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.

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 can identify 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 3,506 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.

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.

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.