Detection of serious adverse drug reactions using diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems.

Canadian hospitals are legally required to report serious adverse drug reactions (ADRs). This study aimed to assess the ability to detect serious ADRs from diagnostic codes and the potential benefit of adding stand-alone diagnostic codes to the regular process for detecting serious ADRs. In this descriptive study, clinical pharmacists and a reference work on drug-induced diseases allowed to identify diagnostic codes in the International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA), reflecting clinical manifestations related to an ADR. Records for admissions to a large urban mother-child hospital in the fiscal year 2018-2019, as coded by medical archivists, were analysed. Of 69 ICD-10-CA diagnostic codes reflecting an ADR identified, 38 were included in the detailed analysis of patient records and 18 (which appeared in 130 admissions) deemed to indicate a serious ADR. Among the 130 admissions analysed, 70 serious ADRs were identified, of which 52 were previously detected by the regular process and 18 were not, increasing the detection of serious ADRs by 34.6% (18/52). These 18 serious ADRs were newly identified from 11 of the 18 codes reflecting clinical manifestation of a serious ADR. Adding ICD-10-CA diagnostic codes not associated with external cause codes can increase the capacity to detect serious ADRs in hospitals. Over a 12-month period, the use of 11 such diagnostic codes increased the detection capacity for serious ADRs by 34.6%.

Impact of adverse drug reactions on the coding of a hospital stay in Quebec: exploratory descriptive study by simulation.

The discharge summary sheet's coding allows calculation of the severity index (SI), mortality index (MI), and resource intensity weight (RIW). These indicators help to describe the burden of care for individual cases and could potentially influence patient-based funding. This study was undertaken to simulate the impact of different adverse drug reactions (ADRs) on the hospital length of stay, thus allowing calculation of the effect of ADRs on the SI, MI, and RIW. This exploratory descriptive study was based on computer simulations. We created, by simulation, seven patient profiles of various complexities representative of our patients. Fifteen types of combination of drug and ADR manifestation comprising 15 ADR caused by eight different drug classes were identified based on the most frequently coded ADR in fiscal years 2016-2017 and 2017-2018. Those 15 combinations were applied to the patient profile to simulate the impact on the SI, MI, and RIW in eight scenarios. From these data, we measured the impact of the ADRs on these indicators. A total of 1,571 simulations were run. In general, the addition of a couple of drug and ADR manifestation contributed to increases in all three of the indicators. More specifically, the SI and RIW both increased in 30.7% (n = 482), whereas the MI increased in 14.6% (n = 229). For a same scenario, the impact on the three indicators could vary depending on the patient profile to which it was applied. This study has presented simulation data on the impact of the coding of ADRs on the hospital stay of a patient in Quebec.

Pediatric SJS/TEN Subdued by a Combination of Dexamethasone, Cyclosporine, and Etanercept.

We report a case of an 17-year-old male with a drug reaction in the spectrum of Stevens-Johnson syndrome (SJS)/toxic epidermal necrolysis (TEN), triggered by carbamazepine, who was succesfully treated with the combination of dexamethasone, cyclosporine, and etanercept. This triple therapy halted and prevented skin epidermolysis without immediate or late onset complications.

Investigational drug labeling variability.

BACKGROUND/AIMS: In comparison with commercial drugs, there are few regulations concerning the labeling of investigational drugs. This leads to variability in their content and layout. This increases the risk of errors during storage, validation, compounding, dispensing and administration. The aim of this study was to evaluate the conformity and variability of investigational drug labels. Additional exploratory aims were to evaluate the use of an automated script to describe the labels and to identify the factors associated with the ease of finding a kit number. METHODS: An 87-criterion list was developed to evaluate content, format and readability. It included eight criteria to evaluate the conformity to the Canadian Food and Drugs Regulation. A systematic cross-sectional evaluation of all investigational drug labels in our 500-bed mother-child center was performed. All active protocols during the period of 14-22 February 2018 were included. Labels from drugs that were sourced locally were excluded. Labels affixed to the outside (external) and inside (internal) containers, as well as labels from American and European sponsors, were compared with the chi-square and Student's t tests. A script was developed in Python to automatically determine key information (number of words, main colors and their proportion). A short survey was conducted with a convenience sample of pharmacists to rate the ease of finding the kit number on labels. Correlation was evaluated with different factors. RESULTS: A total of 27 protocols were included (24 internal and 34 external labels). The majority (33/34) of external labels were compliant with the Regulation. Some internal labels did not state the expiry date (9/13), the sponsor address (2/13) or storing conditions (1/13). A total of 10 criteria were different between internal and external labels, for instance, the number of languages was higher on external labels (median 3 (2-14) vs 10 (2-50); p = 0.013). Five criteria were different depending on the sponsors' location, for instance, European sponsors were more prone to use bold characters (25% vs 61%, p = 0.034). There was a mean of 146 ± 111 words and 78.3% ± 7.3% empty space per label. These were positively correlated (p < 0.001). The proportion of free space on a label was also correlated with the ease of finding the kit number (p = 0.002). CONCLUSION: We measured a high variability in the labeling of investigational drugs. Key information was missing from labels affixed to internal containers, despite the use of a high number of pages. The automation worked well and further work is needed to identify criteria that may improve readability and reduce error risk. Detailed and harmonized international guidelines are needed.