Health occupations

To the Editor: Siru and colleagues have raised potential concerns about the strategy recommended by the Australian Diabetes Society (ADS) and other peak bodies to diagnose gestational diabetes (GDM) during the coronavirus disease 2019 (COVID‐19) pandemic.1 In their study, 46% of subjects diagnosed with GDM had a fasting blood glucose level (BGL) < 4.7 mmol/L but elevated post‐load blood glucose levels, and would be missed by the ADS‐recommended strategy. The authors suggested that this exposes women and their newborns to significant risks with the potential for significant harm. No outcome data were provided to justify these assertions. Evidence from the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) study suggests that such women do not have increased rates of pregnancy‐associated complications.2,3,4,5 The subgroups with the highest odds ratios for newborns who were large for gestational age had an elevated fasting BGL and any elevation of post‐load BGL (odds ratio > 3), whereas subgroups having only elevated fasting or post‐load BGL had a considerably lower odds ratio, equivalent to the diagnostic threshold for GDM of 1.75.2 Further, women with a fasting BGL < 4.5 mmol/L had low rates of some complications irrespective of their post‐load BGL.3 A subsequent analysis of 6128 patients from five centres involved in the HAPO study did not observe any increase in pregnancy‐associated complications in women with a fasting BGL below the 75th centile (4.6 mmol/L).4 A recent analysis of 5974 women in the HAPO study assessed the ADS‐recommended COVID‐19 GDM strategy and reported no increase in any complication.5 There were fewer cases of pregnancy‐associated hypertension and caesarean delivery, with similar rates of large‐for‐gestational‐age newborns and neonatal hypoglycaemia. These data provide reassurance. There is no evidence of harm. When this strategy is used, women with a fasting BGL < 4.7 mmol/L are spared being labelled with GDM and do not require education, monitoring, more frequent follow‐up or transfer to specialist services, freeing up valuable health care resources. Importantly, they will not be advised to inappropriately restrict their dietary intake or commence therapy with insulin or metformin with the potential for harm. An initial fasting BGL test would eliminate the need for a pregnancy oral glucose tolerance test in the majority of women, identifying a smaller group of women at risk of pregnancy‐associated complications where management can be more appropriately targeted.

Michael C d'Emden · Jacobus PJ Ungerer · Susan J Jersey

Implementing voluntary assisted dying legislation demands respectful communication and collaboration between health professionals and community The Voluntary Assisted Dying Act 2017 (Vic) (VAD Act) was passed by the Victorian Parliament in November 2017 and came into effect on 19 June 2019.1 The VAD Act is the only legislation of its kind implemented in Australia, but there are several other international jurisdictions where comparable legislations apply.2,3,4 Victoria is the first state in Australia to implement voluntary assisted dying (VAD). There is a dearth of local evidence available which explores the implementation of assisted dying services into a hospital setting, although potential ethical challenges have been identified.2,5,6 This article aims to outline the experience of a tertiary public health service in Melbourne’s western suburbs which implemented VAD in 2019 and the resultant policies and procedures. With the enactment of the VAD Act, Victorian public health services were expected to develop policies and procedures which apply when a patient requests VAD or related information.7 As a tertiary public health service in Victoria, the health service used policies and guidelines suggested by the Department of Health and Human Services (DHHS) and shared documents from other metropolitan tertiary hospitals as a basis for developing local policies and procedures.7,8 The Victorian legislation provided the eligibility criteria and necessary steps required to access VAD, including timing of requests, medical assessments, medication prescription, reporting and professional requirements.1 In mid‐2018, the health service established a VAD Working Group with senior professional and executive representation, including the Chief Medical Officer; the General Counsel; the Executive Director, Nursing and Midwifery; relevant medical heads of units, senior nurses, allied health representatives, and the Senior Clinical Communications Advisor. The Clinical Communications Advisor conducted 1:1 consultations with the 25 Working Group members to explore the impact of VAD legislation on their professional group and clinical practice between September and December 2018. The outcomes of these consultations highlighted the systemic and ethical complexities inherent in implementing VAD and informed the next steps, including the need to engage with a range of appropriately skilled and experienced clinicians throughout the implementation phase.4 A key consideration during the implementation phase was balancing staff members’ right to conscientiously object to supporting patients when the assistance was related to VAD, with the expectation that health professionals would continue to provide care unrelated to VAD.5 Capacity for moral injury for staff for whom their beliefs and values were at odds with the employing organisation’s approach to VAD needed to be recognised and addressed throughout the implementation process.5,9 To assist with planning, the health service had to decide which VAD model of care pathway would be provided — either A, B or C10 (Supporting Information, appendix 1). The pathway selected by the health service was dependent on the number of suitably qualified medical professionals willing to perform VAD coordination and/or consultation roles, in line with VAD legislation requirements. In 2019, the hospital’s medical professionals were invited to complete an anonymous survey asking them to indicate their willingness to participate in VAD. This survey achieved 208 responses (a 17% response rate), 106 of those were from senior medical staff, with 72% of respondents supporting a patient’s access to VAD at the health service. In addition, eight senior medical staff members expressed a willingness to be involved in the facilitation of VAD. The survey results guided the health service’s management to determine Pathway A as the appropriate model of care for this health service. In parallel with this survey, training for VAD was provided by the DHHS‐led VAD Implementation Taskforce. During these sessions, the need for local VAD procedures were identified, as staff members required further guidance to navigate patients’ requests for VAD and to ensure the health service adhered to legislative requirements. Importantly, the procedures needed to support the right of staff to conscientiously object to VAD while fulfilling lawful access to care.5 The multidisciplinary Working Group met 12 times over an 8‐month period, with the first meeting occurring in November 2018. As implementation drew closer, the Working Group focused on a number of actions to operationalise the legislation, including the development of two VAD procedural flow charts for requesting and assessing VAD (Box 1) and for VAD medication and administration (Box 2). These procedural flow charts, as well as the organisation‐wide VAD policy and procedures and the DHHS guidelines, were distributed to all staff electronically and made available on the organisation’s intranet. The procedures developed applied to all staff, including agency and contract staff. Two open‐forums (“grand rounds”) were held to educate staff on VAD legislation, inform staff of the Pathway A model of care, and launch the hospital’s VAD policy and procedures (Supporting Information, appendices 2 and 3). All clinical staff were invited to attend. These forums attracted more than 500 participants and were part didactic and part panel‐led, with interactive audience discussion. Over 50 questions were received through the anonymous electronic tool Mentimeter (www.mentimeter.com) and verbal contributions were documented. A broad range of perspectives, concerns and clinical scenarios posed throughout these sessions prompted the development of a comprehensive frequently asked questions document, which provided further guidance regarding the integration of VAD into clinical practice. Despite the VAD Act coming into effect from June 2019, the health service wanted to provide adequate VAD advice and training before it became an option for patients. The health service thus determined that the VAD policy, procedures and flow charts would be enacted in July 2019. Challenges implementing voluntary assisted dying There were a number of challenges during the planning phase. Primarily, the health service needing to balance the guiding principles of the legislation, which focused on patient‐centred decisions, while embedding practices to mitigate organisational risk. One example surfaced when the Working Group were deciding where VAD medication would be stored during an inpatient stay. The patient’s autonomy was core, but other safety issues were factored in. In this instance, the decision was made to store the patient’s VAD medication box securely within the central pharmacy rather than on the ward or at the patient’s bedside. Perhaps the largest challenge was fulfilling the responsibility of a Pathway A public health service to provide VAD as an option while respecting the staff member’s decision to conscientiously object to facilitating or being involved in VAD. The need to consider each case individually was highlighted, as it was recognised that there is a spectrum of views in relation to conscientiously objecting. Broad consultation enabled a sensitive and considerate implementation plan, including the addition of known conscientious objectors in the Working Group. Processes were embedded to allow conscientious objectors to distance themselves when patients request VAD, including the provision of informed agency nursing staff to replace potential conscientious objectors on a shift, and the broad promotion of a single contact phone number, to which conscientious objectors could anonymously call and hand over this responsibility. Without comparable local evidence, the expected demand for VAD was inferred from international evidence, which predicted that a low number of people would request VAD.2,3 Over a 14‐month period (June 2019 to September 2020), the health service received 42 patient requests for VAD, with four patients progressing to a prescription of VAD medications and dying as a result. Three of these four patients died after receiving VAD as inpatients and one died at home after being discharged from the health service. Patients who requested VAD were cared for across a number of services and received concurrent palliative care as part of appropriate end‐of‐life care management. The patients who died after receiving VAD were cared for in the ward that was most familiar and suited to their needs; palliative care was provided by the treating team, with specialist input as required. Most VAD requests were from patients in the final weeks of their lives, who therefore did not survive the full length of the VAD assessment process. This observation made it imperative that VAD processes complemented end‐of‐life care, thus not denying the patient and their loved ones appropriate palliative and bereavement care respectively. Indeed, a core tenet of staff education was that progression of VAD may occur during end‐of‐life care; therefore, palliative and comfort care must continue concurrently with VAD processes. Implementing VAD in a hospital setting demanded sensitive, honest and respectful communication between multiple health professional groups and the community, particularly between individuals with opposing views. A significant amount of time was spent engaging with and listening to staff with a myriad of perspectives. The framework provided by the VAD legislation and the DHHS VAD Implementation Taskforce enabled the health service to develop local policy, procedures and resources that most appropriately serve the community. The multidisciplinary Working Group proved a useful forum to deal with the complex issues inherent in implementing a progressive legislation into a large health service. Since the implementation of VAD, statewide monitoring and surveillance of VAD has occurred through multisite data collection and mandated reporting. Locally, discussion of case studies, engagement in multisite research and staff consultation will continue to provide vital guidance to the health service when delivering VAD, improving its processes and responding to the needs of patients and staff. Box 1 – Voluntary assisted dying request and assessment procedural flow chart Source: Western Health. Figure reproduced with permission. Box 2 – Voluntary assisted dying medication and administration procedural flow chart EMR = electronic medical record; iPM = patient administration system. Source: Western Health. Figure reproduced with permission.

Sarah Booth · Paul Eleftheriou · Claire Moody

A 1-year-old boy presented with a 6-month history of a brown plaque on his left forearm

Samuel A Der Sarkissian · Deshan F Sebaratnam

Integrating pharmacists into general practice, aged care, and hospital services will enhance the quality use of medicines

Justin Beilby

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).

Christopher R Freeman · Ian A Scott · Karla Hemming · Luke B Connelly · Carl M Kirkpatrick · Ian Coombes · Jennifer Whitty · James Martin · Neil Cottrell · Nancy Sturman · Grant M Russell · Ian Williams · Caroline Nicholson · Sue Kirsa · Holly Foot

The Royal Commission into Aged Care Quality and Safety has highlighted the high rates of polypharmacy and potential medication‐related harm in residential aged care facilities (RACFs) in Australia.1 Residential medication management review (RMMR) is a government‐funded service for facilitating quality use of medicines in RACFs.2 Previous studies have found that RMMRs by accredited pharmacists and general practitioners identify a mean of 2.7–3.9 medication‐related problems per resident, and 45–84% of pharmacists’ recommendations were accepted by GPs.3 Guidelines recommend that residents should generally receive an RMMR on entering an RACF and when their clinical circumstances change,4 but annual claims data5,6 and recent research indicate that not all residents receive RMMRs.7 We examined time to first RMMR after RACF entry by analysing data for the national historical cohort of the Registry of Senior Australians (ROSA).7 In ROSA, de‐identified data collected during aged care eligibility assessments are linked to information about government‐subsidised aged care services, general practice and allied health services subsidised under the Medicare Benefits Schedule (MBS), medicines subsidised under the Pharmaceutical Benefits Scheme (PBS), and the Australian Institute of Health and Welfare National Death Index.8 Non‐Indigenous people aged 65 years or more who first entered permanent residential care during 1 January 2012 – 31 December 2015, had received an entry‐into‐care assessment within 100 days, and had received at least one PBS‐subsidised medication during the preceding year were included. Recipients of Department of Veterans’ Affairs‐funded services and people who had previously undergone RMMRs (eg, during transition care) were excluded. The cumulative incidence function was used to determine time to first MBS claim lodged by GPs for RMMRs (item code 903) or Home Medicines Reviews (HMRs) (item code 900) after entry to permanent residential care, adjusted for competing events (death, or permanent departure from the first RACF for another reason) using the Fine–Gray method,9 with follow‐up to 31 December 2016. Statistical analyses were undertaken in SAS 9.4. The University of South Australia (reference, 200489) and Australian Institute of Health and Welfare (reference, E02018/1/418) Human Research Ethics Committees provided ethics approval for the study. A total of 176 390 residents in 2799 RACFs were followed for a median 479 days (interquartile range [IQR], 149–858 days). Median age at entry was 84 years (IQR, 79–88 years), 108 908 were women (61.7%), and 84 864 were living with dementia (48.1%). In the year preceding entry, residents received a median of 11 unique prescription medications (IQR, 8–16 medications); 109 765 (62.2%) had received at least one high risk medication (as defined by the United States Institute for Safe Medication Practices10), and 7912 (4.5%) had received HMRs in the 12 months prior to RACF entry. By three months after RACF entry, 19.1% of residents (Wald 95% confidence interval [CI], 18.9–19.3%) had received RMMRs, 11.8% (95% CI, 11.6–11.9%) had died without RMMRs, and 5.7% (95% CI, 5.6–5.8%) had left their RACF for other reasons without RMMRs. At 12 months, 43.1% (95% CI, 42.8–43.3%) had received RMMRs, 20.6% (95% CI, 20.5–20.8%) had died without RMMRs, and 9.0% (95% CI, 8.8–9.1%) had left without receiving RMMRs. By 24 months, 49.7% (95% CI, 49.5–50.0%) had received RMMRs, 25.8% (95% CI, 25.6–26.0%) had died without RMMRs, and 10.2% (95% CI, 10.1–10.4%) had left their first RACF for other reasons without receiving RMMRs (Box). The high burden of medication use at the time of RACF entry suggests that most residents could have benefited from RMMRs, but MBS claims for RMMRs were lodged for fewer than one in five residents within three months of RACF entry, and fewer than one in two within two years. Our findings are generalisable to all older Australians entering RACFs, as ROSA captures data for all people aged 65 years or more who access government‐subsidised permanent residential aged care in Australia. We could not determine why residents were not referred for RMMRs, nor the impact of recent program changes2 on RMMR uptake and resident outcomes. In 2014–15, fewer GP medication review claims were reimbursed under the MBS (54 803 RMMRs, 63 872 HMRs) than pharmacist claims (93 517 RMMRs, 72 607 HMRs).5,6 Analysing GP claims may underestimate the number of RMMR reports prepared by pharmacists because GP claims are submitted after the medication management plan is discussed with the resident or family, while pharmacist claims are submitted after the report is sent to the GP.7 MBS claims may not be lodged if the full RMMR process cannot be completed (eg, because the resident died, their clinical circumstances had changed, or the RMMR report was not received or followed up), or claiming may be overlooked. Linkage with pharmacist claims data at the individual resident level could facilitate investigation of these limitations. Despite RMMRs being a key means for minimising medication‐related harm, MBS claims for RMMRs are lodged for only a fraction of residents who enter RACFs. The potential underuse of the program may be a missed opportunity for identifying and resolving medication‐related problems in Australian RACFs. Box – Stacked cumulative incidence function for time to first residential medication management review (RMMR), for first two years of permanent residential care* RACF = residential aged care facility. * For 176 390 residents (in 2799 residential aged facilities) included in the Registry of Senior Australians.8

Janet K Sluggett · J Simon Bell · Catherine Lang · Megan Corlis · Craig Whitehead · Steven L Wesselingh · Maria C Inacio

To the Editor: The New South Wales Department of Health has taken necessarily stringent steps to reduce the risk of workplace outbreaks during the coronavirus disease 2019 (COVID‐19) pandemic. Currently, two nasopharyngeal samples, analysed by polymerase chain reaction (PCR), negative for severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) are required before asymptomatic individuals can return to high risk workplaces (eg, hospitals, schools and prisons) or close proximity living arrangements (eg, residential aged care facilities, military barracks, and group homes).1,2,3 In Newcastle, existent hospital in the home services have been redeployed as part of a tiered pandemic response under the banner “COVID Care at Home”. COVID Care at Home offers daily telehealth monitoring and efficient clearance certification for patients in isolation or excluded from workplaces. In our experience with 45 patients with COVID‐19 admitted to COVID Care at Home, increased PCR surveillance also uncovered cases of prolonged RNA detection. One passenger from the vessel Ruby Princess tested positive for COVID‐19 52 days after the initial swab and more than 60 days after the first day of symptoms. A review of international data showed that PCR positivity usually persists for 20–30 days regardless of symptomology.4 Cases of SARS‐CoV‐2 RNA detection persisting for 60 or even 80 days have been recorded in the literature.5,6 In the case of our patient, the ongoing exclusion from the workplace created significant psychological and financial burden due to lack of leave entitlement. Similar policies in countries with less worker security are likely to have even greater workforce impact. To tackle the issue of prolonged positivity, we have convened a panel of clinicians in the disciplines of infectious diseases, population health, and microbiology to make informed decisions about patients with prolonged viral RNA detection in regard to their ongoing need for isolation and exclusion from high risk environments. PCR positivity is not synonymous with infectivity.7,8 Regardless, to maintain the good results Australia has enjoyed thus far, we will need to persevere with a high level of vigilance. Making informed and safe decisions about clearance for high risk environments and supporting patients with prolonged exclusions from their workplace will be an ongoing challenge for Australian clinicians during the COVID‐19 pandemic.

Eliza Jane T Milliken · Sarah Browning · Danielle A Rohl

Objective: To identify individual and organisational factors associated with the prevalence, type and impact of unprofessional behaviours among hospital employees. Design, setting, participants: Staff in seven metropolitan tertiary hospitals operated by one health care provider in three states were surveyed (Dec 2017 – Nov 2018) about their experience of unprofessional behaviours — 21 classified as incivility or bullying and five as extreme unprofessional behaviour (eg, sexual or physical assault) — and their perceived impact on personal wellbeing, teamwork and care quality, as well as about their speaking‐up skills. Main outcome measures: Frequency of experiencing 26 unprofessional behaviours during the preceding 12 months; factors associated with experiencing unprofessional behaviour and its impact, including self‐reported speaking‐up skills. Results: Valid surveys (more than 60% of questions answered) were submitted by 5178 of an estimated 15 213 staff members (response rate, 34.0%). 4846 respondents (93.6%; 95% CI, 92.9–94.2%) reported experiencing at least one unprofessional behaviour during the preceding year, including 2009 (38.8%; 95% CI, 37.5–40.1%) who reported weekly or more frequent incivility or bullying; 753 (14.5%; 95% CI, 13.6–15.5%) reported extreme unprofessional behaviour. Nurses and non‐clinical staff members aged 25–34 years reported incivility/bullying and extreme behaviour more often than other staff and age groups respectively. Staff with self‐reported speaking‐up skills experienced less incivility/bullying (odds ratio [OR], 0.53; 95% CI, 0.46–0.61) and extreme behaviour (OR, 0.80; 95% CI, 0.67–0.97), and also less frequently an impact on their personal wellbeing (OR, 0.44; 95% CI, 0.38–0.51). Conclusions: Unprofessional behaviour is common among hospital workers. Tolerance for low level poor behaviour may be an enabler for more serious misbehaviour that endangers staff wellbeing and patient safety. Training staff about speaking up is required, together with organisational processes for effectively eliminating unprofessional behaviour.

Johanna Westbrook · Neroli Sunderland · Ling Li · Alain Koyama · Ryan McMullan · Rachel Urwin · Kate Churruca · Melissa T Baysari · Catherine Jones · Erwin Loh · Elizabeth C McInnes · Sandy Middleton · Jeffrey Braithwaite

An 83-year-old male non- smoker presented with chronic purulent cough

Adrián López Alba · Agustín Blanco Echevarría

To the Editor: Travel restrictions to control the transmission of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), the virus that causes coronavirus disease 2019 (COVID‐19), were rapidly implemented in Australia. Despite its apparent efficacy, this proactive approach has been criticised as unscientific and in breach of the International Health Regulations. A recently published comment1 claimed that travel restrictions were implemented without supporting scientific evidence and had “been challenged by public health researchers”, citing research on Ebola and influenza. However, their interpretation is not consistent with an evidence‐based approach. When managing a novel infection, evidence‐based decision making should (i) use the best available relevant information that is generalisable to the novel infection — for example, an infection with a similar route of transmission; that is, not Ebola, but rather severe acute respiratory syndrome (SARS), influenza, and Middle East respiratory syndrome (MERS) — and (ii) clearly define the outcome of interest (eg, prevention v delay). A recent review2 of travel restrictions for emerging infectious diseases, including SARS and MERS, found only one study regarding coronaviruses. The evidence identified supports the use of air travel bans to prevent the spread of coronavirus epidemics.2 Furthermore, systematic reviews,3,4,5 including the review4 cited in the comment,1 have reported that travel restrictions delayed, but did not prevent, the spread of influenza.3,4 These delays were up to 4 months,4 and up to 10 months if implemented in combination with other local strategies.5 At the start of the COVID‐19 pandemic, this reflected the best available evidence to make evidence‐based decisions regarding travel restrictions. The evidence suggests that travel restrictions may, therefore, be used to delay and attenuate the peak in case numbers to reduce the burden on the health system, allowing for preparations to be made to better manage the outbreak. The preparation measures may include upskilling the health care workforce, building new facilities, improving access to laboratory testing and ventilators, and stockpiling personal protective equipment. This is the primary goal of travel restrictions as public health interventions. We conclude that Australia's rapid introduction of travel restrictions is consistent with an evidence‐based approach that prioritises the precautionary principle and saving lives.

Jessica Stanhope · Philip Weinstein

A recent High Court decision directs and reassures medical and other practitioners in clinical and community settings that no parent or individual can compel this unlawful procedure

Ben Mathews · Elizabeth Dallaston

To the Editor: We thank Davidson and colleagues1 for their comprehensive narrative review on skin infections in Australian Aboriginal children. A significant factor in both individual and mass drug administration therapy of scabies is the uncertainty regarding the safety of oral ivermectin in small children and during pregnancy. Australian guidelines state ivermectin should not be used in children aged under 5 years or who weigh less than 15 kg or in pregnant women.2 A retrospective cohort study of 170 children aged 1–64 months (median age, 15 months) or weighing under 15 kg treated with ivermectin (mean dose, 223 μg/kg) found only minor self‐limiting adverse effects in seven patients (4%).3 A review of previous literature found 60 children aged under 5 years or weighing less than 15 kg who had been treated with ivermectin at a dose range of 150–200 μg/kg for whom safety data were available.4 Only four of 60 children (7%) developed an adverse reaction, all of which were benign and transient, with no long term sequelae. A recent study of oral ivermectin (dose 400 μg/kg) in the treatment of head lice revealed no adverse effects in 54 children aged under 5 years.5 The Ivermectin Exposure in Small Children Study Group expected to commence the analysis in late 2019 of data collected from 2017 to 2019.6 Three studies totalling 363 women with inadvertent maternal exposure to ivermectin 150 μg/kg (76–85% in first trimester) for filariasis and onchocerciasis found no increased risk of congenital malformations, miscarriage or stillbirth.7 A study of 199 pregnancies with maternal treatment in the second trimester with ivermectin and albendazole, and 198 with ivermectin alone in the management of helminth infections, found no increased risk of adverse pregnancy outcomes.8 In France, the use of oral ivermectin is permitted during pregnancy and in children weighing less than 15 kg when topical therapy has failed.9 Further published data regarding the safety of ivermectin in these populations would be useful, particularly with respect to mass drug administration programs.

Sarah K Morton · Adam Morton

Objective: To synthesise what is known about women combining motherhood and a career in medicine by examining the published research into their experiences and perspectives. Study design: We reviewed peer‐reviewed articles published or available in English reporting original research into motherhood and medicine and published during 2008–2019. Two researchers screened each abstract and independently reviewed full text articles. Study quality was assessed. Data sources: CINAHL, MEDLINE, PsycINFO, Web of Science, and Scopus abstract databases. Data synthesis: The database search identified 4200 articles; after screening and full text assessment, we undertook an integrative review synthesis of the 35 articles that met our inclusion criteria. Conclusions: Three core themes were identified: Motherhood: the impact of being a doctor on raising children; Medicine: the impact of being a mother on a medical career; and Combining motherhood and medicine: strategies and policies. Several structural and attitudinal barriers to women pursuing both medical careers and motherhood were identified. It was often reported that women prioritise career advancement by delaying starting a family, and that female doctors believed that career progression would be slowed by motherhood. Few evaluations of policies for supporting pregnant doctors, providing maternity leave, and assisting their return to work after giving birth have been published. We did not find any relevant studies undertaken in Australia or New Zealand, nor any studies with a focus on community‐based medicine or intervention studies. Prospective investigations and rigorous evaluations of policies and support mechanisms in different medical specialties would be appropriate. Protocol registration: PROSPERO CRD42019116228.

Rebekah Hoffman · Judy Mullan · Marisa Nguyen · Andrew D Bonney

The challenge now is how to implement artificial intelligence technology safely into clinical practice Artificial intelligence is a branch of computer science that, in broad terms, deals with either decision making or classification. The aim of artificial intelligence is to surpass human cognitive functioning such that automated decisions can be made. Machine learning — an application of artificial intelligence — is commonly used in image recognition. In general, the machine, or algorithm, learns from exposure to a large dataset. Once learning has taken place, the algorithm can be applied to unseen data. The potential advantages of this approach in health care are clear: machines can learn from very large datasets in relatively short time frames and can apply themselves to new data without fatigue or intra‐observer replication error. Machine learning has recently demonstrated remarkable performance in image‐based diagnosis across various medical fields, including ophthalmology, radiology, pathology and dermatology. In dermatology, the primary focus has been on developing machine learning systems that facilitate classification and decision support for skin cancer management. Skin cancer (including melanocytic and keratinocytic malignancy) is the most common cancer in Australia and among Caucasian populations worldwide. Melanoma is responsible for the majority of skin cancer deaths in Australia and has various presentations.1,2 While dermoscopy has improved the accuracy of melanoma diagnosis, significant variability occurs and is largely a function of clinical expertise. Recent studies show that machine learning algorithms have the potential to surpass the diagnostic performance of experts, and the challenge now is how to implement this new technology safely into clinical practice. Although there are a number of machine learning algorithms that could be used in the dermatology setting, convolutional neural networks (CNNs) are the most promising. This is largely because they learn from data without any feature specification, and they are known to exhibit superior performance for image recognition in comparison with other machine learning algorithms.3 The aim of the CNN is to generalise its previously learned knowledge on unseen images beyond the training dataset. There are numerous parameters within a CNN that can be tweaked to maximise algorithm performance. Most of these parameters are adjusted automatically by the algorithm, without user input. Therefore, very little can be known, in principle, about why and how the algorithm reaches any particular decision. Currently, there are efforts underway to reduce the “black box” effect of CNNs. Some commercial software programs coupled to imaging devices will provide the user with comparable lesions to justify the algorithm's output and improve transparency. However, this retrieval system may fail for rare or unseen cases and does not provide a decision‐making process. While the black box phenomenon remains, there are two potentially negative implications for clinical practice: first, clinicians may have difficulty upskilling by following the algorithms’ outputs; and second, there exists the potential for deskilling and underperforming due to an over‐reliance on technology.4,5 The effect of a faulty system has been explored by manipulating a previously trusted algorithm to generate incorrect classifications and found that doctors of all experience levels were susceptible to being misled by the recommendation.5 Algorithm performance is dependent on both the size and quality of the training image dataset and on whether the algorithm is used in situations for which it was intended. Depending on the training set, the device may be limited in its ability to diagnose specific lesions (eg, non‐pigmented), or lesions in certain skin types (eg, darker skin) or sites (eg, scalp or acral). Retrospective image databases used to train algorithms may be associated with bias. In addition, artefacts (eg, hair, dermoscopic gel, air bubbles, rulers, pen markings, reflections) can distract from key features. However, if a CNN is trained on a large enough cohort, it can learn to deal with potential artefacts. Nonetheless, unbiased lesion selection and standardised image capture would invariably improve algorithm performance, and recent advances in three‐dimensional (3D) imaging modalities will enable this.6 Several studies have now shown that CNNs trained on retrospective image data collected at a single time point are capable of classifying skin cancer with sensitivities and specificities equal or superior to that of dermatologists (Box 1),5,7,8,9,11 and clinicians with less experience gain most from AI support under experimental conditions.5 Hypomelanotic and acral melanoma can be more challenging to diagnose clinically,1 and this could potentially present a challenge for automated classification. However, CNNs have achieved greater accuracy for hypopigmented and acral lesions in comparison with human experts, at least in silica.9,11 In addition to clinical images, CNNs have been applied to histopathological images of melanoma and benign naevi with promising results.10 The ground truth for lesion diagnosis The gold standard for melanoma diagnosis is histopathological assessment. However, there exists significant inter‐ and intra‐observer variability in histological diagnostic labels attributed to atypical melanocytic lesions.12 The existence of such variability in diagnoses poses the dilemma of whether the CNN has learnt from the correct set of diagnoses. Consensus diagnoses, if practical, may help overcome this problem. Molecular biomarkers may assist in establishing a diagnosis13 and identifying high risk biology,14 but they require extensive validation before clinical use. Pathologists and clinicians also rely on metadata (age, personal and family history, lesion symptoms, recent change), which may influence diagnostic likelihoods. Importantly, it is possible to incorporate different data types, including metadata, sequential image data coupled with histopathology, to train future CNN algorithms and improve diagnostic discrimination of borderline lesions (Box 2). Use of artificial intelligence for melanoma screening It is well known that the incidence of invasive melanoma in Australia has increased over the past 40 years. In addition, there has been a striking increase in incidence of in situ melanoma over the past decade, from 32 cases per 100 000 population in 2004 to 80 per 100 000 population in 2019, with age‐standardised mortality remaining fairly stable.2 The potential causes for the increase in incidence are complex, and involve a true increase, driven by poor sun exposure practices of individuals born before the SunSmart era, combined with increased awareness, excessive screening, and overdiagnosis. It has recently been estimated that 54% of melanomas (15% of invasive melanomas) are overdiagnosed.15 Artificial intelligence‐assisted targeted screening of high risk individuals is likely to be a more effective strategy to save lives than the current opportunistic approach. With sequential whole‐body image datasets linked to metadata, molecular biomarkers and clinical outcomes, our ability to identify lesions associated with sinister biological potential will improve (Box 2), thereby reducing unnecessary biopsies, minimising overdiagnosis and other potential harms associated with screening. Use of artificial intelligence in clinical practice There are advantages and disadvantages of introducing artificial intelligence at different points in the patient care pathway.16 An artificial intelligence system used as a triaging tool before clinician assessment would enable automated risk stratification of individuals and/or lesions (Box 2). This approach could dramatically improve clinician workload and timely access to specialist care for people requiring urgent attention. Alternatively, artificial intelligence consulted following an examination by the clinician may act as a second opinion to improve diagnostic sensitivity and reduce unnecessary biopsies.5 The latter is more closely aligned with current clinical workflows and therefore likely to be preferred while the field matures. There is potential for over‐reliance on artificial intelligence systems in both scenarios. A secondary support system may provide the clinician with a diagnosis or a management decision. Doctors are more likely to change their minds if they are uncertain of a diagnosis and an algorithm provides a conflicting result.5 It is thus important to consider how an algorithm might convey uncertainty to avoid false guidance. For example, a decision‐support output (eg, excise, monitor or reassure) avoids the diagnostic dilemma of differentiating between melanoma and dysplastic naevi. However, the problem is complex and arguments exist as to why, in many situations, a diagnostic probability output might be more desirable. Safe implementation of new technologies The Therapeutic Goods Administration (TGA) has developed an action plan to improve the processes by which new devices are approved for use in Australia, strengthen monitoring and follow‐up, and provide more information to consumers about the devices they use.17 International collaborations also exist with groups, such as the International Medical Device Regulators Forum, to establish better processes for medical device regulation globally. If software is classified as a medical device (ie, it is intended for diagnosis, prevention, monitoring, treatment or alleviation of disease), it must be registered on the Australian Register of Therapeutic Goods following TGA approval and before distribution within Australia. Consumers and clinicians need to be aware of the intended use of an application or device. There are several smartphone applications available to the general public, with functionality ranging from education to monitoring and tracking to skin lesion classification. Some of these provide skin lesion risk assessment, although they may state that they are not intended to be used as a diagnostic device. There is concern that, if this is not immediately obvious to the consumer, unregistered applications may be used in lieu of seeking medical advice. Unsupervised consumer‐operated diagnostic devices would require careful testing before they can be recommended. Conclusion As clinicians, we need to be aware of the limitations of any diagnostic tool and interpret outputs accordingly. Although the performance of artificial intelligence to date is promising, it remains to be seen how diagnostic devices in dermatology will influence decision making in the clinic and affect patient outcomes. Regardless of the specialty, any new technologies need to be rigorously tested before implementation and monitored after implementation. Ultimately, responsibility for patient care remains with the clinician and, as such, a high level of clinical acumen must be maintained. Nonetheless, artificial intelligence in dermatology is primed to become a powerful tool in skin cancer assessment. Box 1 – Comparison of skin cancer classification tasks by artificial intelligence (AI) systems and dermatologists/pathologists Study AI architecture Images Classification task Training dataset size Test dataset size AI Dermatologists/pathologists Sensitivity Specificity AUC/overall accuracy Sensitivity Specificity AUC/overall accuracy Tschandl5 ResNet34 CNN Clinical (dermoscopic) Benign v malignant v non‐neoplastic skin lesions 10 015 1412 0.81 (0.79–0.83)* 0.92 (0.90–0.93)* 0.73†(0.70–0.76)* 0.80 (0.78–0.83)* 0.80 (0.77‐0.82)* 0.60† (0.57–0.63)*,‡ 0.86 (0.84–0.88§)* 0.88 (0.87–0.90§)* 0.74† (0.71–0.77§)* Esteva7 GoogleNet Inception v3 CNN Clinical (macroscopic, dermoscopic) Benign v malignant v non‐neoplastic skin lesions 129 450 1942 na na 72.1%¶ ± 0.9% na na 66.0%¶ Haenssle8 GoogleNet Inception v4 CNN Clinical (macroscopic, dermoscopic) Benign melanocytic naevi v melanoma > 100 000 100 86.6%** 82.5%** 0.86** 86.6%** 71.3%** 0.79** 88.9%†† 82.5%†† 0.86†† 88.9%†† 75.7%†† 0.82†† Tschandl9 GoogleNet Inception v3 CNN Clinical (macroscopic, dermoscopic) Benign v malignant hypo‐pigmented lesions 13 724 2072 81% 53.5% 0.73 78% 51.3% 0.68 Hekler10 ResNet50 CNN Histopathology Benign naevus v melanoma 595 100 76% 60% na 51.8%‡‡ 66.5%‡‡ na Fujisawa11 GoogleLeNet DCNN Clinical (macroscopic) Benign v malignant skin lesions§§ 4867 1142 96.3% 89.5% 92.4%¶ ± 2.1% na na 85.3%¶ ± 3.7% AUC = area under the curve; na = not applicable. * 95% CI. † Youden statistic. ‡ Clinicians with varied experience and training. § Clinician accuracy with multiclass probabilistic AI support. ¶ Overall accuracy. ** Level I: AI and human readers provided with dermoscopic images only. †† Level II: AI provided with dermoscopic images only, human readers provided with dermoscopic images, macroscopic images and additional clinical information. ‡‡ Pathologist. §§ 52.6% of melanomas in this study were acral. Box 2 – Incorporation of different data types to train future convolutional neural network (CNN) algorithms and improve diagnostic discrimination of borderline lesions AI = artificial intelligence.

Miki Wada · ZongYuan Ge · Stephen J Gilmore · Victoria J Mar

Telehealth can be used to deliver clinical trials, improve access to novel therapies and develop clinical networks Australia is a vast country. Nearly 32% of Australians reside outside the major capital cities, while 95% of medical specialists practise in cities.1 People living in rural and regional areas consistently experience poorer health outcomes.2 Cancer is a considerable health issue, with 395 new cancer diagnoses per day.3 The regional mortality gap in cancer remains.4 Between 2000 and 2010, patients in regional and rural Australia had a 7% higher cancer mortality compared with those in metropolitan centres, equating to 9000 additional regional and rural cancer deaths.3,5 Barriers to better regional cancer care include travel requirements to metropolitan centres, limited access to expert diagnostics and therapeutics, and less access to clinical trials.6 As well as geographical issues, recruitment and retention of qualified health professionals in regional areas can be difficult, due to professional isolation and a perceived or actual lack of career opportunities.7 These issues relate not only to regional Australia but to many regional populations worldwide.4,8 In the past decade, there has been considerable investment by federal and state governments in the development of regional cancer centres, enabling increased research opportunities.9 Clinical trials remain a gateway to accessing cutting edge therapies and technology. Currently, less than 5% of regional cancer patients participate in any clinical trial; barriers include travel distance to a metropolitan site, a lack of trials available locally, and costs involved for patients and carers such as travel and accommodation and loss of earnings.10 While there are no set targets for participation rates, there has been a correlation between trial participation rates and improved cancer survival, such that a higher rate is desirable.11 In 2017, there were 432 actively recruiting cancer clinical trials in Victoria, totalling 1605 participants. Of these, 426 participants were living in a regional or rural area (27%); however, most participants were enrolled at a metropolitan site, with just 81 (5% of all trial participants) recruited to local clinical trials (personal communication, Christie Allan, Cancer Trials Management Scheme, Cancer Council Victoria, April 2019). Telehealth strategies Telehealth strategies have gained acceptance across many aspects of health care to enable delivery for patients closer to home, including anti‐cancer therapies.12 A logical extension is integration into clinical trial models. Such an approach has many benefits for patients, their families, regional health care, as well as potential economic savings by reducing the need to travel for care. Although this model is a change from usual care, patient safety and quality of care is maintained. The Victorian Comprehensive Cancer Centre (VCCC) is an alliance of ten leading research, clinical and academic institutions in Victoria. The VCCC established a teletrials program to build relationships between regional/rural Victoria and metropolitan centres, using telehealth to provide patients with the opportunity to access clinical trials closer to home. Teletrial framework development In developing a teletrial implementation framework, it was important to consider patient safety, ethical and regulatory requirements. In addition, so that the model would allow for differences across clinical trial requirements and capabilities at individual trial sites, we scoped potential barriers and enablers, to ensure its success. The Clinical Oncology Society of Australia model10 was used as a foundation template for the structure and relational concepts (Box). Importantly, the model recognises the potential for heterogeneity across trials and sites, rather than taking a one‐size‐fits‐all approach. Different sites may perform different roles in different trials; for example, taking blood samples, delivering chemotherapy or medication, trial documentation, or imaging. The model has been used in several teletrials enrolling across Australia.13 An important element was the development of standard operating procedures. Initially developed by Queensland Health, these were modified not only for use in Victoria but for consideration as the basis for national standard operating procedures for teletrials. In developing the teletrial framework, input and feedback were sought from stakeholders in cancer clinical trials. These included contract research organisations; the biopharmaceutical industry; principal investigators; Victorian regional sites through the Regional Trials Network; Human Research Ethics Committees (HRECs); local government through the Victorian Department of Health and Human Services; funding bodies; and consumers. Teletrial supervision plan The teletrial supervision plan (https://www.viccompcancerctr.org/what-we-do/clinical-trials-expansion/teletrials/resources/) contains detailed documentation regarding specific trial conduct and responsibilities, in particular the specific responsibilities of investigators at each site within the trial cluster, and which elements of the trial, imaging and drug delivery are performed at each site. Some trials may have all elements delivered at the local site, others may have most delivered locally but specialist services (eg, radionuclide therapy) at the central site. The supervision plan is site‐, trial‐ and time‐specific. It also includes standard operating procedures, Good Clinical Practice training, monitoring, HREC submissions and oversight, trial‐specific indemnity and contracts, plans for safety reporting, investigational product storage and delivery logistics, and details on joint consultations using telehealth, payments, data entry and document management. The supervision plan is generated in agreement with the principal investigators at the metropolitan and regional sites before the study, but with regular review and modifications as required to allow refinement as needed. Indemnity and legal coverage Teletrial indemnity and legal coverage for trial activities are frequently raised concerns. This can be documented in detail in the supervision plan but is no different for a teletrial over other models. The VCCC commissioned a draft clinical trial activity agreement for investigator‐initiated studies including a teletrial component (https://www.viccompcancerctr.org/what-we-do/clinical-trials-expansion/teletrials/resources/). Governance and ethics approval As with any clinical trial, ethics approval is required, usually through a human research ethics application. Local research governance office requirements will not vary, with local assessment of trial capability, including managing potential toxicities. The principal investigator remains responsible for ethics submissions and communication with HRECs. Each site will obtain local governance approval and be listed on the clinical trial notification form. The process for reporting on safety events remains as per standard of care. Proof of concept Using the framework described, a teletrial has commenced between a metropolitan site and two regional sites in Victoria. The first teletrial site patient was recruited in November 2018 and at 24 July 2020, 91 patients had been successfully recruited in regional centres, with all their trial activity delivered locally. Metropolitan and teletrial sites have successfully undergone study monitoring and further model evaluation is underway. Model evaluation Although the teletrial model is not an intervention in itself, merely a method of trial delivery, it is important to its widespread adoption at a new standard of care that there are benefits to all stakeholders. An ongoing health economic evaluation will evaluate costs associated with the teletrial (and potential savings), patient time and travel estimates, and qualitative assessment of patient and clinician participation in a teletrial to detail possible benefits. In addition, consumer and clinician perspectives studies are planned. A leading contract research organisation was commissioned to undertake an independent process review of the first teletrial to evaluate the model. No major protocol deviations were found in comparison to a conventional site in this pilot study. Potential benefits of a teletrial Teletrials provide a mechanism to enable disadvantaged patients to participate in clinical trials. They may also provide wider benefits14 beyond those experienced by individual participants, including: improved recruitment: as trials have a wider reach, they may recruit faster, translating new interventions to patients faster in a real‐world setting; improved retention: making trial access easier may improve participant retention, reduce missing data and accelerate trial objectives; increased diversity: teletrials may allow for easier access to the increasingly specific and rare subsets of cancer trial populations; professional development: partnerships developed from the trial network may translate into improved routine clinical care delivery and opportunities; and trial cost‐savings: while teletrial costs will be evaluated, the resources required to open a teletrial may be reduced, as much of the trial data will be retained at the primary site. Potential or perceived risks Some of the possible risks raised with the authors by stakeholders have been addressed above, including indemnity, legal and governance issues. Others may include: Clinical safety of new treatments in a regional setting: while a trial may involve a novel therapy, toxicities are often managed on a patient's return home to their regional site. Involving local clinicians in the trial may actually reduce this risk through better education regarding managing novel therapies. Clinical trial expertise: most regional sites already have extensive experience in clinical trials, and Good Clinical Practice training is standard. Trial monitoring challenges: with rapidly increased use of secure digital platforms, monitoring is increasingly becoming a remote activity, so location is not a barrier. We acknowledge that this model represents a change to usual process and therefore requires assessment, transparency and strong support and advocacy to overcome barriers to clinical trial participation.15 Teletrials do more than just meet trial metrics. They develop synchronous partnering between regional and metropolitan centres, allowing regional equity of access to cutting edge diagnostics and therapeutics while maintaining patients’ care delivery closer to home, thereby avoiding disruption to family, work and social interactions. Box – Teletrial model

Ian M Collins · Kate Burbury · Craig R Underhill

Objectives: To develop and validate a frailty index, derived from aged care eligibility assessment data. Design: Retrospective cohort study; analysis of the historical national cohort of the Registry of Senior Australians (ROSA). Participants: 903 996 non‐Indigenous Australians aged 65 years or more, living in the community and assessed for subsidised aged care eligibility during 2003–2013. Main outcome measures: 44‐item frailty index; summary statistics for frailty index score distribution; predictive validity with respect to mortality and entry into permanent residential aged care during the five years after assessment. Results: The mean frailty index score during 2003–2013 was 0.20 (SD, 0.07; range, 0–0.41); the proportion of assessed older people with scores exceeding 0.20 increased from 32.1% in 2003–2005 to 75.0% in 2012–2013. The risks of death and entry into permanent residential aged care at one, three and five years increased with frailty index score level (at one year, high [over 0.35] v low scores [under 0.05]: hazard ratio for death, 5.99; 95% CI, 5.69–6.31; for entry into permanent residential aged care, 8.70; 95% CI, 8.32–9.11). The predictive validity (area under the receiver operating characteristic curve) of Cox proportional hazard models including age, sex, and frailty index score was 0.64 (95% CI, 0.63–0.64) for death and 0.63 (95% CI, 0.62–0.63) for entry into permanent residential aged care within one year of assessment. Conclusions: We used Australian aged care eligibility assessment program data to construct and validate a frailty index. It can be employed in aged care research in Australia, but its application to aged care planning requires further investigation.

Jyoti Khadka · Renuka Visvanathan · Olga Theou · Max Moldovan · Azmeraw T Amare · Catherine Lang · Julie Ratcliffe · Steven L Wesselingh · Maria C Inacio

The thousand doors — the Australian doctors at war series; volume four: the Middle East and Far East 1939–42

Karl James

Objective: To develop a casemix classification to underpin a new funding model for residential aged care in Australia. Design, setting: Cross‐sectional study of resident characteristics in thirty non‐government residential aged care facilities in Melbourne, the Hunter region of New South Wales, and northern Queensland, March 2018 – June 2018. Participants: 1877 aged care residents and 1600 residential aged care staff. Main outcome measures: The Australian National Aged Care Classification (AN‐ACC), a casemix classification for residential aged care based on the attributes of aged care residents that best predict their need for care: frailty, mobility, motor function, cognition, behaviour, and technical nursing needs. Results: The AN‐ACC comprises 13 aged care resident classes reflecting differences in resource use. Apart from the class that included palliative care patients, the primary branches were defined by the capacity for mobility; further classification is based on physical capacity, cognitive function, mental health problems, and behaviour. The statistical performance of the AN‐ACC was good, as measured by the reduction in variation statistic (RIV; 0.52) and class‐specific coefficients of variation. The statistical performance and clinical acceptability of AN‐ACC compare favourably with overseas casemix models, and it is better than the current Australian aged care funding model, the Aged Care Funding Instrument (64 classes; RIV, 0.20). Conclusions: The care burden associated with frailty, mobility, function, cognition, behaviour and technical nursing needs drives residential aged care resource use. The AN‐ACC is sufficiently robust for estimating the funding and staffing requirements of residential aged care facilities in Australia.

Kathy Eagar · Rob Gordon · Milena F Snoek · Carol Loggie · Anita Westera · Peter David Samsa · Conrad Kobel

During the pandemic, cancer survivors are lost in transition

Bogda Koczwara

Objective: To synthesise quantitative data on the effects of rural background and experience in rural areas during medical training on the likelihood of general practitioners practising and remaining in rural areas. Study design: Systematic review and meta‐analysis of the effects of rural pipeline factors (rural background; rural clinical and education experience during undergraduate and postgraduate/vocational training) on likelihood of later general practice in rural areas. Data sources: MEDLINE (Ovid), EMBASE, Informit Health Collection, and ERIC electronic database records published to September 2018; bibliographies of retrieved articles; grey literature. Data synthesis: Of 6709 publications identified by our search, 27 observational studies were eligible for inclusion in our systematic review; when appropriate, data were pooled in random effects models for meta‐analysis. Study quality, assessed with the Newcastle–Ottawa scale, was very good or good for 24 studies, satisfactory for two, and unsatisfactory for one. Meta‐analysis indicated that GPs practising in rural communities was significantly associated with having a rural background (odds ratio [OR], 2.71; 95% CI, 2.12–3.46; ten studies) and with rural clinical experience during undergraduate (OR, 1.75; 95% CI, 1.48–2.08; five studies) and postgraduate training (OR, 4.57; 95% CI, 2.80–7.46; eight studies). Conclusion: GPs with rural backgrounds or rural experience during undergraduate or postgraduate medical training are more likely to practise in rural areas. The effects of multiple rural pipeline factors may be cumulative, and the duration of an experience influences the likelihood of a GP commencing and remaining in rural general practice. These findings could inform government‐led initiatives to support an adequate rural GP workforce. Protocol registration: PROSPERO, CRD42017074943 (updated 1 February 2018).

Jessica Ogden · Scott Preston · Riitta L Partanen · Remo Ostini · Peter Coxeter

To the Editor: The coronavirus disease 2019 (COVID‐19) pandemic has focused whole‐of‐government efforts on protecting Australia's health. Border closures, case quarantine, public health interventions and social distancing have controlled COVID‐19 case numbers, limiting community acquisition. Workplaces at particular risk of occupational exposure to COVID‐19 — hospitals, aged care facilities and, interestingly, abattoirs — require effective infection control. Presenteeism in this context refers to the occupational transmission risk that employees infected with severe acute respiratory syndrome coronavirus 2 pose by continuing to work despite being symptomatic. Such presenteeism may be an issue common to a number of industries.1 Occupational infection has occurred among Australian hospital staff, notably in North West Tasmania.2 Delayed recognition of COVID‐19 cases leading to infection control breaches, presenteeism with infected health care staff working for up to 7 days with respiratory symptoms, along with other factors all contributed to this hospital outbreak.2 In total, 73 of the 114 outbreak cases were hospital staff.2 Meat processing facility workers have been a notable at‐risk group in the United States, with over 4000 COVID‐19 cases reported, representing up to 3% of affected facility workforces and resulting in 20 COVID‐19 related deaths.3 In Australia, a COVID‐19 cluster was reported among abattoir workers in Melbourne.4 There are meat processing industry work practices that enhance COVID‐19 acquisition risks.4 Commonly, the layout of meat processing facilities challenges implementation of appropriate distancing between workers, who may be spaced as little as 30 cm from colleagues during routine operations. Compliance with wearing face masks is difficult given the pace and physical demands of work. Financial imperatives appear to motivate food processing employees to work even if unwell.3 Australian aged care workers and airline baggage handlers have also experienced COVID‐19 outbreaks. Despite concerns expressed by teachers and early childhood educators, as of 16 June 2020, no major outbreaks had occurred in schools and only one cluster had been reported in a NSW childcare centre.5 A NSW investigation of possible transmission in schools showed only two secondary cases in students.6 Some schools have been closed for deep cleaning after detection of community acquired cases of COVID‐19. Design and implementation of effective, industry specific, infection prevention policies are crucial for employer compliance with the Australian Work Health and Safety Strategy principle that “all workers, regardless of their occupation or how they are engaged, have the right to a healthy and safe working environment”.7 This requires strong, industry group, leadership. Recognition of workplace specific infection risks, provision of reliable personal protective equipment, redesign of work practices, discouragement of presenteeism, and improved access to sick leave must all be attended to for the sake of Australia's workforce.

Damon Eisen

To the Editor: We congratulate Cheung and colleagues1 on their large cluster randomised trial of routine blood glucose and automated glycated haemoglobin (HbA1c) testing in emergency departments. This trial reaffirmed the high prevalence of unrecognised diabetes in patients presenting to the emergency department, while demonstrating the feasibility of algorithmic detection. However, the rate of documented follow‐up plans in patients with suspected or newly diagnosed diabetes was low and did not benefit from the trial intervention. Cheung and colleagues1 and Hare and Shaw,2 in their accompanying editorial, suggest that this may relate to diabetes services already operating at full capacity or to overburdened staff documenting abbreviated plans at discharge. The trial highlights the difficulty in improving outcomes when multiple non‐integrated health professionals manage a condition and, hence, the importance of continuity of care. The RAPIDS trial3 was an early intervention model of care consisting of integrated continuous acute diabetes care provided by a dedicated, proactive specialist inpatient diabetes team (IDT). The intervention involved an IDT using a networked blood glucose meter system to remotely identify inpatients with diabetes (known and newly diagnosed) to directly manage these patients, compared with usual care, where diabetes management was mostly provided by parent unit teams.3 This trial showed that direct diabetes management by a dedicated IDT improved glycaemia and decreased the rate of hospital‐acquired infections. During the RAPIDS trial, in patients with newly discovered hyperglycaemia (random capillary glucose > 11.1 mmol/L without known diabetes), treatment and follow‐up plans were documented in 11/34 patients (33%) with usual care, comparable to findings by Cheung et al. However, with the IDT intervention, 22/28 patients (79%) had treatment and follow‐up plans. Similarly, in patients with newly diagnosed diabetes (HbA1c ≥ 6.5%), diabetes treatment was commenced in 8/17 patients (47%) with usual care, and in 11/12 patients (92%) with IDT intervention3 (unpublished data). It is likely that the presence of an IDT at one of the control hospitals in the trial by Cheung and colleagues contributed significantly to the improved plan documentation in that arm. We thus echo the editorial and professional society voices asserting the importance of resourcing clinical services for diabetes in Australian hospitals.4 Establishing IDTs in our hospitals will enable excellent diabetes care despite the increasing prevalence of this disease in Australia.

Spiros Fourlanos · Rahul Barmanray · Mervyn Kyi