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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.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.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.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.

Background Several opioids have pharmacogenomic associations impacting analgesic efficacy. However, germline pharmacogenomic testing is not routinely incorporated into supportive oncology. We hypothesized that CYP2D6 profiling would correlate with opioid prescribing and hospitalizations. Materials and Methods We analyzed 61,572 adult oncology patients from 2012 to 2018 for opioid exposures. CYP2D6 metabolizer phenotype (ultra-rapid [UM], normal metabolizer [NM], intermediate [IM], or poor [PM]), the latter two of which may cause inefficacy of codeine, tramadol, and standard-dose hydrocodone, was determined for patients genotyped for reasons unrelated to pain. The primary endpoint was number of opioid medications received during longitudinal care (IM/PMs vs. NMs). Secondary endpoint was likelihood of pain-related hospital encounters. Results Most patients with cancer (n = 34,675, 56%) received multiple opioids (average 2.8 ± 1.6/patient). Hydrocodone was most commonly prescribed (62%), followed by tramadol, oxycodone, and codeine. In the CYP2D6 genotyped cohort (n = 105), IM/PMs received a similar number of opioids (3.4 ± 1.4) as NMs (3.3 ± 1.9). However, IM/PMs were significantly more likely to experience pain-related hospital encounters compared with NMs, independent of other variables (odds ratio [OR] = 5.4; 95% confidence interval [CI], 1.2–23.6; p = .03). IM/PMs were also more likely to be treated with later-line opioids that do not require CYP2D6 metabolism, such as morphine and hydromorphone (OR = 3.3; 95% CI, 1.1–9.8; p = .03). Conclusion CYP2D6 genotype may identify patients with cancer at increased risk for inadequate analgesia when treated with typical first-line opioids like codeine, tramadol, or standard-dose hydrocodone. Palliative care considerations are an integral part of optimal oncology care, and these findings justify prospective evaluation of preemptive genotyping as a strategy to improve oncology pain management. Implications for Practice Genomic variation in metabolic enzymes can predispose individuals to inefficacy when receiving opioid pain medications. Patients with intermediate and/or poor CYP2D6 metabolizer status do not adequately convert codeine, tramadol, and hydrocodone into active compounds, with resulting increased risk of inadequate analgesia. This study showed that patients with cancer frequently receive CYP2D6-dependent opioids. However, patients with CYP2D6 intermediate and poor metabolizer status had increased numbers of pain-related hospitalizations and more frequently required the potent non-CYP2D6 opioids morphine and hydromorphone. This may reflect inadequate initial analgesia with the common “first-line” CYP2D6-metabolized opioids. Preemptive genotyping to guide opioid prescribing during cancer care may improve pain-related patient outcomes.

OBJECTIVES: Integration of pharmacogenomics into clinical care is being studied in multiple disciplines. We hypothesized that understanding attitudes and perceptions of anesthesiologists, critical care, and pain medicine providers would uncover unique considerations for future implementation within perioperative care. METHODS: A survey (multiple choice and Likert-scale) was administered to providers within our Department of Anesthesia and Critical Care prior to initiation of a department-wide prospective pharmacogenomics implementation program. The survey addressed knowledge, perceptions, experiences, resources, and barriers. RESULTS: Of 153 providers contacted, 149 (97%) completed the survey. Almost all providers (92%) said that genetic results influence drug therapy, and few (22%) were skeptical about the usefulness of pharmacogenomics. Despite this enthusiasm, 87% said their awareness about pharmacogenomic information is lacking. Feeling well-informed about pharmacogenomics was directly related to years in practice/experience: only 38% of trainees reported being well-informed, compared to 46% of those with 1–10 years of experience, and nearly two-thirds with 11+ years (p

OBJECTIVE: We built a novel mock pharmacogenomics web portal to deliver pharmacogenomic information and results to patients. Utilizing a patient focus group, we then sought to understand patient insights on desired features of an effective pharmacogenomics patient portal. METHODS: The mock YourPGx Portal delivered four sample pharmacogenomic results (omeprazole, simvastatin, clopidogrel, and codeine). Patients from our existing institutional, prospective pharmacogenomics implementation study were recruited to pilot the mock portal and then asked to participate in a focus group discussion led by two facilitators. All patients had been previously genotyped, but none had been directly provided access to their own genotyping results and none had previously used the YourPGx portal. The focus group discussion explored nine domains: (i) factors influencing drug response, (ii) concerns about drug effects, (iii) understanding of genomics and pharmacogenomics, (iv) reasons to undergo pharmacogenomic testing, (v) sources of pharmacogenomic information for patient education, (vi) attributes of pharmacogenomic sources of information, (vii) considerations about privacy and personal pharmacogenomic information, (viii) sharing of pharmacogenomic information, and (ix) features of an effective patient portal. RESULTS: The median age of patients (n=10) was 65.5 years old (range 38–72), 70% female, 50% Caucasian/30% Black, and 60% held a bachelor/advanced degree. When asked about resources for seeking pharmacogenomic information, patients preferred consulting their providers first, followed by self-education, then using information provided by university research organizations. A theme emerged regarding attributes of these sources, namely a desire for understandability and trust. Patients said that the effectiveness of a pharmacogenomics patient portal is improved with use of symbolisms/graphics and clear and concise content. Effective use of colors, quantifying information, consistency, and use of layperson’s language were additional important facets. Patients communicated the appeal of secured phone/app-enabled access and said that they would desire linking to their electronic medical records to allow sharing of information with different members of their healthcare team. CONCLUSION: Patients named providers as their primary source of pharmacogenomic information, but a pharmacogenomics patient portal that is carefully constructed to incorporate desired features may be a favorable tool to effectively deliver pharmacogenomic information and results to patients.

Our objective was to build a mock pharmacogenomic (PGx) patient portal and assess its ability to disseminate test results and information to patients. The YourPGx Portal delivered four sample PGx results (omeprazole, simvastatin, clopidogrel, and codeine). We hosted two study groups to assess patient knowledge and perceptions of PGx before and after accessing the portal. Ten PGx‐tested and 10 traditional care participants were included (average 61 years, 60% women, 50% African American, and 55% had a bachelor's/advanced degree). Participants scored significantly higher on the post‐test compared with the pre‐test, with no significant differences between baseline scores or score change between the groups. Patient perceptions also improved after accessing the portal—more patients wanted their providers to have access to test results, and more patients would encourage family/friends to get PGx testing. Patients would share their test results with their healthcare providers, spouse/partner, and family; none would share results with their friends or social media. Almost all patients (95%) said the portal was easy to use and 65% said it was easy to understand. In this pilot study, patients’ knowledge and perceptions of PGx improved after accessing the YourPGx Portal.

Variable responses to medications complicates perioperative care. As a potential solution, we evaluated and synthesized pharmacogenomic evidence that may inform anesthesia and pain prescribing to identify clinically actionable drug/gene pairs. Clinical decision-support (CDS) summaries were developed and were evaluated using Appraisal of Guidelines for Research and Evaluation (AGREE) II. We found that 93/180 (51%) of commonly-used perioperative medications had some published pharmacogenomic information, with 18 having actionable evidence: celecoxib/diclofenac/flurbiprofen/ibuprofen/piroxicam/CYP2C9, codeine/oxycodone/tramadol CYP2D6, desflurane/enflurane/halothane/isoflurane/sevoflurane/succinylcholine/RYR1/CACNA1S, diazepam/CYP2C19, phenytoin/CYP2C9, succinylcholine/mivacurium/BCHE, and morphine/OPRM1. Novel CDS summaries were developed for these 18 medications. AGREE II mean ± standard deviation scores were high for Scope and Purpose (95.0 ± 2.8), Rigor of Development (93.2 ± 2.8), Clarity of Presentation (87.3 ± 3.0), and Applicability (86.5 ± 3.7) (maximum score = 100). Overall mean guideline quality score was 6.7 ± 0.2 (maximum score = 7). All summaries were recommended for clinical implementation. A critical mass of pharmacogenomic evidence exists for select medications commonly used in the perioperative setting, warranting prospective examination for clinical utility.

Background Applied pharmacogenomics presents opportunities for improving patient care through precision medicine, particularly when paired with appropriate clinical decision support (CDS). However, a lack of patient resources for understanding pharmacogenomic test results may hinder shared decision-making and patient confidence in treatment. We sought to create a patient pharmacogenomics education and results delivery platform complementary to a CDS system to facilitate further research on the relevance of patient education to pharmacogenomics. Methods We conceptualized a model that extended the data access layer of an existing institutional CDS tool to allow for the pairing of decision supports offered to providers with patient-oriented summaries at the same level of phenotypic specificity. We built a two-part system consisting of a secure portal for patient use and an administrative dashboard for patient summary creation. The system was built in an ASP.NET and AngularJS architecture, and all data was housed in a HIPAA-compliant data center, with PHI secure in transit and at rest. Results The YourPGx Patient Portal was deployed on the institutional network in June 2019. Fifty-eight unique patient portal summaries have been written so far, which can provide over 4500 results modules to the pilot population of 544 patients. Patient behavior on the portal is being logged for further research. Conclusions To our knowledge, this is the first automated system designed and deployed to provide detailed, personalized patient pharmacogenomics education complementary to a clinical decision support system. Future work will expand upon this system to allow for telemedicine and patient notification of new or updated results.

12089 Background: Several opioid analgesics have well-known germline PGx associations which may predict either inefficacy or exaggerated (toxic) responses, depending on the patient’s genotype. Despite this, germline PGx testing has not been routinely incorporated into oncology care. We hypothesized that CYP2D6 germline PGx profiling offers the potential to improve oncology patients’ pain control by identifying individuals at increased risk for inadequate analgesia with standard opioid dosing. Methods: We retrospectively analyzed the medication histories of over 81,000 adult oncology patients treated at the University of Chicago from 2012-2018 for exposure to opioids. CYP2D6 genotype (permitting assignment of metabolizer phenotype: normal metabolizer [NM], intermediate metabolizer [IM], or poor metabolizer [PM]) was determined post-hoc for 127 patients who were genotyped for other reasons unrelated to pain prescribing. The primary endpoint was the number of opioids required for pain control over the course of longitudinal care, comparing PM/IMs with NMs. The secondary endpoint was the number of hospitalizations for pain control. Results: Over 47,000 oncology patients were exposed to opioids, with an average of 2.67±1.6 different opioid medication exposures per patient. Thirteen percent of genotyped patients were IM/PM, who were at risk for inadequate analgesia. IM/PM patients demonstrated an increased number of different opioid exposures (4.5±2.1) compared to NM (2.7±2.1, P value = 0.002). IM/PM patients were also more likely to have a pain related hospitalization (OR 4.17, CI 1.3-13.2, P = 0.016). Conclusions: Based on population prevalence, we estimate that > 6000 oncology patients (1000 patients/year) who received opioids at our center were IM/PM and thus at risk for inadequate analgesia due to genetic predisposition. CYP2D6 germline PGx profiling offers the potential to improve oncology patients’ pain management.