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Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts.

ABSTRACT: Thoughtful integration of interruptive clinical decision support (CDS) alerts within the electronic health record is essential to guide clinicians on the application of pharmacogenomic results at point of care. St. Jude Children's Research Hospital implemented a preemptive pharmacogenomic testing program in 2011 in a multidisciplinary effort involving extensive education to clinicians about pharmacogenomic implications. We conducted a retrospective analysis of clinicians' adherence to 4783 pharmacogenomically guided CDS alerts that triggered for 12 genes and 60 drugs. Clinicians adhered to the therapeutic recommendations provided in 4392 alerts (92%). In our population of pediatric patients with catastrophic illnesses, the most frequently presented gene/drug CDS alerts were TPMT/NUDT15 and thiopurines (n = 3850), CYP2D6 and ondansetron (n = 667), CYP2D6 and oxycodone (n = 99), G6PD and G6PD high-risk medications (n = 51), and CYP2C19 and proton pump inhibitors (omeprazole and pantoprazole; n = 50). The high adherence rate was facilitated by our team approach to prescribing and our collaborative CDS design and delivery.

SUBMITTER: Nguyen JQ

PROVIDER: S-EPMC9748527 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts.

Nguyen Jenny Q JQ Crews Kristine R KR Moore Ben T BT Kornegay Nancy M NM Baker Donald K DK Hasan Murad M Campbell Patrick K PK Dean Shannon M SM Relling Mary V MV Hoffman James M JM Haidar Cyrine E CE

Journal of the American Medical Informatics Association : JAMIA 20221201 1

Thoughtful integration of interruptive clinical decision support (CDS) alerts within the electronic health record is essential to guide clinicians on the application of pharmacogenomic results at point of care. St. Jude Children's Research Hospital implemented a preemptive pharmacogenomic testing program in 2011 in a multidisciplinary effort involving extensive education to clinicians about pharmacogenomic implications. We conducted a retrospective analysis of clinicians' adherence to 4783 pharm ...[more]

PMID: 36228116

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Project description:BackgroundIndividualized selection of antiretroviral (ARV) therapy is complex, considering drug resistance, comorbidities, drug-drug interactions, and other factors. HIV-ASSIST (www.hivassist.com) is a free, online tool that provides ARV decision support. HIV-ASSIST synthesizes patient and virus-specific attributes to rank ARV combinations based upon a composite objective of achieving viral suppression and maximizing tolerability.ObjectiveTo evaluate concordance of HIV-ASSIST recommendations with ARV selections of experienced HIV clinicians.DesignRetrospective cohort study.PatientsNew and established patients at the Johns Hopkins Bartlett HIV Clinic and San Francisco Veterans Affairs HIV Clinic completing clinic visits were included. Chart reviews were conducted of the most recent clinic visit to generate HIV-ASSIST recommendations, which were compared to prescribed regimens.Main measuresFor each provider-prescribed regimen, we assessed its corresponding HIV-ASSIST "weighted score" (scale of 0 to 10 +, scores of < 2.0 are preferred), rank within HIV-ASSIST's ordered listing of ARV regimens, and concordance with the top five HIV-ASSIST ranked outputs.Key resultsAmong 106 patients (16% female), 23 (22%) were ARV-naïve. HIV-ASSIST outputs for ARV-naïve patients were 100% concordant with prescribed regimens (median rank 1 [IQR 1-3], median weighted score 1.1 [IQR 1-1.2]). For 18 (17%) ARV-experienced patients with ongoing viremia, HIV-ASSIST outputs were 89% concordant with prescribed regimens (median rank 2 [IQR 1-3], median weighted score 1 [IQR 1-1.2]). For 65 (61.3%) patients that were suppressed on a current ARV regimen, HIV-ASSIST recommendations were concordant 88% of the time (median rank 1 [IQR 1-1], median weighted score 1.1 [IQR 1-1.6]). In 18% of cases, HIV-ASSIST weighted score suggested that the prescribed regimen would be considered "less preferred" (score > 2.0) than other available alternatives.ConclusionHIV-ASSIST is an educational decision support tool that provides ARV recommendations concordant with experienced HIV providers from two major academic centers for a diverse set of patient scenarios.

Project description:Importance:Sophisticated evidence-based information resources can filter medical evidence from the literature, integrate it into electronic health records, and generate recommendations tailored to individual patients. Objective:To assess the effectiveness of a computerized clinical decision support system (CDSS) that preappraises evidence and provides health professionals with actionable, patient-specific recommendations at the point of care. Design, Setting, and Participants:Open-label, parallel-group, randomized clinical trial among internal medicine wards of a large Italian general hospital. All analyses in this randomized clinical trial followed the intent-to-treat principle. Between November 1, 2015, and December 31, 2016, patients were randomly assigned to the intervention group, in which CDSS-generated reminders were displayed to physicians, or to the control group, in which reminders were generated but not shown. Data were analyzed between February 1 and July 31, 2018. Interventions:Evidence-Based Medicine Electronic Decision Support (EBMEDS), a commercial CDSS covering a wide array of health conditions across specialties, was integrated into the hospital electronic health records to generate patient-specific recommendations. Main Outcomes and Measures:The primary outcome was the resolution rate, the rate at which medical problems identified and alerted by the CDSS were addressed by a change in practice. Secondary outcomes included the length of hospital stay and in-hospital all-cause mortality. Results:In this randomized clinical trial, 20 563 patients were admitted to the hospital. Of these, 6480 (31.5%) were admitted to the internal medicine wards (study population) and randomized (3242 to CDSS and 3238 to control). The mean (SD) age of patients was 70.5 (17.3) years, and 54.5% were men. In total, 28 394 reminders were generated throughout the course of the trial (median, 3 reminders per patient per hospital stay; interquartile range [IQR], 1-6). These messages led to a change in practice in approximately 4 of 100 patients. The resolution rate was 38.0% (95% CI, 37.2%-38.8%) in the intervention group and 33.7% (95% CI, 32.9%-34.4%) in the control group, corresponding to an odds ratio of 1.21 (95% CI, 1.11-1.32; P < .001). The length of hospital stay did not differ between the groups, with a median time of 8 days (IQR, 5-13 days) for the intervention group and a median time of 8 days (IQR, 5-14 days) for the control group (P = .36). In-hospital all-cause mortality also did not differ between groups (odds ratio, 0.95; 95% CI, 0.77-1.17; P = .59). Alert fatigue did not differ between early and late study periods. Conclusions and Relevance:An international commercial CDSS intervention marginally influenced routine practice in a general hospital, although the change did not statistically significantly affect patient outcomes. Trial Registration:ClinicalTrials.gov identifier: NCT02577198.

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Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts.

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Clinician adherence to pharmacogenomics prescribing recommendations in clinical decision support alerts.

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