Out-of-pocket costs for families and people living with cerebral palsy in Australia.

The most recent cost estimates of cerebral palsy (CP) in Australia did not include out-of-pocket costs for families. This study aimed to: 1) describe and estimate out-of-pocket costs for people with CP and their families by age and gross motor function classification system (GMFCS) level; 2) measure financial distress. A cross-sectional quantitative survey design was used with qualitative approaches to analyse open-ended questions. A CP-specific out-of-pocket costs survey was co-designed with people with lived experience. Adults with CP and carers were recruited from Australian population-based CP Registers and via social media. Sociodemographic variables were analysed descriptively and median (IQR) expenses for health, assistive technology, personal care, housing, occupation, transport, leisure, respite and holidays, by age (0-6; 7-17; 18 years +) and gross motor function [GMFCS level I-II vs III-V] were calculated. The In Charge Financial Distress/Financial Wellbeing Scale measured financial distress. Regression analyses were conducted to investigate costs and financial distress. Additional out-of-pocket costs itemised in open-ended questions were charted. Comments were thematically analysed using the framework approach. 271 surveys were completed for children 0-6 years (n = 47), children/adolescents 7-17 years (n = 124) and adults (n = 100). 94% of participants had out-of-pocket costs associated with CP, with an overall annual median of $4,460 Australian dollars (IQR $11,955). After controlling for income, private insurance and disability funding, the GMFCS III-V group had costs two times higher than the GMFCS I-II group (2.01; 95% CI 1.15-3.51). Age was not significantly associated with costs. 36% of participants had high to overwhelming financial distress; this was not associated with age or GMFCS level after controlling for financial factors. Families had several additional disability costs. Open-ended responses revealed experiences of financial concern were influenced by funding scheme experiences, reduced income, uncertainty, access to support networks and an inability to afford CP-related costs. Cost estimates and financial distress indicators should inform policy, funding and clinical decisions when planning interventions to support people with CP and their families.

Can web-based implementation interventions improve physician early diagnosis of cerebral palsy? Protocol for a 3-arm parallel superiority randomised controlled trial and cost-consequence analysis comparing adaptive and non-adaptive virtual patient instructional designs with control to evaluate effectiveness on physician behaviour, diagnostic skills and patient outcomes.

INTRODUCTION: Cerebral palsy (CP) is the most common childhood physical disability. Accurate diagnosis before 6 months is possible using predictive tools and decision-making skills. Yet diagnosis is typically made at 12-24 months of age, hindering access to early interventions that improve functional outcomes. Change in practice is required for physicians in key diagnostic behaviours. This study aims to close the identified research-practice gap and increase accurate CP diagnosis before 6 months of age through tailored web-based implementation interventions. This trial will determine whether adaptive e-learning using virtual patients, targeting CP diagnostic behaviours and clinical decision-making skills, effectively changes physician behaviour and practice compared with non-adaptive e-learning instructional design or control. METHODS AND ANALYSIS: This study is a 3-arm parallel superiority randomised controlled trial of two tailored e-learning interventions developed to expedite physician CP diagnosis. The trial will compare adaptive (arm 1) and non-adaptive (arm 2) instructional designs with waitlist control (arm 3) to evaluate change in physician behaviour, skills and diagnostic practice. A sample size of 275 paediatric physicians enables detection of small magnitude effects (0.2) of primary outcomes between intervention comparators with 90% power (α=0.05), allowing for 30% attrition. Barrier analysis, Delphi survey, Behaviour Change Wheel and learning theory frameworks guided the intervention designs. Adaptive and non-adaptive video and navigation sequences utilising virtual patients and clinical practice guideline content were developed, integrating formative key features assessment targeting clinical decision-making skills relative to CP diagnosis.Physician outcomes will be evaluated based on postintervention key feature examination scores plus preintervention/postintervention behavioural intentions and practice measures. Associations with CP population registers will evaluate real-world diagnostic patient outcomes. Intervention costs will be reported in a cost-consequence analysis from funders' and societal perspectives. ETHICS AND DISSEMINATION: Ethics approved from The University of Sydney (Project number 2021/386). Results will be disseminated through peer-reviewed journals and scientific conferences. TRIAL REGISTRATION NUMBER: Australian New Zealand Clinical Trials Registry: ACTRN 12622000184774.

Global prevalence of cerebral palsy: A systematic analysis.

AIM: To determine trends and current estimates in regional and global prevalence of cerebral palsy (CP). METHOD: A systematic analysis of data from participating CP registers/surveillance systems and population-based prevalence studies (from birth year 1995) was performed. Quality and risk of bias were assessed for both data sources. Analyses were conducted for pre-/perinatal, postnatal, neonatal, and overall CP. For each region, trends were statistically classified as increasing, decreasing, heterogeneous, or no change, and most recent prevalence estimates with 95% confidence intervals (CI) were calculated. Meta-analyses were conducted to determine current birth prevalence estimates (from birth year 2010). RESULTS: Forty-one regions from 27 countries across five continents were represented. Pre-/perinatal birth prevalence declined significantly across Europe and Australia (11 out of 14 regions), with no change in postneonatal CP. From the limited but increasing data available from regions in low- and middle-income countries (LMICs), birth prevalence for pre-/perinatal CP was as high as 3.4 per 1000 (95% CI 3.0-3.9) live births. Following meta-analyses, birth prevalence for pre-/perinatal CP in regions from high-income countries (HICs) was 1.5 per 1000 (95% CI 1.4-1.6) live births, and 1.6 per 1000 (95% CI 1.5-1.7) live births when postneonatal CP was included. INTERPRETATION: The birth prevalence estimate of CP in HICs declined to 1.6 per 1000 live births. Data available from LMICs indicated markedly higher birth prevalence. WHAT THIS PAPER ADDS: • Birth prevalence of pre-/perinatal cerebral palsy (CP) in high-income countries (HICs) is decreasing. • Current overall CP birth prevalence for HICs is 1.6 per 1000 live births. • Trends in low- and middle-income countries (LMICs) cannot currently be measured. • Current birth prevalence in LMICs is markedly higher than in HICs. • Active surveillance of CP helps to assess the impact of medical advancements and social/economic development. • Population-based data on prevalence and trends of CP are critical to inform policy.

Penalized likelihood estimation of a mixture cure Cox model with partly interval censoring-An application to thin melanoma.

Time-to-event data in medical studies may involve some patients who are cured and will never experience the event of interest. In practice, those cured patients are right censored. However, when data contain a cured fraction, standard survival methods such as Cox proportional hazards models can produce biased results and therefore misleading interpretations. In addition, for some outcomes, the exact time of an event is not known; instead an interval of time in which the event occurred is recorded. This article proposes a new computational approach that can deal with both the cured fraction issues and the interval censoring challenge. To do so, we extend the traditional mixture cure Cox model to accommodate data with partly interval censoring for the observed event times. The traditional method for estimation of the model parameters is based on the expectation-maximization (EM) algorithm, where the log-likelihood is maximized through an indirect complete data log-likelihood function. We propose in this article an alternative algorithm that directly optimizes the log-likelihood function. Extensive Monte Carlo simulations are conducted to demonstrate the performance of the new method over the EM algorithm. The main advantage of the new algorithm is the generation of asymptotic variance matrices for all the estimated parameters. The new method is applied to a thin melanoma dataset to predict melanoma recurrence. Various inferences, including survival and hazard function plots with point-wise confidence intervals, are presented. An R package is now available at Github and will be uploaded to R CRAN.