The Contribution of Pharmacogenetic Drug Interactions to 90-Day Hospital Readmissions: Preliminary Results from a Real-World Healthcare System

David, Sean P.; Singh, Lavisha; Pruitt, Jaclyn; Hensing, Andrew; Hulick, Peter J.; Meltzer, David O.; O’Donnell, Peter H.; Dunnenberger, Henry M.

doi:10.3390/jpm11121242

Cited by 4 publications

(5 citation statements)

References 21 publications

(25 reference statements)

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“…These medications are often prescribed in the post-operative or acute care setting and represent a high-risk patient population that will benefit from implementation of pre-emptive PGx panel testing [ 21 ]. In one retrospective analysis in patients who underwent panel based PGx testing, the presence of a gene-drug interaction for CPIC guideline medications was associated with an increased risk of 90-day hospital readmission by more than 40% [ 22 ]. An ongoing prospective study will determine whether PGx panel testing is feasible in the acute care setting [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population

Verma

Keat

et al. 2022

J Transl Med

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Background Pharmacogenomics (PGx) aims to utilize a patient’s genetic data to enable safer and more effective prescribing of medications. The Clinical Pharmacogenetics Implementation Consortium (CPIC) provides guidelines with strong evidence for 24 genes that affect 72 medications. Despite strong evidence linking PGx alleles to drug response, there is a large gap in the implementation and return of actionable pharmacogenetic findings to patients in standard clinical practice. In this study, we evaluated opportunities for genetically guided medication prescribing in a diverse health system and determined the frequencies of actionable PGx alleles in an ancestrally diverse biobank population. Methods A retrospective analysis of the Penn Medicine electronic health records (EHRs), which includes ~ 3.3 million patients between 2012 and 2020, provides a snapshot of the trends in prescriptions for drugs with genotype-based prescribing guidelines (‘CPIC level A or B’) in the Penn Medicine health system. The Penn Medicine BioBank (PMBB) consists of a diverse group of 43,359 participants whose EHRs are linked to genome-wide SNP array and whole exome sequencing (WES) data. We used the Pharmacogenomics Clinical Annotation Tool (PharmCAT), to annotate PGx alleles from PMBB variant call format (VCF) files and identify samples with actionable PGx alleles. Results We identified ~ 316.000 unique patients that were prescribed at least 2 drugs with CPIC Level A or B guidelines. Genetic analysis in PMBB identified that 98.9% of participants carry one or more PGx actionable alleles where treatment modification would be recommended. After linking the genetic data with prescription data from the EHR, 14.2% of participants (n = 6157) were prescribed medications that could be impacted by their genotype (as indicated by their PharmCAT report). For example, 856 participants received clopidogrel who carried CYP2C19 reduced function alleles, placing them at increased risk for major adverse cardiovascular events. When we stratified by genetic ancestry, we found disparities in PGx allele frequencies and clinical burden. Clopidogrel users of Asian ancestry in PMBB had significantly higher rates of CYP2C19 actionable alleles than European ancestry users of clopidrogrel (p < 0.0001, OR = 3.68). Conclusions Clinically actionable PGx alleles are highly prevalent in our health system and many patients were prescribed medications that could be affected by PGx alleles. These results illustrate the potential utility of preemptive genotyping for tailoring of medications and implementation of PGx into routine clinical care.

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Section: Discussionmentioning

confidence: 99%

Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population

Verma

Keat

et al. 2022

J Transl Med

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“…The study population included patients ages 18 or older who were clinically tested through December 2021 for 13 genes with associated Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines with actionable clinical recommendations. The genotyping method varied based on the clinical offering at the time of testing and the majority of patients were tested as part of a large population screening program using a next generation sequencing (NGS) Color ™ (Burlingame, CA, USA) panel that also included cardiology and hereditary cancer related genes [ 16 , 17 ]. The remaining patients were genotyped with a NGS panel by Sema4 ™ (Stamford, CT, USA) ( n = 3607), by the Center for Personalized Medicine using laboratory developed assays ( n = 2191), or by a third-party vendor ( n = 6).…”

Section: Methodsmentioning

confidence: 99%

“…Previous evaluations of the associations between pharmacogenetic phenotypes (i.e., drug response) and hospital admissions reported mixed results [ 14 , 15 ], yet these studies did not evaluate gene-x-drug interactions identified through genetic testing. In a recent analysis, the presence of one or more gene-x-drug interactions with medications associated with guidance from the Clinical Pharmacogenomics Implementation Consortium (CPIC) increased the risk of hospital readmissions [ 16 ]. That same study also demonstrated that compared to patients with no chronic conditions, patients with multiple comorbidities who were prescribed a medication with CPIC guidance within 30 days of an initial inpatient hospital stay were more than two times more likely to experience a hospital readmission within 90 days.…”

Section: Introductionmentioning

confidence: 99%

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System

Saulsberry

Singh

Pruitt

et al. 2022

JPM

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The present study builds on our prior work that demonstrated an association between pharmacogenetic interactions and 90-day readmission. In a substantially larger, more diverse study population of 19,999 adults tracked from 2010 through 2020 who underwent testing with a 13-gene pharmacogenetic panel, we included additional covariates to evaluate aggregate contribution of social determinants and medical comorbidity with the presence of identified gene-x-drug interactions to moderate 90-day hospital readmission (primary outcome). Univariate logistic regression analyses demonstrated that strongest associations with 90 day hospital readmissions were the number of medications prescribed within 30 days of a first hospital admission that had Clinical Pharmacogenomics Implementation Consortium (CPIC) guidance (CPIC medications) (5+ CPIC medications, odds ratio (OR) = 7.66, 95% confidence interval 5.45–10.77) (p < 0.0001), major comorbidities (5+ comorbidities, OR 3.36, 2.61–4.32) (p < 0.0001), age (65 + years, OR = 2.35, 1.77–3.12) (p < 0.0001), unemployment (OR = 2.19, 1.88–2.64) (p < 0.0001), Black/African-American race (OR 2.12, 1.47–3.07) (p < 0.0001), median household income (OR = 1.63, 1.03–2.58) (p = 0.035), male gender (OR = 1.47, 1.21–1.80) (p = 0.0001), and one or more gene-x-drug interaction (defined as a prescribed CPIC medication for a patient with a corresponding actionable pharmacogenetic variant) (OR = 1.41, 1.18–1.70). Health insurance was not associated with risk of 90-day readmission. Race, income, employment status, and gene-x-drug interactions were robust in a multivariable logistic regression model. The odds of 90-day readmission for patients with one or more identified gene-x-drug interactions after adjustment for these covariates was attenuated by 10% (OR = 1.31, 1.08–1.59) (p = 0.006). Although the interaction between race and gene-x-drug interactions was not statistically significant, White patients were more likely to have a gene-x-drug interaction (35.2%) than Black/African-American patients (25.9%) who were not readmitted (p < 0.0001). These results highlight the major contribution of social determinants and medical complexity to risk for hospital readmission, and that these determinants may modify the effect of gene-x-drug interactions on rehospitalization risk.

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“…David et al first reported that DNA10K patients ( n = 10,104) were significantly more likely to be readmitted within 90 days of hospital discharge if they had one or more PGx interactions with CPIC medications prescribed within 30 days of admission (odds ratio (OR) = 1.42, 95% confidence interval (CI) 1.09–1.84 ( p = 0.01)). After adjustment for comorbidities and other covariates, the odds of readmission were increased by more than 30% for patients with one or more CPIC PGx interactions (OR = 1.32, 95% CI 1.02-1.73) ( p = 0.04) ( David et al, 2021b ). In a follow-up evaluation with roughly twice the sample size, led by Saulsberry and the PMED team, we replicated these findings and also showed that social determinants of health (including race, employment status, and income) were the major drivers of hospital readmission ( Saulsberry et al, 2022 ).…”

Section: Resultsmentioning

confidence: 99%

Personalized medicine in a community health system: the NorthShore experience

David,

Dunnenberger,

Choi

et al. 2023

Front. Genet.

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Genomic and personalized medicine implementation efforts have largely centered on specialty care in tertiary health systems. There are few examples of fully integrated care systems that span the healthcare continuum. In 2014, NorthShore University HealthSystem launched the Center for Personalized Medicine to catalyze the delivery of personalized medicine. Successful implementation required the development of a scalable family history collection tool, the Genetic and Wellness Assessment (GWA) and Breast Health Assessment (BHA) tools; integrated pharmacogenomics programming; educational programming; electronic medical record integration; and robust clinical decision support tools. To date, more than 225,000 patients have been screened for increased hereditary conditions, such as cancer risk, through these tools in primary care. More than 35,000 patients completed clinical genetic testing following GWA or BHA completion. An innovative program trained more than 100 primary care providers in genomic medicine, activated with clinical decision support and access to patient genetic counseling services and digital healthcare tools. The development of a novel bioinformatics platform (FLYPE) enabled the incorporation of genomics data into electronic medical records. To date, over 4,000 patients have been identified to have a pathogenic or likely pathogenic variant in a gene with medical management implications. Over 33,000 patients have clinical pharmacogenomics data incorporated into the electronic health record supported by clinical decision support tools. This manuscript describes the evolution, strategy, and successful multispecialty partnerships aligned with health system leadership that enabled the implementation of a comprehensive personalized medicine program with measurable patient outcomes through a genomics-enabled learning health system model that utilizes implementation science frameworks.

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The Contribution of Pharmacogenetic Drug Interactions to 90-Day Hospital Readmissions: Preliminary Results from a Real-World Healthcare System

Cited by 4 publications

References 21 publications

Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population

Evaluating the frequency and the impact of pharmacogenetic alleles in an ancestrally diverse Biobank population

Effect Modification by Social Determinants of Pharmacogenetic Medication Interactions on 90-Day Hospital Readmissions within an Integrated U.S. Healthcare System

Personalized medicine in a community health system: the NorthShore experience

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