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Record W4364376102 · doi:10.1007/s41669-023-00409-y

Economic Evaluation Comparing Virtual Reality with Child Life Programming for Non-sedated Pediatric Medical Imaging: A Cost-Consequence Analysis

2023· article· en· W4364376102 on OpenAlexafffundabout
John Jacob, Chelsea Stunden, Dhayanand Deenadayalan, Luke Thomas

Bibliographic record

VenuePharmacoEconomics - Open · 2023
Typearticle
Languageen
FieldMedicine
TopicPediatric Pain Management Techniques
Canadian institutionsWestern UniversityBC Children's HospitalUniversity of British Columbia
FundersMitacs
KeywordsVirtual realityPsychologyComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

INTRODUCTION: Effective preparation of children for hospital procedures, including non-sedated medical imaging, is an important clinical issue. This study aimed to assess the costs and consequences (effects) of preparing pediatric patients using two methods of delivering preparation for a scheduled magnetic resonance image (MRI)-virtual reality (VR-MRI) and a certified Child Life Program (CLP). METHODS: A cost-consequence analysis (CCA) was performed using a societal perspective in Canada. The CCA catalogs a wide range of costs and consequences of VR-MRI compared with a CLP. The evaluation uses data from a prior randomized clinical trial evaluating VR and a CLP in a simulated trial. The economic evaluation encompassed health-related effects, including anxiety, safety and adverse events, and non-health effects, including preparation time, displaced time from usual activities, workload capacity, patient-specific adaptation, administrative burden, and user-experience metrics. The costs have been categorized into hospital operational costs, travel costs, other patient costs, and societal costs. RESULTS: VR-MRI has similar benefits to the CLP in managing anxiety, safety and adverse events, as well as converting patients to non-sedated medical imaging. Preparation time and patient-specific adaptation are in favor of the CLP, while displaced time from usual activities, potential workload capacity, and administrative burden are in favor of VR-MRI. Both programs rank favorably in terms of user experience. The hospital operational costs ranged in Canadian dollars (CAN$) from CAN$32.07 for the CLP to between CAN$107.37 and CAN$129.73 for VR-MRI. Travel costs ranged from CAN$50.58 to CAN$2365.18 depending on travel distance for the CLP, and CAN$0 for VR-MRI. Other patient costs involved caregiver time off, and ranged from CAN$190.69 to CAN$$1144.16 for the CLP and CAN$47.67 for VR-MRI. The total cost for the CLP ranged from CAN$315.16 (CAN$277.91-$426.64) to CAN$3843.41 (CAN$3196.59-$4849.91) per patient depending on travel distance and amount of administrative support required, while VR-MRI preparation ranged from CAN$178.30 (CAN$178.20-$188.76) to CAN$283.85 (CAN$283.71-$298.40) per patient. For every instance where patient travel to visit a Certified Child Life Specialist (CCLS) onsite was replaced with VR-MRI, between CAN$119.01 and CAN$3364.62 total costs could be saved per patient. CONCLUSIONS: While it is neither feasible nor appropriate to replace all preparation with VR, using VR to reach children who cannot otherwise visit the CLP onsite could increase access to quality preparation, and using VR in place of the CLP where clinically indicated could reduce the overall costs for patients, the hospital, and society. Our CCA gives decision makers a cost analysis and the relevant effects of each preparation program so they can value the VR and CLP programs more broadly within the potential health and non-health outcomes of pediatric patients scheduled for MRI at their facilities.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.067
GPT teacher head0.416
Teacher spread0.349 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2023
Admission routes3
Has abstractyes

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