Risk of behavioural and developmental difficulties in early childhood in the Australian Capital Territory.

AIM: We aimed to estimate the prevalence of risk for developmental and behavioural problems for children in their first year of full-time primary education in the Australian Capital Territory (ACT). METHODS: We conducted an analysis of the 2014-2017 Kindergarten Health Check (KHC), an annual series of complete enumeration surveys of all children in their first year of full-time primary education in the ACT. Risk for developmental and behavioural problems was determined using the Parents' Evaluation of Developmental Status (PEDS) questionnaire. RESULTS: 19 414 children (mean age 5.56 years; 51.4% boys; 2.3% Aboriginal and Torres Strait Islander; 18.4% quintile of greatest relative disadvantage) who participated in the 2014-2017 KHC were included in the study (87%). More than half of ACT children in their first year of primary education had low/no developmental risk identified through the PEDS questionnaire, with 1 in 10 at high risk. CONCLUSIONS: Those more likely to have a high risk PEDS score were boys, those from the areas experiencing relative disadvantage, and Aboriginal and Torres Strait Islander children. While we can identify children at risk through screening, the greater challenge remains to identify and address the underlying causes of healthy inequalities, even within highly socioeconomically advantaged communities.

Parents' perceptions of their child's weight among children in their first year of primary school: a mixed-methods analysis of an Australian cross-sectional (complete enumeration) study.

BACKGROUND/OBJECTIVES: To describe trends in overweight/obesity in early childhood for all children and those whose parents are concerned about their weight. To describe parents' perceptions of their child's weight and differences by their child's anthropometric and sociodemographic factors. SUBJECTS/METHODS: Analysis of the Kindergarten Health Check, a survey of all children enrolled in their first year of primary education in the Australian Capital Territory. Analysis of detailed data for 2014-2017, including qualitative analysis of parents' comments on weight, and trends for 2001-2017. RESULTS: 71,963 children participated in the survey between 2001 and 2017 (20,427 between 2014 and 2017). The average age of children (2001-2017) was 5 years and 9.6 months at the time of their physical health check. 2377 children (3.5%) were classified as obese based on measured body mass index (BMI) between 2001 and 2017, and a further 7766 (11.6%) overweight. Similar proportions were seen for 2014-2017. Among children with overweight/obesity in 2014-2017, 86.4% of parents (2479/2868) described their children's weight as healthy and 13.3% (382/2868) as overweight/obese. Just 11.5% (339/2946) of parents whose children were later measured with overweight/obesity identified having a concern about their child's weight. Parental comments varied widely and were often incongruent with the known health risks associated with their child's measured BMI. Comments from parents whose children were measured as obese often were normalising e.g., "born big, always big. Definitely NOT overweight, just bigger all over", whilst parents of children in the healthy range expressed concerns about underweight. CONCLUSION: Parents do not accurately perceive their child's weight and few document concerns, even among children measuring in the obese BMI category. This lack of concern makes early interventions challenging as parents are in the "pre-contemplative" stage of behaviour change and may see public health campaigns or clinicians' attempts to address their child's weight as irrelevant or unhelpful.

Use of health and aged care services in Australia following hospital admission for myocardial infarction, stroke or heart failure.

BACKGROUND: Cardiovascular diseases (CVD), including myocardial infarction (MI), stroke and heart failure (HF) are the leading cause of death amongst the older population worldwide. The aim of this study is to investigate trajectories of use of health and aged care services after hospital admission for MI, stroke or HF among community-dwelling people not previously receiving aged care services. METHODS: The study population comprised people aged 65+ years from the 45 and Up Study with linked records for hospital stays, aged care services and deaths for the period 2006-14. Among those with an index hospital admission for MI, stroke or HF, we developed Sankey plots to describe and visualize sequences and trajectories of service use (none, re-hospitalization, community care, residential care, death) in the 12 months following discharge. We used Cox proportional hazards models to estimate hazard ratios (HRs), for commencing community care and entering residential care (and the other outcomes) within 3, 6 and 12 months, compared to a matched group without MI, stroke or HF. RESULTS: Two thousand six hundred thirty-nine, two thousand five hundred and two thousand eight hundred seventy-three people had an index hospitalization for MI, stroke and HF, respectively. Within 3 months of hospital discharge, 16, 32 and 29%, respectively, commenced community care (multivariable-adjusted HRs: 1.26 (95%CI:1.18-1.35), 1.53 (95%CI:1.44-1.64) and 1.39 (95%CI:1.32-1.48)); and 7, 18 and 14%, respectively, entered residential care (HRs: 1.25 (95%CI:1.12-1.41), 2.65 (95%CI:2.42-2.91) and 1.50 (95%CI:1.37-1.65)). Likewise, 26, 15 and 28%, respectively, were rehospitalized within 3 months following discharge (multivariable-adjusted HRs: 4.78 (95%CI:4.31-5.32), 3.26 (95%CI:2.91-3.65) and 4.94 (95%CI:4.47-5.46)). CONCLUSIONS: Older people hospitalized for major CVD may be vulnerable to transition-related risks and have poor health trajectories, thus emphasizing the value of preventing such events and care strategies targeted towards this at-risk group.

Sexual assault and harassment of doctors, by doctors: a qualitative study.

CONTEXT: Although sexual harassment frequently occurs in medical education and medical workplaces, doctors who have been sexually harassed or assaulted by other doctors remain a largely invisible population. This study aimed to identify, using personal accounts, the impact on doctors of sexual harassment and assault by doctors in the workplace. METHODS: This narrative study used in-depth interviews, legal reports and victim impact statements, tracing trajectories from the event's pre-history to its aftermath and impact on professional practice. Participants were six Australian women doctors who had been subjected to one or more non-consensual sexual acts through coercion or intimidation by another doctor in their working environments, within hospital training programmes. RESULTS: All women identified long-term personal and professional impacts of their experience. Three women had never reported the abuse. The meaning and impact of sexual abuse for the doctors followed a trajectory with discrete phases: prelude, assault, limbo, exposure and aftermath. Discounting the event and its impacts, and returning to the workplace were characterised as 'being professional'. Those who sought legal restitution said it damaged their personal well-being and their standing among fellow doctors. DISCUSSION: Understanding the phases of experience of abuse enables the development of effective interventions for different phases. Interventions to minimise the risk of occurrence of sexual abuse must be distinguished from interventions to increase reporting rates, and interventions to mitigate harm and impact on victims' futures. Idealised notions of professionalism can act as obstacles to doctors responding to sexual abuse.

Overcoming the data drought: exploring general practice in Australia by network analysis of big data.

OBJECTIVES: To investigate the organisation and characteristics of general practice in Australia by applying novel network analysis methods to national Medicare claims data. DESIGN: We analysed Medicare claims for general practitioner consultations during 1994-2014 for a random 10% sample of Australian residents, and applied hierarchical block modelling to identify provider practice communities (PPCs). PARTICIPANTS: About 1.7 million patients per year. MAIN OUTCOME MEASURES: Numbers and characteristics of PPCs (including numbers of providers, patients and claims), proportion of bulk-billed claims, continuity of care, patient loyalty, patient sharing. RESULTS: The number of PPCs fluctuated during the 21-year period; there were 7747 PPCs in 2014. The proportion of larger PPCs (six or more providers) increased from 32% in 1994 to 43% in 2014, while that of sole provider PPCs declined from 50% to 39%. The median annual number of claims per PPC increased from 5000 (IQR, 40-19 940) in 1994 to 9980 (190-23 800) in 2014; the proportion of PPCs that bulk-billed all patients was lowest in 2004 (21%) and highest in 2014 (29%). Continuity of care and patient loyalty were stable; in 2014, 50% of patients saw the same provider and 78% saw a provider in the same PPC for at least 75% of consultations. Density of patient sharing in a PPC was correlated with patient loyalty to that PPC. CONCLUSIONS: During 1994-2014, Australian GP practice communities have generally increased in size, but continuity of care and patient loyalty have remained stable. Our novel approach to the analysis of routinely collected data allows continuous monitoring of the characteristics of Australian general practices and their influence on patient care.

Experiencing integration: a qualitative pilot study of consumer and provider experiences of integrated primary health care in Australia.

BACKGROUND: The terms integration and integrated care describe the complex, patient-centred strategies to improve coordination of healthcare services. Frameworks exist to conceptualise these terms, but these have been developed from a professional viewpoint. The objective of this study was to explore consumers' and providers' concepts, expectations and experience of integrated care. A key focus was whether frameworks developed from a professional perspective are effective models to explore people's experiences. METHODS: A qualitative pilot study was undertaken at one Australian multidisciplinary primary health care centre. Semi-structured interviews were conducted with consumers (N = 19) and staff (N = 10). Data were analysed using a framework analysis approach. RESULTS: Consumers' experience of integrated care tended to be implicit in their descriptions of primary healthcare experiences more broadly. Experiences related to the typologies involved clinical and functional integration, such as continuity of providers and the usefulness of shared information. Staff focused on clinical level integration, but also talked about a cultural shift that demonstrated normative, professional and functional integration. CONCLUSIONS: Existing frameworks for integration have been heavily influenced by the provider and organisational perspectives. They are useful for conceptualising integration from a professional perspective, but are less relevant for consumers' experiences. Consumers of integrated primary health care may be more focussed on relational aspects of care and outcomes of care.

Sociodemographic and health characteristics, rather than primary care supply, are major drivers of geographic variation in preventable hospitalizations in Australia.

BACKGROUND: Geographic rates of preventable hospitalization are used internationally as an indicator of accessibility and quality of primary care. Much research has correlated the indicator with the supply of primary care services, yet multiple other factors may influence these admissions. OBJECTIVE: To quantify the relative contributions of the supply of general practitioners (GPs) and personal sociodemographic and health characteristics, to geographic variation in preventable hospitalization. METHODS: Self-reported questionnaire data for 267,091 participants in the 45 and Up Study, Australia, were linked with administrative hospital data to identify preventable hospitalizations. Multilevel Poisson models, with participants clustered in their geographic area of residence, were used to explore factors that explain geographic variation in hospitalization. RESULTS: GP supply, measured as full-time workload equivalents, was not a significant predictor of preventable hospitalization, and explained only a small amount (2.9%) of the geographic variation in hospitalization rates. Conversely, more than one-third (36.9%) of variation was driven by the sociodemographic composition, health, and behaviors of the population. These personal characteristics explained a greater amount of the variation for chronic conditions (37.5%) than acute (15.5%) or vaccine-preventable conditions (2.4%). CONCLUSIONS: Personal sociodemographic and health characteristics, rather than GP supply, are major drivers of preventable hospitalization. Their contribution varies according to condition, and if used for performance comparison purposes, geographic rates of preventable hospitalization should be reported according to individual condition or potential pathways for intervention.