In Germany close to 18 million people are hospitalised every year  and according to their drug history they are prescribed an average of six drugs [1, 13]. Hence, every day roughly 300,000 drug switches are performed in German hospitals and – if performed with similarly poor accuracy as in our pilot study – they will be a major cause for avoidable risks for patients and also a waste of working force.
The potential for medication errors concerning dose adjustments after switching to therapeutic equivalents is well known. In an American study a significant proportion of patients whose cholesterol lowering medication was switched from atorvastatin to simvastatin thereafter received lower therapeutic doses, potentially impairing the quality of care and effectiveness . But in some cases also the appropriateness of generic substitution is still controversially discussed [15, 16]. Even when therapeutic doses and conversion factors are carefully considered the substitution may lead to critical changes in the exposure with additives [17, 18] and – given the generally accepted range of bioequivalence – switching may cause considerably differing exposures to the active compound, which may be relevant for drugs with a narrow therapeutic window . Therefore tight regulations and recommendations defining suitable drugs and drug classes for substitution might improve physicians’ confidence and compliance in the switching procedure .
Accordingly, we formed an interdisciplinary team of specialists (physicians, pharmacists, and computer scientists) to design and develop an electronic tool, which is a standard procedure to create well-fitted and user-friendly systems . After implementation we evaluated a large independent sample of prospectively documented drug switches performed by experienced clinical pharmacists and thus used real clinical data as the most realistic test-cases.
The first test of our newly developed CDSS already showed good performance of our algorithm (93.6% could be switched electronically) but also revealed weaknesses that might have led to medication errors if the CDSS would have been released into clinical routine before meticulous validation. These weaknesses mainly albeit not exclusively concerned the switch to therapeutic equivalents, which in some cases required additional patient information or a switch to formulations with differing release characteristics. After modification, the second version (version 1.0) of the CDSS enabled automatic switching of 91.6% of the cases without any inadequate suggestions. Considering the huge size of the German drug market the performance of the tool is rather remarkable. Indeed with more than 70,000 pharmaceuticals, Germany has one of the largest drug markets worldwide suggesting that the CDSS will likely also efficiently switch drugs prescribed in other countries. Such a CDSS may even be useful in countries whose reimbursement system currently allows continuation of the patient’s own drugs during hospitalised care (such as the UK) because even then formulary substitutions are still required for example when patients are admitted as emergencies or if there is insufficient quantity of medicine to cover the whole inpatient stay.
Even in the optimised version, some drug switches suggested by the CDSS (100/1,333 observed switches) were judged inferior to the switching result of the clinical pharmacists. Analysis of these situations revealed that in most cases the clinical pharmacists derogated from the basic algorithm to improvise in a non-standard situation. For example our CDSS failed to compute an adequate dosage regimen after switching “Metoprolol 100 retard 1A Pharma” (containing 78.09 mg metoprolol) to “Beloc-Zok Retardtabl” (containing 77.82 mg metoprolol) because of slightly differing drug strengths, whose clinical irrelevance is easily recognised by an expert but requires proper specification for consideration by a computer system. Furthermore the human specialist is able to consult information sources beyond the CDSS database (e.g. by contacting the pharmaceutical manufacturer when additional drug information is needed and not available electronically). At last and in contrast to a CDSS, clinical pharmacists were able to consider special patient characteristics (e.g. age/mental state) and therefore to adjust a dosage regimen seeking to simplify the prescription (e.g. by avoiding tablet splitting). Indeed complex and complicated drug regimens (e.g. regimens with multiple administration times or the need for tablet-splitting) are an important prescription characteristic promoting non-adherence of the patients [20, 21] that could be prevented in a large fraction of all prescriptions .
This emphasises areas of unmet need among professionals for support of drug switching in complicated cases that are not yet covered by the CDSS. Nevertheless, already today the CDSS can reduce the workload of these professionals by reliable handling of the large majority of routine substitutions. This is a substantial reduction of time when considering that manual drug switching by American clinicians was estimated to take 11 minutes per medication .
The thorough analysis of drug pairs not yet automatically switched revealed that a meaningful next step would be to support dose adjustment of different application forms and to consider combination products for therapeutic substitution (step 4). In addition, a future switching tool could also enable adoption of new scenarios like patient admission to an intensive care unit where oral forms often have to be switched to parenteral or intravenous forms and the switch back to ambulatory medication at discharge from hospital.
A number of potential limitations should be considered before generalisation of the results to other settings. (1) In our study we only switched drug combinations of surgical patients thus restricting evidence to patients receiving comparable medication regimens. However, as shown in our previous evaluation performed in the same wards , the Charlson score of these patients is high, reflecting the numerous co-morbidities of these patients and suggesting that their drug regimens likely represent also a population of internal medicine patients. (2) In our evaluation we had to exclude about 10% of the switch requests because essential details of the patients’ prescription were missing (e.g. missing dosage regimen, strengths, or information needed to identify the specific brand). This stresses the advantages of an electronic documentation of patient medications in a CPOE linked to drug databases as it enables exact identification of brands, the key information to relevant drug-related data like drug composition, strength, galenic formulation, and the corresponding SPC . Unfortunately SPC information is currently not available in a well structured format , which would facilitate the development of tools like the one described herein. (3) Our evaluation was conducted by project members and not by clinical staff for whom the CDSS was developed. Thus, possible socio-technical incidents, a group of medication errors originating from interactions between clinical staff and the system , have yet to be investigated. (4) Finally the revision of differences between the switching results of pharmacists and the CDSS was performed by only one expert. This senior clinical pharmacist was considered best choice due to her extensive practical experience in switching drugs for years. However, by blinding this expert for the origin of the switching suggestions (pharmacist or CDSS) bias is minimised.