Undercounting diagnoses in Australian general practice: a data quality study with implications for population health reporting.

BACKGROUND: Diagnosis can often be recorded in electronic medical records (EMRs) as free-text or using a term with a diagnosis code. Researchers, governments, and agencies, including organisations that deliver incentivised primary care quality improvement programs, frequently utilise coded data only and often ignore free-text entries. Diagnosis data are reported for population healthcare planning including resource allocation for patient care. This study sought to determine if diagnosis counts based on coded diagnosis data only, led to under-reporting of disease prevalence and if so, to what extent for six common or important chronic diseases. METHODS: This cross-sectional data quality study used de-identified EMR data from 84 general practices in Victoria, Australia. Data represented 456,125 patients who attended one of the general practices three or more times in two years between January 2021 and December 2022. We reviewed the percentage and proportional difference between patient counts of coded diagnosis entries alone and patient counts of clinically validated free-text entries for asthma, chronic kidney disease, chronic obstructive pulmonary disease, dementia, type 1 diabetes and type 2 diabetes. RESULTS: Undercounts were evident in all six diagnoses when using coded diagnoses alone (2.57-36.72% undercount), of these, five were statistically significant. Overall, 26.4% of all patient diagnoses had not been coded. There was high variation between practices in recording of coded diagnoses, but coding for type 2 diabetes was well captured by most practices. CONCLUSION: In Australia clinical decision support and the reporting of aggregated patient diagnosis data to government that relies on coded diagnoses can lead to significant underreporting of diagnoses compared to counts that also incorporate clinically validated free-text diagnoses. Diagnosis underreporting can impact on population health, healthcare planning, resource allocation, and patient care. We propose the use of phenotypes derived from clinically validated text entries to enhance the accuracy of diagnosis and disease reporting. There are existing technologies and collaborations from which to build trusted mechanisms to provide greater reliability of general practice EMR data used for secondary purposes.

Activating pharmacists to reduce the frequency of medication-related problems (ACTMed): a stepped wedge cluster randomised trial.

BACKGROUND: Medicines are the most frequent health care intervention type; their safe use provides significant benefits, but inappropriate use can cause harm. Systemic primary care approaches can manage serious medication-related problems in a timely manner. OBJECTIVES: ACTMed (ACTivating primary care for MEDicine safety) uses information technology and financial incentives to encourage pharmacists to work more closely with general practitioners to reduce the risk of harm, improve patients' experience of care, streamline workflows, and increase the efficiency of medical care. METHODS AND ANALYSIS: The stepped wedge cluster randomised trial in 42 Queensland primary care practices will assess the effectiveness of the ACTMed intervention. The primary outcome will be the proportion of people at risk of serious medication-related problems - patients with atrial fibrillation, heart failure, cardiovascular disease, type 2 diabetes, or asthma or chronic obstructive pulmonary disease - who experience such problems. We will also estimate the cost per averted serious medication-related problem and the cost per averted potentially preventable medication-related hospitalisation. ETHICS APPROVAL: The University of Queensland Human Research Ethics Committee approved the pilot (2021/HE002189) and trial phases of the ACTMed study (2022/HE002136). Access to Patron data was granted by the Patron Data Governance Committee (PAT052ACTMed). Access to linked hospitalisations and deaths data are subject to Public Health Act approval (pending). DISSEMINATION OF FINDINGS: A comprehensive dissemination plan will be co-developed by the researchers, the ACTMed steering committee and consumer advisory group, project partners, and trial site representatives. Aboriginal and Torres Strait Islander communities will be supported in leading community-level dissemination. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (pilot: ACTRN12622000595718; 21 April 2022; full trial: ACTRN12622000574741; 14 April 2022).

Identifying primary care datasets and perspectives on their secondary use: a survey of Australian data users and custodians.

BACKGROUND: Most people receive most of their health care in in Australia in primary care, yet researchers and policymakers have limited access to resulting clinical data. Widening access to primary care data and linking it with hospital or other data can contribute to research informing policy and provision of services and care; however, limitations of primary care data and barriers to access curtail its use. The Australian Health Research Alliance (AHRA) is seeking to build capacity in data-driven healthcare improvement; this study formed part of its workplan. METHODS: The study aimed to build capacity for data driven healthcare improvement through identifying primary care datasets in Australia available for secondary use and understand data quality frameworks being applied to them, and factors affecting national capacity for secondary use of primary care data from the perspectives of data custodians and users. Purposive and snowball sampling were used to disseminate a questionnaire and respondents were invited to contribute additional information via semi-structured interviews. RESULTS: Sixty-two respondents collectively named 106 datasets from eclectic sources, indicating a broad conceptualisation of what a primary care dataset available for secondary use is. The datasets were generated from multiple clinical software systems, using different data extraction tools, resulting in non-standardised data structures. Use of non-standard data quality frameworks were described by two-thirds of data custodians. Building trust between citizens, clinicians, third party data custodians and data end-users was considered by many to be a key enabler to improve primary care data quality and efficiencies related to secondary use. Trust building qualities included meaningful stakeholder engagement, transparency, strong leadership, shared vision, robust data security and data privacy protection. Resources to improve capacity for primary care data access and use were sought for data collection tool improvements, workforce upskilling and education, incentivising data collection and making data access more affordable. CONCLUSIONS: The large number of identified Australian primary care related datasets suggests duplication of labour related to data collection, preparation and utilisation. Benefits of secondary use of primary care data were many, and strong national leadership is required to reach consensus on how to address limitations and barriers, for example accreditation of EMR clinical software systems and the adoption of agreed data and quality standards at all stages of the clinical and research data-use lifecycle. The study informed the workplan of AHRA's Transformational Data Collaboration to improve partner engagement and use of clinical data for research.

The American Heart Association 2030 Impact Goal: A Presidential Advisory From the American Heart Association.

Each decade, the American Heart Association (AHA) develops an Impact Goal to guide its overall strategic direction and investments in its research, quality improvement, advocacy, and public health programs. Guided by the AHA's new Mission Statement, to be a relentless force for a world of longer, healthier lives, the 2030 Impact Goal is anchored in an understanding that to achieve cardiovascular health for all, the AHA must include a broader vision of health and well-being and emphasize health equity. In the next decade, by 2030, the AHA will strive to equitably increase healthy life expectancy beyond current projections, with global and local collaborators, from 66 years of age to at least 68 years of age across the United States and from 64 years of age to at least 67 years of age worldwide. The AHA commits to developing additional targets for equity and well-being to accompany this overarching Impact Goal. To attain the 2030 Impact Goal, we recommend a thoughtful evaluation of interventions available to the public, patients, providers, healthcare delivery systems, communities, policy makers, and legislators. This presidential advisory summarizes the task force's main considerations in determining the 2030 Impact Goal and the metrics to monitor progress. It describes the aspiration that these goals will be achieved by working with a diverse community of volunteers, patients, scientists, healthcare professionals, and partner organizations needed to ensure success.

Privacy-Preserving Record Linkage of Deidentified Records Within a Public Health Surveillance System: Evaluation Study.

BACKGROUND: The Australian Collaboration for Coordinated Enhanced Sentinel Surveillance (ACCESS) was established to monitor national testing and test outcomes for blood-borne viruses (BBVs) and sexually transmissible infections (STIs) in key populations. ACCESS extracts deidentified data from sentinel health services that include general practice, sexual health, and infectious disease clinics, as well as public and private laboratories that conduct a large volume of BBV/STI testing. An important attribute of ACCESS is the ability to accurately link individual-level records within and between the participating sites, as this enables the system to produce reliable epidemiological measures. OBJECTIVE: The aim of this study was to evaluate the use of GRHANITE software in ACCESS to extract and link deidentified data from participating clinics and laboratories. GRHANITE generates irreversible hashed linkage keys based on patient-identifying data captured in the patient electronic medical records (EMRs) at the site. The algorithms to produce the data linkage keys use probabilistic linkage principles to account for variability and completeness of the underlying patient identifiers, producing up to four linkage key types per EMR. Errors in the linkage process can arise from imperfect or missing identifiers, impacting the system's integrity. Therefore, it is important to evaluate the quality of the linkages created and evaluate the outcome of the linkage for ongoing public health surveillance. METHODS: Although ACCESS data are deidentified, we created two gold-standard datasets where the true match status could be confirmed in order to compare against record linkage results arising from different approaches of the GRHANITE Linkage Tool. We reported sensitivity, specificity, and positive and negative predictive values where possible and estimated specificity by comparing a history of HIV and hepatitis C antibody results for linked EMRs. RESULTS: Sensitivity ranged from 96% to 100%, and specificity was 100% when applying the GRHANITE Linkage Tool to a small gold-standard dataset of 3700 clinical medical records. Medical records in this dataset contained a very high level of data completeness by having the name, date of birth, post code, and Medicare number available for use in record linkage. In a larger gold-standard dataset containing 86,538 medical records across clinics and pathology services, with a lower level of data completeness, sensitivity ranged from 94% to 95% and estimated specificity ranged from 91% to 99% in 4 of the 6 different record linkage approaches. CONCLUSIONS: This study's findings suggest that the GRHANITE Linkage Tool can be used to link deidentified patient records accurately and can be confidently used for public health surveillance in systems such as ACCESS.

Utilising a Data Capture Tool to Populate a Cardiac Rehabilitation Registry: A Feasibility Study.

BACKGROUND: Clinical registries are effective for monitoring clinical practice, yet manual data collection can limit their implementation and sustainability. The objective of this study was to assess the feasibility of using a data capture tool to collect cardiac rehabilitation (CR) minimum variables from electronic hospital administration databases to populate a new CR registry in Australia. METHODS: Two CR facilities located in Melbourne, Australia participated, providing data on 42 variables including: patient socio-demographics, risk factors and co-morbidities, CR program information (e.g. number of CR sessions), process indicators (e.g. wait time) and patient outcomes (e.g. change in exercise capacity). A pre-programmed, automated data capture tool (GeneRic Health Network Information for the Enterprise [20]: https://www.grhanite.com/) (GRHANITE™) was installed at the sites to extract data available in an electronic format from hospital sites. Additionally, clinicians entered data on CR patients into a purpose-built web-based tool (Research Electronic Data Capture: https://www.project-redcap.org/) (REDCap). Formative evaluation including staff feedback was collected. RESULTS: The GRHANITE™ tool was successfully installed at the two CR sites and data from 176 patients (median age = 67 years, 76% male) were securely extracted between September-December 2017. Data pulled electronically from hospital databases was limited to seven of the 42 requested variables. This is due to CR sites only capturing basic patient information (e.g. socio-demographics, CR appointment bookings) in hospital administrative databases. The remaining clinical information required for the CR registry was collected in formats (e.g. paper-based, scanned or Excel spreadsheet) deemed unusable for electronic data capture. Manually entered data into the web-tool enabled data collection on all remaining variables. Compared to historical methods of data collection, CR staff reported that the REDCap tool reduced data entry time. CONCLUSIONS: The key benefits of a scalable, automated data capture tool like GRHANITE™ cannot be fully realised in settings with under-developed electronic health infrastructure. While this approach remains promising for creating and maintaining a registry that monitors the quality of CR provided to patients, further investment is required in the digital platforms underpinning this approach.

Gathering data for decisions: best practice use of primary care electronic records for research.

In Australia, there is limited use of primary health care data for research and for data linkage between health care settings. This puts Australia behind many developed countries. In addition, without use of primary health care data for research, knowledge about patients' journeys through the health care system is limited. There is growing momentum to establish "big data" repositories of primary care clinical data to enable data linkage, primary care and population health research, and quality assurance activities. However, little research has been conducted on the general public's and practitioners' concerns about secondary use of electronic health records in Australia. International studies have identified barriers to use of general practice patient records for research. These include legal, technical, ethical, social and resource-related issues. Examples include concerns about privacy protection, data security, data custodians and the motives for collecting data, as well as a lack of incentives for general practitioners to share data. Addressing barriers may help define good practices for appropriate use of health data for research. Any model for general practice data sharing for research should be underpinned by transparency and a strong legal, ethical, governance and data security framework. Mechanisms to collect electronic medical records in ethical, secure and privacy-controlled ways are available. Before the potential benefits of health-related data research can be realised, Australians should be well informed of the risks and benefits so that the necessary social licence can be generated to support such endeavours.

Data linkage.

BACKGROUND: Data linkage has been defined as 'the bringing together from two or more different sources, data that relate to the same individual, family, place or event'. Australia is one of few countries that has invested significantly in the creation of data linkage facilities. OBJECTIVE: This paper provides an overview of data linkage and its relevance to general practice research. DISCUSSION: Data linkage enables large-scale studies of whole populations across the healthcare system. Data linkage has been used for studies of health service outcomes and use, epidemiology, and needs analysis. In Australia, there is growing interest in the potential to link data from general practice to other healthcare datasets. This can be achieved through access to Medicare data (Medicare Benefits Schedule and Pharmaceutical Benefits Scheme data) or potentially using data extraction tools to obtain more detailed clinical general practice data. In this article, we discuss issues that relate to privacy and ethical use of data in linkage studies, and provide examples of the types of research performed using this methodological approach nationally and internationally.

Electronic clinical decision support tool for the evaluation of cardiovascular risk in general practice: A pilot study.

BACKGROUND: Cardiovascular disease (CVD) is a major cause of death in Australia. Electronic medical record (EMR)-based clinical decision support (CDS) tools have the potential to support absolute CVD risk (ACVDR) evaluation and management. The objective of this study was to test the acceptability and feasibility of the Treat to Target CVD (T3CVD), an EMR-based CDS tool, for the evaluation of ACVDR in general practice. METHODS: Five general practitioners (GPs) piloted the T3CVD tool in their clinic. Interviews with the clinicians explored the acceptability and feasibility of the T3CVD tool. RESULTS: The T3CVD tool was acceptable and, in the small pilot, was shown to have the capacity to support GPs in ACVDR assessment and management, and to encourage patient participation and motivation. Technical and structural factors important to ensure feasibility of the tool were identified. DISCUSSION: With further development, the T3CVD tool has the potential to improve ACVDR assessment and management in primary care.

Improving the identification of priority populations to increase hepatitis B testing rates, 2012.

BACKGROUND: It is estimated that over 40 % of the 218,000 people with chronic hepatitis B (CHB) in Australia in 2011 are undiagnosed. A disproportionate number of those with undiagnosed infection were born in the Asia-Pacific region. Undiagnosed CHB can lead to ongoing transmission and late diagnosis limits opportunities to prevent progression to hepatocellular carcinoma (HCC) and cirrhosis. Strategies are needed to increase testing for hepatitis B virus (HBV) (including culturally and linguistically diverse communities, Aboriginal and/or Torres Strait Islander (Indigenous) people and people who inject drugs). General practitioners (GPs) have a vital role in increasing HBV testing and the timely diagnosis CHB. This paper describes the impact of a GP-based screening intervention to improve CHB diagnosis among priority populations in Melbourne, Australia. METHODS: A non-randomised, pre-post intervention study was conducted between 2012 and 2013 with three general practices in Melbourne, Australia. Using clinic electronic health records three priority populations known to be at increased CHB risk in Australia (1: Asian-born patients or patients of Asian ethnicity living in Australia; 2: Indigenous people; or 3): people with a history of injecting drugs were identified and their HBV status recorded. A random sample were then invited to attend their GP for HBV testing and/or vaccination. Baseline and follow-up electronic data collection identified patients that subsequently had a consultation and HBV screening test and/or vaccination. RESULTS: From a total of 33,297 active patients, 2674 (8 %) were identified as a priority population at baseline; 2275 (85.1 %) of these patients had unknown HBV status from which 338 (14.0 %) were randomly sampled. One-fifth (n = 73, 21.6 %) of sampled patients subsequently had a GP consultation during the study period; only four people (5.5 %) were subsequently tested for HBV (CHB detected in n = 1) and none were vaccinated against HBV. CONCLUSION: CHB infection is an important long-term health issue in Australia and strategies to increase appropriate and timely testing are required. The study was effective at identifying whether Asian-born patients and patients of Asian had been tested or vaccinated for HBV; however the intervention was not effective at increasing HBV testing.

Analysis of laboratory testing results collected in an enhanced chlamydia surveillance system in Australia, 2008-2010.

BACKGROUND: Chlamydial infection is the most common notifiable disease in Australia, Europe and the US. Australian notifications of chlamydia rose four-fold from 20,274 cases in 2002 to 80,846 cases in 2011; the majority of cases were among young people aged less than 29 years. Along with test positivity rates, an understanding of the number of tests performed and the demographics of individuals being tested are key epidemiological indicators. The ACCESS Laboratory Network was established in 2008 to address this issue. METHODS: The ACCESS Laboratory Network collected chlamydia testing data from 15 laboratories around Australia over a three-year period using data extraction software. All chlamydia testing data from participating laboratories were extracted from the laboratory information system; patient identifiers converted to a unique, non-reversible code and de-identified data sent to a single database. Analysis of data by anatomical site included all specimens, but in age and sex specific analysis, only one testing episode was counted. RESULTS: From 2008 to 2010 a total of 628,295 chlamydia tests were referred to the 15 laboratories. Of the 592,626 individual episodes presenting for testing, 70% were from female and 30% from male patients. In female patients, chlamydia positivity rate was 6.4% overall; the highest rate in 14 year olds (14.3%). In male patients, the chlamydia positivity rate was 9.4% overall; the highest in 19 year olds (16.5%). The most common sample type was urine (57%). In 3.2% of testing episodes, multiple anatomical sites were sampled. Urethral swabs gave the highest positivity rate for all anatomical sites in both female (7.7%) and male patients (14%), followed by urine (7.6% and 9.4%, respectively) and eye (6.3% and 7.9%, respectively). CONCLUSIONS: The ACCESS Laboratory Network data are unique in both number and scope and are representative of chlamydia testing in both general practice and high-risk clinics. The findings from these data highlight much lower levels of testing in young people aged 20 years or less; in particular female patients aged less than 16 years, despite being the group with the highest positivity rate. Strategies are needed to increase the uptake of testing in this high-risk group.

Seamless EMR data access: Integrated governance, digital health and the OMOP-CDM.

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.

An evaluation of existing text de-identification tools for use with patient progress notes from Australian general practice.

INTRODUCTION: Digitized patient progress notes from general practice represent a significant resource for clinical and public health research but cannot feasibly and ethically be used for these purposes without automated de-identification. Internationally, several open-source natural language processing tools have been developed, however, given wide variations in clinical documentation practices, these cannot be utilized without appropriate review. We evaluated the performance of four de-identification tools and assessed their suitability for customization to Australian general practice progress notes. METHODS: Four tools were selected: three rule-based (HMS Scrubber, MIT De-id, Philter) and one machine learning (MIST). 300 patient progress notes from three general practice clinics were manually annotated with personally identifying information. We conducted a pairwise comparison between the manual annotations and patient identifiers automatically detected by each tool, measuring recall (sensitivity), precision (positive predictive value), f1-score (harmonic mean of precision and recall), and f2-score (weighs recall 2x higher than precision). Error analysis was also conducted to better understand each tool's structure and performance. RESULTS: Manual annotation detected 701 identifiers in seven categories. The rule-based tools detected identifiers in six categories and MIST in three. Philter achieved the highest aggregate recall (67%) and the highest recall for NAME (87%). HMS Scrubber achieved the highest recall for DATE (94%) and all tools performed poorly on LOCATION. MIST achieved the highest precision for NAME and DATE while also achieving similar recall to the rule-based tools for DATE and highest recall for LOCATION. Philter had the lowest aggregate precision (37%), however preliminary adjustments of its rules and dictionaries showed a substantial reduction in false positives. CONCLUSION: Existing off-the-shelf solutions for automated de-identification of clinical text are not immediately suitable for our context without modification. Philter is the most promising candidate due to its high recall and flexibility however will require extensive revising of its pattern matching rules and dictionaries.

Will a fee-for-service payment for a young people's health assessment in general practice increase the detection of health risk behaviours and health conditions? Protocol for a cluster randomised controlled trial (RAd Health Trial).

INTRODUCTION: Adolescence is a period of major transition in physical, cognitive, social and emotional development, and the peak time for the onset of mental health conditions, substance use disorders and sexual and reproductive health risks. Prevention and treatment during this time can improve health and well-being now and into the future. However, despite clinical guidelines recommending annual preventive health assessments for young people, health professionals cite lack of consultation time and adequate funding as key barriers. This trial aims to determine whether a specific fee-for-service ('rebate payment') for a young person's health assessment, is effective and cost-effective at increasing the detection and management of health risk behaviours and conditions among young people. METHODS AND ANALYSIS: This cluster randomised controlled trial will be conducted in Australian general practice. 42 general practices (clusters) will be randomly allocated 1:1 to either an intervention arm where general practitioners receive a rebate payment for each annual health assessment undertaken for 14-24-year-olds during a 2 year study period, or a control arm (no rebate). The rebate amount will be based on the Medical Benefits Schedule (Australia's list of health professional services subsidised by the Australian Government) currently available for similar age-based assessments. Our primary outcome will be the annual rate of risk behaviours and health conditions recorded in the patient electronic health record (eg, alcohol/drug use, sexual activity and mental health issues). Secondary outcomes include the annual rate of patient management activities related to health risks and conditions identified (eg, contraception prescribed, sexually transmitted infection tests ordered). A process evaluation will assess acceptability, adoption, fidelity and sustainability of the rebate; an economic evaluation will assess its cost-effectiveness. Analyses will be intention-to-treat. ETHICS AND DISSEMINATION: Ethics approval has been obtained from University of Melbourne Human and Research Ethics Committee (2022-23435-29990-3). Findings will be published in peer-reviewed journals. TRIAL REGISTRATION NUMBER: ACTRN12622000114741.

Assessment of a primary care e-support package of automated case finding, simplified treatment algorithm and decision support to increase hepatitis B treatment uptake in primary care clinics in Australia (SIMPLY-B Study): protocol for a pilot evaluation.

INTRODUCTION: Despite the availability of effective, subsidised hepatitis B treatment, linkage to care and treatment rates remain very low globally. In Australia, specially trained primary care physicians (general practitioner, GPs) can prescribe hepatitis B treatment, however, most hepatitis B care occurs in specialist clinics. Increasing hepatitis B management by GPs in primary care clinics is essential to achieve national hepatitis B linkage to care and treatment targets by 2030.This pilot study determines the feasibility, acceptability and effectiveness of Simply B, a novel GP hepatitis B e-support package designed to increase hepatitis B management by GPs in primary care clinics. METHODS AND ANALYSIS: This study will be conducted in three parts:Part A: A prospective open-label pilot intervention study, comparing the proportion of people with hepatitis B who are managed by their GP in primary care clinics before, 12 months and 24 months after implementation of the Simply B electronic hepatitis B support package.Part B: A nested qualitative health services feasibility study using semistructured interviews and thematic analysisPart C: Cost-effectiveness analysis. ETHICS AND DISSEMINATION: This study has received ethics approval by St Vincent's Hospital. Data management and analysis will be centralised through the Department of Gastroenterology, St Vincent's Hospital. TRIAL REGISTRATION NUMBER: NCT05614466.

Mapping pathways to public understanding of climate science.

Climate communication is a thriving research area spanning science, social science, and humanities. The field has grown explosively in recent years, necessitating increased efforts to synthesize and make sense of the resulting profusion of studies. To support scholars navigating this quickly evolving knowledge domain, we developed a knowledge map of the climate communication research landscape by applying network analysis and data visualization techniques to the metadata from 2995 publications on climate communication. The map reveals a dense web of connections among five distinct knowledge communities, indicating a tightly knit and intensely collaborative knowledge domain, and suggests new avenues for the application of climate communication knowledge, in particular to support climate services and co-production. The climate communication knowledge map answers the call for synoptic perspectives on areas of science communication while demonstrating a novel visual approach to knowledge synthesis for science communication domains.

Strengthening Care for Children (SC4C): protocol for a stepped wedge cluster randomised controlled trial of an integrated general practitioner-paediatrician model of primary care.

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-<18 years) GP appointments that result in a hospital referral, compared with the control period. Secondary outcomes include GP quality of care; GP experience and confidence in providing paediatric care; family trust in and preference for GP care; and the sustainability of the intervention. An implementation evaluation will assess the model to inform acceptability, adaptability, scalability and sustainability, while a health economic evaluation will measure the cost-effectiveness of the intervention. ETHICS AND DISSEMINATION: Human research ethics committee (HREC) approval was granted by The Royal Children's Hospital Ethics Committee in August 2020 (Project ID: 65955) and site-specific HRECs. The investigators (including Primary Health Network partners) will communicate trial results to stakeholders and participating GPs and general practice clinics via presentations and publications. TRIAL REGISTRATION NUMBER: Australia New Zealand Clinical Trials Registry 12620001299998.

BioGrid Australia and GRHANITE™: privacy-protecting subject matching.

BioGrid Australia provide infrastructure for research currently spanning 16 hospital-based clinical institutions and 50 databases across Victoria, Australia. To-date BioGrid have utilised a probabilistic record linkage engine (Sun Oracle Java CAPS eIndex) that utilises patient identifiers (albeit in a secure manner) during record linkage. BioGrid are now incorporating privacy-protecting record linkage technology from the University of Melbourne Rural Health Academic Centre (GRHANITE™). For the first time in Australia, the GRHANITE™technology is allowing primary care data linkage projects to happen on a large scale (70 sites, 200 planned to date). By utilising GRHANITE™privacy-protecting record linkage technologies, BioGrid are now able to overcome the privacy issues inherent in linking data across national jurisdictional boundaries. By utilising GRHANITE™privacy-protecting record linkage technologies all inter-jurisdictional public health and hospital clinical data collected by BioGrid can be systematically linked to primary care data for research for the first time. This paper describes the architecture of the combined BioGrid and GRHANITE™systems, provides evidence of the efficacy of the linkage technologies and heralds the start of a new era in privacy-protected, record linked research in Australia.

Prevalence and Risk of Violent Ideation and Behavior in Serious Mental Illnesses: An Analysis of 63,572 Patient Records.

Research has consistently demonstrated that people diagnosed with serious mental illness (SMI) are at increased risk for violent ideation and behavior (VIB) and that this is especially the case for SMI patients with comorbid substance use disorders (SUD). Despite this, what is still largely unknown is the relative prevalence of VIB across diagnostic categories, whether the rates of VIB in SMI groups exceed the rates observed in people with SUD only, and which demographic factors increase the likelihood of VIB under different circumstances for people with SMI. To address these questions, we analyzed the intake records of 63,572 patients diagnosed with SMIs (i.e., schizoaffective disorder, schizophrenia, bipolar disorder, and unipolar depression), substance use disorders, and non-SMI psychiatric disorders. Raw prevalence rates for a combined metric of VIB were established and compared for each group, and a series of logistic regression analyses were performed to estimate how various demographic factors influenced the likelihood of VIB endorsement in each study group. Our results revealed that (a) patients with SMI conditions had higher rates of VIB than both patients with non-SMI psychopathology and those with substance use disorders only; (b) patients with SMI and comorbid substance use pathology were responsible for the majority of VIB within each SMI condition; and (c) men with SMI conditions had higher prevalence rates of VIB than females. In addition, we found that for every SMI diagnosis, comorbid substance use disorders and younger age were related to greater risk for VIB, and where race and gender were found to significantly alter the likelihood of VIB endorsement, African American status and female gender were independently related to greater risk. The implications of these findings and directions for future research are discussed.