Can transformational programs aimed at improving hospital management, leadership, and productivity systems affect financial performance?
Notice bibliographique
Résumé
Introduction: Management, leadership, and productivity systems (MLPS) are some of the critical success factors of effective organizations and may be associated with hospital financial performance. As such, many hospitals aim to improve their MLPS and engage in transformational interventions or programs designed for this purpose. The objective of this study was to evaluate trends in financial key performance indicators (KPIs) for hospitals that underwent an MLPS transformational program and to benchmark these trends against matched peer hospitals. Methods: Target hospitals that completed an MLPS transformational program between 2006 and 2010 were identified in the GE Healthcare customer database. MLPS transformation was defined as substantial engagement (typically over a period of three years) in the disciplines of management, leadership, and/or productivity systems (e.g., programs aimed at performance excellence, process improvement, employee engagement, or operational rhythm). A national database of hospital information was obtained, including various demographic and organizational variables for a set of over 5,000 US-based hospitals and hospital systems. Financial KPIs indicative of hospital profitability and cost containment (operating margin and expense per discharge) for 2006 through 2010 were also obtained for the majority of hospitals. A total of 18 target hospitals (those that underwent MLPS transformation) had demographic and financial KPI data available, and each was matched to a peer group of US hospitals using demographic characteristics. Results: Most target hospitals had > 200 beds (67%) and were urban (83%) teaching (67%) institutions located primarily in the South (50%) and Northeast (44%) of the US. The target hospitals were matched to nearly 3,000 peers (range 21 to 1,273 peers per target hospital). Median percent change in operating margin among target hospitals between 2006 and 2010 was 125%, indicating substantial improvement in overall financial performance. Median percent change in expense per discharge for target hospitals was less than 3%, suggesting that they did not experience substantial increase in discharge-related costs between 2006 and 2010. Most of the target hospitals performed better than the median hospital among their peer set of matched hospitals: 78% (14 of 18) demonstrated a higher percent change in operating margin than their respective median peer, and 72% (13 of 18) of the target hospitals outperformed their median peer with a lower percent change in expense per discharge. Conclusion: Overall, between 2006 and 2010, the target hospitals, having undergone an MLPS transformational program, demonstrated improvements in financial performance as measured by profitability and cost containment indicators, and a majority performed better than their peers. MLPS transformational programs may have the potential to improve hospital financial performance as demonstrated by this analysis of financial KPI trends.
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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 | 0,000 |
| 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 | 0,001 | 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) | 0,000 | 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.
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