Detecting adverse drug reactions to improve patient outcomes

Hannan, Terry J.

doi:10.1016/s1386-5056(99)00020-9

Cited by 24 publications

(22 citation statements)

References 8 publications

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“…The use of computer-based decision support tools based on electronic medical records in the management of adverse events has been shown to aid the detection of adverse events, improve patient outcome and enhance clinician competence in drug therapy. 7,[17][18][19] Classen et al demonstrated an 800% increase in the number of adverse drug events identified compared with spontaneous reporting. 11 Therefore, the need for monitoring hospital wards electronically for ADRs has been stressed repeatedly.…”

Section: Discussionmentioning

confidence: 99%

“…The availability and use of large computerized clinical databases linked to electronic medical records could provide a tool for the early detection of ADRs and thus help clinicians to react appropriately in time. 7 It has been shown in several studies that computerized monitoring, using alerts based on laboratory data, can facilitate ADR detection. [8][9][10][11][12] This study was undertaken with the following aims: (i) to provide data on the type and incidence of ADRs in gastroenterology; (ii) to modify the generation of computerized alerts in order to increase the specificity of the system and to evaluate its effectiveness; (iii) to compare chart reviews and modified generation of computerized alerts, representing two different methodological approaches to the identification of ADRs; and (iv) to analyse the impact of ADR detection on the behaviour of physicians.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of a computer‐assisted monitoring system for the detection of adverse drug reactions in gastroenterology

Dormann¹,

Criegee-Rieck

Neubert

et al. 2004

Aliment Pharmacol Ther

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SUMMARYAim: To investigate the effectiveness of a computer monitoring system that detects adverse drug reactions (ADRs) by laboratory signals in gastroenterology. Methods: A prospective, 6-month, pharmacoepidemiological survey was carried out on a gastroenterological ward at the University Hospital Erlangen-Nuremberg. Two methods were used to identify ADRs. (i) All charts were reviewed daily by physicians and clinical pharmacists. (ii) A computer monitoring system generated a daily list of automatic laboratory signals and alerts of ADRs, including patient data and dates of events. Results: One hundred and nine ADRs were detected in 474 admissions (377 patients). The computer monitoring system generated 4454 automatic laboratory signals from 39 819 laboratory parameters tested, and issued 2328 alerts, 914 (39%) of which were associated with ADRs; 574 (25%) were associated with ADRpositive admissions. Of all the alerts generated, signals of hepatotoxicity (1255), followed by coagulation disorders (407) and haematological toxicity (207), were prevalent. Correspondingly, the prevailing ADRs were concerned with the metabolic and hepato-gastrointestinal system (61). The sensitivity was 91%: 69 of 76 ADR-positive patients were indicated by an alert. The specificity of alerts was increased from 23% to 76% after implementation of an automatic laboratory signal trend monitoring algorithm. Conclusion: This study shows that a computer monitoring system is a useful tool for the systematic and automated detection of ADRs in gastroenterological patients.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Implementation of a computer‐assisted monitoring system for the detection of adverse drug reactions in gastroenterology

Dormann¹,

Criegee-Rieck

Neubert

et al. 2004

Aliment Pharmacol Ther

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“…Because medical record review is constrained by the completeness and accuracy of the information recorded (40–42), our analysis may partially reflect quality of documentation rather than quality of care. In addition, medical charts do not provide accurate information on adherence to medical treatment or on the magnitude of use of over‐the‐counter medications (43–46).…”

Section: Discussionmentioning

confidence: 99%

The effects of physician specialty and patient comorbidities on the use and discontinuation of coxibs

Patino¹,

Allison²,

Olivieri³

et al. 2003

Arthritis & Rheumatism

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Objective. To examine the effects of physician specialty and comorbidities on cyclooxygenase 2-selective nonsteroidal antiinflammatory drugs (NSAIDs; coxibs) utilization. Methods. Medical records of 452 patients from a regional managed care organization with >3 consecutive NSAID prescriptions from June 1998 to April 2001 were abstracted. Multivariable adjusted associations between coxib initiation and discontinuation and patient and provider characteristics were examined. Results. A total of 1,142 NSAID prescriptions were written over 9,398 total patient-months of followup. Compared with patients seeing family or general practitioners, patients seeing rheumatologists (odds ratio [OR] 3.4, 95% confidence interval [95% CI] 2.1-5.7) and internists (OR 2.3, 95% CI 1.5-3.6) were significantly more likely to receive a coxib, as well as patients with a history of osteoarthritis (OR 2.6, 95% CI 1.7-3.8), gastrointestinal disease (OR 2.3, 95% CI 1.2-4.5), and congestive heart failure (OR 4.1, 95% CI 1.0 -16.4). Although specialists were more likely than generalists to prescribe coxibs, only family or general practitioners were significantly more likely to selectively use coxibs among their patients with a history of gastrointestinal disease. Fifty-four percent of NSAID prescriptions were discontinued, and coxibs were significantly less likely to be discontinued than were traditional NSAIDs (OR 0.6, 95% CI 0.5-0.8). Conclusion. Our findings suggest significantly greater, but perhaps less selective use of coxibs among specialists, even after accounting for important covariates. The initiation and discontinuation of coxibs was influenced by physician specialty and by patient risk factors.

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“…The amount of prescription data available to clinical researchers, pharmaceutical scientists, and clinician-scientists continues to grow, creating an analyzable resource for generating insights that can help improve the healthcare system [4,5]. Healthcare providers use modern EMR-based systems to identify adverse drug events [6,7], study medication-medication interactions [8], investigate medication effects on particular medical conditions [9,10], and ultimately prevent medication errors [11][12][13].…”

Section: Introductionmentioning

confidence: 99%

Multiple Regression Analysis and Frequent Itemset Mining of Electronic Medical Records: A Visual Analytics Approach Using VISA_M3R3

Abdullah

Rostamzadeh

Sedig

et al. 2020

Data

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Medication-induced acute kidney injury (AKI) is a well-known problem in clinical medicine. This paper reports the first development of a visual analytics (VA) system that examines how different medications associate with AKI. In this paper, we introduce and describe VISA_M3R3, a VA system designed to assist healthcare researchers in identifying medications and medication combinations that associate with a higher risk of AKI using electronic medical records (EMRs). By integrating multiple regression models, frequent itemset mining, data visualization, and human-data interaction mechanisms, VISA_M3R3 allows users to explore complex relationships between medications and AKI in such a way that would be difficult or sometimes even impossible without the help of a VA system. Through an analysis of 595 medications using VISA_M3R3, we have identified 55 AKI-inducing medications, 24,212 frequent medication groups, and 78 medication groups that are associated with AKI. The purpose of this paper is to demonstrate the usefulness of VISA_M3R3 in the investigation of medication-induced AKI in particular and other clinical problems in general. Furthermore, this research highlights what needs to be considered in the future when designing VA systems that are intended to support gaining novel and deep insights into massive existing EMRs.

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Detecting adverse drug reactions to improve patient outcomes

Cited by 24 publications

References 8 publications

Implementation of a computer‐assisted monitoring system for the detection of adverse drug reactions in gastroenterology

Implementation of a computer‐assisted monitoring system for the detection of adverse drug reactions in gastroenterology

The effects of physician specialty and patient comorbidities on the use and discontinuation of coxibs

Multiple Regression Analysis and Frequent Itemset Mining of Electronic Medical Records: A Visual Analytics Approach Using VISA_M3R3

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