Preventing potential drug-drug interactions through alerting decision support systems: A clinical context based methodology

Pirnejad, Habibollah; Amiri, Parastoo; Niazkhani, Zahra; Shiva, Atena; Makhdoomi, Khadijeh; Abkhiz, Saeed; Sijs, Heleen van der; Bal, Roland

doi:10.1016/j.ijmedinf.2019.04.006

Cited by 23 publications

(19 citation statements)

References 38 publications

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“…The 75 non-review, non-opinion articles used a variety of metrics to evaluate the usability and acceptability of their CDS tools, with many using more than one metric. The most common evaluation was via interviews (n=29) 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 , followed by surveys or questionnaires (n=16) 27 29 50 53 55 56 57 58 59 60 61 62 63 64 65 66 . Other qualitative feedback responses were obtained by focus groups or workshops (n=5) 43 57 61 67 68 .…”

Section: Resultsmentioning

confidence: 99%

“…Customizability was another factor that could improve user experience with CDS. Customizability can be at the scale of the hospital or clinic [69,73] or by the end-user altering, for example, which alerts are seen [44]. Additionally, role-tailoring, in which CDS is targeted to users by role such as nurse, pharmacist, physician, etc., was also seen as a way to reduce burnout and increase acceptability in CDS [21,51].…”

Section: Fix It -Improving Cdsmentioning

confidence: 99%

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Clinical Decision Support and Implications for the Clinician Burnout Crisis

Janković

Chen

2020

Yearb Med Inform

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Objectives: This survey aimed to review aspects of clinical decision support (CDS) that contribute to burnout and identify key themes for improving the acceptability of CDS to clinicians, with the goal of decreasing said burnout. Methods: We performed a survey of relevant articles from 2018-2019 addressing CDS and aspects of clinician burnout from PubMed and Web of Science™. Themes were manually extracted from publications that met inclusion criteria. Results: Eighty-nine articles met inclusion criteria, including 12 review articles. Review articles were either prescriptive, describing how CDS should work, or analytic, describing how current CDS tools are deployed. The non-review articles largely demonstrated poor relevance and acceptability of current tools, and few studies showed benefits in terms of efficiency or patient outcomes from implemented CDS. Encouragingly, multiple studies highlighted steps that succeeded in improving both acceptability and relevance of CDS. Conclusions: CDS can contribute to clinician frustration and burnout. Using the techniques of improving relevance, soliciting feedback, customization, measurement of outcomes and metrics, and iteration, the effects of CDS on burnout can be ameliorated.

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Section: Resultsmentioning

confidence: 99%

Section: Fix It -Improving Cdsmentioning

confidence: 99%

Clinical Decision Support and Implications for the Clinician Burnout Crisis

Janković

Chen

2020

Yearb Med Inform

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“…The outpatient transplant clinic of the Urmia Medical Science University (UMSU) has recently implemented a homegrown, renal transplant management system (RTMS). This system has been equipped with a computerized provider order entry (CPOE), a drug-drug interaction CDSS [ 28 ] and a glomerular filtration rate prediction CDSS for upcoming follow up visits [ 29 , 30 ]. Having such a system available in our clinic provided a unique opportunity to develop a DLI-CDSS, alongside others.…”

Section: Methodsmentioning

confidence: 99%

“…In this study, the main focus was on the common medications used orally amongst adult outpatients, and not on those largely used in the inpatient setting or via parenteral routes. These medications were previously identified through a prospective cross-sectional study in the clinic during 2 months [ 28 ]. Then, the DLIs for the oral administration dosages of these medications were extracted from the main pharmacology textbooks and references, including the “Mosby’s diagnostic and laboratory test reference” [ 31 ], the “up-to-date” [ 32 ] as well as the “prescriber’s digital reference” [ 33 ].…”

Section: Methodsmentioning

confidence: 99%

“…To our knowledge, studies of computerized systems being used to manage DLIs are missing in the transplantation field. As part of a longitudinal project to improve the quality of kidney transplantation care (see for example [ 28 , 29 ]), we examined the existing complexities in the context of transplantation care, on the one hand, and the current evidence on DLIs, on the other hand, to develop an evidence-based computerized CDSS to support nephrologists in the safe medication prescribing alongside individual patients’ laboratory values. The processes of this CDSS’s development can be used as a proof-of-concept helping other transplant programs to design and apply more specialized, transplant focused CDSSs.…”

Section: Introductionmentioning

confidence: 99%

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Translation of evidence into kidney transplant clinical practice: managing drug-lab interactions by a context-aware clinical decision support system

Niazkhani

Fereidoni

Khazaee

et al. 2020

BMC Med Inform Decis Mak

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Background Drug-laboratory (lab) interactions (DLIs) are a common source of preventable medication errors. Clinical decision support systems (CDSSs) are promising tools to decrease such errors by improving prescription quality in terms of lab values. However, alert fatigue counteracts their impact. We aimed to develop a novel user-friendly, evidence-based, clinical context-aware CDSS to alert nephrologists about DLIs clinically important lab values in prescriptions of kidney recipients . Methods For the most frequently prescribed medications identified by a prospective cross-sectional study in a kidney transplant clinic, DLI-rules were extracted using main pharmacology references and clinical inputs from clinicians. A CDSS was then developed linking a computerized prescription system and lab records. The system performance was tested using data of both fictitious and real patients. The “Questionnaire for User Interface Satisfaction” was used to measure user satisfaction of the human-computer interface. Results Among 27 study medications, 17 needed adjustments regarding renal function, 15 required considerations based on hepatic function, 8 had drug-pregnancy interactions, and 13 required baselines or follow-up lab monitoring. Using IF & THEN rules and the contents of associated alert, a DLI-alerting CDSS was designed. To avoid alert fatigue, the alert appearance was considered as interruptive only when medications with serious risks were contraindicated or needed to be discontinued or adjusted. Other alerts appeared in a non-interruptive mode with visual clues on the prescription window for easy, intuitive notice. When the system was used for real 100 patients, it correctly detected 260 DLIs and displayed 249 monitoring, seven hepatic, four pregnancy, and none renal alerts. The system delivered patient-specific recommendations based on individual lab values in real-time. Clinicians were highly satisfied with the usability of the system. Conclusions To our knowledge, this is the first study of a comprehensive DLI-CDSS for kidney transplant care. By alerting on considerations in renal and hepatic dysfunctions, maternal and fetal toxicity, or required lab monitoring, this system can potentially improve medication safety in kidney recipients. Our experience provides a strong foundation for designing specialized systems to promote individualized transplant follow-up care.

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Contextualized Drug–Drug Interaction Management Improves Clinical Utility Compared With Basic Drug–Drug Interaction Management in Hospitalized Patients

Wasylewicz

Burgt

Manten

et al. 2022

Clin Pharma and Therapeutics

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Drug-drug interactions (DDIs) frequently trigger adverse drug events or reduced efficacy. Most DDI alerts, however, are overridden because of irrelevance for the specific patient. Basic DDI clinical decision support (CDS) systems offer limited possibilities for decreasing the number of irrelevant DDI alerts without missing relevant ones. Computerized decision tree rules were designed to context-dependently suppress irrelevant DDI alerts. A crossover study was performed to compare the clinical utility of contextualized and basic DDI management in hospitalized patients. First, a basic DDI-CDS system was used in clinical practice while contextualized DDI alerts were collected in the background. Next, this process was reversed. All medication orders (MOs) from hospitalized patients with at least one DDI alert were included. The following outcome measures were used to assess clinical utility: positive predictive value (PPV), negative predictive value (NPV), number of pharmacy interventions (PIs)/1,000 MOs, and the median time spent on DDI management/1,000 MOs. During the basic DDI management phase 1,919 MOs/day were included, triggering 220 DDI alerts/1,000 MOs; showing 57 basic DDI alerts/1,000 MOs to pharmacy staff; PPV was 2.8% with 1.6 PIs/1,000 MOs costing 37.2 minutes/1,000 MOs. No DDIs were missed by the contextualized CDS system (NPV 100%). During the contextualized DDI management phase 1,853 MOs/day were included, triggering 244 basic DDI alerts/1,000 MOs, showing 9.6 contextualized DDIs/1,000 MOs to pharmacy staff; PPV was 41.4% (P < 0.01), with 4.0 PIs/1,000 MOs (P < 0.01) and 13.7 minutes/1,000 MOs. The clinical utility of contextualized DDI management exceeds that of basic DDI management.

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Preventing potential drug-drug interactions through alerting decision support systems: A clinical context based methodology

Cited by 23 publications

References 38 publications

Clinical Decision Support and Implications for the Clinician Burnout Crisis

Clinical Decision Support and Implications for the Clinician Burnout Crisis

Translation of evidence into kidney transplant clinical practice: managing drug-lab interactions by a context-aware clinical decision support system

Contextualized Drug–Drug Interaction Management Improves Clinical Utility Compared With Basic Drug–Drug Interaction Management in Hospitalized Patients

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