Implementation of Surgical Site Infection (SSI) Gap Analysis and Data Visualization Dashboards to Drive Organizational Change
Notice bibliographique
Résumé
Background: Surgical site infections (SSIs) are a major healthcare quality issue; they lead to increased morbidity and mortality rates. They also prolong the length of stay and increase the cost to the patient and the healthcare system. Depending on the procedure, the risk of death is 2 to 11 times greater for patients with an SSI than for patients without an SSI. Additionally, the financial burden and patient burden is considerable; it ranks as the most common and costly of hospital-acquired infections (HAIs) and can extend a patient’s length of stay by 11.2 days. The risk of developing an SSI is affected by multiple factors at the patient, operative, and institutional levels. Methods: A Midwestern healthcare system conducted a review of the recommended best-practice guidelines that are currently accepted as the standards of care in US healthcare facilities. A gap analysis instrument for colorectal SSI prevention was drafted and reviewed for content validity and accuracy by field experts. Hospital infection preventionists worked in conjunction with operating room leaders to disseminate the survey to staff. Responses were collected from June 5 to June 30, 2019. Concurrently, the system infection preventionist team developed a standardized SSI dashboard template that could be used at the hospital, regional, and system level to visualize SSI infection counts, standardized infection ratios (SIRs) as well as procedure count data. These dashboard reports are updated and distributed on a monthly basis to each hospital’s campus executive team and other leaders. Federal- and state-required procedures were included and additional procedures were included based on hospital risk. Results: In total, 35 responses were recorded from 8 ministries across the system. Infection preventionists, operating room directors, physicians, nurses, and surgical technologists were represented among the respondents. The following areas were identified areas for improvement: use of chlorhexidine gluconate (CHG) bathing kit, mechanical bowel preparation with preoperative oral antibiotics, hair removal practices, use of fascial wound protector, maintenance of patients’ blood glucose levels, glove and gown changing procedures, and use of antimicrobial-coated sutures. The development and distribution of the SSI dashboard increased awareness and knowledge of SSIs by hospital and system-level leaders. Conclusions: The implementation of both the gap analysis and dashboard reports improved the awareness areas needed for improvement and knowledge of the burden of SSIs. These findings will drive discussions within the hospitals and at the system-level to implement evidence-based practice to improve care and decrease infections as well as guide the development of SSI patient care bundles. Funding: None Disclosures: None
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 | 0,001 | 0,001 |
| 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 | 0,000 | 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) | 0,001 | 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 ».