Use of Drug Claims Data and a Medication Risk Score to Assess the Impact of CYP2D6 Drug Interactions among Opioid Users on Healthcare Costs.

Cytochrome P450 2D6 (CYP2D6) activity is highly variable due to several factors, including genetic polymorphisms and drug-drug-gene interactions. Hydrocodone, oxycodone, codeine, and tramadol the most commonly prescribed CYP2D6-activated opioids for pain. However, the co-administration of CYP2D6 interacting drugs can modulate CYP2D6-medicated activation of these opioids, affecting drug analgesia, effectiveness, and safety, and can impact healthcare costs. A retrospective, observational cohort analysis was performed in a large (n = 50,843) adult population. This study used drug claims data to derive medication risk scores and matching propensity scores to estimate the effects of opioid use and drug-drug interactions (DDIs) on medical expenditures. 4088 individuals were identified as opioid users; 95% of those were prescribed CYP2D6-activated opioids. Among those, 15% were identified as being at risk for DDIs. Opioid users had a significant increase in yearly medical expenditure compared to non-opioid users ($2457 vs. $1210). In matched individuals, average healthcare expenditures were higher for opioid users with DDIs compared to those without DDIs ($7841 vs. $5625). The derived medication risk score was higher in CYP2D6 opioid users with interacting drug(s) compared to no DDI (15 vs. 12). Higher costs associated with CYP2D6 opioid use under DDI conditions suggest inadequate CYP2D6 opioid prescribing practices. Efforts to improve chronic opioid use in adults should reduce interacting drug combinations, especially among patients using CYP2D6 activated opioids.

Classification and Assessment of Medication Risk in the Elderly (CARE): Use of a Medication Risk Score to Inform Patients' Readmission Likelihood after Hospital Discharge.

Existing risk tools that identify patients at high risk of medication-related iatrogenesis are not sufficient to holistically evaluate a patient's entire medication regimen. This study used a novel medication risk score (MRS) which holistically evaluates medication regimens and provides actionable solutions. The main purpose of this study was to quantify adults ≥ 65 years with a high medication risk burden using the MRS and secondarily, appraise MRS association with hospital readmission. This retrospective cohort study included all consecutive patients in a 6-month period aged 65 years and older, admitted for at least 48 h, and prescribed at least five medications upon discharge. Out of 3017 patients screened, 1386 met all criteria. The primary outcome was the proportion of patients with a score of ≥20 and the secondary outcome was the 30-day readmission rate. In the overall population, 17% of patients had an MRS ≥ 20. For patients discharged home, there was a 19% readmission rate for a score ≥ 20 and 11% for <20 (p = 0.009). A score of ;≥20 was associated with a 1.8-fold increased risk of readmission in patients discharged home. Only 7% of patients met these criteria, which can help direct future use of the MRS at patients with the highest risk of medication-related iatrogenesis.

Association of the MedWise Risk Score with health care outcomes.

OBJECTIVES: Older patients are especially vulnerable to drug-related problems due to multiple prescription drugs, which increases their risk of drug-drug interactions and adverse drug events (ADEs). This study aimed to examine outcomes associated with the MedWise Risk Score (MRS) in a Medicare Part D population, including total medical expenditures, ADEs, falls, mortality, emergency department (ED) visits, hospital admissions, and length of stay (LOS). STUDY DESIGN: Retrospective observational study. METHODS: The association between MRS and patient health outcomes was derived using drug claims data from 213,561 beneficiaries and medication risk stratification using outcomes data in 2018 with 1 year of follow-up. Analyses were conducted with the Max MRS and the Mean MRS calculated over the year. Analyses utilizing the Max MRS performed better, and results using the Max MRS are presented. Statistical analyses were performed using linear regression, logistic regression, negative binomial regression, and zero-inflated Poisson (ZIP) models. RESULTS: Of 203,630 patients studied (mean ±â€…SD age, 76.0 ±â€…8.0 years), 4.9%, 9.8%, 24.5%, and 15.5% experienced at least 1 ADE, fall, ED visit, and hospital admission, respectively, in 2018. The MRS was associated with an 8.5% change in total medical expenditure per 1-unit increase. The adjusted odds ratio (OR) of ADE was 1.058 (95% CI, 1.055-1.06)/unit MRS. ADEs, falls, and death were more likely in elevated MRS categories (eg, OR of 4.45 for ADEs [95% CI, 4.10-4.83], 5.51 for falls [95% CI, 5.17-5.87], and 4.42 for death [95% CI, 3.82-5.12], respectively forSevere MRS group). Our model predicts 7000 ED visits for every 100,000 patients per unit increase of the MRS. The ZIP models estimated ORs of 1.03 and 1.01 for hospital admissions and increase in hospital LOS, respectively, per MRS unit. CONCLUSIONS: This study shows that MRS was associated with health outcomes and therefore could be used to identify patients at increased risk of negative outcomes based primarily on their medication regimens.

Adverse drug event risk assessment by the virtual addition of COVID-19 repurposed drugs to Medicare and commercially insured patients' drug regimens: A drug safety simulation study.

Drug safety is generally established from clinical trials, by pharmacovigilance programs and during observational phase IV safety studies according to drug intended or approved indications. The objective of this study was to estimate the risk of potential adverse drug events (ADEs) associated with drugs repurposed for coronavirus disease 2019 (COVID-19) treatment in a large-scale population. Drug claims were used to calculate a baseline medication risk score (MRS) indicative of ADE risk level. Fictitious claims of repurposed drugs were added, one at a time, to patients' drug regimens to calculate a new MRS and compute a level of risk. Drug claims data from enrollees with Regence health insurance were used and sub-payer analyses were performed with Medicare and commercial insured groups. Simulated interventions were conducted with hydroxychloroquine and chloroquine, alone or combined with azithromycin, and lopinavir/ritonavir, along with terfenadine and fexofenadine as positive and negative controls for drug-induced Long QT Syndrome (LQTS). There were 527,471 subjects (56.6% women; mean [SD] age, 47 years [21]) were studied. The simulated addition of each repurposed drug caused an increased risk of ADEs (median MRS increased by two-to-seven points, p < 0.001). The increase in ADE risk was mainly driven by an increase in CYP450 drug interaction risk score and by drug-induced LQTS risk score. The Medicare group presented a greater risk overall compared to the commercial group. All repurposed drugs were associated with an increased risk of ADEs. Our simulation strategy could be used as a blueprint to preemptively assess safety associated with future repurposed or new drugs.