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Background: Children and families from priority populations experienced significant psychosocial and mental health issues to the COVID-19 pandemic. Yet they also faced significant barriers to service access, particularly families from culturally and linguistically diverse (CALD) backgrounds. With most child and family health nurse clinics ceasing in-person consultations due to the pandemic, many children missed out on health and developmental checks. The aim of this study was to investigate the perspectives and experiences of family members and service providers from an urban, CALD community regarding the implementation of a digital, developmental surveillance, Watch Me Grow-Electronic (WMG-E) program., Methods: Semi-structured interviews were conducted with 17 family members, service navigators, and service providers in a multicultural community in South Western Sydney, Australia. This qualitative study is an implementation evaluation which formed as part of a larger, two-site, randomised controlled trial of the WMG-E program. A reflexive thematic analysis approach, using inductive coding, was adopted to analyse the data., Results: Participants highlighted the comprehensive and personalised support offered by existing child and family health services. The WMG-E was deemed beneficial because the weblink was easy and quick to use and it enabled access to a service navigator who support family access to relevant services. However, the WMG-E was problematic because of technology or language barriers, and it did not facilitate immediate clinician involvement when families completed the weblink., Conclusions: Families and service providers in this qualitative study found that using WMG-E empowered parents and caregivers to access developmental screening and learn more about their child's development and engage with relevant services. This beds down a new and innovative solution to the current service delivery gap and create mechanisms that can engage families currently not accessing services, and increases knowledge around navigating the health and social care services. Notwithstanding the issues that were raised by families and service providers, which include accessibility challenges for CALD communities, absence of clinical oversight during screening, and narrow scope of engagement with available services being offered, it is worth noting that improvements regarding these implementation factors must be considered and addressed in order to have longevity and sustainability of the program., Trial Registration: The study is part of a large randomised controlled trial (Protocol No. 1.0, Version 3.1) was registered with ANZCTR (registration number: ACTRN12621000766819) on July 21st, 2021 and reporting of the trial results will be according to recommendations in the CONSORT Statement., (© 2024. Crown.)

Background: Significant challenges remain in the early identification of child developmental disabilities in the community. Implementing supports and services early in the life course has been shown to promote positive developmental outcomes for children at high likelihood of developmental disabilities, including autism. As part of a cluster randomised controlled trial, this study seeks to examine and compare the perspectives and experiences of Australian general practitioners (GPs) in relation to a digital developmental surveillance program for autism and usual care pathway, in general practice clinics., Methods: A qualitative research methodology with semi-structured interviews and thematic inductive analysis underpinned by grounded theory was utilised. All GPs from South Western Sydney (NSW) and Melbourne (Victoria) who participated in the main program ("GP Surveillance for Autism") were invited to the interview. GPs who provided consent were interviewed either over online or in-person meeting. Interviews were audio-recorded, transcribed, and coded using NVivo12 software. Inductive interpretive approach was adopted and data were analysed thematically., Results: Twenty-three GPs across the two sites (NSW: n = 11; Victoria: n = 12) agreed to be interviewed; data saturation had reached following this number of participants. Inductive thematic coding and analysis yielded eight major themes and highlighted common enablers such as the role of GPs in early identification and subsequent supports, enhanced communication between clinicians/professionals, relationship-building with patients, and having standardised screening tools. Specific facilitators to the feasibility and acceptability of a digital screening program for the early identification of developmental disabilities, including the early signs of autism, and encouraging research and education for GPs. However, several practical and socioeconomic barriers were identified, in addition to limited knowledge and uptake of child developmental screening tools as well as COVID-19 lockdown impacts. Common and specific recommendations involve supporting GPs in developmental/paediatrics training, streamlined screening process, and funding and resources in the primary healthcare services., Conclusions: The study highlighted the need for practice and policy changes, including further training of GPs alongside sufficient time to complete developmental checks and appropriate financial remuneration through a Medicare billing item. Further research is needed on implementation and scale up of a national surveillance program for early identification of developmental disabilities, including autism., (© 2023. BioMed Central Ltd., part of Springer Nature.)

Objectives: One Health considers human, animal and environment health as a continuum. The COVID-19 pandemic started with the leap of a virus from animals to humans. Integrated management systems (IMS) should provide a coherent management framework, to meet reporting requirements and support care delivery. We report IMS deployment during, and retention post the COVID-19 pandemic, and exemplar One Health use cases., Methods: Six volunteer members of the International Medical Association's (IMIA) Primary Care Working Group provided data about any IMS and One Health use to support the COVID-19 pandemic initiatives. We explored how IMS were: (1) Integrated with organisational strategy; (2) Utilised standardised processes, and (3) Met reporting requirements, including public health. Selected contributors provided Unified Modelling Language (UML) use case diagram for a One Health exemplar., Results: There was weak evidence of synergy between IMS and health system strategy to the COVID-19 pandemic. However, there were rapid pragmatic responses to COVID-19, not citing IMS. All health systems implemented IMS to link COVID test results, vaccine uptake and outcomes, particularly mortality and to provide patients access to test results and vaccination certification. Neither proportion of gross domestic product alone, nor vaccine uptake determined outcome. One Health exemplars demonstrated that animal, human and environmental specialists could collaborate., Conclusions: IMS use improved the pandemic response. However, IMS use was pragmatic rather than utilising an international standard, with some of their benefits lost post-pandemic. Health systems should incorporate IMS that enables One Health approaches as part of their post COVID-19 pandemic preparedness., Competing Interests: Uy Hoang has undertaken consultation work for Janssen and Sanofi.Simon de Lusignan has had grants, through his universities for vaccine related research from AstraZenaca, GSK, Sanofi, Seqirus, MSD, Takeda., (IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Tuberculosis (TB) was the leading infectious cause of mortality globally prior to COVID-19 and chest radiography has an important role in the detection, and subsequent diagnosis, of patients with this disease. The conventional experts reading has substantial within- and between-observer variability, indicating poor reliability of human readers. Substantial efforts have been made in utilizing various artificial intelligence-based algorithms to address the limitations of human reading of chest radiographs for diagnosing TB., Objective: This systematic literature review (SLR) aims to assess the performance of machine learning (ML) and deep learning (DL) in the detection of TB using chest radiography (chest x-ray [CXR])., Methods: In conducting and reporting the SLR, we followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. A total of 309 records were identified from Scopus, PubMed, and IEEE (Institute of Electrical and Electronics Engineers) databases. We independently screened, reviewed, and assessed all available records and included 47 studies that met the inclusion criteria in this SLR. We also performed the risk of bias assessment using Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2) and meta-analysis of 10 included studies that provided confusion matrix results., Results: Various CXR data sets have been used in the included studies, with 2 of the most popular ones being Montgomery County (n=29) and Shenzhen (n=36) data sets. DL (n=34) was more commonly used than ML (n=7) in the included studies. Most studies used human radiologist's report as the reference standard. Support vector machine (n=5), k-nearest neighbors (n=3), and random forest (n=2) were the most popular ML approaches. Meanwhile, convolutional neural networks were the most commonly used DL techniques, with the 4 most popular applications being ResNet-50 (n=11), VGG-16 (n=8), VGG-19 (n=7), and AlexNet (n=6). Four performance metrics were popularly used, namely, accuracy (n=35), area under the curve (AUC; n=34), sensitivity (n=27), and specificity (n=23). In terms of the performance results, ML showed higher accuracy (mean ~93.71%) and sensitivity (mean ~92.55%), while on average DL models achieved better AUC (mean ~92.12%) and specificity (mean ~91.54%). Based on data from 10 studies that provided confusion matrix results, we estimated the pooled sensitivity and specificity of ML and DL methods to be 0.9857 (95% CI 0.9477-1.00) and 0.9805 (95% CI 0.9255-1.00), respectively. From the risk of bias assessment, 17 studies were regarded as having unclear risks for the reference standard aspect and 6 studies were regarded as having unclear risks for the flow and timing aspect. Only 2 included studies had built applications based on the proposed solutions., Conclusions: Findings from this SLR confirm the high potential of both ML and DL for TB detection using CXR. Future studies need to pay a close attention on 2 aspects of risk of bias, namely, the reference standard and the flow and timing aspects., Trial Registration: PROSPERO CRD42021277155; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=277155., (©Seng Hansun, Ahmadreza Argha, Siaw-Teng Liaw, Branko G Celler, Guy B Marks. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 03.07.2023.)

In the wake of Coronavirus disease 2019 (COVID-19), several nations have sought to implement digital vaccine passports (DVPs) to enable the resumption of international travel. Comprising a minimum dataset for each unique individual, DVPs have the makings of a global electronic health record, broaching key issues involved in building a global digital health ecosystem. Debate simulations offer a safe, interactive space to foster participatory policy discussions for advancing digital health diplomacy. This study used an online simulation of a Model World Health Assembly to critically analyze the sociotechnical issues associated with the global implementation of DVPs, and to generate useful insights and questions about the role of diplomacy in global digital health. The debate arguments addressed and provided insights into the technological, scientific, ethical, legal, policy, and societal aspects of DVPs. Reflecting on the simulation, we discuss its opportunities and challenges for the digitalization, decolonization, decentralization, and democratization of participatory policymaking., (© The Author(s) 2022. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Objective: While the COVID-19 pandemic provided a global stimulus for digital health capacity, its development has often been inequitable, short-term in planning, and lacking in health system coherence. Inclusive digital health and the development of resilient health systems are broad outcomes that require a systematic approach to achieving them. This paper from the IMIA Primary Care Informatics Working Group (WG) provides necessary first steps for the design of a digital primary care system that can support system equity and resilience., Methods: We report on digital capability and growth in maturity in four key areas: (1) Vaccination/Prevention, (2) Disease management, (3) Surveillance, and (4) Pandemic preparedness for Australia, Canada, and the United Kingdom (data from England). Our comparison looks at seasonal influenza management prior to COVID-19 (2019-20) compared to COVID-19 (winter 2020 onwards)., Results: All three countries showed growth in digital maturity from the 2019-20 management of influenza to the 2020-21 year and the management of the COVID-19 pandemic. However, the degree of progress was sporadic and uneven and has led to issues of system inequity across populations., Conclusion: The opportunity to use the lessons learned from COVID-19 should not be wasted. A digital health infrastructure is not enough on its own to drive health system transformation and to achieve desired outcomes such as system equity and resilience. We must define specific measures to track the growth of digital maturity, including standardized and fit-for-context data that is shared accurately across the health and socioeconomic sectors., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Actualizing the vision of Global Digital Health is a central issue on the Global Health Diplomacy agenda. The COVID-reinforced need for accelerated digital health progress will require political structures and processes to build a foundation for Global Digital Health. Simultaneously, Global Health Diplomacy uses digital technologies in its enactment. Both phenomena have driven interest in the term "Digital Health Diplomacy." A review of the literature revealed 2 emerging but distinct definitions that have been published very recently, each with its associated discourse and practice. This multiplicity of ideas demonstrates the myriad ways in which global digital and political systems are becoming increasingly entangled. Untangling these, this paper proposes and discusses 3 dimensions of Digital Health Diplomacy: "Diplomacy for digital health," "Digital health for diplomacy," and "Digital health in diplomacy." It calls upon digital health professionals, diplomats, political and social scientists, epidemiologists, and clinicians to discuss, critique, and advance this emerging domain., (© The Author(s) 2021. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

In 1995, Pacific Health Ministers articulated their vision of a healthy Pacific as 'a place where children are nurtured in body and mind; environments invite learning and leisure; people work and age with dignity; where ecological balance is a source of pride; and where the ocean is protected.' Central to this vision is the achievement of universal health coverage (UHC). To provide an indication of the UHC-related priorities of Pacific health authorities and promote alignment of domestic and international investments in health sector development, we thematically analyzed the discussion, resolutions, and recommendations from 5 years (2015-2020) of senior-level Pacific health meetings. Five main themes emerged: (i) the Healthy Islands vision has (and continues to have) a unifying influence on action for UHC; (ii) adoption of appropriate service delivery models that support integrated primary health care at the community level are needed; (iii) human resources for health are critical if efforts to achieve UHC are to be successful; (iv) access to reliable health information is core to health sector improvement; and (v) while not a panacea for all challenges, digital health offers many opportunities. Small and isolated populations, chronic workforce limitations, weak governance arrangements, ageing and inadequate health facilities, and supply chain and logistics difficulties (among other issues) interact to challenge primary health care delivery across the Pacific Islands. We found evidence that the Healthy Islands vision is a tool that garners support for UHC; however, to realize the vision, a realistic understanding of needed political, human resource, and economic investments is required. The significant disruptive effect of COVID-19 and the uncertainty it brings for implementation of the medium- to long-term health development agenda raises concern that progress may stagnate or retreat.

Background: We investigated whether we could use influenza data to develop prediction models for COVID-19 to increase the speed at which prediction models can reliably be developed and validated early in a pandemic. We developed COVID-19 Estimated Risk (COVER) scores that quantify a patient's risk of hospital admission with pneumonia (COVER-H), hospitalization with pneumonia requiring intensive services or death (COVER-I), or fatality (COVER-F) in the 30-days following COVID-19 diagnosis using historical data from patients with influenza or flu-like symptoms and tested this in COVID-19 patients., Methods: We analyzed a federated network of electronic medical records and administrative claims data from 14 data sources and 6 countries containing data collected on or before 4/27/2020. We used a 2-step process to develop 3 scores using historical data from patients with influenza or flu-like symptoms any time prior to 2020. The first step was to create a data-driven model using LASSO regularized logistic regression, the covariates of which were used to develop aggregate covariates for the second step where the COVER scores were developed using a smaller set of features. These 3 COVER scores were then externally validated on patients with 1) influenza or flu-like symptoms and 2) confirmed or suspected COVID-19 diagnosis across 5 databases from South Korea, Spain, and the United States. Outcomes included i) hospitalization with pneumonia, ii) hospitalization with pneumonia requiring intensive services or death, and iii) death in the 30 days after index date., Results: Overall, 44,507 COVID-19 patients were included for model validation. We identified 7 predictors (history of cancer, chronic obstructive pulmonary disease, diabetes, heart disease, hypertension, hyperlipidemia, kidney disease) which combined with age and sex discriminated which patients would experience any of our three outcomes. The models achieved good performance in influenza and COVID-19 cohorts. For COVID-19 the AUC ranges were, COVER-H: 0.69-0.81, COVER-I: 0.73-0.91, and COVER-F: 0.72-0.90. Calibration varied across the validations with some of the COVID-19 validations being less well calibrated than the influenza validations., Conclusions: This research demonstrated the utility of using a proxy disease to develop a prediction model. The 3 COVER models with 9-predictors that were developed using influenza data perform well for COVID-19 patients for predicting hospitalization, intensive services, and fatality. The scores showed good discriminatory performance which transferred well to the COVID-19 population. There was some miscalibration in the COVID-19 validations, which is potentially due to the difference in symptom severity between the two diseases. A possible solution for this is to recalibrate the models in each location before use., (© 2022. The Author(s).)

Objective: Internationally, primary care practice had to transform in response to the COVID pandemic. Informatics issues included access, privacy, and security, as well as patient concerns of equity, safety, quality, and trust. This paper describes progress and lessons learned., Methods: IMIA Primary Care Informatics Working Group members from Australia, Canada, United Kingdom and United States developed a standardised template for collection of information. The template guided a rapid literature review. We also included experiential learning from primary care and public health perspectives., Results: All countries responded rapidly. Common themes included rapid reductions then transformation to virtual visits, pausing of non-COVID related informatics projects, all against a background of non-standardized digital development and disparate territory or state regulations and guidance. Common barriers in these four and in less-resourced countries included disparities in internet access and availability including bandwidth limitations when internet access was available, initial lack of coding standards, and fears of primary care clinicians that patients were delaying care despite the availability of televisits., Conclusions: Primary care clinicians were able to respond to the COVID crisis through telehealth and electronic record enabled change. However, the lack of coordinated national strategies and regulation, assurance of financial viability, and working in silos remained limitations. The potential for primary care informatics to transform current practice was highlighted. More research is needed to confirm preliminary observations and trends noted., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (IMIA and Thieme. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Objective: The COVID-19 pandemic and its socio-economic impacts have disrupted our health systems and society. We sought to examine informatics and digital health strategies that supported the primary care response to COVID-19 in Australia. Specifically, the review aims to answer: how Australian primary health care responded and adapted to COVID-19, the facilitators and inhibitors of the Primary care informatics and digital health enabled COVID-19 response and virtual models of care observed in Australia., Methods: We conducted a rapid scoping review complying with the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for scoping reviews guidelines. Two reviewers independently performed the literature search, data extraction, and synthesis of the included studies. Any disagreement in the eligibility screening, data extraction or synthesis was resolved through consensus meeting and if required. was referred to a third reviewer. Evidence was synthesised, summarised, and mapped to several themes that answer the research question s of this review., Results: We identified 377 papers from PubMed, Scopus, Web of Science and Embase. Following title, abstract and full-text screening, 29 eligible papers were included. The majority were "perspectives" papers. The dearth of original research into digital health and COVID-19 in primary care meant limited evidence on effectiveness, access, equity, utility, safety, and quality. Data extraction and evidence synthesis identified 14 themes corresponding to 3 research questions. Telehealth was the key digital health response in primary care, together with mobile applications and national hotlines, to enable the delivery of virtual primary care and support public health. Enablers and barriers such as workforce training, digital resources, patient experience and ethical issues, and business model and management issues were identified as important in the evolution of virtual primary care., Conclusions: COVID-19 has transformed Australian primary care with the rapid adaptation of digital technologies to complement "in-person" primary care with telehealth and virtual models of care. The pandemic has also highlighted several literacy, maturity/readiness, and micro, meso and macro-organisational challenges with adopting and adapting telehealth to support integrated person-centred health care. There is a need for more research into how telehealth and virtual models of care can improve the access, integration, safety, and quality of virtual primary care., (Copyright © 2021. Published by Elsevier B.V.)

• Average monthly GP visits for mental health tripled during the COVID-19 period. • Rates of depression and eating disorders rose by 61% and 56%, respectively. • Females and those from affluent areas had significantly higher visits. This study explored the impacts of COVID-19 on the mental health (MH)-related visits to general practices (GPs) among children and young people (CYP) up to 18 years of age in Australia. This study analysed national-level data captured by the NPS MedicineWise program on monthly CYP MH-related visits per 10,000 visits to GPs from January 2014 to September 2021. We considered the pre-COVID-19 period (January 2014–February 2020) and the COVID-19 period (March 2020–September 2021). We used a Bayesian structural time series (BSTS) model to estimate the impact of COVID-19 on MH-related GP visits per 10,000 visits. A total of 103,813 out of 7,690,874 visits to GP (i.e., about 135 per 10,000 visits) were related to MH during study period. The BSTS model showed a significant increase in the overall MH-related visits during COVID-19 period (33%, 95% Credible Interval (Crl) 8.5%–56%), particularly, visits related to depressive disorders (61%, 95% Crl 29%–91%). The greatest increase was observed among females (39%, 95% Crl 12%–64%) and those living in socioeconomically least disadvantaged areas (36%, 95% Crl 1.2–71%). Our findings highlight the need for resources to be directed towards at-risk CYP to improve MH outcomes and reduce health system burden. [ABSTRACT FROM AUTHOR]