Clinical Utility of Pharmacogenetic Testing and a Clinical Decision Support Tool to Enhance the Identification of Drug Therapy Problems Through Medication Therapy Management in Polypharmacy Patients

Abstract

BACKGROUND: In polypharmacy patients, medication therapy management (MTM) services provide a comprehensive review of current medications and future treatment goals. Pharmacogenetics (PGx) may further optimize the identification of potential drug therapy problems (DTPs); however, the clinical utility of PGx information with a clinical decision support tool (CDST) in an MTM setting in identifying DTPs has not been systematically assessed. OBJECTIVE: To assess the clinical utility of an MTM service enhanced by pharmacogenetic test results and a clinical decision support tool. METHODS: This study was a post hoc analysis of the data obtained from an open-label, randomized, observational trial. Polypharmacy patients eligible for MTM service were randomly assigned to 3 intervention arms: standard MTM (SMTM), MTM incorporating CDST (CMTM), and CMTM further enhanced by PGx test results of CYP450 and VKORC1 enzymes (PGxMTM). Allocation for this post hoc analysis was based on patient adherence to the research protocol and completion of a PGx test. The number of DTPs per patient was compared across the 3 arms using analysis of variance. In addition, the frequency of serious DTPs as a categorical variable (grade 3 or above vs. lower grade) was compared across the 3 arms between PGx driven and non-PGx driven DTP recommendations. Statistical significance was tested using the chi-square test. The level of agreement between the DTP seriousness and the acceptance made by prescribers was presented as Cohen's kappa coefficient. RESULTS: Numbers of patients after cohort reallocation based on completion of PGx testing were 104, 180, and 58 for the SMTM, CMTM, and PGxMTM arms, respectively. On average, 3.08 DTPs were identified for each patient, which was nearly identical across all 3 arms. Blinded clinical pharmacists considered seriousness (grade 3 or 4) in 31% of the PGxrelated DTPs in comparison with 4.9% of the non-PGx DTPs (P < 0.001). The more serious (i.e., grade 3 or above) DTP recommendations were more likely to be accepted by prescribers with the odds ratios of 1.95 (P = 0.05) and 2.39 (P = 0.15), when the analysis was performed for all DTPs and DTPs from the PGxMTM arm only, respectively. CONCLUSIONS: MTM enhanced by PGx testing and the clinical decision support tool did not increase the number of DTPs identified. However, PGx testing and the decision support software helps pharmacists determine more serious DTPs, and resulting subsequent recommendations were more readily accepted by a prescriber. Future study of the patient safety outcomes and overall health care costs associated with the utility of the decision support is warranted.

Use of Clopidogrel and Proton Pump Inhibitors Alone or in Combinations in Persons with Diabetes in Denmark; Potential for CYP2C19 Genotype-Guided Drug Therapy

“…This further substantiates that DGI and DDGI are unrecognized in clinical practice in general and in the elderly [1,2] and in persons with diabetes in particular, who are more exposed to polypharmacy [50]. These added risks are likely to result in increased health care costs [51]. Supportive evidence on cost-effectiveness of applying CYP450 PGx-guided antiplatelet therapy preemptively in cardiovascular diseases [52] and in polypharmacy have emerged [53]; however, still more studies are needed.…”

The Inclusion of Health Data Standards in the Implementation of Pharmacogenomics Systems: A Scoping Review

“…Nine of the 32 studies mentioned data standards, such as HL7, and all but two utilized HL7 to report results into EHR or external systems, as detailed in Table 1 [29,31,[37][38][39][40][41][42][43]. The remaining 23 articles mentioned standardized guidelines in regard to clinical recommendations, like CPIC and DPWG, but were unrelated to standardizing reporting of results [19,20,30,34,[44][45][46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61]. In particular, Bousman et al described four different PGx CDSSs from different companies to determine the consistency and accuracy of results.…”

Utilizing Pharmacogenomics to Reduce Adverse Drug Events

“…This scenario is referred to as a drug-gene interaction (DGI), and it often goes unrecognized as a causative or contributive factor to ADEs [3,12]. A drug-drug-gene interaction (DDGI) involves a drug-drug interaction (DDI) superimposed on a DGI that can result in a process known as phenoconversion [12][13][14]. When phenoconversion occurs, a patient's genetically derived phenotype changes (e.g., normal metabolizer to poor metabolizer), which may also change the drug's response.…”

“…Though dosing guidelines and algorithms are publicly available for healthcare practitioners, PGx testing is woefully underused in clinical practice [27]. One of the contributing factors is that most clinical decision support systems (CDSS) do not have the capability of detecting DGIs, even when PGx test results are available [13,28].…”