Assessing Emerging Health Technologies: An Integrated Perspective
Notice bibliographique
Résumé
Healthcare expenditures account for approximately 9% of GDP in OECD countries and are on an upward trajectory (OECD, 2017). This significant financial burden, combined with an aging global population and increasing demand, emphasizes the imperative for sustained research and innovation to enhance health system efficacy. Key to this transformation are technological advancements, including digital health, which presents novel opportunities for improvement. Emerging digital health technologies, such as virtual consultations, complex imaging procedures, and electronic medical records, are fundamental to modern healthcare infrastructures. However, significant gaps remain in the evaluation and understanding of these innovations, especially for nascent technological areas. This thesis addresses this subject, aiming to delineate how individuals and institutions can bolster their evaluative capabilities, strategic decision-making, and planning for the deployment of emerging digital healthcare technologies. The research methodology amalgamates theoretical exploration, literature scrutiny, and empirical examinations, presenting an integrated perspective that intersects the disciplines of Management & Decision Science, Technology & Innovation, and Health Economics & Outcomes Research. From an applied perspective, this research focuses on developing evidence within the context of pediatric healthcare in Canada — a context notably underrepresented in healthcare management research, despite its disproportionate per capita expenditure. Technologically, the predominant focus is on applications in virtual reality (VR) and three-dimensional (3D) printing and virtualization, though with the aspiration of ensuring the generalizability of results. The current thesis is structured to parallel the progression of the research itself, as three distinct phases; this begins with a comprehensive Background that contextualizes the initial intent, exploring the relationship between technology, innovation, and health outcomes. In this phase, each academic discipline is analyzed to identify base theoretical underpinnings for the research. The second phase of this work includes five empirical studies, each preceded by context-specific literature reviews for the respective technological domain, providing insight into the current state of evidence related to value-based assessment and economic evaluation in that area. Empirical studies included a randomized controlled trial and a cost consequences assessment of VR for pre-procedural preparation for medical imaging. Additionally, novel applications of 3D printing and virtualization are critically analyzed, accompanied by a multi-case study on the implementation of 3D printing in pediatrics, a cost-consequences study of applications for thoracoabdominal surgeries, and an outcomes study on the use of 3D virtualization in medical education during the COVID-19 pandemic. The final phase of this research includes the critical analysis and synthesis of findings into a proposal for a novel value-based assessment and decision-making framework specific to emerging health innovations; this framework integrates insights and resources for clinicians, administrators, and policymakers. The outcomes of this research are skewed toward Knowledge Users, but also aims to advance the theoretical basis for health technology assessment (HTA).
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,025 | 0,038 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,019 | 0,011 |
| Études des sciences et des technologies | 0,003 | 0,014 |
| Communication savante | 0,035 | 0,031 |
| Science ouverte | 0,003 | 0,013 |
| Intégrité de la recherche | 0,006 | 0,006 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».