Assessing Potentially Inappropriate Prescribing in the Elderly Veterans Affairs Population Using the HEDIS 2006 Quality Measure
Notice bibliographique
Résumé
BACKGROUND: Studies have found that 20% to 25% of older patients receive drugs identified as inappropriate by the 1997 Beers criteria. After the addition of 22 new drugs to the 2003 Beers criteria, the National Committee on Quality Assurance convened an expert consensus panel to identify which drugs from the 2003 Beers criteria should always be avoided in the elderly. The resulting list of drugs to avoid was added to the 2006 Health Plan Employer Data and Information Set (HEDIS) to measure the quality of prescribing for the elderly. OBJECTIVE: To use HEDIS 2006 criteria to determine the rate of potentially inappropriate prescribing in the elderly (PIPE) and to determine if patient risk factors are similar to those found using Beers criteria. METHODS: This cross-sectional database study identified older patients receiving drugs included in the HEDIS 2006 criteria using national data from the Veterans Health Administration. Patients aged 65 years or older on October 1, 1999, with at least 2 outpatient visit days during fiscal year 2000, ending September 30, or outpatient visits in fiscal years 1999 and 2000 were included (N=1,096,361). Multivariable logistic regression analyses stratified by gender identified patient characteristics associated with increased risk of HEDIS 2006 drug exposure. Since oral estrogens were considered appropriate at the time of this study, they were excluded from the list of HEDIS 2006 drugs. RESULTS: Overall, 19.6% of older veterans were exposed to HEDIS 2006 drugs. 23.3% of older veteran women and 19.2% of older veteran men. The most commonly prescribed HEDIS 2006 drugs were antihistamines (received by 9.0% of men and 10.7% of women), opioid analgesics (received by 4.6% of men and 5.8% of women), and skeletal muscle relaxants (received by 4.3% of men and 5.3% of women). Propoxyphene was the most commonly used HEDIS 2006 drug, received by 4.5% of men and 5.7% of women, followed by diphenhydramine, received by 3.5% of men and 4.7% of women, and hydroxyzine, received by 3.2% of both men and women. Patients receiving 10 or more medications of any type were at greatest risk of exposure. Men were 8.2 times more likely to receive at least 1 HEDIS 2006 drug than those taking 1 to 3 drugs of any type (95% confidence interval [CI], 8.0-8.4), while women were 9.6 times more likely (95% CI, 8.2-11.2). CONCLUSIONS: Even though we included a slightly different list of drugs to avoid, results for the HEDIS 2006 measure were similar to those of the 1997 Beers criteria. The HEDIS 2006 drugs are commonly prescribed, and there is a distinct need for direct evidence linking HEDIS 2006 PIPE exposure to adverse patient outcomes. To reduce PIPE, it seems necessary to provide additional evidence for clinicians through the conducting of a well-designed study to assess patient outcomes associated with PIPE exposure as defined by the HEDIS criteria.
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 | 0,003 | 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 | 0,001 |
| 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.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».