Hospital length of stay prediction tools for all hospital admissions and general medicine populations: systematic review and meta-analysis.

Background: Unwarranted extended length of stay (LOS) increases the risk of hospital-acquired complications, morbidity, and all-cause mortality and needs to be recognized and addressed proactively. Objective: This systematic review aimed to identify validated prediction variables and methods used in tools that predict the risk of prolonged LOS in all hospital admissions and specifically General Medicine (GenMed) admissions. Method: LOS prediction tools published since 2010 were identified in five major research databases. The main outcomes were model performance metrics, prediction variables, and level of validation. Meta-analysis was completed for validated models. The risk of bias was assessed using the PROBAST checklist. Results: Overall, 25 all admission studies and 14 GenMed studies were identified. Statistical and machine learning methods were used almost equally in both groups. Calibration metrics were reported infrequently, with only 2 of 39 studies performing external validation. Meta-analysis of all admissions validation studies revealed a 95% prediction interval for theta of 0.596 to 0.798 for the area under the curve. Important predictor categories were co-morbidity diagnoses and illness severity risk scores, demographics, and admission characteristics. Overall study quality was deemed low due to poor data processing and analysis reporting. Conclusion: To the best of our knowledge, this is the first systematic review assessing the quality of risk prediction models for hospital LOS in GenMed and all admissions groups. Notably, both machine learning and statistical modeling demonstrated good predictive performance, but models were infrequently externally validated and had poor overall study quality. Moving forward, a focus on quality methods by the adoption of existing guidelines and external validation is needed before clinical application. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier: CRD42021272198.

Hospital length of stay prediction for general surgery and total knee arthroplasty admissions: Systematic review and meta-analysis of published prediction models.

Objective: Systematic review of length of stay (LOS) prediction models to assess the study methods (including prediction variables), study quality, and performance of predictive models (using area under receiver operating curve (AUROC)) for general surgery populations and total knee arthroplasty (TKA). Method: LOS prediction models published since 2010 were identified in five major research databases. The main outcomes were model performance metrics including AUROC, prediction variables, and level of validation. Risk of bias was assessed using the PROBAST checklist. Results: Five general surgery studies (15 models) and 10 TKA studies (24 models) were identified. All general surgery and 20 TKA models used statistical approaches; 4 TKA models used machine learning approaches. Risk scores, diagnosis, and procedure types were predominant predictors used. Risk of bias was ranked as moderate in 3/15 and high in 12/15 studies. Discrimination measures were reported in 14/15 and calibration measures in 3/15 studies, with only 4/39 externally validated models (3 general surgery and 1 TKA). Meta-analysis of externally validated models (3 general surgery) suggested the AUROC 95% prediction interval is excellent and ranges between 0.803 and 0.970. Conclusion: This is the first systematic review assessing quality of risk prediction models for prolonged LOS in general surgery and TKA groups. We showed that these risk prediction models were infrequently externally validated with poor study quality, typically related to poor reporting. Both machine learning and statistical modelling methods, plus the meta-analysis, showed acceptable to good predictive performance, which are encouraging. Moving forward, a focus on quality methods and external validation is needed before clinical application.

Attitudes towards vaccines and intention to vaccinate against COVID-19: a cross-sectional analysis-implications for public health communications in Australia.

OBJECTIVE: To examine SARS-CoV-2 vaccine confidence, attitudes and intentions in Australian adults as part of the iCARE Study. DESIGN AND SETTING: Cross-sectional online survey conducted when free COVID-19 vaccinations first became available in Australia in February 2021. PARTICIPANTS: Total of 1166 Australians from general population aged 18-90 years (mean 52, SD of 19). MAIN OUTCOME MEASURES: Primary outcome: responses to question 'If a vaccine for COVID-19 were available today, what is the likelihood that you would get vaccinated?'.Secondary outcome: analyses of putative drivers of uptake, including vaccine confidence, socioeconomic status and sources of trust, derived from multiple survey questions. RESULTS: Seventy-eight per cent reported being likely to receive a SARS-CoV-2 vaccine. Higher SARS-CoV-2 vaccine intentions were associated with: increasing age (OR: 2.01 (95% CI 1.77 to 2.77)), being male (1.37 (95% CI 1.08 to 1.72)), residing in least disadvantaged area quintile (2.27 (95% CI 1.53 to 3.37)) and a self-perceived high risk of getting COVID-19 (1.52 (95% CI 1.08 to 2.14)). However, 72% did not believe they were at a high risk of getting COVID-19. Findings regarding vaccines in general were similar except there were no sex differences. For both the SARS-CoV-2 vaccine and vaccines in general, there were no differences in intentions to vaccinate as a function of education level, perceived income level and rurality. Knowing that the vaccine is safe and effective and that getting vaccinated will protect others, trusting the company that made it and vaccination recommended by a doctor were reported to influence a large proportion of the study cohort to uptake the SARS-CoV-2 vaccine. Seventy-eight per cent reported the intent to continue engaging in virus-protecting behaviours (mask wearing, social distancing, etc) postvaccine. CONCLUSIONS: Most Australians are likely to receive a SARS-CoV-2 vaccine. Key influencing factors identified (eg, knowing vaccine is safe and effective, and doctor's recommendation to get vaccinated) can inform public health messaging to enhance vaccination rates.

Emergency department usage by adults with cerebral palsy: A retrospective cohort study.

OBJECTIVE: To retrospectively profile the ED usage for a cohort of adults with cerebral palsy (CP). METHODS: Five years of ED data from a Victorian hospital network was analysed to identify participants with CP using the Victorian Emergency Minimum Dataset supplemented with scrutiny of inpatient admission data to identify cases because of limited ED coding of CP. Presentation frequency, emergency diagnoses (International Classification of Diseases, 10th Revision codes) and presentation sequelae were calculated and described. An investigation into rates of low urgency presentations was conducted. Differences between adult and paediatric cohorts were described. RESULTS: Participants with CP constituted 1586 ED presentations. Adults represented 43% (n = 689) of these. Thirty percent of adults presented more than five times over the study period, with respiratory (25%), gastrointestinal (17%) and epilepsy/convulsion diagnoses (11%) being the most common presentations. Rates of inpatient hospital admissions from the ED increased with age in adults (P < 0.001). Low urgency presentations made up 8.9% of total adult presentations. CONCLUSIONS: The high rates of respiratory diagnoses and epilepsy/convulsions, both ambulatory care-sensitive conditions, may be indicative of transitional challenges between paediatric and adult healthcare, potentially highlighting difficulties in accessing primary care services. Relatively low rates of 'low urgency' presentations may suggest perceived medical fragility in this vulnerable population. People with CP who present to ED and were not admitted may be underrepresented in this data. National expansion of this research will aid the development of an evidence-based model of care for CP in Australia.