Assessment of Possible Drug-Drug Interactions in Psychopharmacotherapy after Hospital Discharge using an Interactive Database

被引:6
|
作者
Weih, M. [1 ]
Bachmeier, C. [1 ]
Degirmenci, Ue. [1 ]
Sojer, R. [2 ]
Kreil, S. [1 ]
Thuerauf, N. [1 ]
Prokosch, H. -U. [3 ]
Hiemke, C. [4 ]
Kornhuber, J. [1 ]
机构
[1] Univ Klinikum Erlangen, Psychiat & Psychotherapeut Klin, D-91054 Erlangen, Germany
[2] Univ Erlangen Nurnberg, Lehrstuhl Med Informat, D-8520 Erlangen, Germany
[3] Univ Klinikum Erlangen, Med Zentrum Informat & Kommunikat Tech, D-91054 Erlangen, Germany
[4] Univ Med Mainz, Klin Psychiat & Psychotherapie, Mainz, Germany
关键词
side effects; drug safety; electronic physician order; EVENTS;
D O I
10.1055/s-0029-1245778
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Introduction: Psychiatry is confronted with increasing requirements in quality management, guidelines and an increasing proportion of elderly, chronic multimorbid patients with psychiatric disorders. The latter give rise to polypharmacy which may lead to drug-drug interactions. Assessment of drug interactions is more and more difficult as the total number of drugs taken increases. In the present study hospital discharge medication was analysed semiautomatically for possible drug-drug interactions. Methods: In-hospital cases were randomly selected. Discharge medication was analysed using PsiacOnline, a large web-based database for drug interactions. Results: The selection yielded 342 cases from 213 patients (mean age 46.3 years, 53% females). 86 patients had one psychiatric diagnosis; the other patients had at least two or more diagnoses. The discharge prescription was analysed for 55 different psychotropic drugs from 4 large drug groups (18 antidepressants; 17 antipsychotic drugs; 5 mood stabilisers/epileptic drugs and 13 different hypnotic/anxiolytic drugs). Antipsychotic drugs were the most frequent drugs (n = 334); followed by antidepressants (n = 312) and mood stabilizers (n = 112). 47 patients (13.7%) were discharged with monotherapy. Mean drug number was 2.7. PsiacOnline revealed 535 hits: 126 (23.6%) combinations were non-critical, 86 (16.1%) combinations were critical based on pharmacological properties of the drugs; 232 (43.4%) combinations were critical according to in vitro studies or animal experiments; critical drug combinations in high-risk patients: 67 x (12.5%); combinations with reported risks for side effects due to interaction: 17 x (3.2%) and combinations with documented risks for severe drug interactions: 7 x (1.3%). Conclusion: Although the majority of drug combinations was considered not critical, approximately 3% of cases had an increased risk for adverse drug actions and a further 1.3% cases with a severe risk gave evidence that integration of an IT-based pharmacological expert system in a computerised physician order entry (CPOE) should be considered. Suggested beneficial effects need to be shown by an appropriately-designed clinical study.
引用
收藏
页码:92 / 96
页数:5
相关论文
共 50 条
  • [21] Detecting signals of drug-drug interactions in a spontaneous reports database
    Thakrar, Bharat T.
    Grundschober, Sabine Borel
    Doessegger, Lucette
    BRITISH JOURNAL OF CLINICAL PHARMACOLOGY, 2007, 64 (04) : 489 - 495
  • [22] Assessment of Potential Drug-drug Interactions among Ischaemic Stroke Patients in a Charitable Hospital
    Johnson, Amala
    Thomas, Akshay Abraham
    Jose, Shanty Mary
    Mateti, Uday Venkat
    Kellarai, Adithi
    Shetty, Shraddha
    Chaudhary, Raushan Kumar
    Rawal, Kala Bahadur
    JOURNAL OF CLINICAL AND DIAGNOSTIC RESEARCH, 2022, 16 (07) : CC31 - CC36
  • [23] Identification of Drug-Drug Interactions Using Chemical Interactions
    Chen, Lei
    Chu, Chen
    Zhang, Yu-Hang
    Zheng, Mingyue
    Zhu, LiuCun
    Kong, Xiangyin
    Huang, Tao
    CURRENT BIOINFORMATICS, 2017, 12 (06) : 526 - 534
  • [24] Assessment of Potential Drug-Drug Interactions in an Oncology Unit of a Tertiary Care Teaching Hospital
    Vayalil, Ramya Kuzhikattu
    Shetty, K. Jayarama
    Mateti, Uday Venkat
    INDIAN JOURNAL OF MEDICAL AND PAEDIATRIC ONCOLOGY, 2018, 39 (04) : 436 - 442
  • [25] Measuring drug similarity using drug-drug interactions
    Lv, Ji
    Liu, Guixia
    Ju, Yuan
    Huang, Houhou
    Sun, Ying
    QUANTITATIVE BIOLOGY, 2024, 12 (02) : 164 - 172
  • [26] Predicting Drug-Target Interactions Using Drug-Drug Interactions
    Kim, Shinhyuk
    Jin, Daeyong
    Lee, Hyunju
    PLOS ONE, 2013, 8 (11):
  • [27] Drug-Drug Interactions among Elderly Patients at Hospital Discharge: A Cross-Sectional Descriptive Study
    Balodiya, Sujit
    Kamath, Ashwin
    Shastry, Rajeshwari
    Chowta, Mukta N.
    JOURNAL OF KRISHNA INSTITUTE OF MEDICAL SCIENCES UNIVERSITY, 2019, 8 (03) : 88 - 95
  • [28] Identification of Drug-Drug Interactions Using OCR
    Alrehily, Enas Saleem
    Alhejaili, Rawan Fahad
    Albeladi, Dalal Rasheed
    Syed, Liyakathunisa
    IOT TECHNOLOGIES FOR HEALTH CARE, HEALTHYIOT 2021, 2022, 432 : 125 - 135
  • [29] Assessment of drug-drug interactions between voriconazole and glucocorticoids
    Li, MengXue
    Zhu, Liqin
    Chen, Lu
    Li, Na
    Qi, Fang
    JOURNAL OF CHEMOTHERAPY, 2018, 30 (05) : 296 - 303
  • [30] POTENTIAL DRUG-DRUG INTERACTIONS IN OUTPATIENT PRESCRIPTIONS IN A GENERAL HOSPITAL
    Maria, A.
    Nicoletta, K.
    Pantelis, L.
    BASIC & CLINICAL PHARMACOLOGY & TOXICOLOGY, 2011, 109 : 156 - 157