title: Impact of changes in reimbursement policies and institutional practice algorithm for utilization of erythropoietic-stimulating agents on treatment patterns and costs in anemic lymphoma patients.
abstract: OBJECTIVE
  The objective of this study was to assess the impact of a new evidence-based institutional practice algorithm on the patterns and costs of treatment of chemotherapy-induced anemia (CIA) in lymphoma patients prescribed erythropoietic-stimulating agents (ESAs).
  
  
  METHODS
  The study design was retrospective, with a historical control group. Patient demographic data, clinical data (including chemotherapy and hemoglobin values), and cost data were extracted from patient medical charts and institutional databases. Descriptive statistics, t tests, and chi-square analyses were conducted to evaluate the study objectives.
  
  
  RESULTS
  The study population consisted of 154 patients, 90 patients in the pre-implementation group and 64 in the post-implementation group. Both groups had similar demographic and baseline clinical characteristics. After implementation, there was a significant decrease in the mean hemoglobin level at the time of subsequent ESA dosing from 9.59 to 8.98 g/dL (P < 0.0001). The proportion of patients who received an ESA at a hemoglobin level >10 g/dL decreased significantly from 66% to 17% (P < 0.0001). There was no significant difference in the mean hemoglobin level at week 4 of ESA therapy, which may indicate that patients were not clinically affected by the change in practice. There were also no significant differences in the number of transfusions administered associated with the treatment of CIA in the study population.
  
  
  CONCLUSIONS
  The results of the study show an association between implementation of the new institutional practice algorithm for ESA usage in CIA and a change in ESA utilization patterns.
authors.affiliation: Division of Pharmacy, Unit 90, University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd, Houston, TX 77030, USA. llal@mdanderson.org
authors.forename: Lincy Subha
authors.initials: LS
authors.lastname: Lal
authors.forename: Aditya
authors.initials: A
authors.lastname: Raju
authors.forename: Lesley-Ann
authors.initials: LA
authors.lastname: Miller
authors.forename: Hua
authors.initials: H
authors.lastname: Chen
authors.forename: Rebecca
authors.initials: R
authors.lastname: Arbuckle
authors.forename: Sujit S
authors.initials: SS
authors.lastname: Sansgiry
mesh_terms: D000368:Aged; D000465:Algorithms; D000740:Anemia / Q000139:chemically induced / Q000188:drug therapy* / Q000191:economics; D000970:Antineoplastic Agents / Q000009:adverse effects / Q000191:economics / Q000627:therapeutic use; D014487:Centers for Medicare and Medicaid Services, U.S. / Q000592:standards; D003362:Cost-Benefit Analysis; D018450:Disease Progression; D005260:Female; D006291:Health Policy; D006397:Hematinics / Q000008:administration & dosage / Q000009:adverse effects / Q000191:economics*; D006801:Humans; D007349:Insurance, Health, Reimbursement; D008223:Lymphoma / Q000097:blood* / Q000188:drug therapy / Q000191:economics; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D016019:Survival Analysis; D013781:Texas; D014481:United States
chemical_list: D000970:Antineoplastic Agents; D006397:Hematinics