Barriers and facilitators of following perioperative internal medicine recommendations by surgical teams: a sequential, explanatory mixed-methods study
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Résumé
BACKGROUND: Preoperative medical consultations add expense and burden for patients and the impact of these consults on patient outcomes is conflicting. Previous work suggests that 10-40% of preoperative medical consult recommendations are not followed. This limits measurement of the effect of perioperative medical consultation on patient outcomes and represents a quality gap, given the patient time and healthcare cost associated with consultation. We aimed to measure, characterize, and understand reasons for missed recommendations from preoperative medical consultation. METHODS: This explanatory, sequential mixed-methods study used chart audits followed by semi-structured interviews. Chart audit of consecutive patients seen in preoperative medical clinic were reviewed to measure the proportion and characterize the type of recommendations that were not completed ("missed"). This phase informed the interview participants and questions. The interview guide was developed using the Consolidated Framework for Implementation Research and the Theoretical Domains Framework. Template analysis was used to understand drivers and barriers of missed recommendations RESULTS: Chart audit included 255 patients (n=161, 63.1% female) seen in preadmission clinic between April 1 and April 30, 2019. 55.7% of patients had all recommendations followed (n=142). Postoperative anticoagulation management and postoperative cardiac biomarker surveillance recommendations were least commonly followed (50.0%, n=28, and 68.9%, n=82, respectively). Eighteen surgical team members were interviewed. Missed recommendations were both unintentional and intentional, and the key drivers differed by these categories. Unintentionally missed recommendations occurred due to individual-level factors (drivers: knowledge of the consultation note, lack of routine for reviewing the consultation note, and competing demands on time) and systems-level factors (driver: lack of role clarity). Intentionally missed recommendations occurred due to user error due (drivers: lack of knowledge of guidelines or evidence) and appropriate modifications (driver: need to adapt a preoperative plan for a complicated postoperative course). CONCLUSIONS: Only 55.7% of consult notes had all recommendations followed, suggesting a quality gap in perioperative medical care. Qualitative data suggests multiple drivers of missed recommendations that should be targeted to improve the efficiency of care for these patients.
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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 | 0,003 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,000 |
Scores machine (provisoires)
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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 découle