Direct All-Cause Health Care Costs Associated With Chronic Kidney Disease in Patients With Diabetes and Hypertension: A Managed Care Perspective
Notice bibliographique
Résumé
BACKGROUND: Diabetes and hypertension are the 2 major causes of endstage renal disease. The rate of chronic kidney disease (CKD) secondary to diabetes and/or hypertension is on the rise, and the related health care costs represent a significant economic burden. OBJECTIVE: To quantify from a health system perspective the incremental direct all-cause health care costs associated with a diagnosis of CKD in patients with diabetes and/or hypertension. METHODS: An analysis was conducted of medical claims and laboratory data with dates of service between January 1, 2000, and February 28, 2006, from a managed care database for approximately 30 million members enrolled in 35 health plans. Each patient's observation period began on the date of the first diabetes or hypertension diagnosis (index date) and ended on the earlier of the health plan disenrollment date or February 28, 2006. Inclusion criteria were continuous insurance coverage in the 6 months prior to the index date and during the observation period, age at least 18 years, and at least 2 claims less than 90 days apart with a primary or secondary diagnosis for diabetes or hypertension. Exclusion criteria were cancer, lupus, or organ transplantation or chemotherapy at any time during the observation period. CKD was defined as at least 1 claim with a primary or secondary diagnosis for CKD and at least 2 glomerular filtration rate values of below 60 milliliters per minute per 1.73 square meters of body surface area (60 mL/min/1.73 m(2)) at any time during the observation period. Bivariate and Tobit regression analyses were conducted to compare patients who developed CKD versus those who did not for annualized (per patient per month [PPPM] multiplied by 12) direct, all-cause, health care costs, defined as standardized net provider payments after subtraction of member cost-share. These costs consisted of outpatient services, inpatient services, and pharmacy claims. A subset analysis of the post-versus pre- CKD medical costs was also conducted for cohorts of patients with at least 60 days of observation before and after the development of CKD; that analysis measured both all-cause costs and costs for services directly related to CKD treatment (i.e., claims with a primary or secondary diagnosis of CKD or claims for dialysis services). RESULTS: 11,531 patients with diabetes, 74,759 patients with hypertension, and 4,779 patients with both conditions were identified, of whom 123 (1.1%), 1,137 (1.5%), and 712 (14.9%), respectively, developed CKD during the observation period. The CKD group was older than the no-CKD group in each cohort (mean ages for CKD vs. no-CKD were, respectively, diabetes only cohort: 60.7 vs. 49.9 years, P < 0.001; hypertension only cohort: 63.6 vs. 53.6 years, P < 0.001; diabetes and hypertension cohort: 63.4 vs. 61.8 years, P < 0.001). CKD was associated with significantly higher total direct all-cause health care costs, with unadjusted annualized per patient mean [median] cost differences of $11,814 [$6,895], $8,412 [$4,115], and $10,625 [$7,203], respectively (diabetes: $18,444 [$11,025] vs. $6,631 [$4,131], P < 0.001; hypertension: $14,638 [$7,817] vs. $6,226 [$3,703], P < 0.001; diabetes and hypertension: $21,452 [$13,840] vs. $10,827 [$6,637], P < 0.001). The largest driver of the all-cause mean cost difference associated with CKD for each cohort was hospitalization cost (diabetes: $6,410, P < 0.001; hypertension: $5,498, P < 0.001; diabetes and hypertension: $6,467, P < 0.001). Among patients developing CKD, all-cause mean [median] annualized costs increased significantly following CKD onset (increases for patients with diabetes: $8,829 [$4,899], P = 0.026; hypertension: $4,175 [$2,741], P = 0.004; diabetes and hypertension: $9,397 [$7,240], P < 0.001). In the post-CKD period, costs directly related to treatment of CKD accounted for 9%--19% of all-cause medical service costs--9.2% for patients with diabetes, 11.6% for patients with hypertension, and 18.8% for patients with both diabetes and hypertension. CONCLUSION: CKD was associated with significantly higher all-cause health care costs in managed care patients with diabetes and/or hypertension.
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) | 0,001 | 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 | 0,001 |
| 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 ».