INTRODUCTION: Changes in drug treatment are frequently mandatory with hospital admission and discharge because hospital drug formularies are generally restricted to about 3000 drugs as compared to the many times this number - 62,000 in Germany - that are commercially available. Without computerised support, the process involved with switching drugs to a corresponding generic or a therapeutic equivalent is time-consuming and error-prone. METHODS: We have developed and tested a standardised interchange algorithm for subsequent implementation into a computerised decision support system that switches drugs to the corresponding generic or a therapeutic equivalent if they are not listed on the hospital drug formulary. RESULTS: The algorithm was retrospectively applied to the medication regimens of 120 patients (774 prescribed drugs containing 886 active ingredients) at their time of admission to surgical wards. Of the prescribed drugs, 52.8% (409/774) were part of the hospital drug formulary, thereby rendering a switch unnecessary. The 365 drugs not listed consisted of 392 active ingredients that were successfully switched to a corresponding generic (84.7%) or a therapeutic equivalent (10.2%). No specific switching procedures were defined for only 2.3% (20/886) of the active ingredients. In these cases, the drugs were either discontinued (4/20) or special drug classes, current diseases or co-medication required manual switching (8/20), or the drugs were continued unchanged and ordered from a wholesaler (8/20). CONCLUSION: Using a standardised interchange algorithm, pre-admission drug regimens can successfully be switched to drugs on a hospital drug formulary. These findings suggest that a computerised decision support system will likely be useful to support this important practice.
INTRODUCTION: Changes in drug treatment are frequently mandatory with hospital admission and discharge because hospital drug formularies are generally restricted to about 3000 drugs as compared to the many times this number - 62,000 in Germany - that are commercially available. Without computerised support, the process involved with switching drugs to a corresponding generic or a therapeutic equivalent is time-consuming and error-prone. METHODS: We have developed and tested a standardised interchange algorithm for subsequent implementation into a computerised decision support system that switches drugs to the corresponding generic or a therapeutic equivalent if they are not listed on the hospital drug formulary. RESULTS: The algorithm was retrospectively applied to the medication regimens of 120 patients (774 prescribed drugs containing 886 active ingredients) at their time of admission to surgical wards. Of the prescribed drugs, 52.8% (409/774) were part of the hospital drug formulary, thereby rendering a switch unnecessary. The 365 drugs not listed consisted of 392 active ingredients that were successfully switched to a corresponding generic (84.7%) or a therapeutic equivalent (10.2%). No specific switching procedures were defined for only 2.3% (20/886) of the active ingredients. In these cases, the drugs were either discontinued (4/20) or special drug classes, current diseases or co-medication required manual switching (8/20), or the drugs were continued unchanged and ordered from a wholesaler (8/20). CONCLUSION: Using a standardised interchange algorithm, pre-admission drug regimens can successfully be switched to drugs on a hospital drug formulary. These findings suggest that a computerised decision support system will likely be useful to support this important practice.
Authors: Thomas Gray; Karen Bertch; Kimberly Galt; Michael Gonyeau; Emilie Karpiuk; Lance Oyen; Mary Jane Sudekum; Lee C Vermeulen Journal: Pharmacotherapy Date: 2005-11 Impact factor: 4.705
Authors: Karen A Grace; Jennifer Swiecki; Richard Hyatt; Henry Gibbs; David L Jones; Munazza Sheikh; John Spain; Kent W Maneval; Rebecca Viola; Allen J Taylor Journal: Am J Health Syst Pharm Date: 2002-06-01 Impact factor: 2.637
Authors: Markus G Pruszydlo; Stefanie U Walk-Fritz; Torsten Hoppe-Tichy; Jens Kaltschmidt; Walter E Haefeli Journal: BMC Med Inform Decis Mak Date: 2012-11-27 Impact factor: 2.796