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

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.

Monoclonal antibodies for treating early Alzheimer disease-a commentary on recent 'positive' trials.

Recent phase 3 randomised controlled trials of amyloid-targeting monoclonal antibodies in people with pre-clinical or early Alzheimer disease have reported positive results, raising hope of finally having disease-modifying drugs. Given their far-reaching implications for clinical practice, the methods and findings of these trials, and the disease causation theory underpinning the mechanism of drug action, need to be critically appraised. Key considerations are the representativeness of trial populations; balance of prognostic factors at baseline; psychometric properties and minimal clinically important differences of the primary efficacy outcome measures; level of study fidelity; consistency of subgroup analyses; replication of findings in similar trials; sponsor role and potential conflicts of interest; consistency of results with disease causation theory; cost and resource estimates; and alternative prevention and treatment strategies. In this commentary, we show shortcomings in each of these areas and conclude that monoclonal antibody treatment for early Alzheimer disease is lacking high-quality evidence of clinically meaningful impacts at an affordable cost.

The new paradigm in machine learning - foundation models, large language models and beyond: a primer for physicians.

Foundation machine learning models are deep learning models capable of performing many different tasks using different data modalities such as text, audio, images and video. They represent a major shift from traditional task-specific machine learning prediction models. Large language models (LLM), brought to wide public prominence in the form of ChatGPT, are text-based foundational models that have the potential to transform medicine by enabling automation of a range of tasks, including writing discharge summaries, answering patients questions and assisting in clinical decision-making. However, such models are not without risk and can potentially cause harm if their development, evaluation and use are devoid of proper scrutiny. This narrative review describes the different types of LLM, their emerging applications and potential limitations and bias and likely future translation into clinical practice.

Coping with uncertainty in clinical practice: a narrative review.

Clinicians must make decisions amid the uncertainty that is ubiquitous to clinical practice. Uncertainty in clinical practice can assume many forms depending on its source, such as insufficient personal knowledge or scientific evidence, limited practical understanding or competence, challenging interpersonal relationships, and complexity and ambiguity in clinical encounters. The level and experience of uncertainty varies according to personal traits, clinical context, affective factors and sociocultural norms. Clinicians vary in their tolerance of uncertainty, and maladaptive responses may adversely affect patient care and clinician wellbeing. Various strategies can be used to minimise and manage, but not eliminate, uncertainty and to share uncertainty with patients without compromising the clinician-patient relationship or clinician credibility.

Digital health competencies for the next generation of physicians.

As health care continues to change and evolve in a digital society, there is an escalating need for physicians who are skilled and enabled to deliver care using digital health technologies, while remaining able to successfully broker the triadic relationship among patients, computers and themselves. The focus needs to remain firmly on how technology can be leveraged and used to support good medical practice and quality health care, particularly around resolution of longstanding challenges in health care delivery, including equitable access in rural and remote areas, closing the gap on health outcomes and experiences for First Nations peoples and better support in aged care and those living with chronic disease and disability. We propose a set of requisite digital health competencies and recommend that the acquisition and evaluation of these competencies become embedded in physician training curricula and continuing professional development programmes.

Quality of observational studies of clinical interventions: a meta-epidemiological review.

BACKGROUND: This meta-epidemiological study aimed to assess methodological quality of a sample of contemporary non-randomised clinical studies of clinical interventions. METHODS: This was a cross-sectional study of observational studies published between January 1, 2012 and December 31, 2018. Studies were identified in PubMed using search terms 'association', 'observational,' 'non-randomised' 'comparative effectiveness' within titles or abstracts. Each study was appraised against 35 quality criteria by two authors independently, with each criterion rated fully, partially or not satisfied. These quality criteria were grouped into 6 categories: justification for observational design (n = 2); minimisation of bias in study design and data collection (n = 11); use of appropriate methods to create comparable groups (n = 6); appropriate adjustment of observed effects (n = 5); validation of observed effects (n = 9); and authors interpretations (n = 2). RESULTS: Of 50 unique studies, 49 (98%) were published in two US general medical journals. No study fully satisfied all applicable criteria; the mean (+/-SD) proportion of applicable criteria fully satisfied across all studies was 72% (+/- 10%). The categories of quality criteria demonstrating the lowest proportions of fully satisfied criteria were measures used to adjust observed effects (criteria 20, 23, 24) and validate observed effects (criteria 25, 27, 33). Criteria associated with ≤50% of full satisfaction across studies, where applicable, comprised: imputation methods to account for missing data (50%); justification for not performing an RCT (42%); interaction analyses in identifying independent prognostic factors potentially influencing intervention effects (42%); use of statistical correction to minimise type 1 error in multiple outcome analyses (33%); clinically significant effect sizes (30%); residual bias analyses for unmeasured or unknown confounders (14%); and falsification tests for residual confounding (8%). The proportions of fully satisfied criteria did not change over time. CONCLUSIONS: Recently published observational studies fail to fully satisfy more than one in four quality criteria. Criteria that were not or only partially satisfied were identified which serve as remediable targets for researchers and journal editors.

Research activities in general medicine: a scoping survey by the Internal Medicine Society of Australia and New Zealand.

BACKGROUND: In developing an effective framework for a collaborative research network (RN) that supports members involved in research, the Internal Medicine Society of Australia and New Zealand (IMSANZ) required a better understanding of the current level of research activity and engagement by general physicians, and factors influencing such engagement. AIMS: To explore the current research landscape amongst general physicians in Australia and Aotearoa New Zealand. METHODS: A questionnaire exploring research participation, scope, research enablers and barriers was disseminated to IMSANZ members over a 3-month period. Core functions of IMSANZ-RN, research priorities, potential solutions to perceived barriers and required level of support were also evaluated. RESULTS: A total of 82 members, mostly senior medical staff (74.4%), responded to the survey (11.8% response rate). More than 70% were involved in impactful research across multiple disciplines, encompassing a wide range of research themes and topics. However, there is limited support and resources available to conduct research, with most projects being self-instigated and self-funded. There is overwhelming support to increasing the profile of research in general medicine through the establishment of IMSANZ-RN, whose principal purposes, as identified by respondents, are to foster collaboration, promote research, provide research education and training, and share information among general physicians. Quality improvement studies (56.1%) and clinical trials (41.5%) were also identified as priority research types. CONCLUSIONS: This study has profiled the constraints faced by general physicians in conducting high-quality collaborative research and provides insights into what is needed to support greater research engagement, through development of a discipline-specific clinical RN.

Systematic review of machine learning models for personalised dosing of heparin.

AIM: To identify and critically appraise studies of prediction models, developed using machine learning (ML) methods, for determining the optimal dosing of unfractionated heparin (UFH). METHODS: Embase, PubMed, CINAHL, Web of Science, International Pharmaceutical Abstracts and IEEE Xplore databases were searched from inception to 31 January 2020 to identify relevant studies using key search terms synonymous with artificial intelligence or ML, 'prediction', 'dose', 'activated partial thromboplastin time (aPTT)' and 'UFH.' Studies had to have used ML methods for developing models that predicted optimal dose of UFH or target therapeutic aPTT levels in the hospital setting. The CHARMS Checklist was used to assess quality and risk of bias of included studies. RESULTS: Of 8393 retrieved abstracts, 61 underwent full text review and eight studies met inclusion criteria. Four studies described models for predicting aPTT, three studies described models predicting optimal dose of heparin during dialysis and one study described a model that used surrogate outcomes of clotting and bleeding to predict a therapeutic aPTT. Studies varied widely in reporting of study participants, feature characterisation and selection, handling of missing data, sample size calculations and the intended clinical application of the model. Only one study conducted an external validation and no studies evaluated model impacts in clinical practice. CONCLUSION: Studies of ML models for UFH dosing are few and none report a model ready for routine clinical use. Existing studies are limited by low methodological quality, inadequate reporting of study factors and absence of external validation and impact analysis.

Reducing Medical Admissions and Presentations Into Hospital through Optimising Medicines (REMAIN HOME): a stepped wedge, cluster randomised controlled trial.

OBJECTIVE: To investigate whether integrating pharmacists into general practices reduces the number of unplanned re-admissions of patients recently discharged from hospital. DESIGN, SETTING: Stepped wedge, cluster randomised trial in 14 general practices in southeast Queensland. PARTICIPANTS: Adults discharged from one of seven study hospitals during the seven days preceding recruitment (22 May 2017 - 14 March 2018) and prescribed five or more long term medicines, or having a primary discharge diagnosis of congestive heart failure or exacerbation of chronic obstructive pulmonary disease. INTERVENTION: Comprehensive face-to-face medicine management consultation with an integrated practice pharmacist within seven days of discharge, followed by a consultation with their general practitioner and further pharmacist consultations as needed. MAJOR OUTCOMES: Rates of unplanned, all-cause hospital re-admissions and emergency department (ED) presentations 12 months after hospital discharge; incremental net difference in overall costs. RESULTS: By 12 months, there had been 282 re-admissions among 177 control patients (incidence rate [IR], 1.65 per person-year) and 136 among 129 intervention patients (IR, 1.09 per person-year; fully adjusted IR ratio [IRR], 0.79; 95% CI, 0.52-1.18). ED presentation incidence (fully adjusted IRR, 0.46; 95% CI, 0.22-0.94) and combined re-admission and ED presentation incidence (fully adjusted IRR, 0.69; 95% CI, 0.48-0.99) were significantly lower for intervention patients. The estimated incremental net cost benefit of the intervention was $5072 per patient, with a benefit-cost ratio of 31:1. CONCLUSION: A collaborative pharmacist-GP model of post-hospital discharge medicines management can reduce the incidence of hospital re-admissions and ED presentations, achieving substantial cost savings to the health system. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry, ACTRN12616001627448 (prospective).

Demystifying machine learning: a primer for physicians.

Machine learning is a tool for analysing digitised data sets and formulating predictions that can optimise clinical decision-making. It aims to identify complex patterns in large data sets and encode them into models that can then classify new unseen cases or make predictions on new data. Machine learning methods take several forms and individual models can be of many different types. More than 50 models have been approved for use in routine healthcare, and the numbers continue to grow exponentially. The reliability and robustness of any model depends on multiple factors, including the quality and quantity of the data used to develop the models, and the selection of features in the data considered most important to maximising accuracy. In ensuring models are safe, effective and reproducible in routine care, physicians need to have some understanding of how these models are developed and evaluated, and to collaborate with data and computer scientists in their design and validation. This narrative review introduces principles, methods and examples of machine learning in a way that does not require mastery of highly complex statistical and computational concepts.

Developing critical thinking skills for delivering optimal care.

Healthcare systems across the world are challenged with problems of misdiagnosis, non-beneficial care, unwarranted practice variation and inefficient or unsafe practice. In countering these shortcomings, clinicians must be able to think critically, interpret and assimilate new knowledge, deal with uncertainty and change behaviour in response to compelling new evidence. Three critical thinking skills underpin effective care: clinical reasoning, evidence-informed decision-making and systems thinking. It is important to define these skills explicitly, explain their rationales, describe methods of instruction and provide examples of optimal application. Educational methods for developing and refining these skills must be embedded within all levels of clinician training and continuing professional development.

Development and dissemination of the national strategic action plan for reducing inappropriate polypharmacy in older Australians.

A cohesive, national approach is needed to address inappropriate polypharmacy in older adults and promote deprescribing. We describe the dissemination of the Quality Use of Medicines to Optimise Ageing in Older Australians: Recommendations for a National Strategic Action Plan to Reduce Inappropriate Polypharmacy, and the initiatives taken to date that align with, and assist in operationalising this plan.

Medication use and cognitive impairment among residents of aged care facilities.

BACKGROUND: Potentially inappropriate polypharmacy is common in residential aged care facilities (RACF). This is of particular concern among people with cognitive impairment who, compared with cognitively intact residents, are potentially more sensitive to the adverse effects of medications. AIM: To compare the patterns of medication prescribing of RACF residents based on cognitive status. METHODS: De-identified data collected during telehealth-mediated geriatric consultations with 720 permanent RACF residents were analysed. Residents were categorised into cognitively intact, mild to moderate impairment and severe impairment groups using the interRAI Cognitive Performance Scale. The number of all regular and when-required medications used in the past 3 days, the level of exposure to anti-cholinergic/sedative medications and potentially inappropriate medications and the use of preventive and symptom control medications were compared across the groups. RESULTS: The median number of medications was 10 (interquartile range (IQR) 8-14). Cognitively intact residents were receiving significantly more medications (median (IQR) 13 (10-16)) than those with mild to moderate (10 (7-13)) or severe (9 (7-12)) cognitive impairment (P < 0.001). Overall, 82% of residents received at least one anti-cholinergic/sedative medication and 26.9% were exposed to one or more potentially inappropriate medications, although the proportions of those receiving such medications were not significantly different across the groups. Of 7658 medications residents were taking daily, 21.3% and 11.7% were classified as symptom control and preventive medications respectively with no significant difference among the groups in their use. CONCLUSION: Our findings highlight the need for optimising prescribing in RACF residents, with particular attention to medications with anti-cholinergic effects.

Frailty, a multisystem ageing syndrome.

The management of frail older people is a key component of aged care. There has been a plethora of tools developed for the diagnosis and screening of frailty. Some of these tools are entering routine clinical practice at a time when the higher healthcare costs involved in caring for older people who are frail have become a potential target for cost-cutting. Yet there is still only limited evidence to support the widespread adoption of frailty tools, and foundational factors impact on their accuracy and validity. Despite the acceptance of frailty as a valid term in research and clinical practice, older people believe the term carries stigma. Such issues indicate that there may be a need to reconsider current approaches to frailty. Recent advances in the science of ageing biology can provide a new framework for reconfiguring how we screen, diagnose, treat and prevent frailty. Frailty can be considered to be a multisystem ageing syndrome of decreased physiological and functional reserve, where the biological changes of ageing are seen in most tissues and organs and are the pathogenic mechanism for frailty. Likewise age-related chronic disease and multimorbidity are syndromes where ageing changes occur in one or multiple systems, respectively. This model focusses diagnostic criteria for frailty onto the biomarkers of ageing and generates new targets for the prevention and treatment of frailty based on interventions that influence ageing biology.

Pill testing at music festivals: is it evidence-based harm reduction?

Recent pill-related deaths of young people at music festivals in Australia have led to a concerted push for on-site pill testing as a means for preventing such events. However, whether pill testing (also termed 'safety checking') is an effective harm reduction strategy remains uncertain. This narrative review concludes that pill testing currently lacks evidence of efficacy sufficient to justify publicly funded national roll-out of on-site pill-testing programmes. Australian governments, addiction specialists and public health experts should collaborate in conducting properly designed field studies aimed at confirming clear benefits from such programmes in reducing pill-related harm.

Prevention and treatment of pressure injuries: A meta-synthesis of Cochrane Reviews.

BACKGROUND: There are many high-quality systematic reviews to inform practice around pressure injury (PI) prevention and treatment. However, they are often unable to provide recommendations for practice and research due to low quality trials. OBJECTIVES: To evaluate current systematic review evidence on the prevention and treatment of PI. METHODS: This meta-synthesis was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Only Cochrane Reviews were included. Evidence from reviews was independently screened and assessed for risk of bias and certainty using Grading of Recommendations, Assessment, Development and Evaluations by two authors, with a third resolving discrepancies. Methodological quality of included reviews was assessed using the second version of A Measurement Tool to Assess Systematic Reviews, and a narrative synthesis undertaken. RESULTS: Twenty-five Cochrane Reviews were included; eight for PI prevention and 19 for PI treatment. Prevention reviews included 102 studies (27,933 participants). Treatment reviews included 154 studies (over 16,936 participants). Three prevention reviews and nine treatment reviews reported risk of bias, judging the included trials as having low or very low certainty evidence. Two reviews reported moderate certainty evidence. Methodological quality of the systematic reviews was rated as high for eight reviews (7/19 for treatment and 1/6 for prevention). Recommendations for prevention included repositioning, nutrition and support surfaces. Recommendations for treatment focused on nutrition and repositioning. CONCLUSIONS: This meta-synthesis confirms the low-certainty of PI prevention and treatment trials, resulting in few recommendations to inform clinical practice. Generation of high-quality evidence on PI prevention and treatment is imperative.

The appropriateness of coronary investigation in myocardial injury and type 2 myocardial infarction (ACT-2): A randomized trial design.

BACKGROUND: Elevated troponin level findings among patients presenting with suspected acute coronary syndrome (ACS) or another intercurrent illness undeniably identifies patients at increased risk of mortality. Whilst enhancing our capacity to discriminate risk, the use of high-sensitivity troponin assays frequently identifies patients with myocardial injury (i.e. troponin rise without acute signs of myocardial ischemia) or type 2 myocardial infarction (T2MI; oxygen supply-demand imbalance). This leads to the clinically challenging task of distinguishing type 1 myocardial infarction (T1MI; coronary plaque rupture) from myocardial injury and T2MI in the context of concurrent acute illness. Diagnostic discernment in this context is crucial because MI classification has implications for further investigation and care. Early invasive management is of well-established benefit among patients with T1MI. However, the appropriateness of this investigation in the heterogeneous context of T2MI, where there is high competing mortality risk, remains unknown. Although coronary angiography in T2MI is advocated by some, there is insufficient evidence in existing literature to support this opinion as highlighted by current national guidelines. OBJECTIVE: The objective is to evaluate the clinical and economic impact of early invasive management with coronary angiography in T2MI in terms of all-cause mortality and cost effectiveness. DESIGN: This prospective, pragmatic, multicenter, randomized trial among patients with suspected supply demand ischemia leading to troponin elevation (n=1,800; T2MI [1,500], chronic myocardial injury [300]) compares the impact of invasive angiography (or computed tomography angiography as per local preference) within 5 days of randomization versus conservative management (with or without functional testing at clinician discretion) on all-cause mortality by 2 years. Randomized treatment allocation will be stratified by baseline estimated risk of mortality using the Acute Physiology, Age, and Chronic Health Evaluation (APACHE) III risk score. Cost-effectiveness will be evaluated by follow-up on clinical events, quality of life, and resource utilization over 24 months. SUMMARY: Ascertaining the most appropriate first-line investigative strategy for these commonly encountered high-risk T2MI patients in a randomized comparative study will be pivotal in informing evidence-based guidelines that lead to better patient and health care outcomes.

Audit-based measures of overuse of medical care in Australian hospital practice.

Overuse of care that does not confer benefit to patients and wastes limited resources is being increasingly recognised as a major healthcare problem. The preferred measure of overuse of a specific intervention is applying an evidence- or consensus-based measure of inappropriateness directly to the medical records of individual patients who have received the intervention. This study aimed to assess the extent of overuse of care in hospital practice in Australia based on peer-reviewed literature that reported clinical audits using explicit measures of overuse applied to patient-level clinical data. Thirty-five studies met selection criteria, 14 relating to investigations, 21 to management strategies. Overuse rates above 30% were reported for coagulation tests, blood cultures, troponin assays, abdominal imaging studies, use of telemetry, blood product infusions, polypharmacy in older patients, prescriptions for various medications (gastric acid suppressants, direct oral anticoagulants, inhaled corticosteroids), admissions for low-risk chest pain and futile interventions in end of life care. Hospital physicians may need to audit their current high-volume practices and ensure they align with current criteria of appropriateness.