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Gestational Diabetes Mellitus (GDM) increases the risk of type 2 diabetes. A register can be used to follow-up high risk women for early intervention to prevent progression to type 2 diabetes. We evaluate the performance of the world's first national gestational diabetes register. Observational study that used data linkage to merge: (1) pathology data from the Australian states of Victoria (VIC) and South Australia (SA); (2) birth records from the Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM, VIC) and the South Australian Perinatal Statistics Collection (SAPSC, SA); (3) GDM and type 2 diabetes register data from the National Gestational Diabetes Register (NGDR). All pregnancies registered on CCOPMM and SAPSC for 2012 and 2013 were included-other data back to 2008 were used to support the analyses. Rates of screening for GDM, rates of registration on the NGDR, and rates of follow-up laboratory screening for type 2 diabetes are reported. Estimated GDM screening rates were 86% in SA and 97% in VIC. Rates of registration on the NGDR ranged from 73% in SA (2013) to 91% in VIC (2013). During the study period rates of screening at six weeks postpartum ranged from 43% in SA (2012) to 58% in VIC (2013). There was little evidence of recall letters resulting in screening 12 months follow-up. GDM Screening and NGDR registration was effective in Australia. Recall by mail-out to young mothers and their GP's for type 2 diabetes follow-up testing proved ineffective.

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.

During the termination of the last glacial period the western U.S. experienced exceptionally wet conditions, driven by changes in location and strength of the mid-latitude winter storm track. The distribution of modern winter precipitation is frequently characterized by a north-south wet/dry dipole pattern, controlled by interaction of the storm track with ocean-atmosphere conditions over the Pacific and Atlantic Oceans. Here we show that a dipole pattern of similar geographic extent persisted and switched sign during millennial-scale abrupt climate changes of the last deglaciation, based on a new lake level reconstruction for pluvial Lake Chewaucan (northwestern U.S.), and a compilation of regional paleoclimate records. This suggests the dipole pattern is robust, and one mode may be favored for centuries, thereby creating persistent contrasting wet/dry conditions across the western U.S. The TraCE-21k climate model simulation shows an equatorward enhancement of winter storm track activity in the northeastern Pacific, favoring wet conditions in southwestern U.S. during the second half of Heinrich Stadial 1 (16.1–14.6 ka) and consistent with paleoclimate evidence. During the Bølling/Allerød (14.6–12.8 ka), the northeastern Pacific storm track contracted poleward, consistent with wetter conditions concentrated poleward toward the northwest U.S.

People with a history of injecting drug use are a priority for eliminating blood-borne viruses and sexually transmissible infections. Identifying them for disease surveillance in electronic medical records (EMRs) is challenged by sparsity of predictors. This study introduced a novel approach to phenotype people who have injected drugs using structured EMR data and interactive human-in-the-loop methods. We iteratively trained random forest classifiers removing important features and adding new positive labels each time. The initial model achieved 92.7% precision and 93.5% recall. Models maintained >90% precision and recall after nine iterations, revealing combinations of less obvious features influencing predictions. Applied to approximately 1.7 million patients, the final model identified 128,704 (7.7%) patients as potentially having injected drugs, beyond the 50,510 (2.9%) with known indicators of injecting drug use. This process produced explainable models that revealed otherwise hidden combinations of predictors, offering an adaptive approach to addressing the inherent challenge of inconsistently missing data in EMRs.

New biomedical prevention interventions make the control or elimination of some blood-borne viruses (BBVs) and sexually transmissible infections (STIs) increasingly feasible. In response, the World Health Organization and governments around the world have established elimination targets and associated timelines. To monitor progress toward such targets, enhanced systems of data collection are required. This paper describes the Australian Collaboration for Coordinated Enhanced Sentinel Surveillance (ACCESS). This study aims to establish a national surveillance network designed to monitor public health outcomes and evaluate the impact of strategies aimed at controlling BBVs and STIs. ACCESS is a sentinel surveillance system comprising health services (sexual health clinics, general practice clinics, drug and alcohol services, community-led testing services, and hospital outpatient clinics) and pathology laboratories in each of Australia's 8 states and territories. Scoping was undertaken in each jurisdiction to identify sites that provide a significant volume of testing or management of BBVs or STIs or to see populations with particular risks for these infections (\"priority populations\"). Nationally, we identified 115 health services and 24 pathology laboratories as relevant to BBVs or STIs; purposive sampling was undertaken. As of March 2018, we had recruited 92.0% (104/113) of health services and 71% (17/24) of laboratories among those identified as relevant to ACCESS. ACCESS is based on the regular and automated extraction of deidentified patient data using specialized software called GRHANITE, which creates an anonymous unique identifier from patient details. This identifier allows anonymous linkage between and within participating sites, creating a national cohort to facilitate epidemiological monitoring and the evaluation of clinical and public health interventions. Between 2009 and 2017, 1,171,658 individual patients attended a health service participating in ACCESS network comprising 7,992,241 consultations. Regarding those with unique BBV and STI-related health needs, ACCESS captured data on 366,441 young heterosexuals, 96,985 gay and bisexual men, and 21,598 people living with HIV. ACCESS is a unique system with the ability to track efforts to control STIs and BBVs-including through the calculation of powerful epidemiological indicators-by identifying response gaps and facilitating the evaluation of programs and interventions. By anonymously linking patients between and within services and over time, ACCESS has exciting potential as a research and evaluation platform. Establishing a national health surveillance system requires close partnerships across the research, government, community, health, and technology sectors. DERR1-10.2196/11028.

Intensive insulin treatment effectively delays the onset and slows the progression of microvascular complications in insulin-dependent diabetes mellitus (IDDM). Variable adherence to insulin treatment is thought to contribute to poor glycaemic control, diabetic ketoacidosis, and brittle diabetes in adolescents and young adults with IDDM. We assessed the association between the prescribed insulin dose and the amount dispensed from all community pharmacies with the Diabetes Audit and Research in Tayside Scotland (DARTS) database. We studied 89 patients, mean age 16 (SD 7) years, diabetes duration 8 (4) years, and glycosylated haemoglobin (HbA 1c) 8·4 (1·9)%, who attended a teaching hospital paediatric or young-adult diabetes clinic in 1993 and 1994. The medically recommended insulin dose and cumulative volume of insulin prescriptions supplied were used to calculate the days of maximum possible insulin coverage per annum, expressed as the adherence index. Associations between glycaemic control (HbA 1c), episodes of diabetic ketoacidosis, and all hospital admissions for acute complications and the adherence index were modelled. Insulin was prescribed at 48 (19) IU/day and mean insulin collected from pharmacies was 58 (25) IU/day. 25 (28%) of the 89 patients obtained less insulin than their prescribed dose (mean deficit 115 [68; range 9–246] insulin days/annum). There was a significant inverse association between HbA 1c and the adherence index (R 2 =0·39; p<0·001). In the top quartile (HbA 1c≥10%), 14 (64%) of individuals had an adherence index suggestive of a missed dose of insulin (mean deficit 55 insulin days/annum). There were 36 admissions for complications related to diabetes. The adherence index was inversely related to hospital admissions for diabetic ketoacidosis (p<0·001) and all hospital admissions related to acute diabetes complications (p=0·008). The deterioration in glycaemic control observed in patients aged 10–20 years was associated with a significant reduction (p=0·01) in the adherence index. We found direct evidence of poor compliance with insulin therapy in young patients with IDDM. We suggest that poor adherence to insulin treatment is the major factor that contributes to long-term poor glycaemic control and diabetic ketoacidosis in this age group.

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.

Background This study explored the feasibility of integrating a clinical decision support tool into general practice clinical management software in Australia to prompt for alcohol screening among patients who are pregnant or planning a pregnancy. The study aimed to increase understanding of what is an appropriate and acceptable clinical decision support tool, the circumstances when a prompt to use such a screening tool should occur, and the barriers and enablers of successful implementation. Methods This feasibility study employed a mixed methods approach and purposive sampling to identify key stakeholders to interview. Participants included vendors of clinical software used in Australian general practice, clinicians in general practice, and relevant others. Data from a literature review and 23 interviews were analysed leading to recommendations which were ‘sense-tested’ by an additional 22 stakeholders. Results Although there are at least 18 clinical software packages used in Australian general practice, it is feasible to integrate an alcohol screening tool for pregnancy into software for the majority of general practices in Australia. The AUDIT-C alcohol screening tool for pregnancy was widely accepted as suitable for such a purpose. Clinicians suggested the greatest barriers to screening were lack of time within antenatal consultations and insufficient remuneration for longer consultations. Many clinicians saw opportunity for introducing a multifunctional antenatal tool that could incorporate screening and clinical decision support for alcohol, tobacco and other substance use, mental health, domestic and family violence and potentially other areas informing healthy pregnancy. It could also be used opportunistically for preconception screening and counselling. Deployment of the tool could be supported by an education campaign from professional associations. Conclusion The integration of a tool for screening for alcohol use among women who are pregnant or planning pregnancy into general practice clinical software is feasible; however, a multifunctional antenatal screening tool, incorporating other psychosocial elements, was considered more useful than a stand-alone alcohol screening tool. Codesign is needed with vendors and end-users to develop an acceptable tool that can be widely implemented. Issues with GP renumeration need also to be addressed to encourage alcohol screening pre-pregnancy and in the early months of pregnancy.

Purpose - The purpose of this paper is to explore risk and protective factors associated with suicidal ideation among law enforcement personnel.Design methodology approach - The methodology employed is based on the \"Best Evidence Synthesis\" approach, whereby researchers systematically examine and integrate the most empirically sound available research on the topic under investigation.Findings - Results of studies showed that the interaction of multiple risk factors had a cumulative effect in increasing the risk for suicidal ideation. In total, five prominent aspects of policing were associated with risk for suicidal ideation: organizational stress; critical incident trauma; shift work; relationship problems; and alcohol use and abuse. Studies also indicated that protective factors and preventative measures had stress-buffering effects which decreased the impact of police stressors.Research limitations implications - The model is limited because few studies have employed methodologically-sound research designs to test risk and protective factors related to police suicide. This conceptual overview may facilitate theory development and provide directions for future research.Practical implications - Law enforcement agencies which implement programs that assist police personnel in developing active coping styles, identify and access available social support systems, as well as utilize community-based services may decrease risk for suicidal ideation. This review provides practical applications for law enforcement training, education, and program development.Originality value - The paper represents the most recent review of risk and protective factors related to suicidal ideation among police personnel. This integration of research provides police practitioners with an evidence-based ecological framework that can be applied universally in police management settings.

ObjectivesThe objective of this study was to understand primary care clinician perspectives on a novel linked health data system to facilitate diabetes prevention for individuals with a history of gestational diabetes mellitus (GDM). We used the conceptual example of linking the National Gestational Diabetes Register with primary care electronic health records to understand clinicians’ views on potential implementation.DesignA qualitative study of semistructured interviews with primary care clinicians.SettingAustralian primary care.ParticipantsPrimary care clinicians (n=14). Inclusion criteria were: general practitioners (GPs), practice nurses and/or diabetes educators working in primary care in Australia, and seeing individuals with a history of GDM; aged 18 years and over; and willing to voluntarily contribute to the project. There were no exclusion criteria.ResultsClinicians’ views on acceptability, feasibility and utility were characterised by realistic optimism for a linked data system to improve GP workflow and patient outcomes. Clinicians noted existing pressures on primary care and patient concerns regarding confidentiality and privacy, and that these factors should be considered in the development process. Clinicians envisaged three functions for their clinical management systems: (1) automatically updating a patient’s past history; (2) generating actionable alerts and (3) generating recall lists.DiscussionPrimary care clinicians were unanimously supportive of a linked health data system to facilitate diabetes prevention. Consistent with previous studies, we identified the key clinician-related enabler as the integration into existing GP workflows to facilitate pro-active clinical care. Point-of-care tools and preventative care consultations could increase the uptake of screening and provide opportunities for patient education post partum.ConclusionIn combination with effective prevention programmes, and health policy and system supports, linked health data systems could be part of the equation for type 2 diabetes prevention for individuals with a history of GDM. Larger acceptability, feasibility, co-design and implementation studies are recommended.