Health Check: Analyzing Trends in West Michigan 2013
Notice bibliographique
Résumé
PURPOSE: Health Check provides an ongoing trend analysis of three major issues: Knowledge Foundations, Health Care Trends, and Economic Analysis. SUBJECTS: The focus of the study is on a four-county area - Kent, Ottawa, Muskegon, and Allegan (KOMA). METHODS AND MATERIALS: Understanding Knowledge Foundations provides information on the supply of future workers in healthcare. Analysis of graduation rates and jobs data details supply and demand for the local industry; medical patents give insight to local innovation. Understanding Health Care Trends is beneficial for preventative measures and areas to focus efforts on. The metrics used to monitor these trends include demographics, risk profiles, diseases, and overall health status. Economic Analysis provides comparable results to benchmark the industry’s economic growth in the region. The comparable data pieces include other medical cities similar to Grand Rapids, a hospital survey analysis, and cost analysis of major medical conditions with emphasis on diabetes. ANALYSIS: Data were collected and weighted accordingly for the specific region of interest, in this case KOMA, from several databases and governmental resources, and from Priority Health and Blue Cross Blue Shield. RESULTS: Education facilities are graduating students with healthcare degrees at a rate that will supply the market needs for the foreseeable future; in some cases, there is a surplus of graduates for specific programs. Medical patents are remaining steady thanks in part to the Van Andel Research Institute. Health care trends in West Michigan fall in line with national trends, some instances are more promising than others. As a community, obesity and diabetes is on the rise, along with asthma. Obesity is the largest challenge our healthcare system faces in the future, and the changing demographics will compound the issue. As an industry, the healthcare system in West Michigan is growing. This is a result of either an unhealthier population, a sign the industry is drawing from a greater geographic area, or an increase in healthcare access. In terms of being a medical tourist location, Grand Rapids is gaining ground, but still trails behind Cleveland. It is also cost effective to conduct all tests and evaluations on diabetes patients during upon an initial examination. Conclusion: It is apparent the healthcare system in West Michigan is alive and well, and will continue to meet the needs of the local population. The labor force is strong; the educational structures are intact; the demand for services will continue to grow as the baby boomers continue to age; diabetes and obesity will continue to plague the community and health care systems. It is well documented that as we age past 40, our body composition changes over time by replacing muscle with fat. This physiological effect will be a major contributor to the deterioration of the quality of life of an aging population without education, community involvement, and accessible healthcare.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 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 ».