Pseudo-Worsening of Kidney Function Due to Inhibition of Renal Creatinine Secretion: Quality of Information Provided in Prescribing Information/SmPC.

Determination of serum creatinine concentrations and subsequent calculation of estimated glomerular filtration rates (eGFR) is a cornerstone of clinical medicine. Crucial clinical decisions such as drug treatment discontinuations are based on eGFR calculated from serum creatinine measurements. However, creatinine is not only filtered in the kidneys, but also actively secreted into urine. Creatinine transporters such as OCT2, OCT3, MATE1, MATE2-K, and OAT2 expressed in proximal tubular cells are responsible for active renal secretion of creatinine. Multiple drugs (e.g., oral antitumor drugs) inhibit these transporters thereby causing a pseudo-worsening of kidney function with an increase in serum creatinine concentrations and a decrease in eGFR while other methods for eGFR determination (e.g., by cystatin C) reveal normal kidney function. Since US Prescribing Information (PI) and European Summaries of Product Characteristics (SmPCs) are the most relevant source of information for physicians, we investigated the quality of information in US PI/German SmPCs of drugs with clear evidence for pseudo-worsening of kidney function. 514 drugs putatively interacting with creatinine transporters were identified. For 149 of those drugs, an increase in serum creatinine concentrations has been described. Available data confirmed the existence of pseudo-worsening of kidney function for 30 of those drugs, for the remaining 119 drugs existing data are insufficient. Only 23.5% (12/51) of the 30 drugs' PI/SmPCs contained unambiguous statements on this proven pseudo-worsening of kidney function and gave clear recommendations for clinical management. Taken together, inadequate information provided in PI or SmPCs on the pseudo-worsening of kidney function poses patients at unnecessary risks.

Inconsistencies of absolute drug-drug contraindication reports: Analysis of Summaries of Product Characteristics of commonly prescribed drugs.

AIMS: Prescribing information should follow a defined structure to help prescribers easily find required information. Often information appears in different sections of Summaries of Product Characteristics (SmPCs) in an inconsistent way. Still unknown is how this inconsistency affects absolute contraindications and how it can be improved. Thisstudy aimed to evaluate the structure of absolute contraindications in SmPCs based on absolute drug-drug contraindications (DDCI) in the section 'contraindications' and references to sections 'special warnings and precautions for use' (here as 'warnings') and 'interaction with other medicinal products and other forms of interaction' (here as 'interactions'). METHODS: SmPCs of 693 commonly prescribed drugs were analysed regarding absolute DDCI in 'contraindications' sections. References to sections on 'warnings' and 'interactions' were evaluated to characterize information provided about DDCI. RESULTS: Of 693 analysed SmPCs, 138 (19.9%) contained ≥1 absolute DDCI. Of 178 SmPCs that referred to sections on 'warnings' or 'interactions', 131 (73.6%) did not contain further information on absolute DDCI, whereas 47 (26.4%) did. Such additional information was found in sections on 'interactions' and 'warnings' in 41 (87.2%) and 9 (19.1%) SmPCs, respectively. CONCLUSIONS: Information regarding absolute DDCI was found not only in sections on 'contraindications' but also in sections on 'warnings' and 'interactions'. Information was not given with consistently straightforward phrasing and structure and so can leave uncertainty for prescribers. To improve drug safety, clear definitions and wording for absolute and relative contraindications should be provided, ideally in tables.

Comprehensibility of Contraindications in German, UK and US Summaries of Product Characteristics/Prescribing Information-A Comparative Qualitative and Quantitative Analysis.

Contraindications (CIs) in Summaries of Product Characteristics (SmPCs)/Prescribing Information (PI) that lack clarity may pose a risk to medication safety and increase the risk for adverse drug reactions. We assessed and compared SmPCs/PI from three major drug markets regarding comprehensibility from the prescriber perspective, as well as usability in clinical decision support systems. 158 drugs met the following inclusion criteria: marketed in Germany (DE), United Kingdom (UK) and United States (US) and belonged to the 100 most recently FDA approved and/or 100 most frequently prescribed drugs in either country. In the 474 (3 × 158) SmPCs/PI all expressions for absolute CIs were identified, divided into 3999 stand-alone terms and evaluated according to 'clarity' and 'codability'. The average number of absolute CIs per drug differed drastically between the three markets (DE: 11.7, UK: 9.0, US: 4.6). Expressions were frequently unclear (DE: 27.2% (95% CI 25.2-29.2%), UK: 28.5% (26.2-30.9%), US: 22.6% (19.7-25.8%)). Moreover, 60.9% (58.6-63.1%), 63.6% (61.0-66.0%), and 64.7% (61.2-68.1%) of the expressions were not codable in DE, UK, and US, respectively. Taken together, in three major drug markets, statements regarding CIs in SmPCs/PI substantially differ in frequency and frequently lack clarity and codability which poses an unnecessary obstacle to medication safety.

Use of medication data alone to identify diagnoses and related contraindications: Application of algorithms to close a common documentation gap.

AIMS: Automated checks for medication-related problems have become a cornerstone of medication safety. In many clinical settings medication checks remain confined to drug-drug interactions because only medication data are available in an adequately coded form, leaving possible contraindicated drug-disease combinations unaccounted for. Therefore, we devised algorithms that identify frequently contraindicated diagnoses based on medication patterns related to these diagnoses. METHODS: We identified drugs that are associated with diseases constituting common contraindications based on their exclusive use for these conditions (such as allopurinol for gout or salbutamol for bronchial obstruction). Expert-based and machine learning algorithms were developed to identify diagnoses based on highly specific medication patterns. The applicability, sensitivity and specificity of the approach were assessed by using an anonymized real-life sample of medication and diagnosis data excerpts from 3506 discharge records of geriatric patients. RESULTS: Depending on the algorithm, the desired focus (i.e., sensitivity vs. specificity) and the disease, we were able to identify the diagnoses gout, epilepsy, coronary artery disease, congestive heart failure and bronchial obstruction with a specificity of 44.0-99.8% (95% CI 41.7-100.0%) and a sensitivity of 3.8-83.1% (95% CI 1.0-86.1%). Using only medication data, we were able to identify 123 (51.3%) of 240 contraindications identified by experts with access to medication data and diagnoses. CONCLUSION: This study provides a proof of principle that some key diagnosis-related contraindications can be identified based on a patient's medication data alone, while others cannot be identified. This approach offers new opportunities to analyse drug-disease contraindications in community pharmacy or clinical routine data.

The CredibleMeds® list: Usage of QT interval prolonging drugs in Germany and discordances with prescribing information.

AIMS: A substantial number of Summaries of Product Characteristics (SmPCs)/Prescribing Information (PI) have warnings or contraindications on QT interval prolongation. The goal of this work was to quantify usage of QT interval prolonging drugs according to the CredibleMeds® database of the German outpatient drug prescription market and to evaluate discrepancies between German SmPCs/US PI and CredibleMeds® . METHODS: Drugs listed on CredibleMeds® with known, possible or conditional risk for torsade de pointes were evaluated from 2000 to 2020. The German drug prescription report was used as source for defined daily dose- (DDD-) based prescriptions of the German outpatient drug prescription market of the public health insurance system. German SmPCs and US PI of 253 CredibleMeds® -listed drugs were evaluated for contents regarding QT interval prolongation. RESULTS: Of the drugs currently listed on CredibleMeds® , 59.7% (95% confidence interval [CI] 53.5-65.5%) were listed after 2012. Due to newly listed drugs, the proportion of DDDs of CredibleMeds® drugs among all prescriptions increased from 4.6% in 2013 to 21.1% in 2019. DDD-based usage of the CredibleMeds® drugs already listed in 2013 was similar in 2019. Among the drugs with known QT risk according to CredibleMeds® , 7.5% (95% CI 2.6-19.9%) of German SmPCs and 21.1% (95% CI 11.1-36.3%) of US PI had no mention of QT issues whatsoever. CONCLUSION: A significant proportion of all drugs prescribed in the outpatient sector is associated with QT risks according to CredibleMeds® . SmPCs and PI should systematically be evaluated for concordance with the widely used CredibleMeds® database to increase medication safety.

Documentation of Drug-Related Problems with ICD-11: Application of the New WHO Code-Set to Clinical Routine Data.

Drug-related problems (DRPs), i.e., adverse drug reactions (ADRs) and medication errors (MEs), constitute a serious threat to the patient's safety. DRPs are often insufficiently captured by clinical routine documentation, and thus, they frequently remain unaddressed. The aim of this study was to assess the coverage and usability of the new 11th revision of the WHO International Classification of Diseases (ICD-11) to document DRPs. We refined the 'Quality and Safety Algorithm' from the ICD-11 Reference Guide and used it for DRP reporting to code 100 different anonymized DRPs (50 ADRs and 50 MEs) in a German hospital. The ICD-11 three-part model consisting of harm, cause, and mode was used whenever they were applicable. Of 50 ADRs, 15 (30.0%), such as drug-induced osteoporosis, were fully classifiable and codable by the ICD-11, whereas 35 (70.0%), such as drug-induced hypokalaemia, could not be fully classified due to sanctioning rules preventing the postcoordination (i.e., a combination of specific codes, such as drug and diagnosis). However, coding without the loss of information was possible in the 35 of these 35 (100.0%) ADR cases when we were deviating from the cluster code order of the Reference Guide. In all 50 MEs, the mode could be encoded, but for none of the MEs, postcoordination, i.e., the assignment of the ME to a specific drug, was allowed. In conclusion, the ICD-11 three-part model enables us to acquire more detailed documentation of DRPs than the previous ICD versions did. However, the codability, documentation, and reporting of DRPs could be significantly improved by simple modifications of the current ICD-11 sanctioning rules and by the addition of new ICD-11 codes.