Search

Background: Based on the early international COVID-19 experience, it was anticipated that intensive care services and workforces in Australia would be placed under similar pressure. While surge capacity of medical and nursing workforces was estimated, little was known about baseline allied health staffing, making it difficult to estimate surge capacity and coordinate planning. Objectives: The purpose of this study was to (i) capture baseline allied health staffing levels in Australian adult intensive care units (ICUs) prior to the COVID-19 pandemic emergence in Australia and (ii) describe the allied health pandemic planning and surge response in Australian ICUs during the early waves of the pandemic. Methods: This was a cross-sectional, investigator-devised, prospective survey study. The survey was administered via the national chief allied health network to a convenience sample of senior ICU allied health clinicians at hospitals throughout Australia. Results: A total of 40 responses were received from tertiary and metropolitan hospitals; 12 (30%) physiotherapists and eight (20%) occupational therapists were the most frequent respondents. Prior to the COVID-19 pandemic, 28 (70%) allied health respondents had a mean (interquartile range) of 1.74 (2.00) full-time equivalent staff designated to the ICU, where these ICUs had a mean of 21.53 (15.00) ventilator beds. Few respondents serviced their ICU on a referral-only basis and did not have dedicated ICU full-time equivalent (12; 20%). Surge planning was mostly determined by discussion within the ICU, allied health department, and/or respective disciplines. This approach meant that allied health staffing and associated decision-making was ad hoc at a local level. Conclusions: The baseline rate of allied health coverage in Australian ICUs remains unknown, and the variability across allied health and within the specific disciplines is undetermined. Further research infrastructure to capture ICU allied health workforce dat

Background: Based on the early international COVID-19 experience, it was anticipated that intensive care services and workforces in Australia would be placed under similar pressure. While surge capacity of medical and nursing workforces was estimated, little was known about baseline allied health staffing, making it difficult to estimate surge capacity and coordinate planning. Objectives: The purpose of this study was to (i) capture baseline allied health staffing levels in Australian adult intensive care units (ICUs) prior to the COVID-19 pandemic emergence in Australia and (ii) describe the allied health pandemic planning and surge response in Australian ICUs during the early waves of the pandemic. Methods: This was a cross-sectional, investigator-devised, prospective survey study. The survey was administered via the national chief allied health network to a convenience sample of senior ICU allied health clinicians at hospitals throughout Australia. Results: A total of 40 responses were received from tertiary and metropolitan hospitals; 12 (30%) physiotherapists and eight (20%) occupational therapists were the most frequent respondents. Prior to the COVID-19 pandemic, 28 (70%) allied health respondents had a mean (interquartile range) of 1.74 (2.00) full-time equivalent staff designated to the ICU, where these ICUs had a mean of 21.53 (15.00) ventilator beds. Few respondents serviced their ICU on a referral-only basis and did not have dedicated ICU full-time equivalent (12; 20%). Surge planning was mostly determined by discussion within the ICU, allied health department, and/or respective disciplines. This approach meant that allied health staffing and associated decision-making was ad hoc at a local level. Conclusions: The baseline rate of allied health coverage in Australian ICUs remains unknown, and the variability across allied health and within the specific disciplines is undetermined. Further research infrastructure to capture ICU allied health workforce dat

BACKGROUND: Osteoarthritis (OA) is a chronic, progressive condition that can be effectively managed via conservative treatments including exercise, weight management and education. Offering these treatments contemporaneously and digitally may increase adherence and engagement due to the flexibility and cost-effectiveness of digital program delivery. The objective of this review was to summarise the characteristics of current digital self-management interventions for individuals with OA and synthesise adherence and attrition outcomes. METHODS: Electronic databases were searched for randomised controlled trials utilising digital self-management interventions in individuals with OA. Two reviewers independently screened the search results and extracted data relating to study characteristics, intervention characteristics, and adherence and dropout rates. RESULTS: Eleven studies were included in this review. Intervention length ranged from 6 weeks to 9 months. All interventions were designed for individuals with OA and mostwere multi-component and were constructed around physical activity. The reporting of intervention adherence varied greatly between studies and limited the ability to form conclusions regarding the impact of intervention characteristics. However, of the seven studies that quantified adherence, six reported adherence > 70%. Seven of the included studies reported attrition rates < 20%, with contact and support from researchers not appearing to influence adherence or attrition. CONCLUSIONS: Holistic digital interventions designed for a targeted condition are a promising approach for promoting high adherence and reducing attrition. Future studies should explore how adherence of digital interventions compares to face-to-face interventions and determine potential influencers of adherence.