Medication-related clinical decision support alert overrides in inpatients

Nanji, Karen C.; Seger, Diane L.; Slight, Sarah P; Amato, Mary G.; Beeler, Patrick E.; Her, Qoua L.; Dalleur, Olivia; Eguale, Tewodros; Wong, Adrian; Silvers, Elizabeth R.; Swerdloff, Michael; Hussain, Salman T.; Maniam, Nivethietha; Fiskio, Julie M.; Dykes, Patricia C.; Bates, David W.

doi:10.1093/jamia/ocx115

Cited by 121 publications

(115 citation statements)

References 45 publications

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“…Alert fatigue can negate the potential patient safety benefits of interruptive CDS, and it is a widely discussed concern. 3, 4,7,9,10,14,21,22 Previous research has reported effective techniques for categorizing historical interruptive DDI alert data for critical review, organizing at the drug or drug category level, and calculating frequencies of alert occurrence. [11][12][13][14][15][16] Interdisciplinary panels can review an institution's alert data and safely identify alerts to deactivate or modify.…”

Section: Discussionmentioning

confidence: 99%

Optimizing Drug-Drug Interaction Alerts Using a Multidimensional Approach

Daniels¹,

Burlison²,

Baker

et al. 2019

Pediatrics

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OBJECTIVES: Excessive alerts are a common concern associated with clinical decision support systems that monitor drug-drug interactions (DDIs). To reduce the number of low-value interruptive DDI alerts at our hospital, we implemented an iterative, multidimensional quality improvement effort, which included an interdisciplinary advisory group, alert metrics, and measurement of perceived clinical value.

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Section: Discussionmentioning

confidence: 99%

Optimizing Drug-Drug Interaction Alerts Using a Multidimensional Approach

Daniels¹,

Burlison²,

Baker

et al. 2019

Pediatrics

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“…Our study particularly challenges the usefulness of automated notifications about potassiumincreasing DDIs despite a low alert burden. In this context, we increasingly question the justification for both (i) direct costs due to research, development and maintenance of the information technology and (ii) indirect expenses due to the burden providers experience in handling clinically insignificant notifications that are to be appropriately overridden [5,34]. Ultimately, even if potassium-increasing DDIs were to clearly increase mortality due to serious hyperkalaemic states with fatal cardiac arrhythmias, CDS could still not guarantee clinical effectiveness, which is hampered by high override rates [5].…”

Section: Discussionmentioning

confidence: 99%

Negligible impact of highly patient-specific decision support for potassium-increasing drug-drug interactions – a cluster-randomised controlled trial

et al. 2019

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BACKGROUND AND OBJECTIVE: Clinical decision support (CDS) might improve management of potassium-increasing drug-drug interactions (DDI). We studied CDS with five features intended to increase effectiveness: (i) focus on serious DDIs, (ii) fewer notifications, (iii) presentation of current laboratory results, (iv) timing (when adverse event becomes likelier), (v) removal of notification when appropriate.

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“…However, despite PASS having been adopted by some hospitals, the positive effects are often negligible, and the system override rate continues to remain quite high. Previous studies have documented that monitoring systems do have positive impacts on medical performance [6] and also have highlighted a high level of override rates (73.3%) in PASS contexts [5,7]. One study also presented an insignificant correlation between the system in hospitals and prescription behavior [8].…”

Section: Introduction Backgroundmentioning

confidence: 97%

“…Most hospital information systems (HISs) in China provide informative guidance in order to provide required information for decision-makers, which further aim to support their judgments and adoption of the systems [5]. As a significant part of the HIS, the Prescription Automatic Screening System (PASS) focuses on rational drug usage (e.g., drug interactions, pharmacologic antagonism, chemical incompatibility) and searches for available drug information, which could help in the avoidance of ADEs /ADRs caused by inappropriate drug usage [4].…”

Section: Introduction Backgroundmentioning

confidence: 99%

“…One study also presented an insignificant correlation between the system in hospitals and prescription behavior [8]. These inconsistent results may be due to the fact that not all information is deemed appropriate for treatment, and this would sometimes distract physicians' attention during the decision process and, as a consequence, make the overriding of drug alerts a common practice [5]. Hence, the ways in which the PASS system in hospitals influences medical performance still requires further exploration.…”

Section: Introduction Backgroundmentioning

confidence: 99%

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Exploring the Impact of the Prescription Automatic Screening System in Health Care Services: Quasi-Experiment (Preprint)

Li¹,

Guo²,

Hsu³

et al. 2018

Preprint

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Background: Hospitals have deployed various types of merging technologies (e.g., intelligent diagnosis systems, mobile tablets). However, the impacts of these technologies on behavior change are rather vague, especially the computer-aided diagnosis systems. Although the critical roles of information systems have been demonstrated in previous research, there still remains a substantial amount of unsatisfying results after the implementation of information systems in hospitals, such as the high rate of overrides relating to alerting information generated from Prescription Automatic Screening System (PASS). Objective: The objective of this study is to systematically explore the imperative role of PASS, an aided diagnosis system, on physicians' behavior change in order to clarify the various factors relative to the effective use of PASS. Methods: In order to systematically examine the various impacts of PASS, we adopted a quasiexperiment by using a two-year observation dataset from two hospitals. We then analyzed the data related to physicians' prescription behavior both before and after the deployment of PASS and eliminated the influences from a variety of perplexing factors by utilizing a control hospital which does not use a PASS system. In total, 754 physicians were included in this experiment composed of 11,054 patients, 400 physicians in the treatment group and 354 physicians in the control group, respectively. Moreover, this study was preceded by a series of interviews, which was employed to identify the moderators and we adopted propensity score matching (PSM) integrated with the difference-in-differences (DID) so as to isolate the impacts of PASS. Results: The impacts of PASS on prescription errors and medical treatment costs were all significant (Error: 95% CI -0.40-0.11; P=0.001; Costs: 95% CI -0.75--0.12; P=0.007), and help explain physician behavior over performance. Moreover, institutional pressure decreased the impact of PASS on the error of prescription (95% CI 0.07-0.55; P=0.012) and workload, respectively, thus reducing the impact of PASS on medical treatment costs (95% CI 0.18-0.39; P<0.001). We also suspect that other pressures (e.g., title and risk of illness) also impair physicians' attention to the intelligent alerting from PASS. However, the impacts of PASS did not change among physicians having a higher title or experience or when treating diseases demonstrating high risk. The researcher posits that this is because these physicians will focus more attention on their patients in these situations, regardless of having access to an intelligent system. Conclusions: Auxiliary diagnosis systems (such as PASS) do play a critical role in physicians' behavior change. However, workload and organizational pressure remain problematic in this context, since they will impair the positive impacts of auxiliary diagnosis systems on performance. This again highlights the importance of considering both technical and organizational issues to obtain the highest level of effectiveness when deploying IT in...

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Medication-related clinical decision support alert overrides in inpatients

Abstract: Almost three-quarters of alerts were overridden, and 40% of the overrides were not appropriate. Future research should optimize alert types and frequencies to increase their clinical relevance, reducing alert fatigue so that important alerts are not inappropriately overridden.

Cited by 121 publications

References 45 publications

Optimizing Drug-Drug Interaction Alerts Using a Multidimensional Approach

Optimizing Drug-Drug Interaction Alerts Using a Multidimensional Approach

Negligible impact of highly patient-specific decision support for potassium-increasing drug-drug interactions – a cluster-randomised controlled trial

Exploring the Impact of the Prescription Automatic Screening System in Health Care Services: Quasi-Experiment (Preprint)

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