THE MY HIP & KNEE APP: OUTCOMES AND EXPERIENCES OF 5,433 PATIENTS
Notice bibliographique
Résumé
With the expansion of virtual care since the COVID-19 Pandemic, there has also been increasing interest in the use of digital adjuncts to improve the perioperative patient care experience. We have used a digital application (i.e. myHip&Knee) to facilitate post-operative recovery following total hip replacement (THR) and total knee replacement (TKR) at our centre since 2015. In this study, we aimed to summarize patient outcomes and experience with the App. All patients undergoing primary THR and TKR at our centre were encouraged to download and use the digital ‘App’ on their mobile phones, tablets or via the web application. The App comprises a pre-operative program and a 42-day post-operative program, including daily health checks with personalized feedback that helps the patient track their recovery as well as an educational library (with information provided via text, images, and video media). Self-reported range-of-motion measurements, pain scores, and medication usage were captured daily. We summarized this information utilizing descriptive statistics. A total of 5433 patients used the App since 2015, representing 42.5% of all patients undergoing surgery during that time period. Most patients were between 65 and 74 years of age (40.3%), and 62.2% were female. Of these patients, 2575 (47.4%) underwent THR and 2858 (52.6%) underwent TKR. Among THR patients, resting pain scores peaked on day 1 at a mean score of 2.6 (out of 10) at rest and 5.1 with exercise, while maximum daily opioid use peaked on day 2 at 18.4mg morphine equivalents. Among TKR patients, resting pain scores peaked on day 1 at mean score of 3.7 (out of 10) and pain with exercise peaked at day 1 at 6.2; however, maximum daily opioid use occurred on day 3, with a mean daily use of 34.6mg morphine equivalents. Mean flexion exceeded 100 degrees and began to plateau at 24 days post-operatively. Mean Extension fell below 5 degrees and began to plateau at 12 days post-operatively,. Overall, 98% of patients found the App useful during recovery, and 66% reported that it prevented at least one phone call to their surgeon's office/hospital. Both pain and opioid usage were lower following THR than TKR. Among TKR patients, extension and flexion gains occurred rapidly and plateaued at an average of 2 and 3.5 weeks, respectively. These data provide key insights for health care providers in terms of the ‘normal’ course of recovery following THR and TKR. In addition, high rates of satisfaction, perceived benefit, and data collection can be achieved with the use of well-designed mobile App.
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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 | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| 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 ».