“A Phenomenal Person and Doctor”: Thank You Letters to Medical Care Providers
Notice bibliographique
Résumé
BACKGROUND: Thank you letters to physicians and medical facilities are an untapped resource, providing an invaluable glimpse into what patients notice and appreciate in their care. OBJECTIVE: The aim of this study was to analyze such thank you letters as posted on the Web by medical institutions to find what patients and families consider to be good care. In an age of patient-centered care, it is pivotal to see what metrics patients and families apply when assessing their care and whether they grasp specific versus general qualities in their care. METHODS: Our exploratory inquiry covered 100 thank you letters posted on the Web by 26 medical facilities in the United States and the United Kingdom. We systematically coded and descriptively presented the aspects of care that patients and their families thanked doctors and medical facilities for. We relied on previous work outlining patient priorities and satisfaction (Anderson et al, 2007), to which we added a distinction between global and specific evaluations for each of the already existing categories with two additional categories: general praise and other, and several subcategories, such as treatment outcome, to the category of medical care. RESULTS: In 73% of the letters (73/100), physicians were primarily thanked for their medical treatment. In 71% (71/100) of the letters, they were thanked for their personality and demeanor. In 52% cases (52/100), these two aspects were mentioned together, suggesting that from the perspective of patient as well as the family member, both are deemed necessary in positive evaluation of medical care. Only 8% (8/100) of the letters lacked reference to medical care, personality or demeanor, or communication. No statistically significant differences were observed in the number of letters that expressed gratitude for the personality or demeanor of medical care providers versus the quality of medical care (χ21, N=200=0.1, not statistically significant). Letters tended to express more specific praise for personality or demeanor, such as being supportive, understanding, humane and caring (48/71, 68%) but more general praise for medical care (χ21, N=424=63.9, P<.01). The most often mentioned specific quality of medical care were treatment outcomes (30/73, 41%), followed by technical competence (15/73, 21%) and treatment approach (14/73, 19%). A limitation of this inquiry is that we analyzed the letters that medical centers chose to post on the Web. These are not necessarily a representative sample of all thank you letters as are sent to health care institutions but are still indicative of what centers choose to showcase on the Web. CONCLUSIONS: Physician demeanor and quality of interaction with patients are pivotal in how laymen perceive good care, no less so than medical care per se. This inquiry can inform care providers and medical curricula, leading to an improvement in the perceived quality of care.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,078 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,003 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,007 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 tête enseignante, 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 ».