The Michigan Spine Surgery Improvement Collaborative: a statewide Collaborative Quality Initiative
Notice bibliographique
Résumé
OBJECT Given the scrutiny of spine surgery by policy makers, spine surgeons are motivated to demonstrate and improve outcomes, by determining which patients will and will not benefit from surgery, and to reduce costs, often by reducing complications. Insurers are similarly motivated. In 2013, Blue Cross Blue Shield of Michigan (BCBSM) and Blue Care Network (BCN) established the Michigan Spine Surgery Improvement Collaborative (MSSIC) as a Collaborative Quality Initiative (CQI). MSSIC is one of the newest of 21 other CQIs that have significantly improved-and continue to improve-the quality of patient care throughout the state of Michigan. METHODS MSSIC focuses on lumbar and cervical spine surgery, specifically indications such as stenosis, disk herniation, and degenerative disease. Surgery for tumors, traumatic fractures, deformity, scoliosis, and acute spinal cord injury are currently not within the scope of MSSIC. Starting in 2014, MSSIC consisted of 7 hospitals and in 2015 included another 15 hospitals, for a total of 22 hospitals statewide. A standardized data set is obtained by data abstractors, who are funded by BCBSM/BCN. Variables of interest include indications for surgery, baseline patient-reported outcome measures, and medical history. These are obtained within 30 days of surgery. Outcome instruments used include the EQ-5D general health state score (0 being worst and 100 being the best health one can imagine) and EQ-5D-3 L. For patients undergoing lumbar surgery, a 0 to 10 numeric rating scale for leg and back pain and the Oswestry Disability Index for back pain are collected. For patients undergoing cervical surgery, a 0 to 10 numeric rating scale for arm and neck pain, Neck Disability Index, and the modified Japanese Orthopaedic Association score are collected. Surgical details, postoperative hospital course, and patient-reported outcome measures are collected at 90-day, 1-year, and 2-year intervals. RESULTS As of July 1, 2015, a total of 6397 cases have been entered into the registry. This number reflects 4824 eligible cases with confirmed surgery dates. Of these 4824 eligible cases, 3338 cases went beyond the 120-day window and were considered eligible for the extraction of surgical details, 90-day outcomes, and adverse events. Among these 3338 patients, there are a total of 2469 lumbar cases, 862 cervical cases, and 7 combined procedures that were entered into the registry. CONCLUSIONS In addition to functioning as a registry, MSSIC is also meant to be a platform for quality improvement with the potential for future initiatives and best practices to be implemented statewide in order to improve quality and lower costs. With its current rate of recruitment and expansion, MSSIC will provide a robust platform as a regional prospective registry. Its unique funding model, which is supported by BCBSM/BCN, will help ensure its longevity and viability, as has been observed in other CQIs that have been active for several years.
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 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 | 0,076 | 0,076 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,005 | 0,009 |
| Études des sciences et des technologies | 0,006 | 0,003 |
| Communication savante | 0,009 | 0,005 |
| Science ouverte | 0,005 | 0,020 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,010 | 0,002 |
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 ».