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  • 标题:Reduce Medication Errors with Clinical Decision Support Systems
  • 作者:Sima Ajami ; Fatemeh Amini
  • 期刊名称:Information Technology & Software Engineering
  • 电子版ISSN:2165-7866
  • 出版年度:2013
  • 卷号:3
  • 期号:Spe
  • DOI:10.4172/2165-7866.S7-e001
  • 出版社:OMICS Group
  • 摘要:Now a day, medication error is one of the most problems among care processes by physicians. Medication error generally defined as a deviation from the physician’s medication order as written on the patient’s chart. In hospitals, medication errors occur at a rate of about one per patient per day [1]. Preventable adverse drug events are associated with one out of five injuries or deaths. Estimates reveal that 46% of medication errors occur on admission or discharge from a clinical unit/hospital when patient orders are written [2]. In general, the medication error rate was great among physicians with the least training, but no physician group was error free [3]. Background Medication errors are common, and while most such errors have little potential for harm they cause substantial extra work in hospitals. A small proportion does have the potential to cause injury, and some cause preventable adverse drug events [4]. Many medication errors can occur when ordering and dispensing medicine in hospitals. The clinical decision support system (CDSS) is widely used in an effort to reduce medication errors [5]. Clinical decision support systems (CDSSs) for antimicrobial stewardship require considerable human resources and financial investments [6]. A previous cohort study of 180 actual adverse drug events (ADEs) and 552 potential ADEs (PADEs) at six community hospitals in Massachusetts were analysed to determine the frequency and types of multiple-drug ADEs and the extent to which the ADEs might have been prevented using publicly available clinical decision-support (CDS) knowledge bases. None of the hospitals had a computerized prescriber-order-entry system at the time of data collection (January 2005–August 2006) showed that a total of 17 adverse drug events (ADEs) (rate, 1.4 per 100 admissions) and 146 PADEs (rate, 12.2 per 100 admissions) involving multiple drugs were identified. The documented events were related to drug duplication (n=126), drug–drug interaction (n=21), additive effects (n=14), and therapeutic duplication (n=7) or a combination of those factors. The majority of actual ADEs were due to drug–drug interactions, most commonly involving opioids, benzodiazepines, or cardiac medications; about 75% of the PADEs involved excessive drug doses resulting from order duplication or the prescribing of combination drugs with overlapping ingredients, usually products containing acetaminophen and an opioid. It was determined that 5 (29.4%) of the ADEs and 131 (89.7%) of the PADEs could have been detected through the use of the evaluated CDS tools.
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