Implementation of pharmacogenomics into inpatient general medicine.

Pharmacogenomics is a crucial piece of personalized medicine. Preemptive pharmacogenomic testing is only used sparsely in the inpatient setting and there are few models to date for fostering the adoption of pharmacogenomic treatment in the inpatient setting. We created a multi-institutional project in Chicago to enable the translation of pharmacogenomics into inpatient practice. We are reporting our implementation process and barriers we encountered with solutions. This study, 'Implementation of Point-of-Care Pharmacogenomic Decision Support Accounting for Minority Disparities', sought to implement pharmacogenomics into inpatient practice at three sites: The University of Chicago, Northwestern Memorial Hospital, and the University of Illinois at Chicago. This study involved enrolling African American adult patients for preemptive genotyping across a panel of actionable germline variants predicting drug response or toxicity risk. We report our approach to implementation and the barriers we encountered engaging hospitalists and general medical providers in the inpatient pharmacogenomic intervention. Our strategies included: a streamlined delivery system for pharmacogenomic information, attendance at hospital medicine section meetings, use of physician and pharmacist champions, focus on hospitalists' care and optimizing system function to fit their workflow, hand-offs, and dealing with hospitalists turnover. Our work provides insights into strategies for the initial engagement of inpatient general medicine providers that we hope will benefit other institutions seeking to implement pharmacogenomics in the inpatient setting.

Pilot Findings of Pharmacogenomics in Perioperative Care: Initial Results From the First Phase of the ImPreSS Trial.

BACKGROUND: Pharmacogenomics, which offers a potential means by which to inform prescribing and avoid adverse drug reactions, has gained increasing consideration in other medical settings but has not been broadly evaluated during perioperative care. METHODS: The Implementation of Pharmacogenomic Decision Support in Surgery (ImPreSS) Trial is a prospective, single-center study consisting of a prerandomization pilot and a subsequent randomized phase. We describe findings from the pilot period. Patients planning elective surgeries were genotyped with pharmacogenomic results, and decision support was made available to anesthesia providers in advance of surgery. Pharmacogenomic result access and prescribing records were analyzed. Surveys (Likert-scale) were administered to providers to understand utilization barriers. RESULTS: Of eligible anesthesiology providers, 166 of 211 (79%) enrolled. A total of 71 patients underwent genotyping and surgery (median, 62 years; 55% female; average American Society of Anesthesiologists (ASA) score, 2.6; 58 inpatients and 13 ambulatories). No patients required postoperative intensive care or pain consultations. At least 1 provider accessed pharmacogenomic results before or during 41 of 71 surgeries (58%). Faculty were more likely to access results (78%) compared to house staff (41%; P = .003) and midlevel practitioners (15%) ( P < .0001). Notably, all administered intraoperative medications had favorable genomic results with the exception of succinylcholine administration to 1 patient with genomically increased risk for prolonged apnea (without adverse outcome). Considering composite prescribing in preoperative, recovery, throughout hospitalization, and at discharge, each patient was prescribed a median of 35 (range 15-83) total medications, 7 (range 1-22) of which had annotated pharmacogenomic results. Of 2371 prescribing events, 5 genomically high-risk medications were administered (all tramadol or omeprazole; with 2 of 5 pharmacogenomic results accessed), and 100 genomically cautionary mediations were administered (hydralazine, oxycodone, and pantoprazole; 61% rate of accessing results). Providers reported that although results were generally easy to access and understand, the most common reason for not considering results was because remembering to access pharmacogenomic information was not yet a part of their normal clinical workflow. CONCLUSIONS: Our pilot data for result access rates suggest interest in pharmacogenomics by anesthesia providers, even if opportunities to alter prescribing in response to high-risk genotypes were infrequent. This pilot phase has also uncovered unique considerations for implementing pharmacogenomic information in the perioperative care setting, and new strategies including adding the involvement of surgery teams, targeting patients likely to need intensive care and dedicated pain care, and embedding pharmacists within rounding models will be incorporated in the follow-on randomized phase to increase engagement and likelihood of affecting prescribing decisions and clinical outcomes.

Applicability of Pharmacogenomically Guided Medication Treatment during Hospitalization of At-Risk Minority Patients.

Known disparities exist in the availability of pharmacogenomic information for minority populations, amplifying uncertainty around clinical utility for these groups. We conducted a multi-site inpatient pharmacogenomic implementation program among self-identified African-Americans (AA; n = 135) with numerous rehospitalizations (n = 341) from 2017 to 2020 (NIH-funded ACCOuNT project/clinicaltrials.gov#NCT03225820). We evaluated the point-of-care availability of patient pharmacogenomic results to healthcare providers via an electronic clinical decision support tool. Among newly added medications during hospitalizations and at discharge, we examined the most frequently utilized medications with associated pharmacogenomic results. The population was predominantly female (61%) with a mean age of 53 years (range 19-86). On average, six medications were newly prescribed during each individual hospital admission. For 48% of all hospitalizations, clinical pharmacogenomic information was applicable to at least one newly prescribed medication. Most results indicated genomic favorability, although nearly 29% of newly prescribed medications indicated increased genomic caution (increase in toxicity risk/suboptimal response). More than one of every five medications prescribed to AA patients at hospital discharge were associated with cautionary pharmacogenomic results (most commonly pantoprazole/suboptimal antacid effect). Notably, high-risk pharmacogenomic results (genomic contraindication) were exceedingly rare. We conclude that the applicability of pharmacogenomic information during hospitalizations for vulnerable populations at-risk for experiencing health disparities is substantial and warrants continued prospective investigation.

Antimicrobial Stewardship Review of Automated Candidemia Alerts Using the Epic Stewardship Module Improves Bundle-of-Care Adherence.

BACKGROUND: Antimicrobial stewardship interventions utilizing real-time alerting through the electronic medical record enable timely implementation of the bundle of care (BOC) for patients with severe infections, such as candidemia. Automated alerting for candidemia using the Epic stewardship module has been in place since July 2015 at our medical center. We sought to assess the impact of these alerts. METHODS: All adult inpatients with candidemia between April 1, 2011, and March 31, 2012 (pre-intervention), and June 30, 2016, and July 1, 2017 (post-intervention), were evaluated for BOC adherence. We also evaluated the impact on timeliness to initiate targeted therapy, length of stay (LOS), and 30-day mortality. RESULTS: Eighty-four patients were included, 42 in the pre- and 42 in the post-intervention group. Adherence to BOC was significantly improved, from 48% (pre-intervention) to 83% (post-intervention; P = .001). The median time to initiation of therapy was 4.8 hours vs 3.3 hours (P = .58), the median LOS was 24 and 18 days (P = .28), and 30-day mortality was 19% and 26% (P = .60) in the pre- and post-intervention groups, respectively. CONCLUSIONS: Antimicrobial stewardship program review of automated alerts identifying patients with candidemia resulted in significantly improved BOC adherence and was associated with a 1.5-hour reduction in time to initiation of antifungal therapy. No significant change was observed with 30-day mortality or LOS.

Reducing medication errors involving antiretroviral therapy with targeted electronic medical record modifications.

Medication errors are common among HIV-infected patients on anti-retroviral therapy (ART), especially when transitioning to the inpatient setting. In previous studies, medication error rates among hospitalized patients on ART have been reported to exceed 50%. When patients receiving ART are admitted to the hospital, medication errors can be prevented through optimization of administration instructions and dosing defaults in order-entry screens in the electronic medical record (EMR). We sought to evaluate the impact of EMR modifications (defaulted doses, frequencies, and administration instructions) implemented to improve the order-entry process and reduce errors. All adult patients admitted between 10/1/2010-3/31/2012 (pre-EMR modification) and 10/1/2013-3/31/2014 (post-EMR modification) that continued on ART upon admission were included. The primary outcome was the overall rate of medication errors identified through review by the antimicrobial stewardship program (ASP). We also characterized the types of medication errors identified during the two time periods. Following EMR modifications, the medication error rate identified through ASP review was reduced from 50.2% to 28.2% (P < 0.01). The number of medication related errors relating to dosage (regimens requiring dose optimization, renal dose adjustment, and dose timing) were reduced by 22% (P < 0.01). Modifications at the anti-retroviral medication order-entry screens in the EMR significantly reduced medication errors, particularly with respect to dosing and dose timing.

Impact of a Clinical Decision Support Tool on Cancer Pain Management in Opioid-Tolerant Inpatients.

Background: Pain is both common and undertreated in the hematology/oncology population despite national guidelines and a focus from The Joint Commission. Objective: Herein, we describe the features of a pain clinical decision support tool (PCDST) embedded into the electronic medical record (EMR) and report its impact on oncology inpatients at risk for uncontrolled pain. Methods: The PCDST was developed to identify patients with potentially uncontrolled pain, defined as a pain score ≥4. Clinical pharmacists were encouraged to use the tool to determine whether interventions were needed to better control pain. Pain and safety outcomes between 2 cohorts of opioid-tolerant adult inpatients presenting with severe pain were compared prior to and following the implementation of the PCDST. Results: The primary endpoint, attainment of analgesia at 24 hours from admission, was met in 10 of 30 (33.3%) patients in the preimplementation group and in 14 of 32 (43.8%) of patients in the postimplementation group (P = .78). Secondary endpoints including time to analgesia, mean pain score, frequency of pharmacy intervention, and National Comprehensive Cancer Network (NCCN) guideline-adherent pain regimens were not found to be statistically significantly different between the 2 groups. The number of mean nursing pain assessments in the first 24 hours from admission was found to be significantly higher in the postimplementation group compared with the preimplementation group (12 vs 7.4, P < .001). Safety events were rare and not statistically different between groups. Conclusion: Overall, a modest, but statistically nonsignificant, improvement in pain outcomes was associated with patients admitted after the implementation of a pharmacist-managed electronic pain scoring tool.

Improved rates of antimicrobial stewardship interventions following implementation of the Epic antimicrobial stewardship module.

We evaluated the impact of the Epic antimicrobial stewardship module (EAM) on the number of interventions, antimicrobial usage, and clinical outcomes. Use of the EAM allowed us to significantly increase the number of ASP antimicrobial reviews and interventions while maintaining a sustained impact on antimicrobial utilization.

Criteria for assessing high-priority drug-drug interactions for clinical decision support in electronic health records.

BACKGROUND: High override rates for drug-drug interaction (DDI) alerts in electronic health records (EHRs) result in the potentially dangerous consequence of providers ignoring clinically significant alerts. Lack of uniformity of criteria for determining the severity or validity of these interactions often results in discrepancies in how these are evaluated. The purpose of this study was to identify a set of criteria for assessing DDIs that should be used for the generation of clinical decision support (CDS) alerts in EHRs. METHODS: We conducted a 20-year systematic literature review of MEDLINE and EMBASE to identify characteristics of high-priority DDIs. These criteria were validated by an expert panel consisting of medication knowledge base vendors, EHR vendors, in-house knowledge base developers from academic medical centers, and both federal and private agencies involved in the regulation of medication use. RESULTS: Forty-four articles met the inclusion criteria for assessing characteristics of high-priority DDIs. The panel considered five criteria to be most important when assessing an interaction- Severity, Probability, Clinical Implications of the interaction, Patient characteristics, and the Evidence supporting the interaction. In addition, the panel identified barriers and considerations for being able to utilize these criteria in medication knowledge bases used by EHRs. CONCLUSIONS: A multi-dimensional approach is needed to understanding the importance of an interaction for inclusion in medication knowledge bases for the purpose of CDS alerting. The criteria identified in this study can serve as a first step towards a uniform approach in assessing which interactions are critical and warrant interruption of a provider's workflow.