Latent profiles and predictors of barriers to care in Swiss children and adolescents with rare diseases

OBJECTIVE

Children and adolescents with rare diseases face significant barriers when accessing healthcare. We aimed to assess and predict these barriers and investigate associations with health-related quality of life (HRQoL).

METHOD

We conducted a cross-sectional survey of Swiss parents (N = 189) of children with rare diseases including the Barriers to Care Questionnaire (BCQ), containing six barriers and the Pediatric Quality of Life Inventory (PedsQL). Latent profile analysis (LPA) was used to uncover distinct classes, which were compared using chi-square tests and Mann-Whitney U tests. Relevant medical and sociodemographic class predictors were identified using Elastic Net regression, followed by regression analysis to investigate their role in predicting barriers to care and examine the effects of these classes on HRQoL.

RESULTS

Two distinct groups were identified, a higher barriers class (59%) and a lower barriers class (41%). In the higher barriers class, participants showed elevated scores across all subscales and specifically on pragmatics and expectations. More barriers to care were linked to a nonstable disease course (OR = 2.27, p = .002) and a diagnosis after the age of 3 months (OR = 2.17, p = .006). Individuals in the higher barriers class exhibited more psychological comorbidities (p = .044), congenital malformations/deformations/chromosomal abnormalities (p=.042), and medical misdiagnoses (p = .006). Children in the higher barriers class had significantly lower PedsQL scores compared to the lower barriers class (p <.05).

CONCLUSION

This study highlights the need for comprehensive assessment of barriers to pediatric care in rare diseases, offering potential entry points for targeted interventions.

Developmental Assessment in Children at Higher Likelihood for Developmental Delays - Comparison of Parent Report and Direct Assessment

PURPOSE

Accurate assessment of cognitive development of young children is a vital component of developmental evaluations. Direct assessment of developmental skills is not always feasible, but there is limited information on the agreement between direct assessment and caregiver-reported cognitive skills. There is limited information regarding the accuracy of the parent-reported Developmental Profile 4 (DP-4) in comparison to the widely-used developmental measure, the Bayley Scales of Infant and Toddler Development, Fourth Edition (Bayley-4). The purpose of the current study was to evaluate whether a standardized parent interview can effectively identify children at risk for cognitive developmental delays.

METHODS

We compared the agreement between the Bayley-4 Cognitive and the Developmental Profile 4 (DP-4) in young children being evaluated in-person for early developmental delays. 182 children (134 with an autism diagnosis), ages 6-42 months, completed both assessments.

RESULTS

Results showed that Bayley-4 Cognitive scores had a moderately strong correlation with DP4-Cognitive scores (r = 0.70, p < 0.001). A cutoff of 70 or 69 on the DP-4 Cognitive was determined as ideal for identifying developmental delay based on diagnosis of global developmental delay or the Bayley-4 Cognitive.

CONCLUSIONS

Our analyses revealed good agreement between DP-4 and Bayley-4 Cognitive scores, even after controlling for confounding variables such as degree of ASD characteristics, age, and sex. These results suggest that caregiver-report measures can be a valid and useful tool in the assessment of young children, particularly when direct developmental assessment is not feasible.

Management of Rheumatoid Arthritis in Primary Care: A Scoping Review

Rheumatoid arthritis (RA) can lead to severe joint impairment and chronic disability. Primary care (PC), provided by general practitioners (GPs), is the first level of contact for the population with the healthcare system. The aim of this scoping review was to analyze the approach to RA in the PC setting. PubMed, Scopus, and Web of Science were searched using the MESH terms "rheumatoid arthritis" and "primary care" from 2013 to 2023. The search strategy followed the PRISMA-ScR guidelines. The 61 articles selected were analyzed qualitatively in a table and discussed in two sections, namely criticisms and strategies for the management of RA in PC. The main critical issues in the management of RA in PC are the following: difficulty and delay in diagnosis, in accessing rheumatological care, and in using DMARDs by GPs; ineffective communication between GPs and specialists; poor patient education; lack of cardiovascular prevention; and increase in healthcare costs. To overcome these criticisms, several management strategies have been identified, namely early diagnosis of RA, quick access to rheumatology care, effective communication between GPs and specialists, active patient involvement, screening for risk factors and comorbidities, clinical audit, interdisciplinary patient management, digital health, and cost analysis. PC appears to be the ideal healthcare setting to reduce the morbidity and mortality of chronic disease, including RA, if a widespread change in GPs' approach to the disease and patients is mandatory.

Evaluating Efficiency of a Provincial Telerehabilitation Service in Improving Access to Care During the COVID-19 Pandemic

Scope

Early in the COVID-19 pandemic, community rehabilitation stakeholders from a provincial health system designed a novel telerehabilitation service. The service provided wayfinding and self-management advice to individuals with musculoskeletal concerns, neurological conditions, or post-COVID-19 recovery needs. This study evaluated the efficiency of the service in improving access to care.

Methodology

We used multiple methods including secondary data analyses of call metrics, narrative analyses of clinical notes using artificial intelligence (AI) and machine learning (ML), and qualitative interviews.

Conclusions

Interviews revealed that the telerehabilitation service had the potential to positively impact access to rehabilitation during the COVID-19 pandemic, for individuals living rurally, and for individuals on wait lists. Call metric analyses revealed that efficiency may be enhanced if call handling time was reduced. AI/ML analyses found that pain was the most frequently-mentioned keyword in clinical notes, suggesting an area for additional telerehabilitation resources to ensure efficiency.

Artificial Intelligence Systems Assisting in the Assessment of the Course and Retention of Orthodontic Treatment

This scoping review examines the contemporary applications of advanced artificial intelligence (AI) software in orthodontics, focusing on its potential to improve daily working protocols, but also highlighting its limitations. The aim of the review was to evaluate the accuracy and efficiency of current AI-based systems compared to conventional methods in diagnosing, assessing the progress of patients' treatment and follow-up stability. The researchers used various online databases and identified diagnostic software and dental monitoring software as the most studied software in contemporary orthodontics. The former can accurately identify anatomical landmarks used for cephalometric analysis, while the latter enables orthodontists to thoroughly monitor each patient, determine specific desired outcomes, track progress, and warn of potential changes in pre-existing pathology. However, there is limited evidence to assess the stability of treatment outcomes and relapse detection. The study concludes that AI is an effective tool for managing orthodontic treatment from diagnosis to retention, benefiting both patients and clinicians. Patients find the software easy to use and feel better cared for, while clinicians can make diagnoses more easily and assess compliance and damage to braces or aligners more quickly and frequently.

Telehealth Strategies to Support Referral Management to Secondary Care in Brazil: A Cost-Effectiveness Analysis

OBJECTIVES

This study aimed to assess the cost-effectiveness of a remotely operated referral management system (RORMS) compared with a conventional referral management system (CRMS) in Brazil.

METHODS

This is a model-based cost-effectiveness analysis under the perspective of the Unified Healthcare System (Sistema Único de Saúde [SUS]) in Brazil. A Markov microsimulation model was developed to compare costs and referral outcomes of the RORMS and the CRMS. Model consisted of 4 states representative of sequential stepwise assessments of referral suitability, 3 states representative of referral outcomes, and 1 exit model state. Target population represented cases being referred from primary healthcare units to specialized care in SUS. Model inputs related to costs and effectiveness in the RORMS arm were obtained from the data set of a RORMS between July and December 2019. Model inputs for the CRMS model arm were obtained from administrative data sets of 2 Brazilian localities for the year 2019. Relative effect size of RORMS in comparison with CRMS in SUS was obtained from published studies. Effectiveness outcome was unnecessary referrals averted. The incremental cost-effectiveness ratio was calculated for the base case. Probabilistic sensitivity analysis was conducted.

RESULTS

In the base-case analyses, RORMS dominated CRMS, with expected cost-savings from $50.42 to $80.62 per unnecessary referral averted. RORMS was the dominant strategy in 83.7% of 100 000 simulations in the probabilistic sensitivity analysis. In 16.2% of simulations, incremental cost-effectiveness ratio was between $0 and $222 per unnecessary referral averted.

CONCLUSIONS

Model-based simulations indicate that the RORMS is likely to be cost saving in comparison with the CRMS.

Telehealth to support referral management in a universal health system: a before-and-after study

BACKGROUND

Management of patient flow within a healthcare network, allowing equitable and qualified access to healthcare, is a major challenge for universal health systems. Implementation of telehealth strategies to support referral management has been shown to increase primary care resolution and to promote coordination of care. The objective of this study was to assess the impact of telehealth strategies on waiting lists and waiting times for specialized care in Brazil.

METHODS

Before-and-after study with measures obtained between January 2019 and February 2020. Baseline measurements of waiting lists were obtained immediately before the implementation of a remotely operated referral management system. Post-interventional measurements were obtained monthly, up to six months after the beginning of operation. Data was extracted from the database of the project. General linear models were applied to assess interaction of locality and time over number of cases on waiting lists and waiting times.

RESULTS

At baseline, the median number of cases on waiting lists ranged from 2961 to 12,305 cases. Reductions of the number of cases on waiting lists after six months of operation were observed in all localities. The magnitude of the reduction ranged from 54.67 to 88.97 %. Interaction of time measurements was statistically significant from the second month onward. Median waiting times ranged from 159 to 241 days at baseline. After six months, there was a decrease of 100 and 114 waiting days in two localities, respectively, with reduction of waiting times only for high-risk cases in the third locality.

CONCLUSIONS

Adoption of telehealth strategies resulted in the reduction of number of cases on waiting lists. Results were consistent across localities, suggesting that telehealth interventions are viable in diverse settings.

Telemedicine in the management of patients with headache: current situation and recommendations of the Spanish Society of Neurology's Headache Study Group

INTRODUCTION

The COVID-19 pandemic has caused an unexpected boost to telemedicine. We analyse the impact of the pandemic on telemedicine applied in Spanish headache consultations, review the literature, and issue recommendations for the implementation of telemedicine in consultations.

METHOD

The study comprised 3 phases: 1) review of the MEDLINE database since 1958 (first reported experience with telemedicine); 2) Google Forms survey sent to all members of the Spanish Society of Neurology's Headache Study Group (GECSEN); and 3) online consensus of GECSEN experts to issue recommendations for the implementation of telemedicine in Spain.

RESULTS

COVID-19 has increased waiting times for face-to-face consultations, increasing the use of all telemedicine modalities: landline telephone (from 75% before April 2020 to 97% after), mobile telephone (from 9% to 27%), e-mail (from 30% to 36%), and video consultation (from 3% to 21%). Neurologists are aware of the need to expand the availability of video consultations, which are clearly growing, and other e-health and m-health tools.

CONCLUSIONS

The GECSEN recommends and encourages all neurologists who assist patients with headaches to implement telemedicine resources, with the optimal objective of offering video consultation to patients under 60-65 years of age and telephone calls to older patients, although each case must be considered on an individual basis. Prior approval and advice must be sought from legal and IT services and the centre's management. Most patients with stable headache and/or neuralgia are eligible for telemedicine follow-up, after a first consultation that must always be held in person.