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Johnson D, Del Fiol G, Kawamoto K, Romagnoli KM, Sanders N, Isaacson G, Jenkins E, Williams MS. Genetically guided precision medicine clinical decision support tools: a systematic review. J Am Med Inform Assoc 2024; 31:1183-1194. [PMID: 38558013 PMCID: PMC11031215 DOI: 10.1093/jamia/ocae033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 02/06/2024] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
OBJECTIVES Patient care using genetics presents complex challenges. Clinical decision support (CDS) tools are a potential solution because they provide patient-specific risk assessments and/or recommendations at the point of care. This systematic review evaluated the literature on CDS systems which have been implemented to support genetically guided precision medicine (GPM). MATERIALS AND METHODS A comprehensive search was conducted in MEDLINE and Embase, encompassing January 1, 2011-March 14, 2023. The review included primary English peer-reviewed research articles studying humans, focused on the use of computers to guide clinical decision-making and delivering genetically guided, patient-specific assessments, and/or recommendations to healthcare providers and/or patients. RESULTS The search yielded 3832 unique articles. After screening, 41 articles were identified that met the inclusion criteria. Alerts and reminders were the most common form of CDS used. About 27 systems were integrated with the electronic health record; 2 of those used standards-based approaches for genomic data transfer. Three studies used a framework to analyze the implementation strategy. DISCUSSION Findings include limited use of standards-based approaches for genomic data transfer, system evaluations that do not employ formal frameworks, and inconsistencies in the methodologies used to assess genetic CDS systems and their impact on patient outcomes. CONCLUSION We recommend that future research on CDS system implementation for genetically GPM should focus on implementing more CDS systems, utilization of standards-based approaches, user-centered design, exploration of alternative forms of CDS interventions, and use of formal frameworks to systematically evaluate genetic CDS systems and their effects on patient care.
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Affiliation(s)
- Darren Johnson
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT 84108, United States
| | - Katrina M Romagnoli
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
| | - Nathan Sanders
- School of Medicine, Geisinger Health Systems, Danville, PA 17822, United States
| | - Grace Isaacson
- Family Medicine, Penn Highlands Healthcare, DuBois, PA 16830, United States
| | - Elden Jenkins
- School of Medicine, Noorda College of Osteopathic Medicine, Provo, UT 84606, United States
| | - Marc S Williams
- Department of Genomic Health, Geisinger Health Systems, Danville, PA 17822, United States
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Tang Girdwood S, Hall M, Antoon JW, Kyler KE, Williams DJ, Shah SS, Orth LE, Goldman J, Feinstein JA, Ramsey LB. Opportunities for Pharmacogenetic Testing to Guide Dosing of Medications in Youths With Medicaid. JAMA Netw Open 2024; 7:e2355707. [PMID: 38349656 PMCID: PMC10865156 DOI: 10.1001/jamanetworkopen.2023.55707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 12/19/2023] [Indexed: 02/15/2024] Open
Abstract
Importance There are an increasing number of medications with a high level of evidence for pharmacogenetic-guided dosing (PGx drugs). Knowledge of the prevalence of dispensings of PGx drugs and their associated genes may allow hospitals and clinical laboratories to determine which pharmacogenetic tests to implement. Objectives To investigate the prevalence of outpatient dispensings of PGx drugs among Medicaid-insured youths, determine genes most frequently associated with PGx drug dispenses, and describe characteristics of youths who were dispensed at least 1 PGx drug. Design, Setting, and Participants This serial cross-sectional study includes data from 2011 to 2019 among youths aged 0 to 17 years in the Marketscan Medicaid database. Data were analyzed from August to December 2022. Main Outcomes and Measures PGx drugs were defined as any medication with level A evidence as determined by the Clinical Pharmacogenetics Implementation Consortium (CPIC). The number of unique youths dispensed each PGx drug in each year was determined. PGx drugs were grouped by their associated genes for which there was CPIC level A evidence to guide dosing, and a dispensing rate (No. of PGx drugs/100 000 youths) was determined for each group for the year 2019. Demographics were compared between youths dispensed at least 1 PGx drug and those not dispensed any PGx drugs. Results The number of Medicaid-insured youths queried ranged by year from 2 078 683 youths in 2011 to 4 641 494 youths in 2017, including 4 126 349 youths (median [IQR] age, 9 [5-13] years; 2 129 926 males [51.6%]) in 2019. The proportion of Medicaid-insured youths dispensed PGx drugs increased from 289 709 youths (13.9%; 95% CI, 13.8%-14.0%) in 2011 to 740 072 youths (17.9%; 95% CI, 17.9%-18.0%) in 2019. Genes associated with the most frequently dispensed medications were CYP2C9, CYP2D6, and CYP2C19 (9197.0 drugs [95% CI, 9167.7-9226.3 drugs], 8731.5 drugs [95% CI, 8702.5-8759.5 drugs], and 3426.8 drugs [95% CI, 3408.1-3443.9 drugs] per 100 000 youths, respectively). There was a higher percentage of youths with at least 1 chronic medical condition among youths dispensed at least 1 PGx drug (510 445 youths [69.0%; 95% CI, 68.8%-69.1%]) than among 3 386 277 youths dispensed no PGx drug (1 381 544 youths [40.8%; 95% CI, 40.7%-40.9%) (P < .001) in 2019. Conclusions and Relevance In this study, there was an increasing prevalence of dispensings for PGx drugs. This finding suggests that pharmacogenetic testing of specific drug-gene pairs should be considered for frequently prescribed PGx drugs and their implicated genes.
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Affiliation(s)
- Sonya Tang Girdwood
- Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
- Division of Translational and Clinical Pharmacology, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
| | | | - James W. Antoon
- Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee
- Division of Hospital Medicine, Monroe Carell Jr Children's Hospital at Vanderbilt University Medical Center, Nashville, Tennessee
| | - Kathryn E. Kyler
- Division of Hospital Medicine, Children’s Mercy Kansas City, Kansas City, Missouri
- Division of Clinical Pharmacology, Children’s Mercy Kansas City, Kansas City, Missouri
- School of Medicine, University of Missouri-Kansas City
| | - Derek J. Williams
- Department of Pediatrics, Vanderbilt University School of Medicine, Nashville, Tennessee
- Division of Hospital Medicine, Monroe Carell Jr Children's Hospital at Vanderbilt University Medical Center, Nashville, Tennessee
| | - Samir S. Shah
- Division of Hospital Medicine, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio
- Division of Infectious Diseases, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
| | - Lucas E. Orth
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy, Aurora
| | - Jennifer Goldman
- Division of Clinical Pharmacology, Children’s Mercy Kansas City, Kansas City, Missouri
- School of Medicine, University of Missouri-Kansas City
- Division of Infectious Diseases, Children’s Mercy Kansas City, Kansas City, Missouri
| | - James A. Feinstein
- Adult and Child Consortium for Health Outcomes Research and Delivery Science, Children’s Hospital Colorado, University of Colorado, Aurora
| | - Laura B. Ramsey
- Division of Clinical Pharmacology, Children’s Mercy Kansas City, Kansas City, Missouri
- School of Medicine, University of Missouri-Kansas City
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3
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Lemke LK, Cicali EJ, Williams R, Nguyen KA, Cavallari LH, Wiisanen K. Clinician Response to Pharmacogenetic Clinical Decision Support Alerts. Clin Pharmacol Ther 2023; 114:1350-1357. [PMID: 37716912 PMCID: PMC10726431 DOI: 10.1002/cpt.3051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 08/09/2023] [Indexed: 09/18/2023]
Abstract
The objective of this study was to characterize clinician response following standardization of pharmacogenetic (PGx) clinical decision support alerts at University of Florida (UF) Health. A retrospective analysis of all PGx alerts that fired at a tertiary academic medical center from August 2020 through May 2022 was performed. Alert acceptance rate was calculated and compared across six gene-drug pairs, patient care setting, and clinician specialty. The disposition of the triggering medication was compared with the alert response and evaluated for congruence. There were a total of 818 alerts included for analysis of alert response, 557 alerts included in acceptance rate calculations, and 392 alerts with sufficient information to assess clinical response. The overall acceptance rate was 63%. The alert response and clinical response were congruent for 47% of alerts. Alert response was influenced by the triggering gene-drug pair, clinician specialty, patient care setting, and specialty of the provider who initially ordered the PGx test. Clinical response was mostly incongruent with alert response. Alert acceptance is influenced by the triggering gene-drug pair, clinician specialty, and care setting. Alert response is not a reliable surrogate marker for clinical action. Any future research into the impact of clinical decision support (CDS) alerts should focus on clinical response rather than alert response. Given the reliance on CDS alerts to enhance uptake of PGx, it is worthwhile to further investigate their impact on prescribing and patient outcomes.
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Affiliation(s)
- Lauren K Lemke
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Emily J Cicali
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Roy Williams
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Khoa A Nguyen
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Larisa H Cavallari
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
| | - Kristin Wiisanen
- Pharmacotherapy and Translational Research, University of Florida, Gainesville, USA
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Jamrat S, Sukasem C, Sratthaphut L, Hongkaew Y, Samanchuen T. A precision medicine approach to personalized prescribing using genetic and nongenetic factors for clinical decision-making. Comput Biol Med 2023; 165:107329. [PMID: 37611418 DOI: 10.1016/j.compbiomed.2023.107329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 07/14/2023] [Accepted: 08/07/2023] [Indexed: 08/25/2023]
Abstract
Screening potential drug-drug interactions, drug-gene interactions, contraindications, and other factors is crucial in clinical practice. However, implementing these screening concepts in real-world settings poses challenges. This work proposes an approach towards precision medicine that combines genetic and nongenetic factors to facilitate clinical decision-making. The approach focuses on raising the performance of four potential interaction screenings in the prescribing process, including drug-drug interactions, drug-gene interactions, drug-herb interactions, drug-social lifestyle interactions, and two potential considerations for patients with liver or renal impairment. The work describes the design of a curated knowledge-based model called the knowledge model for potential interaction and consideration screening, the screening logic for both the detection module and inference module, and the personalized prescribing report. Three case studies have demonstrated the proof-of-concept and effectiveness of this approach. The proposed approach aims to reduce decision-making processes for healthcare professionals, reduce medication-related harm, and enhance treatment effectiveness. Additionally, the recommendation with a semantic network is suggested to assist in risk-benefit analysis when health professionals plan therapeutic interventions with new medicines that have insufficient evidence to establish explicit recommendations. This approach offers a promising solution to implementing precision medicine in clinical practice.
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Affiliation(s)
- Samart Jamrat
- Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom, 73170, Thailand; Artificial Intelligence and Metabolomics Research Group, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, 73000, Thailand
| | - Chonlaphat Sukasem
- Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, 10400, Thailand; Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center, Ramathibodi Hospital, Bangkok, 10400, Thailand; Bumrungrad Genomic Medicine Institute, Bumrungrad International Hospital, Bangkok, 10110, Thailand
| | - Lawan Sratthaphut
- Artificial Intelligence and Metabolomics Research Group, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, 73000, Thailand; Department of Biomedicine and Health Informatics, Faculty of Pharmacy, Silpakorn University, Nakhon Pathom, 73000, Thailand
| | - Yaowaluck Hongkaew
- Bumrungrad Genomic Medicine Institute, Bumrungrad International Hospital, Bangkok, 10110, Thailand; Research and Development Laboratory, Bumrungrad International Hospital, Bangkok, 10110, Thailand
| | - Taweesak Samanchuen
- Technology of Information System Management Division, Faculty of Engineering, Mahidol University, Nakhon Pathom, 73170, Thailand.
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Cataldi M, Celentano C, Bencivenga L, Arcopinto M, Resnati C, Manes A, Dodani L, Comnes L, Vander Stichele R, Kalra D, Rengo G, Giallauria F, Trama U, Ferrara N, Cittadini A, Taglialatela M. Identification of Drugs Acting as Perpetrators in Common Drug Interactions in a Cohort of Geriatric Patients from Southern Italy and Analysis of the Gene Polymorphisms That Affect Their Interacting Potential. Geriatrics (Basel) 2023; 8:84. [PMID: 37736884 PMCID: PMC10514861 DOI: 10.3390/geriatrics8050084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Revised: 08/19/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023] Open
Abstract
BACKGROUND Pharmacogenomic factors affect the susceptibility to drug-drug interactions (DDI). We identified drug interaction perpetrators among the drugs prescribed to a cohort of 290 older adults and analysed the prevalence of gene polymorphisms that can increase their interacting potential. We also pinpointed clinical decision support systems (CDSSs) that incorporate pharmacogenomic factors in DDI risk evaluation. METHODS Perpetrator drugs were identified using the Drug Interactions Flockhart Table, the DRUGBANK website, and the Mayo Clinic Pharmacogenomics Association Table. Allelic variants affecting their activity were identified with the PharmVar, PharmGKB, dbSNP, ensembl and 1000 genome databases. RESULTS Amiodarone, amlodipine, atorvastatin, digoxin, esomperazole, omeprazole, pantoprazole, simvastatin and rosuvastatin were perpetrator drugs prescribed to >5% of our patients. Few allelic variants affecting their perpetrator activity showed a prevalence >2% in the European population: CYP3A4/5*22, *1G, *3, CYP2C9*2 and *3, CYP2C19*17 and *2, CYP2D6*4, *41, *5, *10 and *9 and SLC1B1*15 and *5. Few commercial CDSS include pharmacogenomic factors in DDI-risk evaluation and none of them was designed for use in older adults. CONCLUSIONS We provided a list of the allelic variants influencing the activity of drug perpetrators in older adults which should be included in pharmacogenomics-oriented CDSSs to be used in geriatric medicine.
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Affiliation(s)
- Mauro Cataldi
- Department of Neuroscience, Reproductive Sciences and Dentistry, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (C.C.); (C.R.); (A.M.); (L.D.); (M.T.)
| | - Camilla Celentano
- Department of Neuroscience, Reproductive Sciences and Dentistry, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (C.C.); (C.R.); (A.M.); (L.D.); (M.T.)
| | - Leonardo Bencivenga
- Department of Translational Medical Sciences, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (L.B.); (M.A.); (G.R.); (F.G.); (N.F.); (A.C.)
- Gérontopôle de Toulouse, Institut du Vieillissement, CHU de Toulouse, Cité de la Santé, Place Lange, 31300 Toulouse, France
| | - Michele Arcopinto
- Department of Translational Medical Sciences, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (L.B.); (M.A.); (G.R.); (F.G.); (N.F.); (A.C.)
| | - Chiara Resnati
- Department of Neuroscience, Reproductive Sciences and Dentistry, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (C.C.); (C.R.); (A.M.); (L.D.); (M.T.)
| | - Annalaura Manes
- Department of Neuroscience, Reproductive Sciences and Dentistry, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (C.C.); (C.R.); (A.M.); (L.D.); (M.T.)
| | - Loreta Dodani
- Department of Neuroscience, Reproductive Sciences and Dentistry, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (C.C.); (C.R.); (A.M.); (L.D.); (M.T.)
| | - Lucia Comnes
- Datawizard, Via Salaria 719a, 00138 Rome, Italy;
| | - Robert Vander Stichele
- Heymans Institute of Pharmacology, Ghent University, C. Heymanslaan 10, 9000 Ghent, Belgium; (R.V.S.); (D.K.)
- European Institute for Innovation through Health Data, c/o Department Medical Informatics and Statistics, Ghent University Hospital, C. Heymanslaan 10, 9000 Ghent, Belgium
| | - Dipak Kalra
- Heymans Institute of Pharmacology, Ghent University, C. Heymanslaan 10, 9000 Ghent, Belgium; (R.V.S.); (D.K.)
- European Institute for Innovation through Health Data, c/o Department Medical Informatics and Statistics, Ghent University Hospital, C. Heymanslaan 10, 9000 Ghent, Belgium
| | - Giuseppe Rengo
- Department of Translational Medical Sciences, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (L.B.); (M.A.); (G.R.); (F.G.); (N.F.); (A.C.)
- Istituti Clinici Scientifici—ICS Maugeri S.p.A., Via Bagni Vecchi 1, 82037 Telese, Italy
| | - Francesco Giallauria
- Department of Translational Medical Sciences, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (L.B.); (M.A.); (G.R.); (F.G.); (N.F.); (A.C.)
| | - Ugo Trama
- General Directorate for Health Protection and Coordination of the Regional Health System, Regione Campania, Centro Direzionale Is. C3, 80132 Naples, Italy;
| | - Nicola Ferrara
- Department of Translational Medical Sciences, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (L.B.); (M.A.); (G.R.); (F.G.); (N.F.); (A.C.)
- Istituti Clinici Scientifici—ICS Maugeri S.p.A., Via Bagni Vecchi 1, 82037 Telese, Italy
| | - Antonio Cittadini
- Department of Translational Medical Sciences, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (L.B.); (M.A.); (G.R.); (F.G.); (N.F.); (A.C.)
| | - Maurizio Taglialatela
- Department of Neuroscience, Reproductive Sciences and Dentistry, Federico II University of Naples, Via Sergio Pansini 5, 80131 Naples, Italy; (C.C.); (C.R.); (A.M.); (L.D.); (M.T.)
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Fahim SM, Alexander CSW, Qian J, Ngorsuraches S, Hohmann NS, Lloyd KB, Reagan A, Hart L, McCormick N, Westrick SC. Current published evidence on barriers and proposed strategies for genetic testing implementation in health care settings: A scoping review. J Am Pharm Assoc (2003) 2023; 63:998-1016. [PMID: 37119989 DOI: 10.1016/j.japh.2023.04.022] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2022] [Revised: 04/20/2023] [Accepted: 04/22/2023] [Indexed: 05/01/2023]
Abstract
BACKGROUND The slow uptake of genetic testing in routine clinical practice warrants the attention of researchers and practitioners to find effective strategies to facilitate implementation. OBJECTIVES This study aimed to identify the barriers to and strategies for pharmacogenetic testing implementation in a health care setting from published literature. METHODS A scoping review was conducted in August 2021 with an expanded literature search using Ovid MEDLINE, Web of Science, International Pharmaceutical Abstract, and Google Scholar to identify studies reporting implementation of pharmacogenetic testing in a health care setting, from a health care system's perspective. Articles were screened using DistillerSR and findings were organized using the 5 major domains of Consolidated Framework for Implementation Research (CFIR). RESULTS A total of 3536 unique articles were retrieved from the above sources, with only 253 articles retained after title and abstract screening. Upon screening the full texts, 57 articles (representing 46 unique practice sites) were found matching the inclusion criteria. We found that most reported barriers and their associated strategies to the implementation of pharmacogenetic testing surrounded 2 CFIR domains: intervention characteristics and inner settings. Factors relating to cost and reimbursement were described as major barriers in the intervention characteristics. In the same domain, another major barrier was the lack of utility studies to provide evidence for genetic testing uptake. Technical hurdles, such as integrating genetic information to medical records, were identified as an inner settings barrier. Collaborations and lessons from early implementers could be useful strategies to overcome majority of the barriers across different health care settings. Strategies proposed by the included implementation studies to overcome these barriers are summarized and can be used as guidance in future. CONCLUSION Barriers and strategies identified in this scoping review can provide implementation guidance for practice sites that are interested in implementing genetic testing.
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Subasri M, Cressman C, Arje D, Schreyer L, Cooper E, Patel K, Ungar WJ, Barwick M, Denburg A, Hayeems RZ. Translating Precision Health for Pediatrics: A Scoping Review. CHILDREN (BASEL, SWITZERLAND) 2023; 10:children10050897. [PMID: 37238445 DOI: 10.3390/children10050897] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/09/2023] [Accepted: 05/11/2023] [Indexed: 05/28/2023]
Abstract
Precision health aims to personalize treatment and prevention strategies based on individual genetic differences. While it has significantly improved healthcare for specific patient groups, broader translation faces challenges with evidence development, evidence appraisal, and implementation. These challenges are compounded in child health as existing methods fail to incorporate the physiology and socio-biology unique to childhood. This scoping review synthesizes the existing literature on evidence development, appraisal, prioritization, and implementation of precision child health. PubMed, Scopus, Web of Science, and Embase were searched. The included articles were related to pediatrics, precision health, and the translational pathway. Articles were excluded if they were too narrow in scope. In total, 74 articles identified challenges and solutions for putting pediatric precision health interventions into practice. The literature reinforced the unique attributes of children and their implications for study design and identified major themes for the value assessment of precision health interventions for children, including clinical benefit, cost-effectiveness, stakeholder values and preferences, and ethics and equity. Tackling these identified challenges will require developing international data networks and guidelines, re-thinking methods for value assessment, and broadening stakeholder support for the effective implementation of precision health within healthcare organizations. This research was funded by the SickKids Precision Child Health Catalyst Grant.
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Affiliation(s)
- Mathushan Subasri
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
| | - Celine Cressman
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
| | - Danielle Arje
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
- Department of Paediatrics, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Leighton Schreyer
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
| | - Erin Cooper
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
| | - Komal Patel
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
| | - Wendy J Ungar
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5T 3M6, Canada
| | - Melanie Barwick
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5T 3M6, Canada
| | - Avram Denburg
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5T 3M6, Canada
- Division of Haematology/Oncology, Hospital for Sick Children, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Robin Z Hayeems
- Child Health Evaluative Sciences Program, The Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
- Institute for Health Policy, Management and Evaluation, University of Toronto, Toronto, ON M5T 3M6, Canada
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Smith DM, Wake DT, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Scoping Review. Clin Pharmacol Ther 2023; 113:803-815. [PMID: 35838358 DOI: 10.1002/cpt.2711] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Accepted: 07/10/2022] [Indexed: 11/06/2022]
Abstract
Clinical decision support (CDS) is often cited as an essential part of pharmacogenomics (PGx) implementations. A multitude of strategies are available; however, it is unclear which strategies are effective and which metrics are used to quantify clinical utility. The objective of this scoping review was to aggregate previous studies into a cohesive depiction of the current state of PGx CDS implementations and identify areas for future research on PGx CDS. Articles were included if they (i) described electronic CDS tools for PGx and (ii) reported metrics related to PGx CDS. Twenty of 3,449 articles were included and provided data on PGx CDS metrics from 15 institutions, with 93% of programs located at academic medical centers. The most common tools in CDS implementations were interruptive post-test alerts. Metrics for clinical response and alert response ranged from 12-73% and 21-98%, respectively. Few data were found on changes in metrics over time and measures that drove the evolution of CDS systems. Relatively few data were available regarding support of optimal approaches for PGx CDS. Post-test alerts were the most widely studied approach, and their effectiveness varied greatly. Further research on the usability, effectiveness, and optimization of CDS tools is needed.
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Affiliation(s)
- D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, District of Columbia, USA
| | - Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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9
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McDermott JH, Sharma V, Keen J, Newman WG, Pirmohamed M. The Implementation of Pharmacogenetics in the United Kingdom. Handb Exp Pharmacol 2023; 280:3-32. [PMID: 37306816 DOI: 10.1007/164_2023_658] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
There is considerable inter-individual variability in the effectiveness and safety of pharmaceutical interventions. This phenomenon can be attributed to a multitude of factors; however, it is widely acknowledged that common genetic variation affecting drug absorption or metabolism play a substantial contributory role. This is a concept known as pharmacogenetics. Understanding how common genetic variants influence responses to medications, and using this knowledge to inform prescribing practice, could yield significant advantages for both patients and healthcare systems. Some health services around the world have introduced pharmacogenetics into routine practice, whereas others are less advanced along the implementation pathway. This chapter introduces the field of pharmacogenetics, the existing body of evidence, and discusses barriers to implementation. The chapter will specifically focus on efforts to introduce pharmacogenetics in the NHS, highlighting key challenges related to scale, informatics, and education.
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Affiliation(s)
- John H McDermott
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, UK
| | - Videha Sharma
- Division of Informatics, Imaging and Data Science, Centre for Health Informatics, The University of Manchester, Manchester, UK
| | - Jessica Keen
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
| | - William G Newman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, UK
- Division of Evolution and Genomic Sciences, School of Biological Sciences, University of Manchester, Manchester, UK
| | - Munir Pirmohamed
- Department of Pharmacology and Therapeutics, Wolfson Centre for Personalised Medicine, University of Liverpool, Liverpool, UK.
- Liverpool University Hospital Foundation NHS Trust, Liverpool, UK.
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10
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Liu M, Rossow KM, Maxwell-Horn AC, Saucier LA, Van Driest SL. Pediatric considerations for pharmacogenetic selective serotonin reuptake inhibitors clinical decision support. Pharmacotherapy 2022. [PMID: 36524442 DOI: 10.1002/phar.2751] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/27/2022] [Accepted: 10/30/2022] [Indexed: 12/23/2022]
Abstract
Pharmacogenetic testing for psychiatry is growing at a rapid pace, with multiple sites utilizing results to help clinical decision-making. Genotype-guided dosing and drug selection have been implemented at several sites, including Vanderbilt University Medical Center, where clinical decision support (CDS) based on pharmacogenetic results went live for selective serotonin reuptake inhibitors in 2020 for both adult and pediatric patients. Effective and appropriate implementation of CYP2D6- and CYP2C19-guided CDS for the pediatric population requires consideration of the evidence for the pharmacogenetic associations, medication indications, and appropriate alternative therapies to be used when a pharmacogenetic contraindication is identified. In this article, we review these pediatric pharmacogenetic considerations for selective serotonin reuptake inhibitor CDS. We include a case study, the current literature supporting clinical recommendations, considerations when designing pediatric CDS, future implications, and examples of sertraline, (es)citalopram, paroxetine, and fluvoxamine alerts.
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Affiliation(s)
- Michelle Liu
- Department of Pharmacy, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Katelyn M Rossow
- Developmental-Behavioral Pediatrics, Norton Children's Development Center, Louisville, Kentucky, USA
| | - Angela C Maxwell-Horn
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Leigh Ann Saucier
- Vanderbilt Institute for Clinical & Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Sara L Van Driest
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Center for Pediatric Precision Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA
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11
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Medwid S, Kim RB. Implementation of pharmacogenomics: Where are we now? Br J Clin Pharmacol 2022. [PMID: 36366858 DOI: 10.1111/bcp.15591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 11/01/2022] [Accepted: 11/07/2022] [Indexed: 11/13/2022] Open
Abstract
Pharmacogenomics (PGx), examining the effect of genetic variation on interpatient variation in drug disposition and response, has been widely studied for several decades. However, as cost, as well as turnaround time associated with PGx testing, has significantly improved, the use of PGx in the clinical setting has been gaining momentum. Nevertheless, challenges have emerged in the broader clinical implementation of PGx. In this review, we will outline current models of PGx delivery and methodologies of evaluation, and discuss clinically relevant PGx tests and associated medications. Additionally, we will describe our approach for the broad implementation of pre-emptive DPYD genotyping in patients taking fluoropyrimidines in Ontario, Canada, as an example of clinically actionable PGx testing with sufficient clinical evidence of patient benefit that can become a new standard of patient care. We will highlight challenges associated with PGx testing, including a lack of diversity in PGx studies as well as general limitations that impact the broad adoption of PGx testing. Lastly, we examine the future of PGx, discussing new clinical targets, methodologies and analysis approaches.
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Affiliation(s)
- Samantha Medwid
- Department of Medicine, University of Western Ontario, London, Ontario, Canada
- Lawson Health Research Institute, London, Ontario, Canada
- London Health Sciences Centre, London, Ontario, Canada
| | - Richard B Kim
- Department of Medicine, University of Western Ontario, London, Ontario, Canada
- Lawson Health Research Institute, London, Ontario, Canada
- London Health Sciences Centre, London, Ontario, Canada
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12
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Socco S, Wake DT, Lee JC, Dunnenberger HM. Pharmacogenomics of medications given via nonconventional administration routes: a scoping review. Pharmacogenomics 2022; 23:933-948. [DOI: 10.2217/pgs-2022-0093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
Pharmacogenomics (PGx) implementation has become increasingly widespread. One of the most important aspects of this implementation process is the development of appropriate clinical decision support (CDS). Major PGx resources, such as the Clinical Pharmacogenetics Implementation Consortium, provide valuable recommendations for the development of CDS for specific gene–drug pairs but do not specify whether the administration route of a drug is clinically relevant. It is also unknown if PGx alerts for nonorally and non-intravenously administered PGx-relevant medications should be suppressed to reduce alert fatigue. The purpose of this scoping review was to identify studies and their clinical, pharmacokinetic and pharmacodynamic outcomes to better determine if CDS alerts are relevant for nonorally and non-intravenously administered PGx-relevant medications. Although this scoping review identified multiple PGx studies, the results of these studies were inconsistent, and more evidence is needed regarding different routes of medication administration and PGx.
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Affiliation(s)
- Samantha Socco
- Department of Pharmacy Practice, University of Illinois Chicago College of Pharmacy, Chicago, IL 60612, USA
- Department of Precision Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - Dyson T Wake
- Department of Precision Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
| | - James C Lee
- Department of Pharmacy Practice, University of Illinois Chicago College of Pharmacy, Chicago, IL 60612, USA
| | - Henry M Dunnenberger
- Department of Precision Medicine, NorthShore University HealthSystem, Evanston, IL 60201, USA
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13
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Cicali EJ, Lemke L, Al Alshaykh H, Nguyen K, Cavallari LH, Wiisanen K. How to Implement a Pharmacogenetics Service at your Institution. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2022; 5:1161-1175. [PMID: 36589694 PMCID: PMC9799247 DOI: 10.1002/jac5.1699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 07/29/2022] [Indexed: 01/05/2023]
Abstract
The vast majority of patients possess one or more pharmacogenetic variants that can influence optimal medication use. When pharmacogenetic data are used to guide drug choice and dosing, evidence points to improved disease outcomes, fewer adverse effects, and lower healthcare spending. Although its science is well established, clinical use of pharmacogenetic data to guide drug therapy is still in its infancy. Pharmacogenetics essentially involves the intersection of an individual's genetic data with their medications, which makes pharmacists uniquely qualified to provide clinical support and education in this field. In fact, most pharmacogenetics implementations, to date, have been led by pharmacists as leaders or members of a multidisciplinary team or as individual practitioners. A successful large-scale pharmacogenetics implementation requires coordination and synergy among administrators, clinicians, informatics teams, laboratories, and patients. Because clinical implementation of pharmacogenetics is in its early stages, there is an urgent need for guidance and dissemination of shared experiences to provide a framework for clinicians. Many early adopters of pharmacogenetics have explored various strategies among diverse practice settings. This article relies on the experiences of early adopters to provide guidance for critical steps along the pathway to implementation, including strategies to engage stakeholders; evaluate pharmacogenetic evidence; coordinate laboratory testing, results interpretation and their integration into the electronic health record; identify reimbursement avenues; educate providers and patients; and maintain a successful program. Learning from early adopters' published experiences and strategies can allow clinicians leading a new pharmacogenetics implementation to avoid pitfalls and adapt and apply lessons learned by others to their own practice.
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Affiliation(s)
- Emily J Cicali
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Lauren Lemke
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Hana Al Alshaykh
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Khoa Nguyen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
| | - Larisa H Cavallari
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
| | - Kristin Wiisanen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, Gainesville, FL, USA
- Center for Pharmacogenomics and Precision Medicine, University of Florida, Gainesville, Fl, USA
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14
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Haidar CE, Crews KR, Hoffman JM, Relling MV, Caudle KE. Advancing Pharmacogenomics from Single-Gene to Preemptive Testing. Annu Rev Genomics Hum Genet 2022; 23:449-473. [PMID: 35537468 PMCID: PMC9483991 DOI: 10.1146/annurev-genom-111621-102737] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic testing can be an effective tool to enhance medication safety and efficacy. Pharmacogenomically actionable medications are widely used, and approximately 90-95% of individuals have an actionable genotype for at least one pharmacogene. For pharmacogenomic testing to have the greatest impact on medication safety and clinical care, genetic information should be made available at the time of prescribing (preemptive testing). However, the use of preemptive pharmacogenomic testing is associated with some logistical concerns, such as consistent reimbursement, processes for reporting preemptive results over an individual's lifetime, and result portability. Lessons can be learned from institutions that have implemented preemptive pharmacogenomic testing. In this review, we discuss the rationale and best practices for implementing pharmacogenomics preemptively.
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Affiliation(s)
- Cyrine E Haidar
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kristine R Crews
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - James M Hoffman
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
- Office of Quality and Safety, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | - Mary V Relling
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
| | - Kelly E Caudle
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children's Research Hospital, Memphis, Tennessee, USA; , , , ,
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15
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McDermott JH, Wright S, Sharma V, Newman WG, Payne K, Wilson P. Characterizing pharmacogenetic programs using the consolidated framework for implementation research: A structured scoping review. Front Med (Lausanne) 2022; 9:945352. [PMID: 36059837 PMCID: PMC9433561 DOI: 10.3389/fmed.2022.945352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/29/2022] [Indexed: 12/11/2022] Open
Abstract
Several healthcare organizations have developed pre-emptive pharmacogenetic testing programs, where testing is undertaken prior to the prescription of a medicine. This review characterizes the barriers and facilitators which influenced the development of these programs. A bidirectional citation searching strategy identified relevant publications before a standardized data extraction approach was applied. Publications were grouped by program and data synthesis was undertaken using the Consolidated Framework for Implementation Research (CFIR). 104 publications were identified from 40 programs and 4 multi-center initiatives. 26 (66%) of the programs were based in the United States and 95% in high-income countries. The programs were heterogeneous in their design and scale. The Characteristics of the Intervention, Inner Setting, and Process domains were referenced by 92.5, 80, and 77.5% of programs, respectively. A positive institutional culture, leadership engagement, engaging stakeholders, and the use of clinical champions were frequently described as facilitators to implementation. Clinician self-efficacy, lack of stakeholder knowledge, and the cost of the intervention were commonly cited barriers. Despite variation between the programs, there were several similarities in approach which could be categorized via the CFIR. These form a resource for organizations planning the development of pharmacogenetic programs, highlighting key facilitators which can be leveraged to promote successful implementation.
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Affiliation(s)
- John H. McDermott
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
- *Correspondence: John H. McDermott,
| | - Stuart Wright
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Videha Sharma
- Division of Informatics, Centre for Health Informatics, Imaging and Data Science, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - William G. Newman
- Manchester Centre for Genomic Medicine, St Mary’s Hospital, Manchester University Hospitals NHS Foundation Trust, Manchester, United Kingdom
- Division of Evolution, Infection and Genomics, School of Biological Sciences, The University of Manchester, Manchester, United Kingdom
| | - Katherine Payne
- Division of Population Health, Manchester Centre for Health Economics, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
| | - Paul Wilson
- Division of Population Health, Centre for Primary Care and Health Services Research, Health Services Research and Primary Care, School of Health Sciences, The University of Manchester, Manchester, United Kingdom
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16
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Kuruvilla R, Scott K, Pirmohamed SM. Pharmacogenomics of Drug Hypersensitivity. Immunol Allergy Clin North Am 2022; 42:335-355. [DOI: 10.1016/j.iac.2022.01.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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17
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The Value of Pharmacogenetics to Reduce Drug-Related Toxicity in Cancer Patients. Mol Diagn Ther 2022; 26:137-151. [PMID: 35113367 PMCID: PMC8975257 DOI: 10.1007/s40291-021-00575-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/19/2021] [Indexed: 10/19/2022]
Abstract
Many anticancer drugs cause adverse drug reactions (ADRs) that negatively impact safety and reduce quality of life. The typical narrow therapeutic range and exposure-response relationships described for anticancer drugs make precision dosing critical to ensure safe and effective drug exposure. Germline mutations in pharmacogenes contribute to inter-patient variability in pharmacokinetics and pharmacodynamics of anticancer drugs. Patients carrying reduced-activity or loss-of-function alleles are at increased risk for ADRs. Pretreatment genotyping offers a proactive approach to identify these high-risk patients, administer an individualized dose, and minimize the risk of ADRs. In the field of oncology, the most well-studied gene-drug pairs for which pharmacogenetic dosing recommendations have been published to improve safety are DPYD-fluoropyrimidines, TPMT/NUDT15-thiopurines, and UGT1A1-irinotecan. Despite the presence of these guidelines, the scientific evidence showing the benefits of pharmacogenetic testing (e.g., improved safety and cost-effectiveness) and the development of efficient multi-gene genotyping panels, routine pretreatment testing for these gene-drug pairs has not been implemented widely in the clinic. Important considerations required for widespread clinical implementation include pharmacogenetic education of physicians, availability or allocation of institutional resources to build an efficient clinical infrastructure, international standardization of guidelines, uniform adoption of guidelines by regulatory agencies leading to genotyping requirements in drug labels, and development of cohesive reimbursement policies for pretreatment genotyping. Without clinical implementation, the potential of pharmacogenetics to improve patient safety remains unfulfilled.
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18
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Evaluating the feasibility of performing pharmacogenetic
guided‐medication
therapy management in a retirement community: A prospective, single arm study. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2021. [DOI: 10.1002/jac5.1570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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19
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Wake DT, Smith DM, Kazi S, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision. Clin Pharmacol Ther 2021; 112:44-57. [PMID: 34365648 PMCID: PMC9291515 DOI: 10.1002/cpt.2387] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 07/28/2021] [Indexed: 02/06/2023]
Abstract
Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.
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Affiliation(s)
- Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, DC, USA
| | - Sadaf Kazi
- Georgetown University Medical Center, Washington, DC, USA.,National Center for Human Factors in Healthcare, MedStar Health Research Institute Washington, Washington, DC, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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20
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Kisor DF, Petry NJ, Bright DR. Pharmacogenomics in the United States Community Pharmacy Setting: The Clopidogrel- CYP2C19 Example. Pharmgenomics Pers Med 2021; 14:569-577. [PMID: 34040417 PMCID: PMC8140945 DOI: 10.2147/pgpm.s224894] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2021] [Accepted: 04/26/2021] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenomics (PGx) is expanding across health-care practice settings, including the community pharmacy. In the United States, models of implementation of PGx in the community pharmacy have described independent services and those layered on to medication therapy management. The drug-gene pair of clopidogrel-CYP2C19 has been a focus of implementation of PGx in community pharmacy and serves as an example of the evolution of the application of drug-gene interaction information to help optimize drug therapy. Expanded information related to this drug-gene pair has been provided by the US Food and Drug Administration and clinical PGx guidelines have and continue to be updated to support clinical decision-making. Most recently direct-to-consumer (DTC) PGx has resulted in patient generated sample collection and submission to a genetic testing-related company for analysis, with reporting of genotype and related phenotype information directly to the patient without a health-care professional guiding or even being involved in the process. The DTC testing approach needs to be considered in the development or modification of PGx service models in the community pharmacy setting. The example of clopidogrel-CYP2C19 is discussed and current models of PGx implementation in the community pharmacy in the United States are presented. New approaches to PGx services are offered as implementation continues to evolve and may now include DTC information.
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Affiliation(s)
- David F Kisor
- Manchester University, Department of Pharmaceutical Sciences and Pharmacogenomics, Fort Wayne, IN, USA
| | - Natasha J Petry
- North Dakota State University, College of Health Professions, Department of Pharmacy Practice, Fargo, ND, USA
- Sanford Imagenetics, Sioux Falls, ND, USA
| | - David R Bright
- Ferris State University, Department of Pharmaceutical Sciences, Big Rapids, MI, USA
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21
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Keeling NJ, Dunn TJ, Bentley JP, Ramachandran S, Hoffman JM, Rosenthal M. Approaches to assessing the provider experience with clinical pharmacogenomic information: a scoping review. Genet Med 2021; 23:1589-1603. [PMID: 33927377 DOI: 10.1038/s41436-021-01186-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 04/11/2021] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Barriers to the implementation of pharmacogenomics in clinical practice have been thoroughly discussed over the past decade. METHODS The objective of this scoping review was to characterize the peer-reviewed literature surrounding the experiences and actions of prescribers, pharmacists, or genetic counselors when using pharmacogenomic information in real-world or hypothetical research settings. RESULTS A total of 33 studies were included in the scoping review. The majority of studies were conducted in the United States (70%), used quantitative or mixed methods (79%) with physician or pharmacist respondents (100%). The qualitative content analysis revealed five major methodological approaches: hypothetical clinical case scenarios, real-world studies evaluating prescriber response to recommendations or alerts, cross-sectional quantitative surveys, cross-sectional qualitative surveys/interviews, and a quasi-experimental real-world study. CONCLUSION The findings of this scoping review can guide further research on the factors needed to successfully integrate pharmacogenomics into clinical care.
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Affiliation(s)
- Nicholas J Keeling
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - Tyler J Dunn
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA.
| | - John P Bentley
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - Sujith Ramachandran
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - James M Hoffman
- Department of Pharmaceutical Sciences and Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Meagen Rosenthal
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
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22
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Luczak T, Brown SJ, Armbruster D, Hundertmark M, Brown J, Stenehjem D. Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs. Pharmacogenomics 2021; 22:345-364. [PMID: 33829852 DOI: 10.2217/pgs-2020-0181] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Pharmacogenetic (PGx) literature has shown beneficial outcomes in safety, efficacy and cost when evidence-based gene-drug decision making is incorporated into clinical practice. PGx programs with successfully implemented clinical services have been published in a variety of settings including academic health centers and community practice. The primary objective was to systematically scope the literature to characterize the current trends, extent, range and nature of clinical PGx programs. Forty articles representing 19 clinical PGx programs were included in analysis. Most programs are in urban, academic institutions. Education, governance and workflow were commonly described while billing/reimbursement and consent were not. This review provides an overview of current PGx models that can be used as a reference for institutions beginning the implementation process.
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Affiliation(s)
- Tiana Luczak
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA.,Essentia Health, Duluth, MN 55805, USA
| | - Sarah Jane Brown
- Health Sciences Libraries, University of Minnesota, MN 55455, USA
| | - Danielle Armbruster
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Megan Hundertmark
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - Jacob Brown
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
| | - David Stenehjem
- Department of Pharmacy Practice & Pharmaceutical Sciences, University of Minnesota, College of Pharmacy, Duluth, MN 55812, USA
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23
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Liko I, Lee YM, Stutzman DL, Blackmer AB, Deininger KM, Reynolds AM, Aquilante CL. Providers' perspectives on the clinical utility of pharmacogenomic testing in pediatric patients. Pharmacogenomics 2021; 22:263-274. [PMID: 33657875 DOI: 10.2217/pgs-2020-0112] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Aim: To assess providers' knowledge, attitudes, perceptions, and experiences related to pharmacogenomic (PGx) testing in pediatric patients. Materials & methods: An electronic survey was sent to multidisciplinary healthcare providers at a pediatric hospital. Results: Of 261 respondents, 71.3% were slightly or not at all familiar with PGx, despite 50.2% reporting prior PGx education or training. Most providers, apart from psychiatry, perceived PGx to be at least moderately useful to inform clinical decisions. However, only 26.4% of providers had recent PGx testing experience. Unfamiliarity with PGx and uncertainty about the clinical value of testing were common perceived challenges. Conclusion: Low PGx familiarity among pediatric providers suggests additional education and electronic resources are needed for PGx examples in which data support testing in children.
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Affiliation(s)
- Ina Liko
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA.,Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Yee Ming Lee
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Danielle L Stutzman
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA.,Department of Pharmacy, Children's Hospital Colorado, Aurora, CO 80045, USA.,Pediatric Mental Health Institute, Children's Hospital Colorado, Aurora, CO 80045, USA
| | - Allison B Blackmer
- Department of Clinical Pharmacy, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA.,Department of Pharmacy, Children's Hospital Colorado, Aurora, CO 80045, USA.,Special Care Clinic, Children's Hospital Colorado, Aurora, CO 80045, USA
| | - Kimberly M Deininger
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
| | - Ann M Reynolds
- Special Care Clinic, Children's Hospital Colorado, Aurora, CO 80045, USA.,Department of Pediatrics, University of Colorado School of Medicine & Children's Hospital Colorado, Aurora, CO 80045, USA
| | - Christina L Aquilante
- Department of Pharmaceutical Sciences, University of Colorado Skaggs School of Pharmacy & Pharmaceutical Sciences, Aurora, CO 80045, USA
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24
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Roosan D, Hwang A, Roosan MR. Pharmacogenomics cascade testing (PhaCT): a novel approach for preemptive pharmacogenomics testing to optimize medication therapy. THE PHARMACOGENOMICS JOURNAL 2021; 21:1-7. [PMID: 32843688 PMCID: PMC7840503 DOI: 10.1038/s41397-020-00182-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/08/2019] [Revised: 06/18/2020] [Accepted: 08/12/2020] [Indexed: 11/08/2022]
Abstract
The implementation of pharmacogenomics (PGx) has come a long way since the dawn of utilizing pharmacogenomic data in clinical patient care. However, the potential benefits of sharing PGx results have yet to be explored. In this paper, we explore the willingness of patients to share PGx results, as well as the inclusion of family medication history in identifying potential family members for pharmacogenomics cascade testing (PhaCT). The genetic similarities in families allow for identifying potential gene variants prior to official preemptive testing. Once a candidate patient is determined, PhaCT can be initiated. PhaCT recognizes that further cascade testing throughout a family can serve to improve precision medicine. In order to make PhaCT feasible, we propose a novel shareable HIPAA-compliant informatics platform that will enable patients to manage not only their own test results and medications but also those of their family members. The informatics platform will be an external genomics system with capabilities to integrate with patients' electronic health records. Patients will be given the tools to provide information to and work with clinicians in identifying family members for PhaCT through this platform. Offering patients the tools to share PGx results with their family members for preemptive testing could be the key to empowering patients. Clinicians can utilize PhaCT to potentially improve medication adherence, which may consequently help to distribute the burden of health management between patients, family members, providers, and payers.
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Affiliation(s)
- Don Roosan
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA, USA.
| | - Angela Hwang
- Department of Pharmacy Practice and Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA, USA
| | - Moom R Roosan
- Department of Pharmacy Practice, School of Pharmacy, Chapman University, School of Pharmacy, Irvine, CA, USA.
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Rostam Niakan Kalhori S, Tanhapour M, Gholamzadeh M. Enhanced childhood diseases treatment using computational models: Systematic review of intelligent experiments heading to precision medicine. J Biomed Inform 2021; 115:103687. [PMID: 33497811 DOI: 10.1016/j.jbi.2021.103687] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2020] [Revised: 12/05/2020] [Accepted: 01/18/2021] [Indexed: 10/22/2022]
Abstract
INTRODUCTION Precision or personalized Medicine (PM) is used for the prevention and treatment of diseases by considering a huge amount of information about individuals variables. Due to high volume of information, AI-based computational models are required. A large set of studies conducted to examine the PM approach to improve childhood clinical outcomes. Thus, the main goal of this study was to review the application of health information technology and especially artificial intelligence (AI) methods for the treatment of childhood disease using PM. METHODS PubMed, Scopus, Web of Science, and EMBASE databases were searched up to December 18, 2019. Articles that focused on informatics applications for childhood disease PM included in this study. Included papers were classified for qualitative analysis and interpreting results. The results were analyzed using Microsoft Excel 2019. RESULTS From 341 citations, 62 papers met our inclusion criteria. The number of published papers that used AI methods to apply for PM in childhood diseases increased from 2010 to 2019. Our results showed that most applied methods were related to machine learning discipline. In terms of clinical scope, the largest number of clinical articles are devoted to oncology. Besides, the analysis showed that genomics was the most PM approach used regarding childhood disease. CONCLUSION This systematic review examined papers that used AI methods for applying PM approaches in childhood diseases from medical informatics perspectives. Thus, it provided new insight to researchers who are interested in knowing research needs in this field.
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Affiliation(s)
- Sharareh Rostam Niakan Kalhori
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Mozhgan Tanhapour
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran
| | - Marsa Gholamzadeh
- Department of Health Information Management, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran.
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Patients dispensed medications with actionable pharmacogenomic biomarkers: rates and characteristics. Genet Med 2021; 23:782-786. [PMID: 33420348 PMCID: PMC9067543 DOI: 10.1038/s41436-020-01044-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 11/11/2020] [Accepted: 11/12/2020] [Indexed: 11/08/2022] Open
Abstract
PURPOSE Pharmacogenomic biomarkers are increasingly listed on medication labels and authoritative guidelines but pharmacogenomic-guided prescribing is not yet common. Our objective was to assess the potential for incorporating knowledge of patients' genomic characteristics into prescribing practices. METHODS We performed a retrospective analysis of claims data for 2,096,971 beneficiaries with pharmacy coverage from a national, commercial health insurance plan between January 2017 and December 2019. Children between 0 and 17 years comprised 21% of the cohort. Adults were age 18 to 64. Medications with actionable pharmacogenomic biomarkers (MAPBs) were identified using public information from the US Food and Drug Administration (FDA), Clinical Pharmacogenomics Implementation Consortium (CPIC), and PharmGKB. RESULTS MAPBs were dispensed to 63% of the adults and 29% of the children in the cohort. Most frequently dispensed were ibuprofen, ondansetron, codeine, and oxycodone. Most common were medications with CYP2D6, G6PD, or CYPC19 pharmacogenomic biomarkers. Ten percent of the cohort were codispensed more than one MAPB for at least 30 days. CONCLUSION The number of people who might benefit from pharmacogenomic-guided prescribing is substantial. Future work should address obstacles to integrating genomic data into prescriber workflows, complex factors contributing to the magnitude of benefit, and the clinical availability of reliable on-demand or pre-emptive pharmacogenomic testing.
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Roosan D, Hwang A, Law AV, Chok J, Roosan MR. The inclusion of health data standards in the implementation of pharmacogenomics systems: a scoping review. Pharmacogenomics 2020; 21:1191-1202. [PMID: 33124487 DOI: 10.2217/pgs-2020-0066] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023] Open
Abstract
Background: Despite potential benefits, the practice of incorporating pharmacogenomics (PGx) results in clinical decisions has yet to diffuse widely. In this study, we conducted a review of recent discussions on data standards and interoperability with a focus on sharing PGx test results among health systems. Materials & methods: We conducted a literature search for PGx clinical decision support systems between 1 January 2012 and 31 January 2020. Thirty-two out of 727 articles were included for the final review. Results: Nine of the 32 articles mentioned data standards and only four of the 32 articles provided solutions for the lack of interoperability. Discussions: Although PGx interoperability is essential for widespread implementation, a lack of focus on standardized data creates a formidable challenge for health information exchange. Conclusion: Standardization of PGx data is essential to improve health information exchange and the sharing of PGx results between disparate systems. However, PGx data standards and interoperability are often not addressed in the system-level implementation.
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Affiliation(s)
- Don Roosan
- Assistant Professor, Department of Pharmacy Practice & Administration, College of Pharmacy, Western University of Health Sciences, 309 E 2nd street, Pomona, CA 91766, USA
| | - Angela Hwang
- Research Assistant, Department of Pharmacy Practice & Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Anandi V Law
- Professor, Department of Pharmacy Practice & Administration, College of Pharmacy, Western University of Health Sciences, Pomona, CA 91766, USA
| | - Jay Chok
- Associate Professor, School of Applied Life Sciences, Keck Graduate Institute, Claremont Colleges, Pomona, CA 91711, USA
| | - Moom R Roosan
- Assistant Professor, School of Pharmacy, Department of Pharmacy Practice, Chapman University, Irvine, CA 92618, USA
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Gregornik D, Salyakina D, Brown M, Roiko S, Ramos K. Pediatric pharmacogenomics: challenges and opportunities: on behalf of the Sanford Children's Genomic Medicine Consortium. THE PHARMACOGENOMICS JOURNAL 2020; 21:8-19. [PMID: 32843689 DOI: 10.1038/s41397-020-00181-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/28/2019] [Revised: 06/15/2020] [Accepted: 08/12/2020] [Indexed: 01/13/2023]
Abstract
The advent of digital, electronic, and molecular technologies has allowed the study of complete genomes. Integrating this information into drug development has opened the door for pharmacogenomic (PGx) interventions in direct patient care. PGx allows clinicians to better identify drug of choice and optimize dosing regimens based on an individual's genetic characteristics. Integrating PGx into pediatric care is a priority for the Sanford Children's Genomic Medicine Consortium, a partnership of ten children's hospitals across the US committed to the innovation and advancement of genomics in pediatric care. In this white paper, we review the current state of PGx research and its clinical utility in pediatrics, a largely understudied population, and make recommendations for advancing cutting-edge practice in pediatrics.
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Affiliation(s)
- David Gregornik
- Pharmacogenomics Program, Children's Minnesota, Minneapolis, MN, USA.
| | - Daria Salyakina
- Research Institute and Personalized Medicine Initiative, Nicklaus Children's Hospital, Miami, FL, USA
| | - Marilyn Brown
- Research Institute and Personalized Medicine Initiative, Nicklaus Children's Hospital, Miami, FL, USA
| | - Samuel Roiko
- Children's Research Institute, Minnesota, Minneapolis, MN, USA
| | - Kenneth Ramos
- Texas A&M University System, College Station, TX, USA.
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Hoffman JM, Flynn AJ, Juskewitch JE, Freimuth RR. Biomedical Data Science and Informatics Challenges to Implementing Pharmacogenomics with Electronic Health Records. Annu Rev Biomed Data Sci 2020. [DOI: 10.1146/annurev-biodatasci-020320-093614] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Pharmacogenomic information must be incorporated into electronic health records (EHRs) with clinical decision support in order to fully realize its potential to improve drug therapy. Supported by various clinical knowledge resources, pharmacogenomic workflows have been implemented in several healthcare systems. Little standardization exists across these efforts, however, which limits scalability both within and across clinical sites. Limitations in information standards, knowledge management, and the capabilities of modern EHRs remain challenges for the widespread use of pharmacogenomics in the clinic, but ongoing efforts are addressing these challenges. Although much work remains to use pharmacogenomic information more effectively within clinical systems, the experiences of pioneering sites and lessons learned from those programs may be instructive for other clinical areas beyond genomics. We present a vision of what can be achieved as informatics and data science converge to enable further adoption of pharmacogenomics in the clinic.
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Affiliation(s)
- James M. Hoffman
- Department of Pharmaceutical Sciences and the Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, Tennessee 38105, USA
| | - Allen J. Flynn
- Department of Learning Health Sciences, Medical School, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Justin E. Juskewitch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota 55905, USA
| | - Robert R. Freimuth
- Division of Digital Health Sciences, Department of Health Sciences Research, Center for Individualized Medicine, and Information and Knowledge Management, Mayo Clinic, Rochester, Minnesota 55905, USA
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Deverka PA, Douglas MP, Phillips KA. Use of Real-World Evidence in US Payer Coverage Decision-Making for Next-Generation Sequencing-Based Tests: Challenges, Opportunities, and Potential Solutions. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2020; 23:540-550. [PMID: 32389218 PMCID: PMC7219085 DOI: 10.1016/j.jval.2020.02.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Revised: 01/26/2020] [Accepted: 02/02/2020] [Indexed: 05/05/2023]
Abstract
OBJECTIVES Given the potential of real-world evidence (RWE) to inform understanding of the risk-benefit profile of next-generation sequencing (NGS)-based testing, we undertook a study to describe the current landscape of whether and how payers use RWE as part of their coverage decision making and potential solutions for overcoming barriers. METHODS We performed a scoping literature review of existing RWE evidentiary frameworks for evaluating new technologies and identified barriers to clinical integration and evidence gaps for NGS. We synthesized findings as potential solutions for improving the relevance and utility of RWE for payer decision-making. RESULTS Payers require evidence of clinical utility to inform coverage decisions, yet we found a relatively small number of published RWE studies, and these are predominately focused on oncology, pharmacogenomics, and perinatal/pediatric testing. We identified 3 categories of innovation that may help address the current undersupply of RWE studies for NGS: (1) increasing use of RWE to inform outcomes-based contracting for new technologies, (2) precision medicine initiatives that integrate clinical and genomic data and enable data sharing, and (3) Food and Drug Administration reforms to encourage the use of RWE. Potential solutions include development of data and evidence review standards, payer engagement in RWE study design, use of incentives and partnerships to lower the barriers to RWE generation, education of payers and providers concerning the use of RWE and NGS, and frameworks for conducting outcomes-based contracting for NGS. CONCLUSIONS We provide numerous suggestions to overcome the data, methodologic, infrastructure, and policy challenges constraining greater integration of RWE in assessments of NGS.
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Affiliation(s)
| | - Michael P Douglas
- Center for Translational and Policy Research on Personalized Medicine, Department of Clinical Pharmacy, University of California at San Francisco, San Francisco, CA, USA
| | - Kathryn A Phillips
- Center for Translational and Policy Research on Personalized Medicine, Department of Clinical Pharmacy, University of California at San Francisco, San Francisco, CA, USA; Philip R. Lee Institute for Health Policy, University of California, San Francisco, San Francisco, CA, USA; Helen Diller Family Comprehensive Cancer, University of California at San Francisco, San Francisco, CA, USA
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Dexter P, Ong H, Elsey A, Bell G, Walton N, Chung W, Rasmussen L, Hicks K, Owusu-Obeng A, Scott S, Ellis S, Peterson J. Development of a Genomic Data Flow Framework: Results of a Survey Administered to NIH-NHGRI IGNITE and eMERGE Consortia Participants. AMIA ... ANNUAL SYMPOSIUM PROCEEDINGS. AMIA SYMPOSIUM 2020; 2019:363-370. [PMID: 32308829 PMCID: PMC7153090] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Precision health's more individualized molecular approach will enrich our understanding of disease etiology and patient outcomes. Universal implementation of precision health will not be feasible, however, until there is much greater automation of processes related to genomic data transmission, transformation, and interpretation. In this paper, we describe a framework for genomic data flow developed by the Clinical Informatics Work Group of the NIH National Human Genome Research Institute (NHGRI) IGNITE Network consortium. We subsequently report the results of a genomic data flow survey administered to sites funded by NIH-NHGRI for large scale genomic medicine implementations. Finally, we discuss insights and challenges identified through these survey results as they relate to both the current and a desirable future state of genomic data flow.
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Affiliation(s)
- Paul Dexter
- Indiana University School of Medicine, Indianapolis, IN
- Regenstrief Institute, Inc., Indianapolis, IN
| | - Henry Ong
- Vanderbilt University Medical Center, Nashville, TN
| | | | | | | | | | | | | | | | - Stuart Scott
- Icahn School of Medicine at Mount Sinai, New York, NY
| | - Steve Ellis
- Icahn School of Medicine at Mount Sinai, New York, NY
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Abstract
Pharmacogenetics is a key component of precision medicine. Genetic variation in drug metabolism enzymes can lead to variable exposure to drugs and metabolites, potentially leading to inefficacy and drug toxicity. Although the evidence for pharmacogenetic associations in children is not as extensive as for adults, there are several drugs across diverse therapeutic areas with robust pediatric data indicating important, and relatively common, drug-gene interactions. Guidelines to assist gene-based dose optimization are available for codeine, thiopurine drugs, selective serotonin reuptake inhibitors, atomoxetine, tacrolimus, and voriconazole. For each of these drugs, there is an opportunity to clinically implement precision medicine approaches with children for whom genetic test results are known or are obtained at the time of prescribing. For many more drugs that are commonly used in pediatric patients, additional investigation is needed to determine the genetic factors influencing appropriate dose.
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Affiliation(s)
- Laura B Ramsey
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio 45267, USA
- Divisions of Research in Patient Services and Clinical Pharmacology, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio 45229, USA
| | - Jacob T Brown
- Department of Pharmacy Practice and Pharmaceutical Sciences, University of Minnesota College of Pharmacy, Duluth, Minnesota 55812, USA
| | - Susan I Vear
- Department of Hematology & Oncology, Nationwide Children's Hospital, Columbus, Ohio 43205, USA
| | - Jeffrey R Bishop
- Department of Experimental and Clinical Pharmacology, University of Minnesota College of Pharmacy, and Department of Psychiatry, University of Minnesota Medical School, Minneapolis, Minnesota 55455, USA
| | - Sara L Van Driest
- Departments of Pediatrics and Medicine, Vanderbilt University School of Medicine, Nashville, Tennessee 37232, USA;
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A pediatric perspective on genomics and prevention in the twenty-first century. Pediatr Res 2020; 87:338-344. [PMID: 31578042 DOI: 10.1038/s41390-019-0597-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 09/18/2019] [Indexed: 12/19/2022]
Abstract
We present evidence from diverse disciplines and populations to identify the current and emerging role of genomics in prevention from both medical and public health perspectives as well as key challenges and potential untoward consequences of increasing the role of genomics in these endeavors. We begin by comparing screening in healthy populations (newborn screening), with testing in symptomatic populations, which may incidentally identify secondary findings and at-risk relatives. Emerging evidence suggests that variants in genes subject to the reporting of secondary findings are more common than expected in patients who otherwise would not meet the criteria for testing and population testing for variants in these genes may more precisely identify discrete populations to target for various prevention strategies starting in childhood. Conversely, despite its theoretical promise, recent studies attempting to demonstrate benefits of next-generation sequencing for newborn screening have instead demonstrated numerous barriers and pitfalls to this approach. We also examine the special cases of pharmacogenomics and polygenic risk scores as examples of ways genomics can contribute to prevention amongst a broader population than that affected by rare Mendelian disease. We conclude with unresolved questions which will benefit from future investigations of the role of genomics in disease prevention.
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Hicks JK, Aquilante CL, Dunnenberger HM, Gammal RS, Funk RS, Aitken SL, Bright DR, Coons JC, Dotson KM, Elder CT, Groff LT, Lee JC. Precision Pharmacotherapy: Integrating Pharmacogenomics into Clinical Pharmacy Practice. JOURNAL OF THE AMERICAN COLLEGE OF CLINICAL PHARMACY 2019; 2:303-313. [PMID: 32984775 DOI: 10.1002/jac5.1118] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Precision pharmacotherapy encompasses the use of therapeutic drug monitoring; evaluation of liver and renal function, genomics, and environmental and lifestyle exposures; and analysis of other unique patient or disease characteristics to guide drug selection and dosing. This paper articulates real-world clinical applications of precision pharmacotherapy, focusing exclusively on the emerging field of clinical pharmacogenomics. This field is evolving rapidly, and clinical pharmacists now play an invaluable role in the clinical implementation, education, and research applications of pharmacogenomics. This paper provides an overview of the evolution of pharmacogenomics in clinical pharmacy practice, together with recommendations on how the American College of Clinical Pharmacy (ACCP) can support the advancement of clinical pharmacogenomics implementation, education, and research. Commonalities among successful clinical pharmacogenomics implementation and education programs are identified, with recommendations for how ACCP can leverage and advance these common themes. Opportunities are also provided to support the research needed to move the practice and application of pharmacogenomics forward.
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Ohno-Machado L, Kim J, Gabriel RA, Kuo GM, Hogarth MA. Genomics and electronic health record systems. Hum Mol Genet 2019; 27:R48-R55. [PMID: 29741693 DOI: 10.1093/hmg/ddy104] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2018] [Accepted: 03/19/2018] [Indexed: 01/27/2023] Open
Abstract
Several reviews and case reports have described how information derived from the analysis of genomes are currently included in electronic health records (EHRs) for the purposes of supporting clinical decisions. Since the introduction of this new type of information in EHRs is relatively new (for instance, the widespread adoption of EHRs in the United States is just about a decade old), it is not surprising that a myriad of approaches has been attempted, with various degrees of success. EHR systems undergo much customization to fit the needs of health systems; these approaches have been varied and not always generalizable. The intent of this article is to present a high-level view of these approaches, emphasizing the functionality that they are trying to achieve, and not to advocate for specific solutions, which may become obsolete soon after this review is published. We start by broadly defining the end goal of including genomics in EHRs for healthcare and then explaining the various sources of information that need to be linked to arrive at a clinically actionable genomics analysis using a pharmacogenomics example. In addition, we include discussions on open issues and a vision for the next generation systems that integrate whole genome sequencing and EHRs in a seamless fashion.
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Affiliation(s)
- Lucila Ohno-Machado
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA
| | - Jihoon Kim
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA
| | - Rodney A Gabriel
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA.,Department of Anesthesiology, University of California San Diego, La Jolla, CA, USA
| | - Grace M Kuo
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, USA
| | - Michael A Hogarth
- UCSD Health Department of Biomedical Informatics, University of California San Diego, La Jolla, CA, USA
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Dressler LG, Bell GC, Abernathy PM, Ruch K, Denslow S. Implementing pharmacogenetic testing in rural primary care practices: a pilot feasibility study. Pharmacogenomics 2019; 20:433-446. [PMID: 30983513 DOI: 10.2217/pgs-2018-0200] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
Aim: Assess feasibility and perspectives of pharmacogenetic testing/PGx in rural, primary care physician (PCP) practices when PCPs are trained to interpret/apply results and testing costs are covered. Methods: Participants included PCPs who agreed to training, surveys and interviews and eligible patients who agreed to surveys and testing. 51 patients from three practices participated. Results: Prestudy, no PCP had ever ordered a PGx test. Test results demonstrated gene variations in 30% of patients, related to current medications, with PCPs reporting changes to drug management. Poststudy, test cost was still a concern, but now PCPs reported practical barriers, including the utilization of PGx results over time. PCPs and patients had favorable responses to testing. Summary: PGx testing is feasible in rural PCP practices.
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Affiliation(s)
- Lynn G Dressler
- Mission Health Personalized Medicine & Pharmacogenomics Program; currently Independent Consultant, LGDconsulting 512, Fairview, NC 28730, USA
| | - Gillian C Bell
- Mission Health Personalized Medicine & Pharmacogenomics Program, Asheville, NC 28801, USA
| | - Pearl M Abernathy
- Mission Health Personalized Medicine & Pharmacogenomics Program, Asheville, NC 28801, USA
| | - Karl Ruch
- Mission Health Personalized Medicine & Pharmacogenomics Program; currently OneOME, Minneapolis, MN,55405, USA
| | - Sheri Denslow
- Mission Health, Mission Research Institute, Asheville, NC 28801, USA
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Shankar P, Anderson N. Advances in Sharing Multi-sourced Health Data on Decision Support Science 2016-2017. Yearb Med Inform 2018; 27:16-24. [PMID: 30157504 PMCID: PMC6115214 DOI: 10.1055/s-0038-1641215] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
INTRODUCTION Clinical decision support science is expanding to include integration from broader and more varied data sources, diverse platforms and delivery modalities, and is responding to emerging regulatory guidelines and increased interest from industry. OBJECTIVE Evaluate key advances and challenges of accessing, sharing, and managing data from multiple sources for development and implementation of Clinical Decision Support (CDS) systems in 2016-2017. METHODS Assessment of literature and scientific conference proceedings, current and pending policy development, and review of commercial applications nationally and internationally. RESULTS CDS research is approaching multiple landmark points driven by commercialization interests, emerging regulatory policy, and increased public awareness. However, the availability of patient-related "Big Data" sources from genomics and mobile health, expanded privacy considerations, applications of service-based computational techniques and tools, the emergence of "app" ecosystems, and evolving patient-centric approaches reflect the distributed, complex, and uneven maturity of the CDS landscape. Nonetheless, the field of CDS is yet to mature. The lack of standards and CDS-specific policies from regulatory bodies that address the privacy and safety concerns of data and knowledge sharing to support CDS development may continue to slow down the broad CDS adoption within and across institutions. CONCLUSION Partnerships with Electronic Health Record and commercial CDS vendors, policy makers, standards development agencies, clinicians, and patients are needed to see CDS deployed in the evolving learning health system.
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Affiliation(s)
- Prabhu Shankar
- Division of Health Informatics, Department of Public Health Sciences, School of Medicine, University of California, Davis, CA, USA
| | - Nick Anderson
- Division of Health Informatics, Department of Public Health Sciences, School of Medicine, University of California, Davis, CA, USA
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Caudle KE, Keeling NJ, Klein TE, Whirl-Carrillo M, Pratt VM, Hoffman JM. Standardization can accelerate the adoption of pharmacogenomics: current status and the path forward. Pharmacogenomics 2018; 19:847-860. [PMID: 29914287 DOI: 10.2217/pgs-2018-0028] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Successfully implementing pharmacogenomics into routine clinical practice requires an efficient process to order genetic tests and report the results to clinicians and patients. Lack of standardized approaches and terminology in clinical laboratory processes, ordering of the test and reporting of test results all impede this workflow. Expert groups such as the Association for Molecular Pathology and the Clinical Pharmacogenetics Implementation Consortium have published recommendations for standardizing laboratory genetic testing, reporting and terminology. Other resources such as PharmGKB, ClinVar, ClinGen and PharmVar have established databases of nomenclature for pharmacogenetic alleles and variants. Opportunities remain to develop new standards and further disseminate existing standards which will accelerate the implementation of pharmacogenomics.
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Affiliation(s)
- Kelly E Caudle
- Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, TN 38105, USA
| | - Nicholas J Keeling
- Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, TN 38105, USA.,Department of Pharmacy Administration, University of Mississippi School of Pharmacy, Oxford, MS 38655, USA
| | - Teri E Klein
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | | | - Victoria M Pratt
- Department of Medical & Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - James M Hoffman
- Department of Pharmaceutical Sciences, St Jude Children's Research Hospital, Memphis, TN 38105, USA.,Office of Quality & Patient Care, St Jude Children's Research Hospital, Memphis, TN 38105, USA
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Weitzel KW, Smith DM, Elsey AR, Duong BQ, Burkley B, Clare-Salzler M, Gong Y, Higgins TA, Kong B, Langaee T, McDonough CW, Staley BJ, Vo TT, Wake DT, Cavallari LH, Johnson JA. Implementation of Standardized Clinical Processes for TPMT Testing in a Diverse Multidisciplinary Population: Challenges and Lessons Learned. Clin Transl Sci 2018; 11:175-181. [PMID: 29351371 PMCID: PMC5867028 DOI: 10.1111/cts.12533] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2017] [Accepted: 12/03/2017] [Indexed: 01/11/2023] Open
Abstract
Although thiopurine S‐methyltransferase (TPMT) genotyping to guide thiopurine dosing is common in the pediatric cancer population, limited data exist on TPMT testing implementation in diverse, multidisciplinary settings. We established TPMT testing (genotype and enzyme) with clinical decision support, provider/patient education, and pharmacist consultations in a tertiary medical center and collected data over 3 years. During this time, 834 patients underwent 873 TPMT tests (147 (17%) genotype, 726 (83%) enzyme). TPMT tests were most commonly ordered for gastroenterology, rheumatology, dermatology, and hematology/oncology patients (661 of 834 patients (79.2%); 580 outpatient vs. 293 inpatient; P < 0.0001). Thirty‐nine patients had both genotype and enzyme tests (n = 2 discordant results). We observed significant differences between TPMT test use and characteristics in a diverse, multispecialty environment vs. a pediatric cancer setting, which led to unique implementation needs. As pharmacogenetic implementations expand, disseminating lessons learned in diverse, real‐world environments will be important to support routine adoption.
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Affiliation(s)
- Kristin W Weitzel
- University of Florida Health Personalized Medicine Program, Gainesville, Florida, USA.,University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - D Max Smith
- University of Florida Health Personalized Medicine Program, Gainesville, Florida, USA.,University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Amanda R Elsey
- University of Florida Health Personalized Medicine Program, Gainesville, Florida, USA.,University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA.,University of Florida Clinical and Translational Science Institute, Gainesville, Florida, USA
| | - Benjamin Q Duong
- University of Florida Health Personalized Medicine Program, Gainesville, Florida, USA.,University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Benjamin Burkley
- University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Michael Clare-Salzler
- UF Department of Immunology, Pathology, and Laboratory Medicine, Gainesville, Florida, USA.,UF Health Pathology Laboratories, Gainesville, Florida, USA
| | - Yan Gong
- University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Tara A Higgins
- UF Health Shands Hospital Department of Pharmacy, Gainesville, Florida, USA
| | - Benjamin Kong
- Oregon Health and Science University, Portland, Oregon, USA
| | - Taimour Langaee
- University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Caitrin W McDonough
- University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Benjamin J Staley
- UF Health Shands Hospital Department of Pharmacy, Gainesville, Florida, USA
| | - Teresa T Vo
- University of South Florida Health College of Pharmacy, Tampa, Florida, USA
| | - Dyson T Wake
- NorthShore University Health System, Evanston, Illinois, USA
| | - Larisa H Cavallari
- University of Florida Health Personalized Medicine Program, Gainesville, Florida, USA.,University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
| | - Julie A Johnson
- University of Florida Health Personalized Medicine Program, Gainesville, Florida, USA.,University of Florida College of Pharmacy Center for Pharmacogenomics, Gainesville, Florida, USA
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40
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Kennell TI, Willig JH, Cimino JJ. Clinical Informatics Researcher's Desiderata for the Data Content of the Next Generation Electronic Health Record. Appl Clin Inform 2017; 8:1159-1172. [PMID: 29270955 DOI: 10.4338/aci-2017-06-r-0101] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023] Open
Abstract
OBJECTIVE Clinical informatics researchers depend on the availability of high-quality data from the electronic health record (EHR) to design and implement new methods and systems for clinical practice and research. However, these data are frequently unavailable or present in a format that requires substantial revision. This article reports the results of a review of informatics literature published from 2010 to 2016 that addresses these issues by identifying categories of data content that might be included or revised in the EHR. MATERIALS AND METHODS We used an iterative review process on 1,215 biomedical informatics research articles. We placed them into generic categories, reviewed and refined the categories, and then assigned additional articles, for a total of three iterations. RESULTS Our process identified eight categories of data content issues: Adverse Events, Clinician Cognitive Processes, Data Standards Creation and Data Communication, Genomics, Medication List Data Capture, Patient Preferences, Patient-reported Data, and Phenotyping. DISCUSSION These categories summarize discussions in biomedical informatics literature that concern data content issues restricting clinical informatics research. These barriers to research result from data that are either absent from the EHR or are inadequate (e.g., in narrative text form) for the downstream applications of the data. In light of these categories, we discuss changes to EHR data storage that should be considered in the redesign of EHRs, to promote continued innovation in clinical informatics. CONCLUSION Based on published literature of clinical informaticians' reuse of EHR data, we characterize eight types of data content that, if included in the next generation of EHRs, would find immediate application in advanced informatics tools and techniques.
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Affiliation(s)
- Timothy I Kennell
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - James H Willig
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States.,Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
| | - James J Cimino
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States.,Department of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, United States
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Hinderer M, Boeker M, Wagner SA, Lablans M, Newe S, Hülsemann JL, Neumaier M, Binder H, Renz H, Acker T, Prokosch HU, Sedlmayr M. Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development. BMC Med Inform Decis Mak 2017; 17:81. [PMID: 28587608 PMCID: PMC5461630 DOI: 10.1186/s12911-017-0480-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 05/30/2017] [Indexed: 01/05/2023] Open
Abstract
Background Pharmacogenomic clinical decision support systems (CDSS) have the potential to help overcome some of the barriers for translating pharmacogenomic knowledge into clinical routine. Before developing a prototype it is crucial for developers to know which pharmacogenomic CDSS features and user-system interactions have yet been developed, implemented and tested in previous pharmacogenomic CDSS efforts and if they have been successfully applied. We address this issue by providing an overview of the designs of user-system interactions of recently developed pharmacogenomic CDSS. Methods We searched PubMed for pharmacogenomic CDSS published between January 1, 2012 and November 15, 2016. Thirty-two out of 118 identified articles were summarized and included in the final analysis. We then compared the designs of user-system interactions of the 20 pharmacogenomic CDSS we had identified. Results Alerts are the most widespread tools for physician-system interactions, but need to be implemented carefully to prevent alert fatigue and avoid liabilities. Pharmacogenomic test results and override reasons stored in the local EHR might help communicate pharmacogenomic information to other internal care providers. Integrating patients into user-system interactions through patient letters and online portals might be crucial for transferring pharmacogenomic data to external health care providers. Inbox messages inform physicians about new pharmacogenomic test results and enable them to request pharmacogenomic consultations. Search engines enable physicians to compare medical treatment options based on a patient’s genotype. Conclusions Within the last 5 years, several pharmacogenomic CDSS have been developed. However, most of the included articles are solely describing prototypes of pharmacogenomic CDSS rather than evaluating them. To support the development of prototypes further evaluation efforts will be necessary. In the future, pharmacogenomic CDSS will likely include prediction models to identify patients who are suitable for preemptive genotyping. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0480-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marc Hinderer
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany.
| | - Martin Boeker
- Medical Informatics, Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Sebastian A Wagner
- Department of Medicine, Hematology/Oncology, Goethe University, Frankfurt, Germany
| | - Martin Lablans
- Medical Informatics in Translational Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Stephanie Newe
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany
| | | | - Michael Neumaier
- Institute for Clinical Chemistry, Medical Faculty Mannheim, Ruprecht-Karls-University Heidelberg, Mannheim, Germany
| | - Harald Binder
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Harald Renz
- University of Marburg, Institute of Laboratory Medicine, Marburg, Germany
| | - Till Acker
- Institute of Neuropathology, University of Giessen, Giessen, Germany
| | - Hans-Ulrich Prokosch
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany
| | - Martin Sedlmayr
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany
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Cousin MA, Matey ET, Blackburn PR, Boczek NJ, McAllister TM, Kruisselbrink TM, Babovic-Vuksanovic D, Lazaridis KN, Klee EW. Pharmacogenomic findings from clinical whole exome sequencing of diagnostic odyssey patients. Mol Genet Genomic Med 2017; 5:269-279. [PMID: 28546997 PMCID: PMC5441410 DOI: 10.1002/mgg3.283] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2016] [Revised: 02/17/2017] [Accepted: 02/20/2017] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND We characterized the pharmacogenomics (PGx) results received by diagnostic odyssey patients as secondary findings during clinical whole exome sequencing (WES) testing as a part of their care in Mayo Clinic's Individualized Medicine Clinic to determine the potential benefits and limitations to this cohort. METHODS WES results on 94 patients included a subset of PGx variants in CYP2C19,CYP2C9, and VKORC1 if identified in the patient. Demographic, phenotypic, and medication usage information was abstracted from patient medical data. A pharmacist interpreted the PGx results in the context of the patients' current medication use and made therapeutic recommendations. RESULTS The majority was young with a median age of 10 years old, had neurological involvement in the disease presentation (71%), and was currently taking medications (90%). Of the 94 PGx-evaluated patients, 91% had at least one variant allele reported and 20% had potential immediate implications on current medication use. CONCLUSION Due to the disease complexity and medication needs of diagnostic odyssey patients, there may be immediate benefit obtained from early life PGx testing for many and most will likely find benefit in the future. These results require conscientious interpretation and management to be actionable for all prescribing physicians throughout the lifetime of the patient.
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Affiliation(s)
- Margot A Cousin
- Center for Individualized MedicineMayo ClinicRochesterMinnesota.,Department of Health Sciences ResearchMayo ClinicRochesterMinnesota
| | - Eric T Matey
- Center for Individualized MedicineMayo ClinicRochesterMinnesota
| | - Patrick R Blackburn
- Center for Individualized MedicineMayo ClinicJacksonvilleFlorida.,Department of Health Sciences ResearchMayo ClinicJacksonvilleFlorida
| | - Nicole J Boczek
- Center for Individualized MedicineMayo ClinicRochesterMinnesota.,Department of Health Sciences ResearchMayo ClinicRochesterMinnesota
| | | | | | - Dusica Babovic-Vuksanovic
- Center for Individualized MedicineMayo ClinicRochesterMinnesota.,Department of Clinical GenomicsMayo ClinicRochesterMinnesota
| | - Konstantinos N Lazaridis
- Center for Individualized MedicineMayo ClinicRochesterMinnesota.,Department of GastroenterologyMayo ClinicRochesterMinnesota
| | - Eric W Klee
- Center for Individualized MedicineMayo ClinicRochesterMinnesota.,Department of Health Sciences ResearchMayo ClinicRochesterMinnesota.,Department of Clinical GenomicsMayo ClinicRochesterMinnesota
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Melton BL, Zillich AJ, Saleem J, Russ AL, Tisdale JE, Overholser BR. Iterative Development and Evaluation of a Pharmacogenomic-Guided Clinical Decision Support System for Warfarin Dosing. Appl Clin Inform 2016; 7:1088-1106. [PMID: 27878205 DOI: 10.4338/aci-2016-05-ra-0081] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2016] [Accepted: 09/30/2016] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE Pharmacogenomic-guided dosing has the potential to improve patient outcomes but its implementation has been met with clinical challenges. Our objective was to develop and evaluate a clinical decision support system (CDSS) for pharmacogenomic-guided warfarin dosing designed for physicians and pharmacists. METHODS Twelve physicians and pharmacists completed 6 prescribing tasks using simulated patient scenarios in two iterations (development and validation phases) of a newly developed pharmacogenomic-driven CDSS prototype. For each scenario, usability was measured via efficiency, recorded as time to task completion, and participants' perceived satisfaction which were compared using Kruskal-Wallis and Mann Whitney U tests, respectively. Debrief interviews were conducted and qualitatively analyzed. Usability findings from the first (i.e. development) iteration were incorporated into the CDSS design for the second (i.e. validation) iteration. RESULTS During the CDSS validation iteration, participants took more time to complete tasks with a median (IQR) of 183 (124-247) seconds versus 101 (73.5-197) seconds in the development iteration (p=0.01). This increase in time on task was due to the increase in time spent in the CDSS corresponding to several design changes. Efficiency differences that were observed between pharmacists and physicians in the development iteration were eliminated in the validation iteration. The increased use of the CDSS corresponded to a greater acceptance of CDSS recommended doses in the validation iteration (4% in the first iteration vs. 37.5% in the second iteration, p<0.001). Overall satisfaction did not change statistically between the iterations but the qualitative analysis revealed greater trust in the second prototype. CONCLUSIONS A pharmacogenomic-guided CDSS has been developed using warfarin as the test drug. The final CDSS prototype was trusted by prescribers and significantly increased the time using the tool and acceptance of the recommended doses. This study is an important step toward incorporating pharmacogenomics into CDSS design for clinical testing.
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Affiliation(s)
| | | | | | | | | | - Brian R Overholser
- Brian R. Overholser, PharmD, FCCP, Associate Professor, Purdue University College of Pharmacy, Research Institute 2: Room 402, 950 W. Walnut St., Indianapolis, IN 46202, Office (317) 278-4001, Fax: (317) 880-0568,
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44
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Cutting E, Banchero M, Beitelshees AL, Cimino JJ, Fiol GD, Gurses AP, Hoffman MA, Jeng LJB, Kawamoto K, Kelemen M, Pincus HA, Shuldiner AR, Williams MS, Pollin TI, Overby CL. User-centered design of multi-gene sequencing panel reports for clinicians. J Biomed Inform 2016; 63:1-10. [PMID: 27423699 DOI: 10.1016/j.jbi.2016.07.014] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2015] [Revised: 07/11/2016] [Accepted: 07/13/2016] [Indexed: 11/15/2022]
Abstract
The objective of this study was to develop a high-fidelity prototype for delivering multi-gene sequencing panel (GS) reports to clinicians that simulates the user experience of a final application. The delivery and use of GS reports can occur within complex and high-paced healthcare environments. We employ a user-centered software design approach in a focus group setting in order to facilitate gathering rich contextual information from a diverse group of stakeholders potentially impacted by the delivery of GS reports relevant to two precision medicine programs at the University of Maryland Medical Center. Responses from focus group sessions were transcribed, coded and analyzed by two team members. Notification mechanisms and information resources preferred by participants from our first phase of focus groups were incorporated into scenarios and the design of a software prototype for delivering GS reports. The goal of our second phase of focus group, to gain input on the prototype software design, was accomplished through conducting task walkthroughs with GS reporting scenarios. Preferences for notification, content and consultation from genetics specialists appeared to depend upon familiarity with scenarios for ordering and delivering GS reports. Despite familiarity with some aspects of the scenarios we proposed, many of our participants agreed that they would likely seek consultation from a genetics specialist after viewing the test reports. In addition, participants offered design and content recommendations. Findings illustrated a need to support customized notification approaches, user-specific information, and access to genetics specialists with GS reports. These design principles can be incorporated into software applications that deliver GS reports. Our user-centered approach to conduct this assessment and the specific input we received from clinicians may also be relevant to others working on similar projects.
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Affiliation(s)
- Elizabeth Cutting
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Meghan Banchero
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Amber L Beitelshees
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - James J Cimino
- Informatics Institute, School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Guilherme Del Fiol
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States
| | - Ayse P Gurses
- Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, United States; Armstrong Institute for Patient Safety and Quality, Johns Hopkins University School of Medicine, United States; Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, United States
| | - Mark A Hoffman
- University of Missouri - Kansas City, Kansas City, MO, United States; Children's Mercy Hospital, Kansas City, MO, United States
| | - Linda Jo Bone Jeng
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States; Departments of Medicine, Pathology and Pediatrics, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Kensaku Kawamoto
- Department of Biomedical Informatics, University of Utah, Salt Lake City, UT, United States
| | - Mark Kelemen
- University of Maryland Medical Center, Baltimore, MD, United States
| | - Harold Alan Pincus
- Columbia University and New York-Presbyterian Hospital, New York, NY, United States
| | - Alan R Shuldiner
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Marc S Williams
- Genomic Medicine Institute, Geisinger Health System, Danville, PA, United States
| | - Toni I Pollin
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States
| | - Casey Lynnette Overby
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, United States; Division of Health Sciences Informatics, Johns Hopkins University School of Medicine, United States; Division of General Internal Medicine, Johns Hopkins University School of Medicine, United States.
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