Notice bibliographique
Résumé
crowding: crowdingFigureAn emergency department is a resource-limited environment that often has too much demand for too little supply of nearly everything, especially beds. Crowding has become the most pressing issue in our nation's emergency departments over the past two decades, with entire careers being devoted to solving this problem. One of those careers belongs to a former resident of mine, who took an administrative position in our hospital a few years ago. His primary goal is to improve ED throughput, the vogue term for moving patients out of ED hallways. It has been an uphill battle with many frustrations and hard-fought victories even with him regularly pleading our case to hospital administration. Our ED tried not to let crowding become the new normal, but I wonder if this has become a quagmire without a clear solution. Are we playing a zero-sum game? I recently happened upon an email thread that cleverly summarized the positions of the opposing parties in the ED crowding debate. If a hospital limits the number of elective admissions for procedures when there are too many ED holds, it risks a significant decrease in revenue while angering surgeons and cardiologists who are essential to maintaining the hospital's financial viability. Or it forces floor nurses to accept assignments for hallway patients. Countless exasperated emergency physicians and nurses have screamed that “their halls are just as good as ours,” but this just encourages floor nurses to quit, more beds to be closed, and ED crowding to worsen. Another idea is to limit or stop outside transfers of (insured) patients so that (uninsured) ED holds can be moved up to the floor, but this hurts the bottom line. Then there is the “build it and they will come” solution—increase the number of ED and inpatient beds. It seems intuitive that this would work. Twenty more floor beds for admissions would seem to be a great way to decompress an overburdened ED. Would this actually work? One example that argues against this hypothesis is something most of us deal with every day: traffic. Sitting in bumper-to-bumper traffic is the bane of many people's existence. Nothing is quite as likely to jack up your blood pressure as looking at an endless stream of tail lights. Traffic is a common political issue with many constantly asking for an increase in road capacity. As with ED beds, increasing the supply of a limited resource sounds like the perfect solution to make everyone's everyday life much better. Unfortunately, this is a beautiful hypothesis ruined by an ugly fact. A Fool's Errand Economists Matthew Turner, PhD, and Gilles Duranton, PhD, compared the amount of new road construction to the total miles driven over 20 years in Toronto and Philadelphia. Their research found a fascinating correlation: Increases in road construction had a one-to-one correlation with miles driven. If road capacity went up seven percent, the total amount of miles driven went up seven percent as well. Twelve percent more road capacity was associated with 12 percent more miles. Drs. Turner and Duranton named their finding the Fundamental Law of Road Congestion. Many seasoned emergency physicians have seen a similar effect with increases in the number of beds in their hospitals. More ED or inpatient beds might decompress the ED for a while, but it does not take long for word to get out on the street (or the internet) about how quickly you can now be seen at that hospital's ED, and more and more people will show up. A colleague of mine at another hospital went through something like this about five years ago when they increased the number of ED beds and physician staff. Everyone was pretty excited for a while, and it seemed to work. But then administration bragged on the local news about how they had decreased ED wait times. Shortly after this, their census blew up, holds increased, nurses got angry and quit, and they ended up in a bigger hole than when they started. This phenomenon is not lost on experienced hospital administrators either. Many veteran CEOs are loath to add more ED and inpatient beds just to lose more money, and EPs need to recognize their concerns. Adding more beds can be risky because they may be filled with patients incapable of paying their bills. It may seem heartless, but so is laying off hospital employees and cutting back services. If a hospital's financial bottom line is not sustainable, no one wins. The answer to ED crowding is likely a combination of many factors, the most painful of which for emergency physicians is to adjust their expectations. This is not to say EPs should give up or accept an unsafe practice environment, but they need to be open to the idea that spending a lot of money to increase bed capacity might be a fool's errand. The sustainable solution is likely the implementation of several processes that divert patients away from the ED during peak census, increase the efficiency of inpatient discharges, and mandate regular meetings of key players to monitor what is working and what is not. Dr. Cookis the program director of the emergency medicine residency at Palmetto Health Richland in Columbia, SC. He is also the founder of 3rd Rock Ultrasound (http://emergencyultrasound.com). Friend him atwww.facebook.com/3rdRockUltrasound, follow him on Twitter@3rdRockUS, and read his past columns athttp://bit.ly/EMN-Match.
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 | 0,000 | 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 | 0,000 | 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) | 0,051 | 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».