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Abstract 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.

Objectives In this overview, we describe theObservational Medical Outcomes Partnership Common Data Model (OMOP-CDM), the established governance processes employed in EMR data repositories, and demonstrate how OMOP transformed data provides a lever for more efficient and secure access to electronic medical record (EMR) data by health service providers and researchers.Methods Through pseudonymisation and common data quality assessments, the OMOP-CDM provides a robust framework for converting complex EMR data into a standardised format. This allows for the creation of shared end-to-end analysis packages without the need for direct data exchange, thereby enhancing data security and privacy. By securely sharing de-identified and aggregated data and conducting analyses across multiple OMOP-converted databases, patient-level data is securely firewalled within its respective local site.Results By simplifying data management processes and governance, and through the promotion of interoperability, the OMOP-CDM supports a wide range of clinical, epidemiological, and translational research projects, as well as health service operational reporting.Discussion Adoption of the OMOP-CDM internationally and locally enables conversion of vast amounts of complex, and heterogeneous EMR data into a standardised structured data model, simplifies governance processes, and facilitates rapid repeatable cross-institution analysis through shared end-to-end analysis packages, without the sharing of data.Conclusion The adoption of the OMOP-CDM has the potential to transform health data analytics by providing a common platform for analysing EMR data across diverse healthcare settings.

Embedding research users into the research process can better support its translation into health systems and services. Still, the role of health decision-makers (HDMs) as research partners is poorly understood. HDMs, such as policymakers, administrators, directors or other managers, understand the broader contexts of a health service and have a mandate to facilitate change where appropriate, so they could play an important partnership role in research activities.

Abstract 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.

BackgroundThe Health eLiteracy for Prevention in General Practice trial is a primary health care–based behavior change intervention for weight loss in Australians who are overweight and those with obesity from lower socioeconomic areas. Individuals from these areas are known to have low levels of health literacy and are particularly at risk for chronic conditions, including diabetes and cardiovascular disease. The intervention comprised health check visits with a practice nurse, a purpose-built patient-facing mobile app (mysnapp), and a referral to telephone coaching. ObjectiveThis study aimed to assess mysnapp app use, its user profiles, the duration and frequency of use within the Health eLiteracy for Prevention in General Practice trial, its association with other intervention components, and its association with study outcomes (health literacy and diet) to determine whether they have significantly improved at 6 months. MethodsIn 2018, a total of 22 general practices from 2 Australian states were recruited and randomized by cluster to the intervention or usual care. Patients who met the main eligibility criteria (ie, BMI>28 in the previous 12 months and aged 40-74 years) were identified through the clinical software. The practice staff then provided the patients with details about this study. The intervention consisted of a health check with a practice nurse and a lifestyle app, a telephone coaching program, or both depending on the participants’ choice. Data were collected directly through the app and combined with data from the 6-week health check with the practice nurses, the telephone coaching, and the participants’ questionnaires at baseline and 6-month follow-up. The analyses comprised descriptive and inferential statistics. ResultsOf the 120 participants who received the intervention, 62 (52%) chose to use the app. The app and nonapp user groups did not differ significantly in demographics or prior recent hospital admissions. The median time between first and last app use was 52 (IQR 4-95) days, with a median of 5 (IQR 2-10) active days. App users were significantly more likely to attend the 6-week health check (2-sided Fisher exact test; P

BackgroundTuberculosis (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. ObjectiveThis 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]). MethodsIn 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. ResultsVarious 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. ConclusionsFindings 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 RegistrationPROSPERO CRD42021277155; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=277155

Abstract 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.

Abstract Background Evidence-based medicine (EBM) is a core skillset for enhancing the quality and safety of patients’ care. Online EBM education could improve clinicians’ skills in EBM, particularly when it is conducted during vocational training. There are limited studies on the impact of online EBM training on clinical practice among general practitioner (GP) registrars (trainees in specialist general practice). We aimed to describe and evaluate the acceptability, utility, satisfaction and applicability of the GP registrars experience with the online course. The course was developed by content-matter experts with educational designers to encompass effective teaching methods (e.g. it was interactive and used multiple teaching methods). Methods Mixed-method data collection was conducted after individual registrars’ completion of the course. The course comprised six modules that aimed to increase knowledge of research methods and application of EBM skills to everyday practice. GP registrars who completed the online course during 2016–2020 were invited to complete an online survey about their experience and satisfaction with the course. Those who completed the course within the six months prior to data collection were invited to participate in semi-structured phone interviews about their experience with the course and the impact of the course on clinical practice. A thematic analysis approach was used to analyse the data from qualitative interviews. Results The data showed the registrars were generally positive towards the course and the concept of EBM. They stated that the course improved their confidence, knowledge, and skills and consequently impacted their practice. The students perceived the course increased their understanding of EBM with a Cohen’s d of 1.6. Registrars identified factors that influenced the impact of the course. Of those, some were GP-related including their perception of EBM, and being comfortable with what they already learnt; some were work-place related such as time, the influence of supervisors, access to resources; and one was related to patient preferences. Conclusions This study showed that GP registrars who attended the online course reported that it improved their knowledge, confidence, skill and practice of EBM over the period of three months. The study highlights the supervisor’s role on GP registrars’ ability in translating the EBM skills learnt in to practice and suggests exploring the effect of EBM training for supervisors.

Objectives Implementing support and services early in the life course has been shown to promote positive developmental outcomes for children at high likelihood of developmental conditions including autism. This study examined parents’/caregivers’ experiences and perceptions about a digital developmental surveillance pathway for autism, the autism surveillance pathway (ASP), and usual care, the surveillance as usual (SaU) pathway, in the primary healthcare general practice setting.Design This qualitative study involves using a convenience selection process of the full sample of parents/caregivers that participated in the main programme, ‘General Practice Surveillance for Autism’, a cluster-randomised controlled trial study. All interviews were audio-recorded, transcribed and coded using NVivo V.12 software. An inductive thematic interpretive approach was adopted and data were analysed thematically.Participants Twelve parents/caregivers of children with or without a developmental condition/autism (who participated in the main programme) in South Western Sydney and Melbourne were interviewed.Settings All interviews were completed over the phone.Results There were seven major themes and 20 subthemes that included positive experiences, such as pre-existing patient–doctor relationships and their perceptions on the importance of knowing and accessing early support/services. Barriers or challenges experienced while using the SaU pathway included long waiting periods, poor communication and lack of action plans, complexity associated with navigating the healthcare system and lack of understanding by general practitioners (GPs). Common suggestions for improvement included greater awareness/education for parents/carers and the availability of accessible resources on child development for parents/caregivers.Conclusion The findings support the use of digital screening tools for developmental surveillance, including for autism, using opportunistic contacts in the general practice setting.Trial registration number ANZCTR (ACTRN12619001200178).

Objectives To evaluate a multifaceted intervention on diet, physical activity and health literacy of overweight and obese patients attending primary care.Design A pragmatic two-arm cluster randomised controlled trial.Setting Urban general practices in lower socioeconomic areas in Sydney and Adelaide.Participants We aimed to recruit 800 patients in each arm. Baseline assessment was completed by 215 patients (120 intervention and 95 control).Intervention A practice nurse-led preventive health check, a mobile application and telephone coaching.Primary and secondary outcome measures Primary outcomes were measured at baseline, 6 and 12 months, and included patient health and eHealth literacy, weight, waist circumference and blood pressure. Secondary outcomes included changes in diet and physical activity, preventive advice and referral, blood lipids, quality of life and costs. Univariate and multivariate analyses of difference-in-differences (DiD) estimates for each outcome were conducted.Results At 6 months, the intervention group, compared with the control group, demonstrated a greater increase in Health Literacy Questionnaire domain 8 score (ability to find good health information; mean DiD 0.22; 95% CI 0.01 to 0.44). There were similar differences for domain 9 score (understanding health information well enough to know what to do) among patients below the median at baseline. Differences were reduced and non-statistically significant at 12 months. There was a small improvement in diet scores at 6 months (DiD 0.78 (0.10 to 1.47); p=0.026) but not at 12 months. There were no differences in eHealth literacy, physical activity scores, body mass index, weight, waist circumference or blood pressure.Conclusions Targeted recruitment and engagement were challenging in this population. While the intervention was associated with some improvements in health literacy and diet, substantial differences in other outcomes were not observed. More intensive interventions and using codesign strategies to engage the practices earlier may produce a different result. Codesign may also be valuable when targeting lower socioeconomic populations.Trial registration number Australian New Zealand Clinical Trials Registry (ACTRN 12617001508369) (http://www.ANZCTR.org.au/ACTRN12617001508369.aspx).Trial protocol The protocol for this trial has been published (open access; https://bmjopen.bmj.com/content/8/6/e023239).

Introduction Australia’s current healthcare system for children is neither sustainable nor equitable. As children (0–4 years) comprise the largest proportion of all primary care-type emergency department presentations, general practitioners (GPs) report feeling undervalued as an integral member of a child’s care, and lacking in opportunities for support and training in paediatric conditions. This Strengthening Care for Children (SC4C) randomised trial aims to evaluate a novel, integrated GP-paediatrician model of care, that, if effective, will improve GP quality of care, reduce burden to hospital services and ensure children receive the right care, at the right time, closer to home.Methods and analysis SC4C is a stepped wedge cluster randomised controlled trial (RCT) of 22 general practice clinics in Victoria and New South Wales, Australia. General practice clinics will provide control period data before being exposed to the 12-month intervention which will be rolled out sequentially each month (one clinic per state) until all 22 clinics receive the intervention. The intervention comprises weekly GP-paediatrician co-consultation sessions; monthly case discussions; and phone and email paediatrician support, focusing on common paediatric conditions. The primary outcome of the trial is to assess the impact of the intervention as measured by the proportion of children’s (0–

Introduction The increasing prevalence of developmental disorders in early childhood poses a significant global health burden. Early detection of developmental problems is vital to ensure timely access to early intervention, and universal developmental surveillance is recommended best practice for identifying issues. Despite this, there is currently considerable variation in developmental surveillance and screening between Australian states and territories and low rates of developmental screening uptake by parents. This study aims to evaluate an innovative web-based developmental surveillance programme and a sustainable approach to referral and care pathways, linking primary care general practice (GP) services that fall under federal policy responsibility and state government-funded child health services.Methods and analysis The proposed study describes a longitudinal cluster randomised controlled trial (c-RCT) comparing a ‘Watch Me Grow Integrated’ (WMG-I) approach for developmental screening, to Surveillance as Usual (SaU) in GPs. Forty practices will be recruited across New South Wales and Queensland, and randomly allocated into either the (1) WMG-I or (2) SaU group. A cohort of 2000 children will be recruited during their 18-month vaccination visit or opportunistic visit to GP. At the end of the c-RCT, a qualitative study using focus groups/interviews will evaluate parent and practitioner views of the WMG-I programme and inform national and state policy recommendations.Ethics and dissemination The South Western Sydney Local Health District (2020/ETH01625), UNSW Sydney (2020/ETH01625) and University of Queensland (2021/HE000667) Human Research Ethics Committees independently reviewed and approved this study. Findings will be reported to the funding bodies, study institutes and partners; families and peer-reviewed conferences/publications.Trial registration number ANZCTR12621000680864.

Abstract Background Linking process of care data from general practice (GP) and hospital data may provide more information about the risk of hospital admission and re-admission for people with type-2 diabetes mellitus (T2DM). This study aimed to extract and link data from a hospital, a diabetes clinic (DC). A second aim was to determine whether the data could be used to predict hospital admission for people with T2DM. Methods Data were extracted using the GRHANITE™ extraction and linkage tool. The data from nine GPs and the DC included data from the two years prior to the hospital admission. The date of the first hospital admission for patients with one or more admissions was the index admission. For those patients without an admission, the census date 31/03/2014 was used in all outputs requiring results prior to an admission. Readmission was any admission following the index admission. The data were summarised to provide a comparison between two groups of patients: 1) Patients with a diagnosis of T2DM who had been treated at a GP and had a hospital admission and 2) Patients with a diagnosis of T2DM who had been treated at a GP and did not have a hospital admission. Results Data were extracted for 161,575 patients from the three data sources, 644 patients with T2DM had data linked between the GPs and the hospital. Of these, 170 also had data linked with the DC. Combining the data from the different data sources improved the overall data quality for some attributes particularly those attributes that were recorded consistently in the hospital admission data. The results from the modelling to predict hospital admission were plausible given the issues with data completeness. Conclusion This project has established the methodology (tools and processes) to extract, link, aggregate and analyse data from general practices, hospital admission data and DC data. This study methodology involved the establishment of a comparator/control group from the same sites to compare and contrast the predictors of admission, addressing a limitation of most published risk stratification and admission prediction studies. Data completeness needs to be improved for this to be useful to predict hospital admissions.

Engaging citizens with digital technology to co-create data, information and knowledge has widely become an important strategy for informing the policy response to COVID-19 and the ‘infodemic’ of misinformation in cyberspace. This move towards digital citizen participation aligns well with the United Nations’ agenda to encourage the use of digital tools to enable data-driven, direct democracy. From data capture to information generation, and knowledge co-creation, every stage of the data lifecycle bears important considerations to inform policy and practice. Drawing on evidence of participatory policy and practice during COVID-19, we outline a framework for citizen ‘e-participation’ in knowledge co-creation across every stage of the policy cycle. We explore how coupling the generation of information with that of social capital can provide opportunities to collectively build trust in institutions, accelerate recovery and facilitate the ‘e-society’. We outline the key aspects of realising this vision of data-driven direct democracy by discussing several examples. Sustaining participatory knowledge co-creation beyond COVID-19 requires that local organisations and institutions (e.g. academia, health and welfare, government, business) incorporate adaptive learning mechanisms into their operational and governance structures, their integrated service models, as well as employing emerging social innovations.

Background and Objectives: Statins have been extensively utilised in atherosclerotic cardiovascular disease (ASCVD) prevention and can inhibit inflammation. However, the association between statin therapy, subclinical inflammation and associated health outcomes is poorly understood in the primary care setting. Materials and Methods: Primary care electronic health record (EHR) data from the electronic Practice-Based Research Network (ePBRN) from 2012–2019 was used to assess statin usage and adherence in South-Western Sydney (SWS), Australia. Independent determinants of elevated C-reactive protein (CRP) were determined. The relationship between baseline CRP levels and hospitalisation rates at 12 months was investigated. Results: The prevalence of lipid-lowering medications was 14.0% in all adults and 44.6% in the elderly (≥65 years). The prevalence increased from 2012 to 2019 despite a drop in statin use between 2013–2015. A total of 55% of individuals had good adherence (>80%). Hydrophilic statin use and higher intensity statin therapy were associated with elevated CRP levels. However, elevated CRP levels were not associated with all-cause or ASCVD hospitalisations after adjusting for confounders. Conclusions: The prevalence and adherence patterns associated with lipid-lowering medications highlighted the elevated ASCVD-related burden in the SWS population, especially when compared with the Australian general population. Patients in SWS may benefit from enhanced screening protocols, targeted health literacy and promotion campaigns, and timely incorporation of evidence into ASCVD clinical guidelines. This study, which used EHR data, did not support the use of CRP as an independent marker of future short-term hospitalisations.

Background Healthcare organisations are undergoing a major transformational shift in the use of information and digital health technologies. Enterprise architecture (EA) has been incrementally adopted in many healthcare organisations globally to facilitate this change. EA can increase the effectiveness of an organisation’s digital health capabilities and resources. However, little is known about the status of EA adoption in low-income and middle-income countries. This study aimed to evaluate the challenges, goals and benefits associated with adoption of EA for healthcare in the Asia eHealth Information Network (AeHIN) member countries .Methods We developed an EA Adoption Evaluation framework with four principal layers: governance, strategy, EA and performance. The framework guided the development of a questionnaire to investigate the goals, challenges and benefits faced before and during EA adoption by healthcare organisations.Sample 26 participants from 18 healthcare organisations in the Asia-Pacific region representing 11 countries. Organisations included Ministries of Health, Universities, Non-Governmental Organisations and Technical Advisory Groups.Findings Only 5 of the 18 organisations had begun adopting EA. The goals expressed for EA adoption were to address issues such as interoperability, lack of technical infrastructure and poor alignment of business and information technology strategies. Cost reduction was less emphasised. The main challenges to adopting EA was the lack of EA knowledge, leadership and involvement of senior management.Conclusion The adoption of EA is incipient in AeHIN member healthcare organisations. To encourage EA adoption, these organisations need to invest in internal capacity building, senior management training and seek independent EA expert advice to systematically identify and address the barriers to adopting EA.

South Western Sydney (SWS) is one of the fastest growing regions in the state of New South Wales (Australia). Much of the population live in local government areas (LGAs) with levels of disadvantage higher than the state average, with a predominance of non-communicable and chronic diseases that are typically associated with age-related and behavioural factors. This necessitates the management of social determinants of health through the integrated provision of primary and social care. The SWS Local Health District and Primary Health Network is exploring the potential of community health alliances (CHAs) as an innovative approach to support the provision of integrated health services. CHAs are a population health approach for addressing health challenges faced by people who share a common area of residence, sociocultural characteristic or health need, and are characterised by a shared mission, shared resource needs and acquiring/developing necessary organisational knowledge and skills. We explore how CHAs operate as social enterprises that utilise digital health and citizen engagement to deliver integrated people-centred health services (IPCHS) by conducting two case studies of CHAs operating in SWS: in Wollondilly and Fairfield LGAs. Using this approach, we aim to unpack the conceptual convergence that enables social enterprises to utilise digital health interventions and citizen engagement strategies to co-produce IPCHS with a view to developing theory and a framework for engaging digital citizens in integrated primary health care via social enterprise.

Abstract Background Traditional gender roles result in women lagging behind men in the use of modern technologies, especially in developing countries. Although there is rapid uptake of mobile phone use in Bangladesh, investigation of gender differences in the ownership, access and use of mobile phones in general and mHealth in particular has been limited. This paper presents gender differentials in the ownership of mobile phones and knowledge of available mHealth services in a rural area of Bangladesh. Methods We interviewed 4915 randomly selected respondents aged 18 years and above. Associations between gender and knowledge of available mHealth services, use of existing mHealth services and intentions to use mHealth services in the future were examined by multivariate logistic regression analysis, controlling for the effect of categorised covariates. Results Of the 4915 respondents to the survey, 61.8% of men (1213/1964) and 34.4% of women (1015/2951) owned a mobile phone. For men, mobile phone ownership was highest among those aged 18–29 years (n = 663, 76.3%), and for women among those aged 30–39 years (n = 825, 44.7%). A higher proportion of men owned phones compared to women, irrespective of socioeconomic status (SES) as indicated by asset index (p

Introduction:The proportion of people aged over 60 years is increasing globally and expected to double by 2050 [1]. The World Health Organization and health systems globally have identified mobile health (mHealth) as an important strategy to address the health needs of this growing population group. Healthcare innovations focused on ageing, including mHealth interventions, provide an opportunity to enhance service delivery. A systematic review [2] was undertaken to answer the following questions: 1. How is mHealth being used to promote healthy ageing and support the delivery of age-friendly health and long-term care services? 2. What are the effective models for implementing mHealth interventions? 3. What are the lessons learnt from implementation of mHealth initiatives? 4. Is there enough evidence to support the impact of mHealth interventions? Methods:The review was conducted in late 2017, following the PRISMA[3] guidelines for systematic reviews. MEDLINE, EMBASE, Global Health, PsycINFO, Scopus, ScienceDirect, CINAHL and the Cochrane Library were searched.A combination of the terms ‘mHealth OR mobile health’ AND 'healthy ageing’ AND 'aged care’ was used along with the five domains of the RE-AIM framework [4]. The inclusion criteria were: (i) literature published from 2007 to 2017 on mHealth interventions, and (ii) mHealth interventions conducted on people aged 45 years and older. Results:Of 2883 records identified, 133 studies were included in the qualitative synthesis. Most mHealth interventions were an adjunct to existing age-friendly health services, particularly for older adults with chronic health conditions. There were no examples of scaled-up implementations or systematic evaluations of successful feasibility and usability studies that implemented mHealth.The rapid pace of technological change as well as development, adoption and demise of mHealth apps presents crucial challenges for consumers, health care providers and policy makers. Overall, there is a lack of conclusive evidence regarding cost-effectiveness of mHealth to improve healthy ageing and support age-friendly health services. Implications for policy, practice and research: Future mHealth research needs robust experimental designs and a person-centred, biopsychosocial approach that looks at multi-level determinants of health care. Collaborative partnerships for the design, development, testing, implementation and evaluation of mHealth apps are essential.Robust governance frameworks for mHealth strategies are also required, as there is a risk the mHealth initiatives will further fragment care due to development and use of too many disparate apps and platforms without shared data frameworks or governance. References: 1. World Health Organization (2016). World report on ageing and health 2015. 2. Liaw ST, Ansari S, Jonnagaddala J, Narasimhan P, Ashraf MM, Harris-Roxas B and Harris M (2017). A systematic review of the use of mHealth to promote healthy ageing and support the delivery of age-friendly health and long-term care services. PROSPERO CRD42017082383. 3. Moher D, Liberati A, Tetzlaff J, Altman DG and Group P (2009). Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS medicine. 6(7):e1000097. 4. Gaglio B, Shoup JA and Glasgow RE (2013). The RE-AIM Framework: A Systematic Review of Use Over Time. American Journal of Public Health. 103(6):e38-e46.

Introduction: Well-child Care is the provision of preventative health care services for children and their families. The approach, however, to the universal provision of those services is contentious. Methods: We undertook a realist synthesis to enhance understanding of the theoretical mechanisms driving Well-child Care by searching for published and grey literature from multiple databases. Findings: Well-child Care is re-conceptualised as an integrated program delivered in the continuum of pregnancy, infancy and childhood. Depending on the context, Well-child Care can be a policy, a strategy, or an actual clinical practice that promotes child and family health. The main mechanisms include: role, training and continuity of health providers; administrators’ views of the return of investment on achieved outcomes; access to services by families; and the adaptation of programs to meet the dynamic needs of stakeholders. Evidence indicates that for most outcomes, Well-child Care is best delivered in partnerships between community health, social care, and early childhood education sectors. Conclusions: We conclude that Well-child Care policy and program leaders should shift their focus to the integration of: human and physical resources; policy instruments; and shared agreement on outcomes measures across health, social and education sectors. In addition, countries should work towards strengthening universal early education programs and parents’ health literacy regarding child development, health and safety.

Sharing health and social care data is essential to the delivery of high quality health care as well as disease surveillance, public health, and for conducting research. However, these societal benefits may be constrained by privacy and data protection principles. Hence, societies are striving to find a balance between the two competing public interests. Whilst the spread of IT advancements in recent decades has increased the demand for an increased privacy and data protection in many ways health is a special case. UK, are adopting guidelines, codes of conduct and regulatory instruments aimed to implement privacy principles into practical settings and enhance public trust. Accordingly, in 2015, the UK National Data Guardian (NDG) requested to conduct a further review of data protection, referred to as Caldicott 3. The scope of this review is to strengthen data security standards and confidentiality. It also proposes a consent system based on an “opt-out” model rather than on “opt-in. Across Europe as well as internationally the privacy-health data sharing balance is not fixed. In Europe enactment of the new EU Data Protection Regulation in 2016 constitute a major breakthrough, which is likely to have a profound effect on European countries and beyond. In Australia and across North America different ways are being sought to balance out these twin requirements of a modern society - to preserve privacy alongside affording high quality health care for an ageing population. Whilst in the UK privacy legal framework remains complex and fragmented into different layers of legislation, which may negatively impact on both the rights to privacy and health the UK is at the forefront in the uptake of international and EU privacy and data protection principles. And, if the privacy regime were reorganised in a more comprehensive manner, it could be used as a sound implementation model for other countries.

Background The use of health data for public health, surveillance, quality improvement and research is crucial to improve health systems and health care. However, bodies responsible for privacy and ethics often limit access to routinely collected health data. Ethical approvals, issues around protecting privacy and data access are often dealt with by different layers of regulations, making approval processes appear disjointed.Objective To create a comprehensive framework for defining the ethical and privacy status of a project and for providing guidance on data access.Method The framework comprises principles and related questions. The core of the framework will be built using standard terminology definitions such as ethics-related controlled vocabularies and regional directives. It is built in this way to reduce ambiguity between different definitions. The framework is extensible: principles can be retired or added to, as can their related questions. Responses to these questions should allow data processors to define ethical issues, privacy risk and other unintended consequences.Results The framework contains three steps: (1) identifying possible ethical and privacy principles relevant to the project; (2) providing ethics and privacy guidance questions that inform the type of approval needed; and (3) assessing case-specific ethics and privacy issues. The outputs from this process should inform whether the balance between public interests and privacy breach and any ethical considerations are tipped in favour of societal benefits. If they are then this should be the basis on which data access is permitted. Tightly linking ethical principles to governance and data access may help maintain public trust.

An algorithm that detects errors in diagnosis, classification or coding of diabetes in primary care computerised medial record (CMR) systems is currently available. However, this was developed on CMR systems that are “Episode orientated” medical records (EOMR); and don’t force the user to always code a problem or link data to an existing one. More strictly problem orientated medical record (POMR) systems mandate recording a problem and linking consultation data to them.

INTRODUCTION:Well-Child Care (WCC) is the provision of preventive health care services for children and their families. Prior research has highlighted that several barriers exist for the provision of WCC services. OBJECTIVES:To study "real life" visits of parents and children with health professionals in order to enhance the theoretical understanding of factors affecting WCC. METHODS:Participant observations of a cross-sectional sample of 71 visits at three general practices were analysed using a mixed-methods approach. RESULTS:The median age of the children was 18 months (IQR, 6-36 months), and the duration of visits was 13 mins (IQR, 9-18 mins). The reasons for the visits were immunisation in 13 (18.5%), general check-up in 10 (13.8%), viral illness in 33 (49.2%) and miscellaneous reasons in 15 (18.5%). Two clusters with low and high WCC emerged; WCC was associated with higher GP patient-centeredness scores, younger age of the child, fewer previous visits, immunisation and general check-up visits, and the solo general practitioner setting. Mothers born overseas received less WCC advice, while longer duration of visit increased WCC. GPs often made observations on physical growth and development and negotiated mothers concerns to provide reassurance to them. The working style of the GP which encouraged informal conversations with the parents enhanced WCC. There was a lack of systematic use of developmental screening measures. CONCLUSIONS:GPs and practice nurses are providing parent/child centered WCC in many visits, particularly when parents present for immunisation and general check-ups. Providing funding and practice nurse support to GPs, and aligning WCC activities with all immunisation visits, rather than just a one-off screening approach, appears to be the best way forward. A cluster randomised trial for doing structured WCC activities with immunisation visits would provide further evidence for cost-effectiveness studies to inform policy change.

Introduction Increasing investment in eHealth aims to improve cost effectiveness and safety of care. Data extraction and aggregation can create new data products to improve professional practice and provide feedback to improve the quality of source data. A previous systematic review concluded that locally relevant clinical indicators and use of clinical record systems could support clinical governance. We aimed to extend and update the review with a theoretical framework.Methods We searched PubMed, Medline, Web of Science, ABI Inform (Proquest) and Business Source Premier (EBSCO) using the terms curation, information ecosystem, data quality management (DQM), data governance, information governance (IG) and data stewardship. We focused on and analysed the scope of DQM and IG processes, theoretical frameworks, and determinants of the processing, quality assurance, presentation and sharing of data across the enterprise.Findings There are good theoretical reasons for integrated governance, but there is variable alignment of DQM, IG and health system objectives across the health enterprise. Ethical constraints exist that require health information ecosystems to process data in ways that are aligned with improving health and system efficiency and ensuring patient safety. Despite an increasingly ‘big-data’ environment, DQM and IG in health services are still fragmented across the data production cycle. We extend current work on DQM and IG with a theoretical framework for integrated IG across the data cycle.Conclusions The dimensions of this theory-based framework would require testing with qualitative and quantitative studies to examine the applicability and utility, along with an evaluation of its impact on data quality across the health enterprise.

Even though informatics is a term used commonly in healthcare, it can be a confusing and disengaging one. Many definitions exist in the literature, and attempts have been made to develop a clear taxonomy. Despite this, informatics is still a term that lacks clarity in both its scope and the classification of sub-terms that it encompasses.This paper reviews the importance of an agreed taxonomy and explores the challenges of establishing exactly what is meant by health informatics (HI). It reviews what a taxonomy should do, summarises previous attempts at categorising and organising HI and suggests the elements to consider when seeking to develop a system of classification.The paper does not provide all the answers, but it does clarify the questions. By plotting a path towards a taxonomy of HI, it will be possible to enhance understanding and optimise the benefits of embracing technology in clinical practice.

Health care, in common with many other industries, is generating large amounts of routine data, data that are challenging to process, analyse or curate, so-called ‘big data’. A challenge for health informatics is to make sense of these data. Part of the answer will come from the development of ontologies that support the use of heterogeneous data sources and the development of intermediate processors of health information (IPHI). IPHI will sit between the generators of health data and information, often the providers of health care, and the managers, commissioners, policy makers, researchers, and the pharmaceutical and other healthcare industries. They will create a health ecosystem by processing data in a way that stimulates improved data quality and potentially health care delivery by providers of health care, and by providing greater insights to legitimate users of data. Exemplars are provided of how a health ecosystem might be encouraged and developed to promote patient safety and more efficient health care. These are in the areas of how to integrate data around the unsafe use of alcohol and to explore vaccine safety. A challenge for IPHI is how to ensure that their processing of data is valid, safe and maintains privacy. Development of the healthcare ecosystem and IPHI should be actively encouraged internationally. Governments, regulators and providers of health care should facilitate access to health data and the use of national and international comparisons to monitor standards. However, most importantly, they should pilot new methods of improving quality and safety through the intermediate processing of health data.

Background: General practitioners (GPs) are increasing involved in the care of children with autism spectrum disorders (ASDs), and prescribe and/or manage psychotropic medications for these children. Few published reports of perceptions of GPs regarding use of these medications exist in the literature. Objective: Qualitative analysis of comments by 177 GPs regarding psychopharmacology use in children with ASDs. Methods: A postal questionnaire survey containing both close- and open-ended questions was conducted in New South Wales, Australia. Results: Respondent GPs were more likely to be females graduated from Australian medical schools and reported an interest either in child or in mental health. The respondents demonstrated good understanding of the issues surrounding psychopharmacology use in children with ASD based on contemporary literature on this topic. The main themes included concerns regarding medication safety, evidence for their use, and role of these medications as an adjuvant to behavior management. GPs reported a lack of experience of these medications, and would often prescribe only under the supervision of specialists. GPs with greater confidence and involvement with children of ASDs prescribed more medications; whereas GP reporting more concerns with regard to medications prescribed less. Conclusion: Respondent GPs have good understanding of psychotropic medications but need support from specialists for managing these medications in children with ASDs. Future larger studies should explore the utility of collaborative models of care for GPs to work in close partnerships with specialists.

General practice should become the hub of integrated health neighbourhoods (IHNs), which involves sharing of information to ensure that medical homes are also part of learning organisations that use electronic health record (EHR) data for care, decision making, teaching and learning, quality improvement and research. The IHN is defined as the primary and ambulatory care services in a locality that relates largely to a single hospital-based secondary care service provider and is the logical denominator and unit of comparison for the optimal use of EHR data and health information exchange (HIE) to facilitate integration and coordination of care. Its size may vary based on the geography and requirements of the population, for example between city, suburban and rural areas. The conceptual framework includes context; integration of data, information and knowledge; integration of clinical workflow and practice; and inter-professional integration to ensure coordinated shared care to deliver safe and effective services that are equitable, accessible and culturally respectful. We illustrate how this HIE-supported IHN vision may be achieved with an Australian case study demonstrating the integration of linked pseudonymised records with knowledge- and evidence-based guidelines using semantic web tools and informatics-based methods, researching causal links bewteen data quality and quality of care and the key issues to address. The data presented in this paper form part of the evaluation of the informatics infrastructure - HIE and data repository – for its reliability and utility in supporting the IHN. An IHN can only be created if the necessary health informatics infrastructure is put in place. Integrated care may struggle to be effective without HIE.

Background The burden of chronic disease is increasing, and research and quality improvement will be less effective if case finding strategies are suboptimal. Objective To describe an ontology-driven approach to case finding in chronic disease and how this approach can be used to create a data dictionary and make the codes used in case finding transparent. Method A five-step process: (1) identifying a reference coding system or terminology; (2) using an ontology-driven approach to identify cases; (3) developing metadata that can be used to identify the extracted data; (4) mapping the extracted data to the reference terminology; and (5) creating the data dictionary. Results Hypertension is presented as an exemplar. A patient with hypertension can be represented by a range of codes including diagnostic, history and administrative. Metadata can link the coding system and data extraction queries to the correct data mapping and translation tool, which then maps it to the equivalent code in the reference terminology. The code extracted, the term, its domain and subdomain, and the name of the data extraction query can then be automatically grouped and published online as a readily searchable data dictionary. An exemplar online is: www.clininf.eu/qickd-data-dictionary.html Conclusion Adopting an ontology-driven approach to case finding could improve the quality of disease registers and of research based on routine data. It would offer considerable advantages over using limited datasets to define cases. This approach should be considered by those involved in research and quality improvement projects which utilise routine data.

Embedding research users into the research process can better support its translation into health systems and services. Still, the role of health decisionmakers (HDMs) as research partners is poorly understood. HDMs, such as policymakers, administrators, directors or other managers, understand the broader contexts of a health service and have a mandate to facilitate change where appropriate, so they could play an important partnership role in research activities. [ABSTRACT FROM AUTHOR]