Association of hematopoietic cell transplantation-specific comorbidity index with resource utilization after allogeneic transplantation

Comorbidities affect clinical outcomes and costs in medicine. The hematopoietic cell transplantation (HCT)-specific comorbidity index (HCT-CI) predicts mortality risk after HCT. Its association with resource utilization (RU) is unknown. In this single-center, retrospective study, we examined the ass...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Bone marrow transplantation (Basingstoke) 2017-07, Vol.52 (7), p.998-1002
Hauptverfasser: Decook, L, Chang, Y-H, Slack, J, Gastineau, D, Leis, J, Noel, P, Palmer, J, Sproat, L, Sorror, M, Khera, N
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Comorbidities affect clinical outcomes and costs in medicine. The hematopoietic cell transplantation (HCT)-specific comorbidity index (HCT-CI) predicts mortality risk after HCT. Its association with resource utilization (RU) is unknown. In this single-center, retrospective study, we examined the association of HCT-CI with RU (readmissions, length of hospital stay (LOS) and days out of hospital alive (DOHA)) in first 100 days ( n =328) and 1 year ( n =226) in allogeneic HCT patients from January 2010 to June 2014. Age, disease risk, conditioning and use of antithymocyte globulin were significantly different in the four groups with HCT-CI 0 to1 ( n =138), 2 ( n =56), 3 ( n =55) or ⩾4 ( n =79). Although the readmissions were higher in the first 100 days for patients with HCT-CI >0–1 ( P =0.03), they were not significantly different in patients over 1 year ( P =0.13). In the multivariable analysis, patients with HCT-CI score of >0 to 1 had increased LOS and fewer DOHA in both 100 days and 1 year after HCT. In this exploratory analysis, we found that HCT-CI >0 to 1 is associated with increased RU after allogeneic HCT. Recognizing predictors of RU can identify patients at risk of high utilization and help understand what drives health-care costs.
ISSN:0268-3369
1476-5365
DOI:10.1038/bmt.2017.70