Venous Thromboembolism: A United States Cost Model for a Preventable and Costly Adverse Event,
Notice bibliographique
Résumé
Abstract Abstract 4224 Introduction. Venous thromboembolism (VTE) is comprised of deep vein thrombosis (DVT) and pulmonary embolism (PE). VTE is a common cause of serious morbidity and mortality associated predominantly with hospitalization. The concept of “preventable” DVT has recently emerged in the medical literature. VTE remains the number one cause of preventable death in hospitalized patients. To date, VTE costs at a United States (US) national level for total costs, hospital-acquired costs, and “preventable” hospital-acquired costs have not yet been well-defined. Recently, investigators have defined US annual total, hospital-acquired, and preventable DVT costs ranged from $7.5 to $39.5 billion, $5 to $26.5 billion, and $2.5 to $19.5 billion, respectively, in 2010 US dollars. When a multi-way sensitivity analysis was applied, taking into consideration higher incidence rates and costs, annual US total, hospital-acquired, and “preventable” DVT costs ranged from $9.8 to $52 billion, $6.8 to $36 billion, and $3.4 to $27 billion, respectively. In addition, it was estimated that the US annual prophylaxis cost of at-risk patients is less than $600 million per year. PE costs have not yet been defined within the US. Defining PE costs would allow for definition of total US VTE costs on an annual basis. Methods. The authors undertook a thorough research review to identify morbidities, incident rates of morbidities, costs of morbidities and incidences of death associated with PE. Identified references were then hand-searched to ensure no pertinent publications had been overlooked. A decision tree and cost model were developed to estimate the United States healthcare costs for PE, total hospital-acquired PE, and total “preventable” PE. The decision tree contains probability information on: PE's that are hospital-acquired or community-acquired; fatal vs. non-fatal; readmissions; VTE recurrence; minor bleed; major bleed; heparin induced thrombocytopenia; chronic thromboembolic pulmonary hypertension; and resolution of symptoms. Based on the decision tree, a cost model with calculations performed via Microsoft Office Excel was developed. The cost model contains all potential outcomes, representing all branches, to reflect all possible outcomes for a PE patient. The product of each outcome's probabilities and costs yields the average cost of a patient going down that respective path of the PE decision tree. Similarly, each branch contains a sum that reflects the average cost of a patient in that branch. Results. Preliminary estimates of US annual direct total, hospital-acquired, and preventable PE costs are likely to range (at a minimum) from $5 to $27 billion, $2.5 to $18 billion, and $2.1 to $15.4 billion, respectively, in 2010 US dollars. Indirect costs, primarily from death due to PE, are estimated to be a minimum of $19.5 billion per year with approximately $11 billion per year of this being “preventable.” A multi-way sensitivity analysis will be applied which will take into consideration higher incidence rates and costs. Final results of the cost analysis, with the multi-way sensitivity analysis will be presented. Preliminary estimates suggest minimum total annualized, direct, VTE costs of approximately $12.5 to $66 billion per year with a minimum of $4.6 to $34.9 billion per year being “preventable.” When factoring in the indirect costs of $11 billion per year, minimum, “preventable” VTE costs within the US appear to range from $15.6 to $45.9 billion per year. Final results of the cost analysis with the multi-way sensitivity analysis will be presented. Conclusions. Considerable savings and reduced morbidity and mortality could be realized if improved prevention rates were achieved and systems were implemented throughout the US. To date, US VTE costs have been underestimated. The DVT and PE cost models may be applied to estimate costs in the European Union and other countries. VTE prophylaxis is cost effective and may be a good target for healthcare savings with healthcare reform on the horizon. Mandating VTE quality measures, such as those from the Joint Commission and National Quality Forum, would expedite reducing health care costs and reduce unnecessary morbidity and mortality. Disclosures: No relevant conflicts of interest to declare.
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 | 0,004 | 0,013 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,004 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
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 ».