Development of a Continuous Sampling System for In Situ Monitoring of Anaerobic Coculture; Assessing the United States’ Healthcare System through an Actor Network Theory Framework
Notice bibliographique
Résumé
The thesis and the technical report are related in that they are geared towards improving healthcare in the U.S.. The technical report is focused at a more specific scale, designing a technology that aims to reduce hospital-borne infections through early diagnosis. The thesis approaches healthcare improvement at a much broader perspective, providing suggestions on how the macroscale healthcare system could change to benefit most everyone in the U.S., lowering overall healthcare expenditures along with improving upon healthcare metrics at the same time. The technical report was based on the work from my capstone project. The goal of this project was to develop a continuous sampling system for in situ monitoring of anaerobic coculture using Clostridiodes difficile (C. difficile) growth kinetics and germination as a model. The Swami laboratory plans to incorporate this coculture system with impedance cytometry, which is a research method to assess the electrical properties of a population of cells in a fast, label-free manner. Upon successful completion of the capstone project and further design validations, the anaerobic coculture system will be able to rapidly assess patient susceptibility to C. difficile infection in the clinic, reducing the amount of nosocomial C. difficile infections since proper sanitation procedures can be utilized with susceptible patients. This will save both the hospital and patients money and time and improve healthcare outcomes overall. The thesis was focused on the United States (U.S) healthcare system from a broader perspective. Specifically, key actors of the U.S. healthcare system were identified in order to most properly depict the system and identify reasons why the U.S. spends the most on healthcare out of any country, yet ranks relatively low in healthcare metrics such as mean life expectancy. Case studies were then performed on the Canadian healthcare system and the Swedish healthcare system. The healthcare system networks were first described, and then unique aspects contributing to the successes of their respective healthcare systems were identified. Some of these ideas include a small, universal healthcare plan, increasing the government’s role in healthcare, and creating more emphasis on preventative healthcare in various aspects of society. These ideas would shift the current healthcare network, but not so significantly that the solutions should be deemed unrealistic, as detailed in the thesis. Overall, by completing the technical paper, I learned how to utilize the engineering design process from start to finish. I have learned how to build a device from scratch, keeping the long-term clinical application in mind while accomplishing short-term experiments and deliverables. Additionally, I have learned how to combine various technologies into one integrated product that has potential for even further scientific discoveries. With the STS thesis, I have learned how to utilize various social theories and methodologies to identify problems within the macroscale healthcare system. More importantly, I have learned how to apply these frameworks and analytical methods to be able to provide realistic suggestions for healthcare improvement.
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 | 0,005 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,003 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
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 ».