implementing Pathways for Cancer Early Diagnosis). Canberra: Commonwealth of Australia, 2024. https://www.cancervic.org.au/get‐support/for‐health‐professionals/optimal‐care‐pathways (viewed Apr 2024).
18. Cancer Australia. GP guides and resources. https://www.canceraustralia.gov.au/clinical‐best‐practice/gynaecological‐cancers/gp‐guides‐and‐resources. Canberra: Commonwealth of Australia, 2021. (viewed Apr 2024).
19. Chiang PPC, Glance D, Walker J, et al. Implementing a QCancer risk tool into general practice consultations: an exploratory study using simulated consultations with Australian general practitioners. Br J Cancer 2015; 112 (Suppl): S77‐S83.
20. National Institute for Health and Care Excellence. Suspected cancer: recognition and referral [NICE guideline NG12; updated Oct 2023]. Manchester (UK): NICE, 2015. https://www.nice.org.uk/guidance/ng12 (viewed Mar 2024).
21. Conroy T, Pfeiffer P, Vilgrain V, et al. Pancreatic cancer: ESMO clinical practice guideline for diagnosis, treatment and follow‐up. Ann Oncol 2023; 34: 987‐1002.
22. Hamilton W. The CAPER studies: five case‐control studies aimed at identifying and quantifying the risk of cancer in symptomatic primary care patients. Br J Cancer 2009; 101 (Suppl): S80‐S86.
23. Hamilton W, Green T, Martins T, et al. Evaluation of risk assessment tools for suspected cancer in general practice: a cohort study. Br J Gen Pract 2013; 63: e30‐e36.
24. Price S, Spencer A, Medina‐Lara A, Hamilton W. Availability and use of cancer decision‐support tools: a cross‐sectional survey of UK primary care. Br J Gen Pract 2019; 69: e437‐e443.
25. Hamilton W, Mounce L, Abel GA, et al. Protocol for a pragmatic cluster randomised controlled trial assessing the clinical effectiveness and cost‐effectiveness of Electronic RIsk‐assessment for CAncer for patients in general practice (ERICA). BMJ Open 2023; 13: e065232.
26. Royal Australian College of General Practitioners. Electronic clinical decision support in general practice [website]. Melbourne: RACGP, 2024. https://www.racgp.org.au/advocacy/position‐statements/view‐all‐position‐statements/clinical‐and‐practice‐management/electronic‐clinical‐decision‐support (viewed Mar 2024).
27. Chima S, Reece JC, Milley K, et al. Decision support tools to improve cancer diagnostic decision making in primary care: a systematic review. Br J Gen Pract 2019; 69: e809‐e818.
28. Hunter B, Biezen R, Alexander K, et al. Future Health Today: codesign of an electronic chronic disease quality improvement tool for use in general practice using a service design approach. BMJ Open 2020; 10: e040228.
29. Davies D, Morgan M, de Wet C. Supporting quality and safety in general practice: Response rates to computer decision support. Aust J Gen Pract 2022; 51: 884‐892.

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Research

How should artificial intelligence be used in Australian health care? Recommendations from a citizens’ jury

Stacy M Carter, Yves Saint James Aquino, Lucy Carolan, Emma Frost, Chris Degeling, Wendy A Rogers, Ian A Scott, Katy JL Bell, Belinda Fabrianesi and Farah Magrabi

Med J Aust 2024; 220 (8): . || doi: 10.5694/mja2.52283
Published online: 6 May 2024

Topics

Information science

Health services administration

Social determinants of health

Abstract

Objective: To support a diverse sample of Australians to make recommendations about the use of artificial intelligence (AI) technology in health care.

Study design: Citizens’ jury, deliberating the question: “Under which circumstances, if any, should artificial intelligence be used in Australian health systems to detect or diagnose disease?”

Setting, participants: Thirty Australian adults recruited by Sortition Foundation using random invitation and stratified selection to reflect population proportions by gender, age, ancestry, highest level of education, and residential location (state/territory; urban, regional, rural). The jury process took 18 days (16 March – 2 April 2023): fifteen days online and three days face‐to‐face in Sydney, where the jurors, both in small groups and together, were informed about and discussed the question, and developed recommendations with reasons. Jurors received extensive information: a printed handbook, online documents, and recorded presentations by four expert speakers. Jurors asked questions and received answers from the experts during the online period of the process, and during the first day of the face‐to‐face meeting.

Main outcome measures: Jury recommendations, with reasons.

Results: The jurors recommended an overarching, independently governed charter and framework for health care AI. The other nine recommendation categories concerned balancing benefits and harms; fairness and bias; patients’ rights and choices; clinical governance and training; technical governance and standards; data governance and use; open source software; AI evaluation and assessment; and education and communication.

Conclusions: The deliberative process supported a nationally representative sample of citizens to construct recommendations about how AI in health care should be developed, used, and governed. Recommendations derived using such methods could guide clinicians, policy makers, AI researchers and developers, and health service users to develop approaches that ensure trustworthy and responsible use of this technology.

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1 University of Wollongong, Wollongong, NSW
2 Australian Centre for Health Engagement, Evidence and Values, University of Wollongong, Wollongong, NSW
3 Macquarie University, Sydney, NSW
4 University of Queensland, Brisbane, QLD
5 Princess Alexandra Hospital, Brisbane, QLD
6 University of Sydney, Sydney, NSW
7 Australian Institute for Health Innovation, Macquarie University, Sydney, NSW

Correspondence: stacyc@uow.edu.au

Open access:

Open access publishing facilitated by University of Wollongong, as part of the Wiley – University of Wollongong agreement via the Council of Australian University Librarians.

Data sharing:

Individual deidentified participant data will be partially shared. The ethics approval for the study stipulated that transcripts of recordings of the jurors’ deliberations would remain confidential because of the risk of individual identification. Our study did not involve data dictionaries. Extensive information about the study protocol, and data generated for and in the study (including descriptions of the process, the expert witness videos, questions generated by the jury, and answers provided by the experts) are available at https://uow.info/TAWSYN_JURY.

Acknowledgements:

This study was supported by the National Health and Medical Research Council (1181960).

Competing interests:

No relevant disclosures.

1. Australian Department of Industry, Science and Resources. Supporting responsible AI: discussion paper. Government's interim response. 17 Jan 2024. https://consult.industry.gov.au/supporting‐responsible‐ai (viewed Mar 2024).
2. Lyell D, Wang Y, Coiera E, Magrabi F. More than algorithms: an analysis of safety events involving ML‐enabled medical devices reported to the FDA. J Am Med Inform Assoc 2023; 30: 1227‐1226.
3. Wadie J. A roadmap for artificial intelligence in healthcare for Australia news]. Australian Alliance for Artificial Intelligence in Healthcare, 1 Dec 2021. https://aihealthalliance.org/2021/12/01/a‐roadmap‐for‐ai‐in‐healthcare‐for‐australia (viewed Oct 2023).
4. Coiera EW, Verspoor K, Hansen DP. We need to chat about artificial intelligence. Med J Aust 2023; 219: 98‐100. https://www.mja.com.au/journal/2023/219/3/we‐need‐chat‐about‐artificial‐intelligence
5. Pearce C, McLeod A, Rinehart N, et al. Artificial intelligence and the clinical world: a view from the front line. Med J Aust 2019; 210 (6 Suppl): S38‐S40. https://www.mja.com.au/journal/2019/210/6/artificial‐intelligence‐and‐clinical‐world‐view‐front‐line
6. Moodie C. Australian Medical Association calls for national regulations around AI in health care. ABC News (Australia), 28 May 2023. https://www.abc.net.au/news/2023‐05‐28/ama‐calls‐for‐national‐regulations‐for‐ai‐in‐health/102381314 (viewed Oct 2023).
7. Mathews DJH, Balatbat CA, Dzau VJ. Governance of emerging technologies in health and medicine: creating a new framework. N Engl J Med 2022; 386: 2239‐2242.
8. Degeling C, Carter SM, Rychetnik L. Which public and why deliberate? A scoping review of public deliberation in public health and health policy research. Soc Sci Med 2015; 131: 114‐121.
9. Flanigan B, Gölz P, Gupta A, et al. Fair algorithms for selecting citizens’ assemblies. Nature 2021; 596: 548‐552.
10. Australian Centre for Health Engagement Evidence and Values. Artificial intelligence in health: community jury. Undated. https://uow.info/TAWSYN_JURY (viewed Oct 2023).
11. White K, Hunter N, Greaves K. Facilitating deliberation: a practical guide. Melbourne: MosaicLab, 2022.
12. Brown J, Isaacs D. The world café: shaping our futures through conversations that matter. San Francisco: Berrett–Koehler, 2005.
13. Aquino YSJ, Carter SM, Houssami N, et al. Practical, epistemic and normative implications of algorithmic bias in healthcare artificial intelligence: a qualitative study of multidisciplinary expert perspectives. J Med Ethics 2023: jme‐2022‐108850.
14. Thomas R, Sims R, Degeling C, et al. CJCheck Stage 1: development and testing of a checklist for reporting community juries: Delphi process and analysis of studies published in 1996–2015. Health Expect 2016; 20: 626‐637.
15. Australian Bureau of Statistics. Snapshot of Australia, 2021. 28 June 2022. https://www.abs.gov.au/statistics/people/people‐and‐communities/snapshot‐australia/2021 (viewed Oct 2023).
16. Australian Bureau of Statistics. Education and training: census, 2021. 28 June 2022. https://www.abs.gov.au/statistics/people/education/education‐and‐training‐census/latest‐release (viewed Oct 2023).
17. Australian Bureau of Statistics. National state and territory population, December 2023. 28 June 2022. https://www.abs.gov.au/statistics/people/population/national‐state‐and‐territory‐population/dec‐2021 (viewed Oct 2023).
18. Australian Institute of Health and Welfare. Profile of Australia's population. 6 June 2023. https://www.aihw.gov.au/reports/australias‐health/profile‐of‐australias‐population (viewed Oct 2023).
19. van der Veer SN, Riste L, Cheraghi‐Sohi S, et al. Trading off accuracy and explainability in AI decision‐making: findings from 2 citizens’ juries. J Am Med Inform Assoc 2021; 28: 2128‐2138.
20. Forum for Ethical AI. Democratising decisions about technology: a toolkit. 24 Oct 2019. https://www.thersa.org/reports/democratising‐decisions‐technology‐toolkit (viewed Oct 2023).
21. Ada Lovelace Institute. The Citizens’ Biometrics Council London: report with recommendations and findings of a public deliberation on biometrics technology, policy and governance. 30 Mar 2021. https://www.adalovelaceinstitute.org/report/citizens‐biometrics‐council (viewed Oct 2023).
22. European Commission. Proposal for a regulation of the European parliament and the council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain union legislative acts (COM/2021/206 final). 21 Apr 2021. https://eur‐lex.europa.eu/legal‐content/EN/TXT/?uri=CELEX:52021PC0206 (viewed Oct 2023).
23. Therapeutic Goods Administration. Regulation of software based medical devices. 28 Sept 2023. https://www.tga.gov.au/how‐we‐regulate/manufacturing/medical‐devices/manufacturer‐guidance‐specific‐types‐medical‐devices/regulation‐software‐based‐medical‐devices (viewed Oct 2023).
24. Street J, Duszynski K, Krawczyk S, Braunack‐Mayer A. The use of citizens' juries in health policy decision‐making: a systematic review. Soc Sci Med 2014; 109: 1‐9.

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Towards national paediatric clinical practice guidelines

Mike Starr

Med J Aust || doi: 10.5694/mja2.52272
Published online: 15 April 2024

Topics

General medicine

Pediatric medicine

Clinical practice guidelines (CPGs) are intended to improve the quality of clinical care by promoting evidence‐based care, reducing inappropriate variation, and producing optimal outcomes for patients.

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1 Royal Children's Hospital, Melbourne, VIC
2 University of Melbourne, Melbourne, VIC

Correspondence: mike.starr@rch.org.au

Open access:

Open access publishing facilitated by The University of Melbourne, as part of the Wiley ‐ The University of Melbourne agreement via the Council of Australian University Librarians.

Acknowledgements:

The PIC CPG work is funded in part by Clinical Excellence Queensland, the NSW Agency for Clinical Innovation, Safer Care Victoria, RCH Melbourne, and the RCH Foundation. Kate Harding, Matthew O'Meara and Mike South have had an integral role in the work of the CPG committee and PIC steering committee.

Competing interests:

No relevant disclosures.

1. Cohn SL, Gautam B, Preddy JS, et al. Barriers to the use of paediatric clinical practice guidelines in rural and regional New South Wales Australia. Aust J Rural Health 2016; 24, 23‐28.
2. Braithwaite J, Hibbert PD, Jaffe A, et al. Quality of health care for children in Australia, 2012‐2013. JAMA 2018; 319: 1113‐1124.
3. Duggan A, Koff E, Marshall V. Clinical variation: why it matters. Med J Aust 2016; 205: S3‐S4. https://www.mja.com.au/journal/2016/205/10/clinical‐variation‐why‐it‐matters
4. Royal Children's Hospital Melbourne. Clinical Practice Guidelines: CPG information. https://www.rch.org.au/clinicalguide/about_rch_cpgs/CPG_information/ (viewed July 2023).
5. Rea CJ, Alvarez FJ, Tieder JS. The silent crisis of pediatric clinical practice guidelines. JAMA Pediatr 2021; 175: 1201‐1202.
6. Flores G, Lee M, Bauchner H. Pediatricians’ attitudes, beliefs, and practices regarding clinical practice guidelines: a national survey. Pediatrics 2000; 105: 496‐501.

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Ethics and law

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Mainstreaming genomic testing: pre‐test counselling and informed consent

Michaela Cormack, Kathryn B Irving, Fiona Cunningham and Andrew P Fennell

Med J Aust || doi: 10.5694/mja2.52254
Published online: 8 April 2024

Topics

Medical genetics

Ethics and law

General medicine

Health services administration

Nervous system diseases

There is unprecedented, increasing demand for genomic testing in Australia.1,2 Recent developments in paediatric neurology alone include Medical Benefits Schedule, industry and research sponsored testing for monogenic causes of epilepsy, neuromuscular disorders, and syndromic intellectual disability, among others. To be ethically and legally valid, patients must undergo pre‐test counselling before they consent to genomic testing.

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1 Monash Health, Melbourne, VIC
2 Royal Children's Hospital, Melbourne, VIC
3 University of Melbourne, Melbourne, VIC
4 Monash University, Melbourne, VIC

Correspondence: michaela.cormack@monashhealth.org

Consent for publication:

Consent for publication of the case study described and discussed in this article was obtained from both parents on behalf of the child.

Open access:

Open access publishing facilitated by Monash University, as part of the Wiley ‐ Monash University agreement via the Council of Australian University Librarians.

Competing interests:

No relevant disclosures.

1. Fennell AP, Hunter MF, Corboy GP. The changing face of clinical genetics service delivery in the era of genomics: a framework for monitoring service delivery and data from a comprehensive metropolitan general genetics service. Genet Med 2020; 22: 210‐218.
2. National Health and Medical Research Council. DNA genetic testing in the Australian context: a statement from the National Health and Medical Research Council (NHMRC). https://www.nhmrc.gov.au/sites/default/files/2022‐10/dna‐genetic‐testing‐in‐the‐australian‐context.pdf (viewed Sept 2023).
3. Blackburn HL, Schroeder B, Turner C, et al. Management of incidental findings in the era of next‐generation sequencing. Curr Genomics 2015; 16: 159‐174.
4. Meiser B, Irle J, Lobb E, Barlow‐Stewart K. Assessment of the content and process of genetic counseling: a critical review of empirical studies. J Genet Couns 2008; 17: 434‐451.
5. Pacyna JE, Radecki Breitkopf C, Jenkins SM, et al. Should pretest genetic counselling be required for patients pursuing genomic sequencing? Results from a survey of participants in a large genomic implementation study. J Med Genet 2019; 56: 317‐324.
6. Chair SY, Law BMH, Zang Y, et al. The effects of decision aids for genetic counselling among people considering genetic testing: a systematic review. J Clin Nurs 2023; 32: 6796‐6810.
7. Stark Z, Dolman L, Manolio TA, et al. Integrating genomics into healthcare: a global responsibility. Am J Hum Genet 2019; 104: 13‐20.
8. Otlowski MF, Williamson R. Ethical and legal issues and the “new genetics”. Med J Aust 2003; 178: 582‐585. https://www.mja.com.au/journal/2003/178/11/ethical‐and‐legal‐issues‐and‐new‐genetics
9. Miller IO, Sotero de Menezes MA. SCN1A seizure disorders. 2007 [Updated 2022]. In: Adam MP, Mirzaa GM, Pagon RA, et al, editors. GeneReviews. Initial posting: 29 Nov 2007; last revision: 17 Feb 2022. https://www.ncbi.nlm.nih.gov/books/NBK1318/ (viewed Sept 2023).
10. Li W, Schneider AL, Scheffer IE. Defining Dravet syndrome: an essential pre‐requisite for precision medicine trials. Epilepsia 2021; 62: 2205‐2217.
11. Nisselle A, King E, Terrill B, et al. Investigating genomic medicine practice and perceptions amongst Australian non‐genetics physicians to inform education and implementation. NPJ Genom Med 2023; 8: 13.
12. Uhlmann WR, Roberts JS. Ethical issues in neurogenetics. Handb Clin Neurol 2018; 147: 23‐36.
13. Human Genetics Society of Australasia. Code of ethics for genetic counsellors. 2022. https://www.hgsa.org.au/documents/item/9589 (viewed Oct 2023).
14. Tiller J, Lacaze P, Otlowski M. The Australian moratorium on genetics and life insurance: evaluating policy compared to Parliamentary recommendations regarding genetic discrimination. Public Health Res Pract 2022; 32: e3242235.
15. Willcox D, Trent RJA, Lyons N, et al. Making good on the promise of genomics in healthcare: the NSW Health perspective. Aust Health Rev 2023; 47: 631‐633.
16. King E, Halliday J, Archibald AD. et al. Development and use of the Australian reproductive genetic carrier screening decision aid. Eur J Hum Genet 2022; 30: 194‐202.
17. Wright H, Zhao L, Birks M, Mills J. Genomic literacy of registered nurses, and midwives in Australia: a cross‐sectional survey. J Nurs Scholarsh 2019; 51: 40‐49.

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Medicare‐funded reproductive genetic carrier screening in Australia has arrived: are we ready?

Alice P Rogers, Lara Fitzgerald, Jan Liebelt and Christopher Barnett

Med J Aust || doi: 10.5694/mja2.52261
Published online: 8 April 2024

Topics

Women's health

Medical genetics

Health occupations

Reproductive genetic carrier screening (RGCS) is a preventive health strategy performed to identify healthy couples and individuals who are at increased chance of having a child affected by a serious, childhood onset autosomal recessive or X‐linked genetic condition (Box 1).

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1 SA Clinical Genetics Service, Women's and Children's Hospital, Adelaide, SA
2 University of Adelaide, Adelaide, SA
3 Repromed (Adelaide Fertility Centre), Adelaide, SA

Correspondence: christopher.barnett@sa.gov.au

Open access:

Open access publishing facilitated by The University of Adelaide, as part of the Wiley ‐ The University of Adelaide agreement via the Council of Australian University Librarians.

Competing interests:

Jan Liebelt and Lara Fitzgerald are employed by Repromed, whose laboratory offers preconception RGCS. They also provide genetic counselling services.

1. Kaback MM, Nathan TJ, Greenwald S. Tay‐Sachs disease: heterozygote screening and prenatal diagnosis—US experience and world perspective. Prog Clin Biol Res 1977; 18: 13‐36.
2. Watson EK, Mayall E, Chapple J, et al. Screening for carriers of cystic fibrosis through primary health care services. BMJ 1991; 303: 504‐507.
3. Srinivasan BS, Evans EA, Flannick J, et al. A universal carrier test for the long tail of Mendelian disease. Reprod Biomed Online 2010; 21: 537‐551.
4. Grody WW, Thompson BH, Gregg AR, et al. ACMG position statement on prenatal/preconception expanded carrier screening. Genet Med 2013; 15: 482‐483.
5. Royal Australian and New Zealand College of Obstetricians and Gynaecologists. Genetic carrier screening. Mar 2019. https://ranzcog.edu.au/wp‐content/uploads/2022/05/Genetic‐carrier‐screeningC‐Obs‐63New‐March‐2019_1.pdf (viewed Nov 2023).
6. Haque IS, Lazarin GA, Kang HP, et al. Modeled fetal risk of genetic diseases identified by expanded carrier screening. JAMA 2016; 316: 734‐742.
7. Archibald AD, Smith MJ, Burgess T, et al. Reproductive genetic carrier screening for cystic fibrosis, fragile X syndrome, and spinal muscular atrophy in Australia: outcomes of 12,000 tests. Genet Med 2018; 20: 513‐523.
8. Fridman H, Yntema HG, Mägi R, et al. The landscape of autosomal‐recessive pathogenic variants in European populations reveals phenotype‐specific effects. Am J Hum Genet 2021; 108: 608‐619.
9. Best S, Long J, Theodorou T, et al. Health practitioners’ perceptions of the barriers and enablers to the implementation of reproductive genetic carrier screening: a systematic review. Prenat Diagn 2021; 41: 708‐719.
10. Goldberg JD, Pierson S, Johansen Taber K. Expanded carrier screening: what conditions should we screen for? Prenat Diagn 2023; 43: 496‐505.
11. Gregg AR, Aarabi M, Klugman S, et al. Screening for autosomal recessive and X‐linked conditions during pregnancy and preconception: a practice resource of the American College of Medical Genetics and Genomics (ACMG). Genet Med 2021; 23: 1793‐1806.
12. Henneman L, Borry P, Chokoshvili D, et al. Responsible implementation of expanded carrier screening. Eur J Hum Genet 2016; 24: e1‐e12.
13. Committee Opinion No. 690 summary: Carrier screening in the age of genomic medicine. Obstet Gynecol 2017; 129: e35‐e40.
14. Grody WW, Cutting GR, Klinger KW, et al. Laboratory standards and guidelines for population‐based cystic fibrosis carrier screening. Genet Med 2001; 3: 149‐154.
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The 2023 report of the MJA–Lancet Countdown on health and climate change: sustainability needed in Australia's health care sector

Paul J Beggs, Stefan Trueck, Martina K Linnenluecke, Hilary Bambrick, Anthony G Capon, Ivan C Hanigan, Nicolas Borchers Arriagada, Troy J Cross, Sharon Friel, Donna Green, Maddie Heenan, Ollie Jay, Harry Kennard, Arunima Malik, Celia McMichael, Mark Stevenson, Sotiris Vardoulakis, Tran N Dang, Gail Garvey, Raymond Lovett, Veronica Matthews, Dung Phung, Alistair J Woodward, Marina B Romanello and Ying Zhang

Med J Aust || doi: 10.5694/mja2.52245
Published online: 25 March 2024

Topics

Environment and public health

Mental disorders

Health services administration

Statistics, epidemiology and research design

Summary

The MJA–Lancet Countdown on health and climate change in Australia was established in 2017 and produced its first national assessment in 2018 and annual updates in 2019, 2020, 2021 and 2022. It examines five broad domains: health hazards, exposures and impacts; adaptation, planning and resilience for health; mitigation actions and health co‐benefits; economics and finance; and public and political engagement. In this, the sixth report of the MJA–Lancet Countdown, we track progress on an extensive suite of indicators across these five domains, accessing and presenting the latest data and further refining and developing our analyses.
Our results highlight the health and economic costs of inaction on health and climate change. A series of major flood events across the four eastern states of Australia in 2022 was the main contributor to insured losses from climate‐related catastrophes of $7.168 billion — the highest amount on record. The floods also directly caused 23 deaths and resulted in the displacement of tens of thousands of people.
High red meat and processed meat consumption and insufficient consumption of fruit and vegetables accounted for about half of the 87 166 diet‐related deaths in Australia in 2021. Correction of this imbalance would both save lives and reduce the heavy carbon footprint associated with meat production.
We find signs of progress on health and climate change. Importantly, the Australian Government released Australia's first National Health and Climate Strategy, and the Government of Western Australia is preparing a Health Sector Adaptation Plan. We also find increasing action on, and engagement with, health and climate change at a community level, with the number of electric vehicle sales almost doubling in 2022 compared with 2021, and with a 65% increase in coverage of health and climate change in the media in 2022 compared with 2021.
Overall, the urgency of substantial enhancements in Australia's mitigation and adaptation responses to the enormous health and climate change challenge cannot be overstated. Australia's energy system, and its health care sector, currently emit an unreasonable and unjust proportion of greenhouse gases into the atmosphere. As the Lancet Countdown enters its second and most critical phase in the leadup to 2030, the depth and breadth of our assessment of health and climate change will be augmented to increasingly examine Australia in its regional context, and to better measure and track key issues in Australia such as mental health and Aboriginal and Torres Strait Islander health and wellbeing.

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1 Macquarie University, Sydney, NSW
2 University of Technology Sydney, Sydney, NSW
3 National Centre for Epidemiology and Population Health, Australian National University, Canberra, ACT
4 Monash Sustainable Development Institute, Monash University, Melbourne, VIC
5 Curtin University, Perth, WA
6 Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS
7 University of Sydney, Sydney, NSW
8 Australian National University, Canberra, ACT
9 Climate Change Research Centre and ARC Centre of Excellence for Climate Extremes, UNSW, Sydney, NSW
10 Australian Prevention Partnership Centre, Sax Institute, Sydney, NSW
11 The George Institute for Global Health, Sydney, NSW
12 Thermal Ergonomics Laboratory, University of Sydney, Sydney, NSW
13 Center on Global Energy Policy, Columbia University, New York, NY, USA
14 University of Melbourne, Melbourne, VIC
15 Transport, Health and Urban Design (THUD) Research Lab, University of Melbourne, Melbourne, VIC
16 University of Medicine and Pharmacy at Ho Chi Minh City, Ho Chi Minh City, Vietnam
17 University of Queensland, Brisbane, QLD
18 Australian Institute of Aboriginal and Torres Strait Islander Studies, Canberra, ACT
19 University Centre for Rural Health, University of Sydney, Sydney, NSW
20 University of Auckland, Auckland, NZ
21 Institute for Global Health, University College London, London, UK

Correspondence: paul.beggs@mq.edu.au

Open access:

Open access publishing facilitated by Macquarie University, as part of the Wiley ‐ Macquarie University agreement via the Council of Australian University Librarians.

Acknowledgements:

We thank Robert Fawcett, Justin Peter, and John Nairn (all from the Australian Bureau of Meteorology) for indicators 1.1 Exposure of vulnerable populations to heatwaves and 2.2 Climate information for health. Ivan Hanigan's access to data for indicators 1.4 and 3.3 was supported by the Centre for Air Pollution, Energy, and Health Research Data Platform funded by the NHMRC Centre for Safe Air (https://www.car‐cre.org.au/; https://cardat.github.io), which received funding from the Australian Research Data Commons for the Integrated National Air Pollution and Health Data project (https://doi.org/10.47486/PS022), and he acknowledges the HEAL (Healthy Environments And Lives) National Research Network, which receives funding from the NHMRC (grant no. 2008937). The Bushfires indicator was generated with support from NASA Applied Sciences Program (grant no. 80NSSC21K0507) and we thank Yang Liu and Qiao Zhu (Emory University) as well as Yun Hang (now at University of Texas Health Science Center) for the Australian data used for this indicator (1.3). We also thank Fay Johnston for assistance with this indicator. We thank Carole Dalin (University College London) for assistance with indicator 3.5 Emissions from agricultural production and consumption. We thank the Lancet Countdown for providing the results for indicators 3.6 Diet and health co‐benefits, and 3.7 Health care sector emissions. We thank the NHMRC for providing the data for indicator 5.4 Health and climate change research funding.

Competing interests:

No relevant disclosures.

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Perspectives

Online first

Call to end shackling of hospitalised palliative prisoner patients

Lara Pemberton, Stacey Panozzo and Jennifer Philip

Med J Aust || doi: 10.5694/mja2.52240
Published online: 18 March 2024

Topics

Palliative care

Social determinants of health

In the face of an ageing prison population, there is growing pressure for correctional health staff to provide end‐of‐life care for the incarcerated.1 This article evaluates the literature and examines the practices surrounding the use of shackles and restraints in palliative prisoner patients cared for in the hospital setting. Although we recognise that the use of restraints is a reasonable strategy in certain circumstances to maintain community safety, it is not clear that age, illness or immobility are always factored into these decisions.

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1 Biomedicine Discovery Institute, Monash University, Melbourne, VIC
2 St Vincent's Hospital Melbourne, Melbourne, VIC
3 University of Melbourne, Melbourne, VIC

Correspondence: stacey.panozzo@svha.org.au

Open access:

Open access publishing facilitated by The University of Melbourne, as part of the Wiley ‐ The University of Melbourne agreement via the Council of Australian University Librarians.

Competing interests:

No relevant disclosures.

1. Kendall M, Streitberg L, Levy MH. Meeting end‐of‐life care needs for patients in custody. Med J Aust 2015; 202: 77‐78. https://www.mja.com.au/journal/2015/202/2/meeting‐end‐life‐care‐needs‐patients‐custody
2. United Nations Office on Drug and Crime. The United Nations Standard Minimum Rules for the Treatment of Prisoners (the Nelson Mandela Rules). Vienna: UNODC, 2015. https://www.unodc.org/documents/justice‐and‐prison‐reform/GA‐RESOLUTION/E_ebook.pdf (viewed Aug 2023).
3. Farthing S, Howell J, Santow E. Implementing OPCAT in Australia. Sydney: Australian Human Rights Commission, 2020. https://humanrights.gov.au/our‐work/rights‐and‐freedoms/publications/implementing‐opcat‐australia‐2020 (viewed Oct 2023).
4. Department of Justice. Use of force, tactical options, instruments of restraint and chemical agents. In: Correctional Management Standards for men's prisons in Victoria. Melbourne: State Government of Victoria, 2011. https://www.corrections.vic.gov.au/correctional‐management‐standards‐for‐mens‐prisons‐in‐victoria (viewed Apr 2023).
5. Australian Medical Association. Medical ethics in custodial settings — 2013 [amended 2015]. Canberra: AMA, 2016. https://www.ama.com.au/position‐statement/medical‐ethics‐custodial‐settings‐2013 (viewed Apr 2023).
6. Bansal AD, Haber LA. On a ventilator in shackles. J Gen Intern Med 2021; 36: 3878‐3879.
7. DiTomas M, Bick J, Williams B. Shackled at the end of life: we can do better. Am J Bioeth 2019, 19: 61‐63.
8. Klock Z, Liantonio J. End‐of‐life care in imprisoned persons. J Pain Symptom Manage 2018; 55: e4‐e6.
9. Stephens S. What does ethical treatment of a dying inmate entail? Am J Bioeth 2019; 19: 58‐59.
10. Ombudsman SA. Inappropriate restraint and shackling of prisoners while receiving medical treatment in hospital. Adelaide: Department for Correctional Services, 2013. https://www.ombudsman.sa.gov.au/publication‐documents/investigation‐reports/2012/correctional_services_july_2012.pdf (viewed Apr 2023).
11. Terminally ill SA prisoner shackled to bed. 9NEWS 2018; 13 Aug. https://www.9news.com.au/national/terminally‐ill‐sa‐prisoner‐shackled‐to‐bed/db8e0cf7‐b7dc‐4bbd‐a070‐2716d4fb0bc5 (viewed Apr 2023).
12. Ryan E; Office of the Inspector of Custodial Services. Routine restraint of people in custody in Western Australia. Perth: Government of Western Australia, 2020. https://www.oics.wa.gov.au/wp‐content/uploads/2020/06/Routine‐use‐of‐restraints‐review.pdf (viewed Aug 2023).
13. Coroner's Court of New South Wales. Inquest into the death of Eric Whittaker [2020]. https://coroners.nsw.gov.au/documents/findings/2020/Whittaker_Findings_Final‐28.2.20_v2.pdf (viewed Aug 2023).
14. Le Gautier R, Panozzo S, Bryan T, et al. A thematic analysis of hospital medical records of patients with advanced illness experiencing incarceration in the last 3 months of life. Palliat Med 2023; 37: 638‐645.
15. Newcomen N. Learning from PPO Investigations: end of life care. London: Prisons and Probation Ombudsman, 2013. https://search.issuelab.org/resource/learning‐from‐ppo‐investigations‐end‐of‐life‐care.html (viewed Feb 2024).
16. Rome RB, Luminais HH, Bourgeois DA, Blais CM. The role of palliative care at the end of life. Ochsner J 2011; 11: 348‐352.
17. Schaefer I, DiGiacomo M, Heneka N, et al. Palliative care needs and experiences of people in prison: a systematic review and meta‐synthesis. Palliat Med 2022: 36: 443‐461.
18. Panozzo S, Bryan T, Collins A, et al. Complexities and constraints in end‐of‐life care for hospitalized prisoner patients. J Pain Symptom Manage 2020; 60: 984‐991.
19. Pickles H, Norton E, Ginn E, Schleicher T. Physical restraint and the protection of the human rights of immigration detainees in hospitals. Clin Med (Lond) 2015; 15: 334‐336.
20. Lillie K, Corcoran M, Hunt K, et al. Encountering offenders in community palliative care settings: challenges for care provision. Int J Palliat Nurs 2018; 24: 368‐375.
21. Robinson M, Lavere K, Porsa E. End the routine shackling of incarcerated inpatients. J Hosp Med 2021; 16: 376‐377.
22. Tarzian A. A call to justice in serving hospitalized prisoners. Am J Bioeth 2019; 19: 56‐57.
23. Haber LA, Pratt LA, Erickson HP, Williams BA. Shackling in the hospital. J Gen Intern Med 2022; 37: 1258‐1260.
24. Aday RH. Aging prisoners’ concerns toward dying in prison. OMEGA – Journal of Death and Dying 2006; 52: 199‐216.
25. Lescure T. No patient should have to die in shackles. The Washington Post 2021; 5 Oct. https://www.washingtonpost.com/opinions/2021/10/05/no‐patient‐should‐have‐die‐shackles/ (viewed Apr 2023).

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Research

Expanding access to fracture liaison services in Australia for people with minimal trauma fractures: a system dynamics modelling study

Alicia R Jones, Danielle Currie, Cindy Peng, Peter R Ebeling, Jackie R Center, Gustavo Duque, Sean Lybrand, Greg Lyubomirsky, Rebecca J Mitchell, Sallie Pearson, Markus J Seibel and Jo‐An Occhipinti

Med J Aust 2024; 220 (5): . || doi: 10.5694/mja2.52241
Published online: 18 March 2024

Topics

Musculoskeletal diseases

Statistics, epidemiology and research design

Health services administration

Abstract

Objectives: To project how many minimal trauma fractures could be averted in Australia by expanding the number and changing the operational characteristics of fracture liaison services (FLS).

Study design: System dynamics modelling.

Setting, participants: People aged 50 years or more who present to hospitals with minimal trauma fractures, Australia, 2020–31.

Main outcome measures: Numbers of all minimal trauma fractures and of hip fractures averted by increasing the FLS number (from 29 to 58 or 100), patient screening rate (from 30% to 60%), and capacity for accepting new patients (from 40 to 80 per service per month), and reducing the proportion of eligible patients who do not attend FLS (from 30% to 15%); cost per fracture averted.

Results: Our model projected a total of 2 441 320 minimal trauma fractures (258 680 hip fractures; 2 182 640 non‐hip fractures) in people aged 50 years or older during 2020–31, including 1 211 646 second or later fractures. Increasing the FLS number to 100 averted a projected 5405 fractures (0.22%; $39 510 per fracture averted); doubling FLS capacity averted a projected 3674 fractures (0.15%; $35 835 per fracture averted). Our model projected that neither doubling the screening rate nor reducing by half the proportion of eligible patients who did not attend FLS alone would reduce the number of fractures. Increasing the FLS number to 100, the screening rate to 60%, and capacity to 80 new patients per service per month would together avert a projected 13 672 fractures (0.56%) at a cost of $42 828 per fracture averted.

Conclusion: Our modelling indicates that increasing the number of hospital‐based FLS and changing key operational characteristics would achieve only moderate reductions in the number of minimal trauma fractures among people aged 50 years or more, and the cost would be relatively high. Alternatives to specialist‐led, hospital‐based FLS should be explored.

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1 Monash Centre for Health Research and Implementation, Monash University, Melbourne, VIC
2 Monash Health, Melbourne, VIC
3 Sax Institute, Sydney, NSW
4 Monash University, Melbourne, VIC
5 Garvan Institute of Medical Research, Sydney, NSW
6 St Vincent's Hospital Sydney, Sydney, NSW
7 Australian Institute for Musculoskeletal Science (AIMSS), University of Melbourne and Western Health, Melbourne, VIC
8 Western Health, Melbourne, VIC
9 Amgen Europe, Rotkreuz, Switzerland
10 Healthy Bones Australia, Sydney, NSW
11 Australian Institute of Health Innovation, Macquarie University, Sydney, NSW
12 Centre for Big Data Research in Health, University of New South Wales, Sydney, NSW
13 Centre of Research Excellence in Medicines Intelligence, University of New South Wales, Sydney, NSW
14 Concord Clinical School, University of Sydney, Sydney, NSW
15 ANZAC Research Institute, University of Sydney, Sydney, NSW
16 Brain and Mind Centre, University of Sydney, Sydney, NSW
17 Computer Simulation and Advanced Research Technologies (CSART), Sydney, NSW

Correspondence: alicia.jones@monash.edu

Open access:

Open access publishing facilitated by Monash University, as part of the Wiley – Monash University agreement via the Council of Australian University Librarians.

Acknowledgements:

This investigation was funded by Amgen Australia. It was overseen by an expert advisory panel, including a representative from the funder, with an independent chair. The funder contributed to the scope and design of this study, and preparation and review of the manuscript, but did not influence the collation, management, analysis, and interpretation of the data, or the decision to submit the manuscript for publication.

We thank Janet Sluggett (University of South Australia, Adelaide), Cathie Sherrington (Institute for Musculoskeletal Health, University of Sydney, Sydney), Matthew Jennings (Liverpool Hospital, Sydney), Henry Cutler (Centre for Health Economy, Macquarie University, Sydney), Jacqueline Close (Prince of Wales Hospital, Sydney), and Mark Heffernan (Western Sydney University, Sydney) for their contributions to the advisory group and modelling.

Competing interests:

Jo‐An Occhipinti is managing director of Computer Simulation and Advanced Research Technologies. Alicia Jones holds a National Health and Medical Research Council (NHMRC) postgraduate research scholarship (1169192). Markus J Seibel holds an NHMRC Investigator Grant for research into secondary fracture prevention (APP1196062). Sean Lybrand is an employee of Amgen Australia.

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Narrative reviews

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The provision of general surgery in rural Australia: a narrative review

Jessica Paynter, Kirby R Qin, Janelle Brennan, David J Hunter‐Smith and Warren M Rozen

Med J Aust || doi: 10.5694/mja2.52232
Published online: 4 March 2024

Topics

Health services administration

Surgical procedures, operative

Summary

Rural surgery is most commonly provided by general surgeons to the 29% of people (7 million) living in rural Australia.
The provision of rural general surgery to enable equitable and safe surgical care for rural Australians is a multifaceted issue concerning recruitment, training, retention, surgical procedures and surgical outcomes.
Sustaining the rural general surgical workforce will be dependent upon growing an increased number of resident rural general surgeons, as well as changed models of care, with a need for ongoing review to track the outcomes of these changes.
To increase recruitment, rural general surgical training must improve to be less stressful for trainees and to be incorporated alongside a rural‐facing generalist curriculum.
Rural general surgical outcomes (excluding some oncology conditions) achieve comparable results to metropolitan centres.
Access to, and outcomes of, surgical oncology services continues to be inequitable for rural Australians and should be a major focus for improved service delivery.

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1 Monash Rural Health — Bendigo, Monash University, Bendigo, VIC
2 Bendigo Health, Bendigo, VIC
3 Monash University, Melbourne, VIC

Correspondence: jess.paynter@monash.edu

Open access:

Open access publishing facilitated by Monash University, as part of the Wiley ‐ Monash University agreement via the Council of Australian University Librarians.

Competing interests:

No relevant disclosures.

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