Healthcare reimbursement costs of children with type 1 diabetes in the Netherlands, a observational nationwide study (Young Dudes-4)

Does size matter? Hospital volume and resource use in paediatric diabetes care

AIMS

Paediatric diabetes care has become increasingly specialised due to the multidisciplinary approach and technological developments. Guidelines recommend sufficient experience of treatment teams. This study evaluates associations between hospital volume and resource use and hospital expenditure in Dutch children with diabetes.

METHODS

Retrospective cohort study using hospital claims data of 5082 children treated across 44 Dutch hospitals (2019-2020). Hospitals were categorised into three categories; small (≥20-100 patients), medium (≥100-200 patients) and large (≥200 patients). All-cause hospitalisations, consultations, technology and hospital expenditure were analysed and adjusted for age, sex, socio-economic status (SES) and hospital of treatment.

RESULTS

Fewer hospitalisations were observed in large hospitals compared to small hospitals (OR 0.48; [95% CI 0.32-0.72]; p < 0.001). Median number of yearly paediatrician visits was 7 in large and 6 in small hospitals, the significance of which was attenuated in multilevel analysis (OR ≥7 consultations: 1.89; [95%CI 0.74-4.83]; p = 0.18). Technology use varies between individual hospitals, whereas pump usage and real-time continuous glucose monitoring showed no significant differences between hospital volumes. Mean overall expenditure was highest in medium-sized centres with €6434 per patient (IQR €2555-7955); the difference in diabetes care costs was not significant between hospital patient volumes.

CONCLUSIONS

Care provision patterns vary by hospital patient volume. Large hospitals had the lowest hospitalisation rates. The use of diabetes technology was not different between hospital patient volumes. Medium-sized hospitals showed the highest overall expenditure, but diabetes care costs were similar across hospital volumes.

The Impact of Parental Electronic Health Literacy on Disease Management and Outcomes in Pediatric Type 1 Diabetes Mellitus: Cross-Sectional Clinical Study

BACKGROUND

Despite the growing uptake of smart technologies in pediatric type 1 diabetes mellitus (T1DM) care, little is known about caregiving parents' skills to deal with electronic health information sources.

OBJECTIVE

We aimed to assess the electronic health literacy of parents caring for children with T1DM and investigate its associations with disease management and children's outcomes.

METHODS

A cross-sectional survey was performed involving 150 parent-child (8-14 years old with T1DM) dyads in a university pediatric diabetology center. Parents' electronic health literacy (eHealth Literacy Scale [eHEALS]), general health literacy (Chew questionnaire and Newest Vital Sign [NVS]), and attitudes toward T1DM care (Parental Self-Efficacy Scale for Diabetes Management [PSESDM] and Hypoglycemia Fear Survey [HFS]) were investigated. Children's treatment, HbA1c level, and quality of life (Pediatric Quality of Life Inventory Diabetes Module [PedsQL Diab] and EQ-5D-Y-3L) were assessed. Multiple linear regression analysis was performed to investigate the determining factors of 6-month average HbA1c.

RESULTS

Of the 150 children, 38 (25.3%) used a pen, 55 (36.7%) used a pen plus a sensor, 6 (4.0%) used an insulin pump, and 51 (34.0%) used an insulin pump plus a sensor. Parents' average eHEALS score (mean 31.2, SD 4.9) differed significantly by educational level (P=.04) and the children's treatment (P=.005), being the highest in the pump + sensor subgroup. The eHEALS score showed significant Pearson correlations with the Chew score (r=-0.45; P<.001), NVS score (r=0.25; P=.002), and PSESDM score (r=0.35; P<.001) but not with the children's HbA1c (r=-0.143; P=.08), PedsQL Diab (r=-0.0002; P>.99), and EQ-5D-Y-3L outcomes (r=-0.13; P=.12). Regression analysis revealed significant associations of the child's HbA1c level with sex (β=0.58; P=.008), treatment modality (pen + sensor: β=-0.66; P=.03; pump + sensor: β=-0.93; P=.007), and parents' self-efficacy (PSESDM; β=-0.08; P=.001).

CONCLUSIONS

Significantly higher parental electronic health literacy was found in T1DM children using a glucose sensor. The electronic health literacy level was associated with parents' diabetes management attitude but not with the child's glycemic control. Studies further investigating the role of parental electronic health literacy in T1DM children managed at different levels of care and the local context are encouraged.

Healthcare expenditure and technology use in pediatric diabetes care

BACKGROUND

Diabetes mellitus is one of the most common chronic diseases in childhood. With more advanced care options including ever-evolving technology, allocation of resources becomes increasingly important to guarantee equal care for all. Therefore, we investigated healthcare resource utilization, hospital costs, and its determinants in Dutch children with diabetes.

METHODS

We conducted a retrospective, observational analysis with hospital claims data of 5,474 children with diabetes mellitus treated in 64 hospitals across the Netherlands between 2019-2020.

RESULTS

Total hospital costs were €33,002,652 per year, and most of these costs were diabetes-associated (€28,151,381; 85.3%). Mean annual diabetes costs were €5,143 per child, and treatment-related costs determined 61.8%. Diabetes technology significantly increased yearly diabetes costs compared to no technology: insulin pumps € 4,759 (28.7% of children), Real-Time Continuous Glucose Monitoring € 7,259 (2.1% of children), and the combination of these treatment modalities € 9,579 (27.3% of children). Technology use increased treatment costs significantly (5.9 - 15.3 times), but lower all-cause hospitalisation rates were observed. In all age groups, diabetes technology use influenced healthcare consumption, yet in adolescence usage decreased and consumption patterns changed.

CONCLUSIONS

These findings suggest that contemporary hospital costs of children with diabetes of all ages are driven primarily by the treatment of diabetes, with technology use as an important additive factor. The expected rise in technology use in the near future underlines the importance of insight into resource use and cost-effectiveness studies to evaluate if improved outcomes balance out these short-term costs of modern technology.

Financial burden for families of children with type 1 diabetes: a cross-sectional survey from North India

Introduction

Type 1 diabetes (T1D) incurs substantial out-of-pocket expenses (OOPE) on insulin and diabetes-related supplies. The information on OOPE is scarce from low- and middle-income countries. We aimed to estimate annual OOPE for children with T1D attending our diabetes clinic located in North India.

Methods

An online survey was conducted among parents of 380 children with T1D (mean age: 10.3 ± 4.6 years). Modified BG Prasad scale was used to estimate the socioeconomic status (SES).

Results

The mean duration of T1D was 3.6 ± 2.6 years; 54.9% of children were boys. The median HbA1c (IQR) was 7.9% (5–15%). 51.9% belonged to lower or lower-middle SES. Mean annual spending on glucose monitoring, insulin administration, and laboratory investigations were Indian Rupee (INR) 21,576, INR 28,965, and INR 5069, respectively (total INR 55,185, IQR: 26,575–105,027). The cost of a single visit to the doctor was approximately INR 2889. Thirty children required hospitalization during the last year, which costs INR 27,495 on average. 30.3% had more than 50% of their total family income spent on diabetes care, with a significant negative correlation with their SES (r =  – 0.738, p = 0.00). Only 11.6% were receiving financial support from any agency. 36.6% of families had to borrow money; the OOPE exceeded income from all sources in 8.2% of families.

Conclusions

There is a high financial burden of T1D care for North Indian children, almost on the verge of losing sustainability. Further studies are warranted to furnish larger OOPE data to guide policy decisions aimed at reducing direct costs to patients.