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Purpose: To define the signals that a new artificial intelligence (AI) system must emit to improve adverse drug events (ADEs) management in oral antineoplastic agents (OAA)., Methods: A multidisciplinary group of experts in patient safety was set up to define what signals the new AI system must emit to improve ADEs management in OAAs. The baseline data for the new AI system were generated through an observational and ambispective study carried out in a university hospital. All patients who met the inclusion criteria were selected consecutively every working day for 6 months. The ADEs were collected by interview and by the review of health records. The ADEs were categorised according to how they could be detected: patient, analysis, examination., Results: The group defined what signals the AI system must emit to improve ADEs management in OAAs: a signal to educate the patient when the possible ADEs were categorised as patient, a signal as a reminder to request a blood test or a microbiological culture when the possible ADEs were categorised as analysis, and a signal as a reminder for the necessity of a clinical examination when the possible ADEs were categorised as examination. A total of 1652 ADEs were reported in the interviews (ADE-interview) with the pharmacist, and doctors noted 1989 ADEs in the health record (ADE-HR). The most frequent ADEs were identified in the patient category., Conclusion: This study opens a new way for better management of ADEs and is the first step in the development of a future technology, which will improve the quality of life of patients., Competing Interests: Competing interests: None declared., (© European Association of Hospital Pharmacists 2024. No commercial re-use. See rights and permissions. Published by BMJ.)

Objective: To analyse the applications for drugs in special situations (compassionate use, off-label use and foreign drugs) for solid  tumours, and to assess the level of evidence supporting these applications, as  well as the effectiveness and safety of most frequent drugs., Method: We performed a cross-sectional study of all applications for drugs in  special situations during 2018 and 2019 in a representative third-level centre.  We collected data about generic names of drugs, clinical indications, and level  of evidence provided on the application form. Furthermore, tumour response  was assessed according to the Response Evaluation Criteria in Solid Tumours  version 1.1., Progression Free Survival and Overall Survival. Safety was  evaluated with the National Cancer Institute Common Terminology Criteria for  Adverse Events, version 5.0., Results: 2,273 drugs in special situations were approved between January  2018 and December 2019. In 431 cases (19%), they were used to treat solid  tumours. Out of 431, 291 (67.5%) applications were offlabel drugs, 76 (18%)  foreign drugs, and 64 (15%) were compassionate use of drugs. Most of them  were supported by phase 3 (47%) or phase 2 (33%)  clinical trials. The  majority of adverse effects were grade 1 and only in 6/67 cases the treatment  was discontinued due to toxicity., Conclusions: A significant number of drugs in special situations are prescribed  to Oncology patients. The majority of applications of these drugs was supported by clinical trials. The real-life experience showed an effectiveness and tolerance profile similar to those described in randomised  clinical trials., (Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.)

Objective: The aim of this study was to stratify medications used in hospital  care according to their potential risk., Method: The RAND/UCLA Appropriateness Method was used. Anatomical Therapeutic Chemical subgroups were classified according to their potential risk. A literature search, bulletins, and alerts issued by patient safety organizations were used to identify the potential safety risk of  these subgroups. Nine experts in patient/medication safety were selected to score the subgroups for their appropriateness in the classification. Two evaluation rounds were conducted: the first by email and the second by a  panel meeting., Results: A total of 298 Anatomical Therapeutic Chemical subgroups were  evaluated. They were classified into three scenarios (low, medium, and high  risk). In the first round, 266 subgroups were classified as appropriate to the  assigned scenario, 32 were classified as uncertain, and none were classified as  inappropriate. In the second round, all subgroups were classified as appropriate.  The most frequent subgroups in the low-risk scenario belonged to  group A "Alimentary tract and metabolism" (44%); the most frequent in the  medium-risk scenario belonged to group J "Antiinfectives for systemic use"  (32%); and the most frequent in the high-risk scenario belonged to group L  "Antineoplastic and immunomodulating agents" (29%) and group N "Nervous  system" (26%)., Conclusions: Based on the RAND/UCLA appropriateness method, Anatomical  Therapeutic Chemical subgroups used in hospital care were classified according  to their potential risk (low, medium, or high). These lists can be incorporated  into a risk-scoring tool for future patient/medication safety studies., (Copyright AULA MEDICA EDICIONES 2014. Published by AULA MEDICA. All rights reserved.)