Patient-Reported Opioid Consumption and Pain Intensity After Common Orthopedic and Urologic Surgical Procedures With Use of an Automated Text Messaging System
Notice bibliographique
Résumé
Importance: Surgeons must balance management of acute postoperative pain with opioid stewardship. Patient-centered methods that immediately evaluate pain and opioid consumption can be used to guide prescribing and shared decision-making. Objective: To assess the difference between the number of opioid tablets prescribed and the self-reported number of tablets taken as well as self-reported pain intensity and ability to manage pain after orthopedic and urologic procedures with use of an automated text messaging system. Design, Setting, and Participants: This quality improvement study was conducted at a large, urban academic health care system in Pennsylvania. Adult patients (aged ≥18 years) who underwent orthopedic and urologic procedures and received postoperative prescriptions for opioids were included. Data were collected prospectively using automated text messaging until postoperative day 28, from May 1 to December 31, 2019. Main Outcomes and Measures: The primary outcome was the difference between the number of opioid tablets prescribed and the patient-reported number of tablets taken (in oxycodone 5-mg tablet equivalents). Secondary outcomes were self-reported pain intensity (on a scale of 0-10, with 10 being the highest level of pain) and ability to manage pain (on a scale of 0-10, with 10 representing very able to control pain) after orthopedic and urologic procedures. Results: Of the 919 study participants, 742 (80.7%) underwent orthopedic procedures and 177 (19.2%) underwent urologic procedures. Among those who underwent orthopedic procedures, 384 (51.8%) were women, 491 (66.7%) were White, and the median age was 48 years (interquartile range [IQR], 32-61 years); 514 (69.8%) had an outpatient procedure. Among those who underwent urologic procedures, 145 (84.8%) were men, 138 (80.7%) were White, and the median age was 56 years (IQR, 40-67 years); 106 (62%) had an outpatient procedure. The mean (SD) pain score on day 4 after orthopedic procedures was 4.72 (2.54), with a mean (SD) change by day 21 of -0.40 (1.91). The mean (SD) ability to manage pain score on day 4 was 7.32 (2.59), with a mean (SD) change of -0.80 (2.72) by day 21. The mean (SD) pain score on day 4 after urologic procedures was 3.48 (2.43), with a mean (SD) change by day 21 of -1.50 (2.12). The mean (SD) ability to manage pain score on day 4 was 7.34 (2.81), with a mean (SD) change of 0.80 (1.75) by day 14. The median quantity of opioids prescribed for patients who underwent orthopedic procedures was high compared with self-reported consumption (20 tablets [IQR, 15-30 tablets] vs 6 tablets used [IQR, 0-14 tablets]), similar to findings for patients who underwent urologic procedures (7 tablets [IQR, 5-10 tablets] vs 1 tablet used [IQR, 0-4 tablets]). Over the study period, 9452 of 15 581 total tablets prescribed (60.7%) were unused. A total of 589 patients (64.1%) used less than half of the amount prescribed, and 256 patients (27.8%) did not use any opioids (179 [24.1%] who underwent orthopedic procedures and 77 [43.5%] who underwent urologic procedures). Conclusions and Relevance: In this quality improvement study of adult patients reporting use of opioids after common orthopedic and urologic surgical procedures through a text messaging system, the quantities of opioids prescribed and the quantity consumed differed. Patient-reported data collected through text messaging may support clinicians in tailoring prescriptions and guide shared decision-making to limit excess quantities of prescribed opioids.
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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 | 0,002 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 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 ».