Notice bibliographique
Résumé
Intensive care was initially developed with a raison d' être of “save a life.” As extracorporeal organ replacement therapy rapidly evolved, this attitude matured into concern about the function and quality of life (QOL) of survivors of ICU (1). Recognition that medical errors caused morbidity and mortality raised concerns about patient safety and led to an increased focus on adverse events and the quality of care delivered (2). Organization and regionalization of pediatric critical care services improved survival in children admitted to intensive care (3); likewise the organization of trauma care saved lives (4). Even in countries with well-developed systems of care, ongoing development and refinement is necessary, as the implementation of the London Trauma System in April 2010 highlights (5). In this issue of Pediatric Critical Care Medicine, Cooper et al (6) compare quality improvement (QI) practices in 184 trauma centers (adult, mixed adult and pediatric, and pediatric) in the United States, Canada, Australia, and New Zealand. The number of quality indicators recorded and used for adult, mixed, and pediatric trauma centers was 27, 23, and 26, respectively. The most commonly used activities for QI included morbidity and mortality conferences and quality of care audits. Report cards were used in approximately half the centers and internal (80%, 81%, and 68%) and external (78%, 78%, and 68%) benchmarking were also used. When QI was classified by phases of care, structure indicators were measured in approximately one third or less (36%, 17%, and 21%), but patient outcome indicators were measured by most centers (89%, 83%, and 95%). All trauma centers that measured QI also measured processes of care. Gruen et al (7) have recently reviewed “trauma system performance” and how we may evaluate the provision of effective and safe care for patients following an acute traumatic injury. These include the following: 1) How is the trauma system organized? 2) Which part of the system is being evaluated (prehospital, hospital, rehabilitation, or prevention)? 3) What is the purpose of the evaluation? 4) Which phase of the “trauma care” is being evaluated (structure, process, or outcome)? and 5) What patient outcome is being measured (mortality, function, or QOL)? Once these have been considered, we then need to decide whether we will review the entire system or an individual hospital performance and then address another fundamental question, namely, what makes a good quality indicator? The National Quality Forum (8) considered these following criteria as useful for a measure of quality 1) importance (relevant to a large number of patients or a large improvement in a few); 2) scientific acceptability with both reliability and validity (reliability is the ability for the indicator to produce the same result on repeated measures and validity is that the indicator measures what it intended); 3) feasibility (able to be done); and 4) usability (can be easily understood by the intended groups). There are a number of differences between adult and pediatric trauma. The relationship between the volume of patients treated and the outcome for complex diseases is well established, and the volume of trauma presenting to stand-alone pediatric trauma centers is often small. The type of injuries that children suffer differs significantly from adults (9), albeit adolescents tend to have adult-type injuries (10). The prevalence of head injury in patients admitted to intensive care after trauma is much higher in children than adults (11). These differences immediately create debate about whether the best system of care for children is a stand-alone pediatric program or as part of an adult program (9). The marked variation in the care of children with splenic injuries depending on the type of treating trauma center highlights this (12). As stated by Cooper et al (6), no attempt was made by their study to evaluate the actual QIs themselves. However, they did note some other differences between adult and pediatric centers, including the focus on QI for safety, medical errors, and adverse events in adults compared to timeliness, diagnosis, and monitoring in children. What quality indicators should we use? In 2009, a scoping review by Stelfox et al (13) looked at what quality indicators existed for the evaluation of trauma care and found many QIs (1,572) had been proposed; these were divided into eight categories: American College of Surgeons-Committee on Trauma (ACS-COT) audit filters (42%), ACS-COT audit filters (19%), patient safety indicators (13%), trauma center/system indicators (10%), measures of outcome (7.5%), peer review (5.5%), general audit measures (2%), and guideline presence and use (1%). Indicators related to the phase of care were prehospital and hospital processes (60%) and outcomes (23%), posthospital and secondary prevention less than 5%. Many QIs are used but while audit filters that monitor the timeliness of specific actions (such as time to surgery), diagnostic tests (such as CT scan), or expected outcomes are inherently appealing, unfortunately, they are not supported by evidence of benefit (14). However, a recent study shows that delay in operative intervention (craniotomy, intracranial pressure monitoring, and abdominal surgery) led to a longer ICU and hospital stay with no difference in mortality (15); this may or may not be considered beneficial depending on what your outcome measure may be! We can group the care in hospital into the well-established, three phases of care, namely, the structure of the system (availability of highly trained staff, resources available for care, ongoing education and training, etc.), the processes of care (time to CT, blood transfusion or urgent surgery, etc.), and the outcome of care (mortality or long-term quality). Clearly for critical illness in children including trauma, we are most concerned with patient outcome. Initially survival but increasingly long-term QOL is used as the measured outcome. Good outcomes occur with mild injuries, use of a proxy, and short-term follow-up whereas a much poorer QOL occurs with severe injuries and longer term follow-up (16). Other “non quality of care” factors can have a major influence on long-term outcome. These include the availability or lack of community and family and social supports (17). Also changes in societal religious and legal attitudes over time may lead to an improvement in mortality but at the cost of increased survival of children with major cognitive impairment, motor dysfunction, and difficulties with higher executive functions (18). It is imperative that we evaluate the quality of healthcare offered to all children especially after trauma. This study is yet another effort by Cooper et al (6) to continue to raise the broad issues and complexities of quality indicators and how they are recorded and how they vary widely. They continue to highlight the need for more research to determine and then measure simple robust indicators of quality of care that will allow further improvement in treatments offered to critically ill patients and hopefully translate into improved outcomes (long-term QOL) for patients and their families.
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 | 0,022 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 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 ».