title: Frequency of hospitalizations prior to and after conversion to a rebate pharmaceutical in depression patients in Germany.
abstract: BACKGROUND
  The aim of this study was to investigate the frequency of hospitalization in depression patients with and without conversion to a rebate pharmaceutical and to show the negative consequences of rebate contracts on the health of patients with depression.
  
  
  METHODS
  This retrospective study was performed using two databases that included data on ~ 10 millions patients gathered between July 2009 and June 2012. This study included adults (> 18 years) on an antidepressive drug therapy who had statutory health insurance with rebate contracts on antidepressive pharmaceuticals.
  
  
  RESULTS
  In total, 47,968 patients on an antidepressive drug therapy were included in the persistence analysis using the IMS Disease Analyzer database. Of those, 26,651 patients were converted to a rebate product whereas 21,317 patients continued with the initial pharmaceutical product. After adjusting for the majority of demographic and clinical variables, the risk of hospitalization was 57% higher in patients who switched to a rebate pharmaceutical in comparison to patients who did not. When projected to the national level, this was found to equal an additional 34,157 patients hospitalized due to conversion to a rebate pharmaceutical resulting in direct inpatient costs amounting to 363.8 million EUR per year in Germany.
  
  
  CONCLUSIONS
  Despite some limitations, this analysis presents a clear association between the initiation of rebate contracts and a negative impact on the health of patients on an antidepressive drug therapy.
authors.affiliation: IMS Health, Frankfurt am Main, Germany. kkostev@de.imshealth.com
authors.forename: Karel
authors.initials: K
authors.lastname: Kostev
authors.forename: Uwe
authors.initials: U
authors.lastname: May
authors.forename: Christian
authors.initials: C
authors.lastname: Ott
authors.forename: Marc
authors.initials: M
authors.lastname: Paul
authors.forename: Klaus
authors.initials: K
authors.lastname: Schetschok
authors.forename: Malte
authors.initials: M
authors.lastname: Tingelhoff
authors.forename: Carolin
authors.initials: C
authors.lastname: Claus
authors.forename: Lilia
authors.initials: L
authors.lastname: Waehlert
mesh_terms: D000368:Aged; D000928:Antidepressive Agents / Q000009:adverse effects / Q000191:economics / Q000627:therapeutic use*; D003284:Contract Services / Q000191:economics; D003863:Depression / Q000175:diagnosis / Q000188:drug therapy* / Q000191:economics / Q000453:epidemiology; D016527:Drug Costs; D057915:Drug Substitution / Q000009:adverse effects / Q000191:economics; D005260:Female; D005858:Germany / Q000453:epidemiology; D017721:Hospital Costs; D006760:Hospitalization / Q000191:economics; D006801:Humans; D007349:Insurance, Health, Reimbursement / Q000191:economics; D007356:Insurance, Pharmaceutical Services / Q000191:economics; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D012044:Regression Analysis; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D016896:Treatment Outcome
chemical_list: D000928:Antidepressive Agents