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Background: The accessibility to affordable primary healthcare services contributes to population health and health equity. A key aspect to accessibility is the geographical distribution of primary healthcare services. Limited studies have assessed the nationwide spatial distribution of bulk billing-only medical practices or 'no-fee' services. The aim of this study was to provide a nationwide approximation of bulk billing-only services and evaluate the socio-demographic status and population characteristics in relation to the distribution of bulk billing-only GP services. Methods: The methodology in this study used Geographic Information System (GIS) technology to map the locations of all bulk bulking-only medical practices collected in mid-2020 and linked this with population data. The population data and practice locations were analysed at the level of Statistical Areas Level 2 (SA2) regions and used the most recent Census data. Results: The study sample included (n = 2095) bulk billing-only medical practice locations. The nationwide average Population-to-Practice (PtP) ratio was 1 practice to 8529 people for regions with access to bulk billing-only practice, and 57.4% of the Australian population lives within an SA2 that has access to at least one bulk billing-only medical practices. No significant associations were identified between practice distribution and area socio-economic status. Conclusion: The study identified areas with low access to affordable GP services, with many SA2 regions having no access to bulk billing-only practices. Findings also indicate that there was no association between area socio-economic status and the distribution of bulk billing-only services. Inadequate subsidisation of the Medicare rebate threatens the survival of bulk billing only GP services. Little is known of the socio-economic status of bulk billing only practice localities and whether they target disadvantaged populations. This research provides a current estimation of the distribution of bulk billing only GP services in Australia in relation to surrounding population socio-economic demographics. [ABSTRACT FROM AUTHOR]

Aims: To describe the involvement and need for specialists in special needs dentistry (SND) in the multidisciplinary management of patients and to characterize the complexity of patients with special health care needs. Methods: Referrals for SND review from the Fiona Stanley Hospital head and neck cancer (HNC) multidisciplinary team between January 1 and December 31, 2019 were screened. Data recorded included demographic information, medical history, dental status, and dental treatment provided prior to HNC management. Results: In total 127 patients were referred to the SND clinic in 2019 of which 89.0% were males and 74.8% were aged 50–79. The mean waiting time for SND review was 19.6 days. On average patients had a decayed, missing, filled tooth (DMFT) score of 20.3. During the study period 407 extractions and 30 restorations were completed. Seventeen patients (13.4%) had all their teeth removed prior to HNC management. The majority of patients (79.6%) were categorized as either moderate or severe complexity. Increasing complexity was seen in older age groups. Conclusions: Significant oral disease is seen in patients with HNC often requiring extensive dental treatment. Complexity is seen in patients requiring multidisciplinary care however characteristics that constitute complexity are varied given the spectrum encompassing 'special needs'. [ABSTRACT FROM AUTHOR]

Dental caries remains the most common chronic disease in childhood, affecting almost half of all children globally. Dental care and examination of children living in remote and rural areas is an ongoing challenge that has been compounded by COVID. The development of a validated system with the capacity to screen large numbers of children with some degree of automation has the potential to facilitate remote dental screening at low costs. In this study, we aim to develop and validate a deep learning system for the assessment of dental caries using color dental photos. Three state-of-the-art deep learning networks namely VGG16, ResNet-50 and Inception-v3 were adopted in the context. A total of 1020 child dental photos were used to train and validate the system. We achieved an accuracy of 79% with precision and recall respectively 95% and 75% in classifying 'caries' versus 'sound' with inception-v3. [ABSTRACT FROM AUTHOR]

Objectives: It is well known that there are associations between overall health, age, socioeconomic status and rural residency. The objective of this study was to determine the distribution of Australia's aged population by socioeconomic status, as well as remoteness. Methods: The study employed the Australian Statistical Geography Standard (Statistical Area Level 1 and Remoteness Areas). The database of the geographic boundaries was integrated into the ageing population and socioeconomic data using the Geographic Information System. The socioeconomic data was analysed through the Index of Relative Socioeconomic Disadvantage. Results: Over a decade, the older population in Australia has increased noticeably. In 2016, there was a high percentage of older people (≥65 years) in Tasmania (Tas), 19%, while the lowest percentage was recorded in the Northern Territory (NT), 7%. Across the country, Tasmania had the highest percentage of older citizens living in the most disadvantaged areas since 2006, with 48% recorded in 2016. There was an association between the remoteness areas and the education and income levels of the ageing cohort. However, this association differed between the states and territories. This socioeconomic gap becomes more evident in the very remote areas of the country. Conclusions: The ageing population in Australia is increasing rapidly; this was associated with an evolving socioeconomic disparity among this ageing society. Our results demonstrated that socioeconomic inequalities were to be found among the older people based on their distribution over the remoteness areas in Australia. This information should be used to target healthcare and ageing policies that meet the specific needs of older people. [ABSTRACT FROM AUTHOR]