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Enregistrement W2989880289 · doi:10.1182/blood-2019-124219

Use of Routine Bloodwork on General Internal Medicine Inpatients: A Retrospective Cohort Study

2019· article· en· W2989880289 sur OpenAlexaffabout
William K. Silverstein, Adina Weinerman, Rick Wang, Lisa K. Hicks, R. Sacha Bhatia, Wendy Levinson, Fahad Razak, Amol A. Verma

Notice bibliographique

RevueBlood · 2019
Typearticle
Langueen
DomaineHealth Professions
ThématiqueHealthcare cost, quality, practices
Établissements canadiensWomen in Science and Engineering Newfoundland and LabradorWomen's College HospitalSt. Michael's HospitalUniversity of TorontoUniversity Health NetworkHealth Sciences CentreSunnybrook Health Science Centre
Organismes subventionnairesnon disponible
Mots-clésMedicineRetrospective cohort studyIntensive care unitEmergency medicineCohortPopulationBlood transfusionCohort studyAnemiaInternal medicine

Résumé

récupéré en direct d'OpenAlex

Introduction Choosing Wisely (CW) recommendations in Canada and the United States advise against routine blood work on stable inpatients because it is unlikely to improve patient care, is associated with anemia and pain, and increases costs. While numerous local quality improvement initiatives have effectively reduced the use of routine blood work (RBW), no population-level analyses have assessed the use of RBW on hospitalized patients in the CW era. This study aimed to describe the use of RBW between 2010 and 2017 by physicians caring for General Internal Medicine (GIM) inpatients at 7 hospitals. We hypothesized that RBW use would decrease over time and that increased use of RBW would be associated with greater reductions in hemoglobin. Methods We performed a retrospective cohort study using the General Medicine Inpatient Initiative (GEMINI) database, based in Ontario, Canada. The GEMINI database contains clinical and administrative data for all patients admitted to a GIM service at seven hospitals (5 academic centres; 2 community hospitals) in Toronto and Mississauga. We included all patients included in the GEMINI database, admitted from April 1, 2010 (prior to CW Canada), to March 31, 2017 (3 years after CW Canada's launch). Patients were excluded if they were admitted with a bleeding diagnosis, underwent an endoscopic or surgical procedure, were admitted to an Intensive Care Unit, or were admitted to hospital for less than 72 hours or greater than 30 days. Patients that received a blood transfusion during the first 48 hours of admission, or did not have hemoglobin measured within their first 48 hours of admission were also excluded. Physicians were excluded if they were the most responsible physician (MRP) for fewer than 100 admissions. Our primary outcome was the mean volume of RBW ordered per patient per day by the MRP. RBW was defined as complete blood count, electrolytes, extended electrolytes, creatinine, liver panel, INR, or PTT. To examine changes in the distribution of RBW ordering over time, we report RBW use at the following physician percentiles: 10, 25, 50, 75, 90. Prior analyses of the relationship between RBW use and reduction in Hgb in hospital are confounded (sicker patients receive more bloodwork). To avoid this confounding, we examined change in Hgb among patients of physicians stratified by RBW use. Patients are quasirandomly allocated to physicians in GIM, and thus, observed differences can be attributed to physician practice, not patient factors. We report the mean change in Hgb as a continuous outcome, and also percentage of patients who experienced a clinically significant reduction in Hgb, which was prespecified as at least 10 g/L. Statistical significance was determined using Chi-square tests for categorical variables, and Kruskall-Wallis tests for continuous variables. Results We included 65,507 hospital admissions. The mean volume of RBW ordered per patient per day significantly decreased from 2010 to 2016, for all percentiles (p<0.001 for all percentiles; as an example: 7.23cc in 2010 to 6.17cc in 2016 for patients admitted to physicians in the 25-50th percentile) (Figure 1). The mean volume of RBW ordered per patient per day significantly decreased from 2010 to 2016 in all but one hospital (Figure 2). However, the spread between the 10th and 90th percentile physicians did not change much between 2010 (1.77cc/patient/day) and 2016 (1.84 cc/patient/day). There was a dose-response relationship between MRP use of RBW and reductions in patient Hgb (Table 1). Compared to patients of MRPs in the lowest 10% of RBW use, patients of physicians in the highest 10% had a greater mean reduction in Hgb (4.93 g/L vs 3.34 g/L, p<0.001), and were more likely to have a clinically significant reduction in Hgb (23.1% vs. 18.7%, p<0.001). Conclusion This large, multi-centre cohort study demonstrated that greater use of RBW on GIM inpatients was associated with clinically significant reductions in Hgb. To our knowledge, this is the first study to rigorously demonstrate that greater use of RBW may be associated with clinically meaningful reductions in Hgb, independent of patient-level confounding. We further found that RBW use decreased overall with time, and in 6 out of 7 hospitals, between 2010 and 2017. However, the spread between 10th and 90th percentile physicians has not changed, suggesting that opportunities still exist to reduce RBW use at both the hospital and physician level. 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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,003
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,346
Score d'incertitude au seuil0,688

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,003
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0020,004
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0010,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,378
Tête enseignante GPT0,505
Écart entre enseignants0,127 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations2
Publié2019
Routes d'admission2
Résumé présentoui

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