Is Real-Time Feedback of Burn-Specific Patient-Reported Outcome Measures in Clinical Settings Practical and Useful? A Pilot Study Implementing the Young Adult Burn Outcome Questionnaire
Notice bibliographique
Résumé
Long-term follow-up care of survivors after burn injuries can potentially be improved by the application of patient-reported outcome measures (PROMs). PROMs can inform clinical decision-making and foster communication between the patient and provider. There are no previous reports using real-time, burn-specific PROMs in clinical practice to track and benchmark burn recovery over time. This study examines the feasibility of a computerized, burn-specific PROM, the Young Adult Burn Outcome Questionnaire (YABOQ), with real-time benchmarking feedback in a burn outpatient practice. The YABOQ was redesigned for formatting and presentation purposes using images and transcribed to a computerized format. The redesigned questionnaire was administered to young adult burn survivors (ages 19-30 years, 1-24 months from injury) via an ipad platform in the office before outpatient visits. A report including recovery curves benchmarked to a nonburned relatively healthy age-matched population and to patients with similar injuries was produced for the domains of physical function and social function limited by appearance. A copy of the domain reports as well as a complete copy of the patient's responses to all domain questions was provided for use during the clinical visit. Patients and clinicians completed satisfaction surveys at the conclusion of the visit. Free-text responses, included in the satisfaction surveys, were treated as qualitative data adding contextual information about the assessment of feasibility. Eleven patients and their providers completed the study for 12 clinical visits. All patients found the ipad survey and report "easy" or "very easy" to use. In nine instances, patients "agreed" or "strongly agreed" that it helped them communicate their situation to their doctor/nurse practitioner. Patients "agreed" or "strongly agreed" that the report helped them understand their course of recovery in 10 visits. In 11 visits, the patients "agreed" or "strongly agreed" that they would recommend this feedback to others. Qualitative comments included: "it helped organize my thoughts of recovery," "it opened lines of communication with the doctor," "it showed me how far I have come, and how far I need to go," and "it raised questions I would not have thought of." Only four of 12 provider surveys agreed that it helped them understand a patient's condition; however, in two visits, the providers stated that it helped identify a pertinent clinical issue. During two visits, providers stated that a treatment plan was discussed or recommended based on the survey results. Separately, qualitative comments from the providers included "survey was not sensitive enough to identify that this patient needed surgery for their scars." This is the first report describing clinical use of a burn-specific patient reported outcome measure. Real-time feedback using the ipad YABOQ was well received for the most part by the clinicians and burn survivors in the outpatient clinic setting. The information provided by the reports can be tested in a future randomized controlled clinical study evaluating impacts on physician decisions.
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 | 0,018 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».