Patented drug extension strategies on healthcare spending: a cost-evaluation analysis.

BACKGROUND: Drug manufacturers have developed "evergreening" strategies to compete with generic medication after patent termination. These include marketing of slightly modified follow-on drugs. We aimed to estimate the financial impact of these drugs on overall healthcare costs and also to examine the impact of listing these drugs in hospital restrictive drug formularies (RDFs) on the healthcare system as a whole ("spillover effect"). METHODS AND FINDINGS: We used hospital and community pharmacy invoice office data in the Swiss canton of Geneva to calculate utilisation of eight follow-on drugs in defined daily doses between 2000 and 2008. "Extra costs" were calculated for three different scenarios assuming replacement with the corresponding generic equivalent for prescriptions of (1) all brand (i.e., initially patented) drugs, (2) all follow-on drugs, or (3) brand and follow-on drugs. To examine the financial spillover effect we calculated a monthly follow-on drug market share in defined daily doses for medications prescribed by hospital physicians but dispensed in community pharmacies, in comparison to drugs prescribed by non-hospital physicians in the community. Estimated "extra costs" over the study period were €15.9 (95% CI 15.5; 16.2) million for scenario 1, €14.4 (95% CI 14.1; 14.7) million for scenario 2, and €30.3 (95% CI 29.8; 30.8) million for scenario 3. The impact of strictly switching all patients using proton-pump inhibitors to esomeprazole at admission resulted in a spillover "extra cost" of €330,300 (95% CI 276,100; 383,800), whereas strictly switching to generic cetirizine resulted in savings of €7,700 (95% CI 4,100; 11,100). Overall we estimated that the RDF resulted in "extra costs" of €503,600 (95% CI 444,500; 563,100). CONCLUSIONS: Evergreening strategies have been successful in maintaining market share in Geneva, offsetting competition by generics and cost containment policies. Hospitals may be contributing to increased overall healthcare costs by listing follow-on drugs in their RDF. Therefore, healthcare providers and policy makers should be aware of the impact of evergreening strategies.

Modelling the impact of antibiotic use on antibiotic-resistant Escherichia coli using population-based data from a large hospital and its surrounding community.

OBJECTIVES: To determine the temporal relationship between antibiotic use and incidence of antibiotic-resistant Escherichia coli in both the inpatient and outpatient setting of a large urban area. METHODS: A retrospective observational time-series analysis was performed to evaluate the incidence of non-duplicate clinical isolates of E. coli resistant to ciprofloxacin, trimethoprim/sulfamethoxazole and cefepime from January 2000 through December 2007, combined with a transfer function model of aggregated data on antibiotic use in both settings obtained from the hospital's pharmacy and outpatient billing offices. RESULTS: Ciprofloxacin resistance increased from 6.0% (2000) to 15.4% (2007; P<0.0001) and cefepime resistance from 0.9% (2002) to 3.2% (2007; P=0.01). Trimethoprim/sulfamethoxazole resistance remained stable (23.7%-25.8%). Total antibiotic use increased in both settings, while fluoroquinolone use increased significantly only among outpatients. A temporal effect between fluoroquinolone resistance in community E. coli isolates and outpatient use of ciprofloxacin (immediate effect and time lag 1 month) and moxifloxacin (time lag 4 months) was observed, explaining 51% of the variance over time. The incidence of cefepime resistance in E. coli was correlated with ciprofloxacin use in the inpatient (lag 1 month) and outpatient (lag 4 months) settings and with the use of ceftriaxone (lag 0 month), piperacillin/tazobactam (3 months) and cefepime (3 months) in the hospital (R2=51%). CONCLUSIONS: These results support efforts to reduce prescribing of fluoroquinolones for control of resistant E. coli including extended-spectrum ß-lactamase producers and show the added value of time-series analysis to better understand the interaction between community and hospital antibiotic prescribing and its spill-over effect on antibiotic resistance.