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Real-World Impact of a Pharmacogenomics-Enriched Comprehensive Medication Management Program.

ABSTRACT: The availability of clinical decision support systems (CDSS) and other methods for personalizing medicine now allows evaluation of their real-world impact on healthcare delivery. For example, addressing issues associated with polypharmacy in older patients using pharmacogenomics (PGx) and comprehensive medication management (CMM) is thought to hold great promise for meaningful improvements across the goals of the Quadruple Aim. However, few studies testing these tools at scale, using relevant system-wide metrics, and under real-world conditions, have been published to date. Here, we document a reduction of ~$7000 per patient in direct medical charges (a total of $37 million over 5288 enrollees compared to 22,357 non-enrolled) in Medicare Advantage patients (≥65 years) receiving benefits through a state retirement system over the first 32 months of a voluntary PGx-enriched CMM program. We also observe a positive shift in healthcare resource utilization (HRU) away from acute care services and toward more sustainable and cost-effective primary care options. Together with improvements in medication risk assessment, patient/provider communication via pharmacist-mediated medication action plans (MAP), and the sustained positive trends in HRU, we suggest these results validate the use of a CDSS to unify PGx and CMM to optimize care for this and similar patient populations.

SUBMITTER: Jarvis JP

PROVIDER: S-EPMC8949247 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Real-World Impact of a Pharmacogenomics-Enriched Comprehensive Medication Management Program.

Jarvis Joseph P JP Peter Arul Prakasam AP Keogh Murray M Baldasare Vince V Beanland Gina M GM Wilkerson Zachary T ZT Kradel Steven S Shaman Jeffrey A JA

Journal of personalized medicine 20220308 3

The availability of clinical decision support systems (CDSS) and other methods for personalizing medicine now allows evaluation of their real-world impact on healthcare delivery. For example, addressing issues associated with polypharmacy in older patients using pharmacogenomics (PGx) and comprehensive medication management (CMM) is thought to hold great promise for meaningful improvements across the goals of the Quadruple Aim. However, few studies testing these tools at scale, using relevant sy ...[more]

PMID: 35330421

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Project description:BackgroundPoor adherence to medication regimens and medical record inconsistencies result in incomplete knowledge of medication therapy in polypharmacy patients. By quantitatively identifying medications in the blood of patients and reconciling detected medications with the medical record, we have defined the severity of this knowledge gap and created a path toward optimizing medication therapy.Methods and findingsWe validated a liquid chromatography-tandem mass spectrometry assay to detect and/or quantify 38 medications across a broad range of chronic diseases to obtain a comprehensive survey of patient adherence, medical record accuracy, and exposure variability in two patient populations. In a retrospectively tested 821-patient cohort representing U.S. adults, we found that 46% of medications assessed were detected in patients as prescribed in the medical record. Of the remaining medications, 23% were detected, but not listed in the medical record while 30% were prescribed to patients, but not detected in blood. To determine how often each detected medication fell within literature-derived reference ranges when taken as prescribed, we prospectively enrolled a cohort of 151 treatment-regimen adherent patients. In this cohort, we found that 53% of medications that were taken as prescribed, as determined using patient self-reporting, were not within the blood reference range. Of the medications not in range, 83% were below and 17% above the lower and upper range limits, respectively. Only 32% of out-of-range medications could be attributed to short oral half-lives, leaving extensive exposure variability to result from patient behavior, undefined drug interactions, genetics, and other characteristics that can affect medication exposure.ConclusionsThis is the first study to assess compliance, medical record accuracy, and exposure as determinants of real-world treatment and response. Variation in medication detection and exposure is greater than previously demonstrated, illustrating the scope of current therapy issues and opening avenues that warrant further investigation to optimize medication therapy.

Project description:BackgroundMedication errors (MEs) are harmful to patients during hospitalization, especially elderly patients. To reduce MEs, an integrated medication management (IMM) model was developed in a 2500-bed medical center, allowing a clinical pharmacist to participate in the daily ward round and perform medication reconciliation and medication reviews. This study aimed to evaluate the impact of the IMM model on MEs and medication utilization using a quasi-experimental design.MethodsWe conducted an interrupted time-series study using the aggregated data of monthly admissions from two wards of a medical center, where one ward served as the intervention and the other served as the external control. The pre- and post-intervention phases comprised of 40 and 12 monthly observational units, respectively. The primary outcome was the mean number of ME reports, which were further investigated for different ME types. The mean number of daily inpatient prescriptions, mean number of daily self-prepared medications, and median daily medication costs were measured. All outcomes were measured per admission episode. Segmented regression was used to evaluate the level and slope changes in the outcomes after IMM model implementation, and subgroup analyses were performed to examine the effects on different groups.ResultsAfter IMM model implementation, the mean number of ME reports increased (level change: 1.02, 95% confidence interval [CI]: 0.68 to 1.35, P < 0.001). The number of reports has shown a dramatic increase in omissions or medication discrepancies, inappropriate drug choices, and inappropriate routes or formulations. Furthermore, the mean number of daily inpatient prescriptions was reduced for patients aged ≥75 years (level change: -1.78, 95% CI: -3.06 to -0.50, P = 0.009). No significant level or slope change was observed in the control ward during the post-intervention phase.ConclusionsThe IMM model improved patient safety and optimized medication utilization by increasing the reporting of MEs and decreasing the number of medications used.

Dataset Information

Real-World Impact of a Pharmacogenomics-Enriched Comprehensive Medication Management Program.

Publications

Real-World Impact of a Pharmacogenomics-Enriched Comprehensive Medication Management Program.

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