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Polasek TM. Pharmacogenomics - a minor rather than major force in clinical medicine. Expert Rev Clin Pharmacol 2024; 17:203-212. [PMID: 38307498 DOI: 10.1080/17512433.2024.2314726] [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: 11/01/2023] [Accepted: 02/01/2024] [Indexed: 02/04/2024]
Abstract
INTRODUCTION Pharmacogenomics (PGx) is touted as essential for the future of precision medicine. But the opportunity cost of PGx from the prescribers' perspective is rarely considered. The aim of this article is to critique PGx-guided prescribing using clinical pharmacology principles so that important cases for PGx testing are not missed by doctors responsible for therapeutic decision making. AREAS COVERED Three categories of PGx and their limitations are outlined - exposure PGx, response PGx, and immune-mediated safety PGx. Clinical pharmacology reasons are given for the narrow scope of PGx-guided prescribing apart from a few medical specialties. Clinical problems for doctors that may arise from PGx are then explained, including mismatch between patients' expectations of PGx testing and the benefits or answers it provides. EXPERT OPINION Contrary to popular opinion, PGx is unlikely to become the cornerstone of precision medicine. Sound clinical pharmacology reasons explain why PGx-guided prescribing is unnecessary for most drugs. Pharmacogenomics is important for niche areas of prescribing but has limited clinical utility more broadly. The opportunity cost of PGx-guided prescribing is currently too great for most doctors.
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Affiliation(s)
- Thomas M Polasek
- Centre for Medicine Use and Safety, Monash University, Melbourne, Australia
- CMAX Clinical Research, Adelaide, Australia
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2
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Principi N, Petropulacos K, Esposito S. Impact of Pharmacogenomics in Clinical Practice. Pharmaceuticals (Basel) 2023; 16:1596. [PMID: 38004461 PMCID: PMC10675377 DOI: 10.3390/ph16111596] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 11/03/2023] [Accepted: 11/06/2023] [Indexed: 11/26/2023] Open
Abstract
Polymorphisms of genes encoding drug metabolizing enzymes and transporters can significantly modify pharmacokinetics, and this can be associated with significant differences in drug efficacy, safety, and tolerability. Moreover, genetic variants of some components of the immune system can explain clinically relevant drug-related adverse events. However, the implementation of drug dose individualization based on pharmacogenomics remains scarce. In this narrative review, the impact of genetic variations on the disposition, safety, and tolerability of the most commonly prescribed drugs is reported. Moreover, reasons for poor implementation of pharmacogenomics in everyday clinical settings are discussed. The literature analysis showed that knowledge of how genetic variations can modify the effectiveness, safety, and tolerability of a drug can lead to the adjustment of usually recommended drug dosages, improve effectiveness, and reduce drug-related adverse events. Despite some efforts to introduce pharmacogenomics in clinical practice, presently very few centers routinely use genetic tests as a guide for drug prescription. The education of health care professionals seems critical to keep pace with the rapidly evolving field of pharmacogenomics. Moreover, multimodal algorithms that incorporate both clinical and genetic factors in drug prescribing could significantly help in this regard. Obviously, further studies which definitively establish which genetic variations play a role in conditioning drug effectiveness and safety are needed. Many problems must be solved, but the advantages for human health fully justify all the efforts.
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Affiliation(s)
| | | | - Susanna Esposito
- Pediatric Clinic, Department of Medicine and Surgery, University Hospital of Parma, 43126 Parma, Italy
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3
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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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4
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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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5
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Preys CL, Blout Zawatsky CL, Massmann A, Heukelom JV, Green RC, Hajek C, Hickingbotham MR, Zoltick ES, Schultz A, Christensen KD. Attitudes about pharmacogenomic testing vary by healthcare specialty. Pharmacogenomics 2023; 24:539-549. [PMID: 37458095 PMCID: PMC10621761 DOI: 10.2217/pgs-2023-0039] [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: 03/06/2023] [Accepted: 06/27/2023] [Indexed: 07/18/2023] Open
Abstract
Aim: To understand how attitudes toward pharmacogenomic (PGx) testing among healthcare providers varies by specialty. Methods: Providers reported comfort ordering PGx testing and its perceived utility on web-based surveys before and after genetics education. Primary quantitative analyses compared primary care providers (PCPs) to specialty providers at both timepoints. Results: PCPs were more likely than specialty care providers to rate PGx testing as useful at both timepoints. Education increased comfort ordering PGx tests, with larger improvements among PCPs than specialty providers. Over 90% of cardiology and internal medicine providers rated PGx testing as useful at pre- and post-education. Conclusion: PCPs overwhelmingly perceive PGx to be useful, and provider education is particularly effective for improving PCPs' confidence. Education for all specialties will be essential to ensure appropriate integration into routine practice.
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Affiliation(s)
- Charlene L Preys
- MGH Institute of Health Professions, Charlestown, MA 02129, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
| | - Carrie L Blout Zawatsky
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
| | - Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Robert C Green
- Department of Medicine, Brigham and Women's Hospital, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Helix OpCo, LLC, San Diego, CA 92121, USA
| | - Madison R Hickingbotham
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Emilie S Zoltick
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermilion, SD 57069, USA
| | - Kurt D Christensen
- Ariadne Labs, Boston, MA 02215, USA
- Precision Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02115, USA
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6
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Massmann A, Van Heukelom J, Green RC, Hajek C, Hickingbotham MR, Larson EA, Lu CY, Wu AC, Zoltick ES, Christensen KD, Schultz A. SLCO1B1 gene-based clinical decision support reduces statin-associated muscle symptoms risk with simvastatin. Pharmacogenomics 2023; 24:399-409. [PMID: 37232094 PMCID: PMC10242433 DOI: 10.2217/pgs-2023-0056] [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: 04/03/2023] [Accepted: 05/09/2023] [Indexed: 05/27/2023] Open
Abstract
Background: SLCO1B1 variants are known to be a strong predictor of statin-associated muscle symptoms (SAMS) risk with simvastatin. Methods: The authors conducted a retrospective chart review on 20,341 patients who had SLCO1B1 genotyping to quantify the uptake of clinical decision support (CDS) for genetic variants known to impact SAMS risk. Results: A total of 182 patients had 417 CDS alerts generated, and 150 of these patients (82.4%) received pharmacotherapy that did not increase risks for SAMS. Providers were more likely to cancel simvastatin orders in response to CDS alerts if genotyping had been done prior to the first simvastatin prescription than after (94.1% vs 28.5%, respectively; p < 0.001). Conclusion: CDS significantly reduces simvastatin prescribing at doses associated with SAMS.
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Affiliation(s)
- Amanda Massmann
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Joel Van Heukelom
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Robert C Green
- Department of Medicine, Brigham & Women's Hospital & Harvard Medical School, Boston, MA 02115, USA
- Ariadne Labs, Boston, MA 02215, USA
- Broad Institute of Harvard & MIT, Cambridge, MA 02142, USA
| | - Catherine Hajek
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Helix OpCo, LLC, San Mateo, CA 94401, USA
| | - Madison R Hickingbotham
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Eric A Larson
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
| | - Christine Y Lu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Ann Chen Wu
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Emilie S Zoltick
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
| | - Kurt D Christensen
- Broad Institute of Harvard & MIT, Cambridge, MA 02142, USA
- PRecisiOn Medicine Translational Research (PROMoTeR) Center, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA
- Department of Population Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - April Schultz
- Sanford Imagenetics, Sanford Health, Sioux Falls, SD 57105, USA
- Department of Internal Medicine, University of South Dakota School of Medicine, Vermillion, SD 57069, USA
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7
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Mostafa S, Polasek TM, Bousman CA, Müeller DJ, Sheffield LJ, Rembach J, Kirkpatrick CM. Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing. Pharmacogenomics 2022; 23:857-867. [PMID: 36169629 DOI: 10.2217/pgs-2022-0104] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Pharmacogenomic (PGx) testing of cytochrome P450 (CYP) enzymes may improve the efficacy and/or safety of some medications. This is facilitated by increased availability and affordability of genotyping, the development of clinical practice PGx guidelines and regulatory support. However, the common occurrence of CYP phenoconversion, a mismatch between genotype-predicted CYP phenotype and the actual CYP phenotype, currently limits the application of PGx testing for precision dosing in psychiatry. This review proposes a stepwise approach to assist precision dosing in psychiatry via the introduction of PGx stewardship programs and innovative PGx education strategies. A future perspective on delivering precision dosing for psychiatrists is discussed that involves innovative clinical decision support systems powered by model-informed precision dosing.
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Affiliation(s)
- Sam Mostafa
- Centre for Medicine Use & Safety, Monash University, Parkville, Victoria, 3052, Australia.,MyDNA Life, Australia Limited, South Yarra, Victoria, Australia
| | - Thomas M Polasek
- Centre for Medicine Use & Safety, Monash University, Parkville, Victoria, 3052, Australia.,Certara, Princeton, NJ 08540, USA.,Department of Clinical Pharmacology, Royal Adelaide Hospital, Adelaide, South Australia, 5000, Australia
| | - Chad A Bousman
- Department of Psychiatry, Melbourne Neuropsychiatry Centre, University of Melbourne & Melbourne Health, Melbourne, Victoria, 3010, Australia.,The Cooperative Research Centre (CRC) for Mental Health, Carlton, Victoria, 3053, Australia.,Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.,Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, Alberta, T2N 1N4, Canada.,Departments of Medical Genetics, Psychiatry, & Physiology & Pharmacology, University of Calgary, Calgary, Alberta, T2N 1N4, Canada
| | - Daniel J Müeller
- Pharmacogenetics Research Clinic, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, M5T 1R8, Canada
| | | | - Joel Rembach
- MyDNA Life, Australia Limited, South Yarra, Victoria, Australia
| | - Carl Mj Kirkpatrick
- Centre for Medicine Use & Safety, Monash University, Parkville, Victoria, 3052, Australia
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8
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Blagec K, Swen JJ, Koopmann R, Cheung KC, Crommentuijn-van Rhenen M, Holsappel I, Konta L, Ott S, Steinberger D, Xu H, Cecchin E, Dolžan V, Dávila-Fajardo CL, Patrinos GP, Sunder-Plassmann G, Turner RM, Pirmohamed M, Guchelaar HJ, Samwald M. Pharmacogenomics decision support in the U-PGx project: Results and advice from clinical implementation across seven European countries. PLoS One 2022; 17:e0268534. [PMID: 35675343 PMCID: PMC9176797 DOI: 10.1371/journal.pone.0268534] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 04/26/2022] [Indexed: 12/18/2022] Open
Abstract
Background The clinical implementation of pharmacogenomics (PGx) could be one of the first milestones towards realizing personalized medicine in routine care. However, its widespread adoption requires the availability of suitable clinical decision support (CDS) systems, which is often impeded by the fragmentation or absence of adequate health IT infrastructures. We report results of CDS implementation in the large-scale European research project Ubiquitous Pharmacogenomics (U-PGx), in which PGx CDS was rolled out and evaluated across more than 15 clinical sites in the Netherlands, Spain, Slovenia, Italy, Greece, United Kingdom and Austria, covering a wide variety of healthcare settings. Methods We evaluated the CDS implementation process through qualitative and quantitative process indicators. Quantitative indicators included statistics on generated PGx reports, median time from sampled upload until report delivery and statistics on report retrievals via the mobile-based CDS tool. Adoption of different CDS tools, uptake and usability were further investigated through a user survey among healthcare providers. Results of a risk assessment conducted prior to the implementation process were retrospectively analyzed and compared to actual encountered difficulties and their impact. Results As of March 2021, personalized PGx reports were produced from 6884 genotyped samples with a median delivery time of twenty minutes. Out of 131 invited healthcare providers, 65 completed the questionnaire (response rate: 49.6%). Overall satisfaction rates with the different CDS tools varied between 63.6% and 85.2% per tool. Delays in implementation were caused by challenges including institutional factors and complexities in the development of required tools and reference data resources, such as genotype-phenotype mappings. Conclusions We demonstrated the feasibility of implementing a standardized PGx decision support solution in a multinational, multi-language and multi-center setting. Remaining challenges for future wide-scale roll-out include the harmonization of existing PGx information in guidelines and drug labels, the need for strategies to lower the barrier of PGx CDS adoption for healthcare institutions and providers, and easier compliance with regulatory and legal frameworks.
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Affiliation(s)
- Kathrin Blagec
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Jesse J Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Rudolf Koopmann
- Diagnosticum Center for Human Genetics, Frankfurt am Main, Germany.,Institute for Human Genetics, Justus Liebig University, Giessen, Germany
| | - Ka-Chun Cheung
- Medicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, The Netherlands
| | | | - Inge Holsappel
- Medicines Information Centre, Royal Dutch Pharmacists Association (KNMP), The Hague, The Netherlands
| | - Lidija Konta
- Diagnosticum Center for Human Genetics, Frankfurt am Main, Germany
| | - Simon Ott
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Daniela Steinberger
- Diagnosticum Center for Human Genetics, Frankfurt am Main, Germany.,Institute for Human Genetics, Justus Liebig University, Giessen, Germany
| | - Hong Xu
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
| | - Erika Cecchin
- Experimental and Clinical Pharmacology Unit, Centro di Riferimento Oncologico di Aviano (CRO) IRCCS, Aviano, Italy
| | - Vita Dolžan
- Faculty of Medicine, Institute of Biochemistry and Molecular Genetics, Pharmacogenetics Laboratory, University of Ljubljana, Ljubljana, Slovenia
| | - Cristina Lucía Dávila-Fajardo
- Clinical Pharmacy Department, Hospital Universitario Virgen de las Nieves, Instituto de Investigación Biosanitaria Granada (Ibs.Granada), Granada, Spain
| | - George P Patrinos
- Department of Pharmacy, Laboratory of Pharmacogenomics and Individualized Therapy, University of Patras School of Health Sciences, Patras, Greece
| | - Gere Sunder-Plassmann
- Division of Nephrology and Dialysis, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Richard M Turner
- The Wolfson Centre for Personalised Medicine, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom
| | - Munir Pirmohamed
- Department of Molecular and Clinical Pharmacology, Royal Liverpool University Hospital and University of Liverpool, Liverpool, United Kingdom
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthias Samwald
- Institute of Artificial Intelligence, Center for Medical Statistics, Informatics, and Intelligent Systems, Medical University of Vienna, Vienna, Austria
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9
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Barker CIS, Groeneweg G, Maitland-van der Zee AH, Rieder MJ, Hawcutt DB, Hubbard TJ, Swen JJ, Carleton BC. Pharmacogenomic testing in paediatrics: clinical implementation strategies. Br J Clin Pharmacol 2021; 88:4297-4310. [PMID: 34907575 PMCID: PMC9544158 DOI: 10.1111/bcp.15181] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Revised: 10/22/2021] [Accepted: 11/09/2021] [Indexed: 11/27/2022] Open
Abstract
Pharmacogenomics (PGx) relates to the study of genetic factors determining variability in drug response. Implementing PGx testing in paediatric patients can enhance drug safety, helping to improve drug efficacy or reduce the risk of toxicity. Despite its clinical relevance, the implementation of PGx testing in paediatric practice to date has been variable and limited. As with most paediatric pharmacological studies, there are well‐recognised barriers to obtaining high‐quality PGx evidence, particularly when patient numbers may be small, and off‐label or unlicensed prescribing remains widespread. Furthermore, trials enrolling small numbers of children can rarely, in isolation, provide sufficient PGx evidence to change clinical practice, so extrapolation from larger PGx studies in adult patients, where scientifically sound, is essential. This review paper discusses the relevance of PGx to paediatrics and considers implementation strategies from a child health perspective. Examples are provided from Canada, the Netherlands and the UK, with consideration of the different healthcare systems and their distinct approaches to implementation, followed by future recommendations based on these cumulative experiences. Improving the evidence base demonstrating the clinical utility and cost‐effectiveness of paediatric PGx testing will be critical to drive implementation forwards. International, interdisciplinary collaborations will enhance paediatric data collation, interpretation and evidence curation, while also supporting dedicated paediatric PGx educational initiatives. PGx consortia and paediatric clinical research networks will continue to play a central role in the streamlined development of effective PGx implementation strategies to help optimise paediatric pharmacotherapy.
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Affiliation(s)
- Charlotte I S Barker
- Department of Medical & Molecular Genetics, King's College London, London, UK.,Department of Clinical Genetics, Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Gabriella Groeneweg
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,Pharmaceutical Outcomes Programme, BC Children's Hospital, Vancouver, British Columbia, Canada
| | - Anke H Maitland-van der Zee
- Respiratory Medicine/Pediatric Respiratory Medicine, Academic Medical Center, University of Amsterdam, Amsterdam, the Netherlands
| | - Michael J Rieder
- Departments of Paediatrics, Physiology and Pharmacology and Medicine, Western University, London, Ontario, Canada.,Molecular Medicine Group, Robarts Research Institute, London, Ontario, Canada
| | - Daniel B Hawcutt
- Department of Women's and Children's Health, University of Liverpool, Liverpool, UK.,NIHR Clinical Research Facility, Alder Hey Children's Hospital, Liverpool, UK
| | - Tim J Hubbard
- Department of Medical & Molecular Genetics, King's College London, London, UK.,Genomics England, London, UK
| | - Jesse J Swen
- Department of Clinical Pharmacy and Toxicology, Leiden University Medical Center, Leiden, The Netherlands.,Leiden Network for Personalized Therapeutics, Leiden, The Netherlands
| | - Bruce C Carleton
- Division of Translational Therapeutics, Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada.,Pharmaceutical Outcomes Programme, BC Children's Hospital, Vancouver, British Columbia, Canada.,BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada
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10
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Gong J, Sihag V, Kong Q, Zhao L. Visualizing Knowledge Evolution Trends and Research Hotspots of Personal Health Data Research: Bibliometric Analysis. JMIR Med Inform 2021; 9:e31142. [PMID: 34723823 PMCID: PMC8593818 DOI: 10.2196/31142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 08/17/2021] [Accepted: 09/17/2021] [Indexed: 11/13/2022] Open
Abstract
Background The recent surge in clinical and nonclinical health-related data has been accompanied by a concomitant increase in personal health data (PHD) research across multiple disciplines such as medicine, computer science, and management. There is now a need to synthesize the dynamic knowledge of PHD in various disciplines to spot potential research hotspots. Objective The aim of this study was to reveal the knowledge evolutionary trends in PHD and detect potential research hotspots using bibliometric analysis. Methods We collected 8281 articles published between 2009 and 2018 from the Web of Science database. The knowledge evolution analysis (KEA) framework was used to analyze the evolution of PHD research. The KEA framework is a bibliometric approach that is based on 3 knowledge networks: reference co-citation, keyword co-occurrence, and discipline co-occurrence. Results The findings show that the focus of PHD research has evolved from medicine centric to technology centric to human centric since 2009. The most active PHD knowledge cluster is developing knowledge resources and allocating scarce resources. The field of computer science, especially the topic of artificial intelligence (AI), has been the focal point of recent empirical studies on PHD. Topics related to psychology and human factors (eg, attitude, satisfaction, education) are also receiving more attention. Conclusions Our analysis shows that PHD research has the potential to provide value-based health care in the future. All stakeholders should be educated about AI technology to promote value generation through PHD. Moreover, technology developers and health care institutions should consider human factors to facilitate the effective adoption of PHD-related technology. These findings indicate opportunities for interdisciplinary cooperation in several PHD research areas: (1) AI applications for PHD; (2) regulatory issues and governance of PHD; (3) education of all stakeholders about AI technology; and (4) value-based health care including “allocative value,” “technology value,” and “personalized value.”
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Affiliation(s)
- Jianxia Gong
- School of Economics and Management, Southeast University, Nanjing, China
| | - Vikrant Sihag
- Department of Industrial Engineering and Innovation Sciences, Eindhoven University of Technology, Eindhoven, Netherlands
| | - Qingxia Kong
- Department of Technology and Operations Management, Erasmus University Rotterdam, Rotterdam, Netherlands
| | - Lindu Zhao
- School of Economics and Management, Southeast University, Nanjing, China
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11
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Virelli CR, Mohiuddin AG, Kennedy JL. Barriers to clinical adoption of pharmacogenomic testing in psychiatry: a critical analysis. Transl Psychiatry 2021; 11:509. [PMID: 34615849 PMCID: PMC8492820 DOI: 10.1038/s41398-021-01600-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 08/23/2021] [Accepted: 08/27/2021] [Indexed: 12/21/2022] Open
Abstract
Pharmacogenomics (PGx) is the study of genetic influences on an individual's response to medications. Improvements in the quality and quantity of PGx research over the past two decades have enabled the establishment of commercial markets for PGx tests. Nevertheless, PGx testing has yet to be adopted as a routine practice in clinical care. Accordingly, policy regulating the commercialization and reimbursement of PGx testing is in its infancy. Several papers have been published on the topic of challenges, or 'barriers' to clinical adoption of this healthcare innovation. However, many do not include recent evidence from randomized controlled trials, economic utility studies, and qualitative assessments of stakeholder opinions. The present paper revisits the most cited barriers to adoption of PGx testing: evidence for clinical utility, evidence for economic effectiveness, and stakeholder awareness. We consider these barriers in the context of reviewing PGx literature published over the past two decades and emphasize data from commercial PGx testing companies, since they have published the largest datasets. We conclude with a discussion of existing limitations to PGx testing and recommendations for progress.
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Affiliation(s)
- Catherine R. Virelli
- grid.155956.b0000 0000 8793 5925Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Translational Research Program, Institute of Medical Science, University of Toronto, Toronto, ON Canada
| | - Ayeshah G. Mohiuddin
- grid.155956.b0000 0000 8793 5925Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Translational Research Program, Institute of Medical Science, University of Toronto, Toronto, ON Canada
| | - James L. Kennedy
- grid.155956.b0000 0000 8793 5925Tanenbaum Centre for Pharmacogenetics, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, ON Canada ,grid.17063.330000 0001 2157 2938Department of Psychiatry, University of Toronto, Toronto, ON Canada
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12
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Hayward J, McDermott J, Qureshi N, Newman W. Pharmacogenomic testing to support prescribing in primary care: a structured review of implementation models. Pharmacogenomics 2021; 22:761-776. [PMID: 34467776 PMCID: PMC8438972 DOI: 10.2217/pgs-2021-0032] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023] Open
Abstract
The application of pharmacogenomics could meaningfully contribute toward medicines optimization within primary care. This review identified 13 studies describing eight implementation models utilizing a multi-gene pharmacogenomic panel within a primary care or community setting. These were small feasibility studies (n <200). They demonstrated importance and feasibility of pre-test counseling, the role of the pharmacist, data integration into the electronic medical record and point-of-care clinical decision support systems (CDSS). Findings were considered alongside existing primary care prescribing practices and implementation frameworks to demonstrate how issues may be addressed by existing nationalized healthcare and primary care infrastructure. Development of point-of-care CDSS should be prioritized; establishing clinical leadership, education programs, defining practitioner roles and responsibilities and addressing commissioning issues will also be crucial.
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Affiliation(s)
- Judith Hayward
- Yorkshire Regional Genetics Service, Chapel Allerton Hospital, Leeds Teaching Hospitals Trust, Leeds, LS7 4SA, UK.,Affinity Care, Shipley Medical Practice, Shipley, BD18 3EG, UK
| | - John McDermott
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.,Division of Evolution, Infection and Genomics, School of Biological Sciences, University of Manchester, Manchester, M14 5BZ, UK
| | - Nadeem Qureshi
- Primary Care Stratified Medicine Research Group (PRISM), University of Nottingham, Nottingham, NG7 2UH, UK
| | - William Newman
- Manchester Centre for Genomic Medicine, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK.,Division of Evolution, Infection and Genomics, School of Biological Sciences, University of Manchester, Manchester, M14 5BZ, UK
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13
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Zubiaur P, Mejía-Abril G, Navares-Gómez M, Villapalos-García G, Soria-Chacartegui P, Saiz-Rodríguez M, Ochoa D, Abad-Santos F. PriME-PGx: La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics. J Clin Med 2021; 10:jcm10173772. [PMID: 34501219 PMCID: PMC8432257 DOI: 10.3390/jcm10173772] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Revised: 08/15/2021] [Accepted: 08/19/2021] [Indexed: 12/18/2022] Open
Abstract
The implementation of clinical pharmacogenetics in daily practice is limited for various reasons. Today, however, it is a discipline in full expansion. Accordingly, in the recent times, several initiatives promoted its implementation, mainly in the United States but also in Europe. In this document, the genotyping results since the establishment of our Pharmacogenetics Unit in 2006 are described, as well as the historical implementation process that was carried out since then. Finally, this progress justified the constitution of La Princesa University Hospital Multidisciplinary Initiative for the Implementation of Pharmacogenetics (PriME-PGx), promoted by the Clinical Pharmacology Department of Hospital Universitario de La Princesa (Madrid, Spain). Here, we present the initiative along with the two first ongoing projects: the PROFILE project, which promotes modernization of pharmacogenetic reporting (i.e., from classic gene-drug pair reporting to complete pharmacogenetic reporting or the creation of pharmacogenetic profiles specific to the Hospital’s departments) and the GENOTRIAL project, which promotes the communication of relevant pharmacogenetic findings to any healthy volunteer participating in any bioequivalence clinical trial at the Clinical Trials Unit of Hospital Universitario de La Princesa (UECHUP).
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Affiliation(s)
- Pablo Zubiaur
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
- Correspondence: (P.Z.); (F.A.-S.); Tel.: +34-915-202-425 (P.Z. & F.A.-S.); Fax: +34-915-202-540 (P.Z. & F.A.-S.)
| | - Gina Mejía-Abril
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
| | - Marcos Navares-Gómez
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Gonzalo Villapalos-García
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Paula Soria-Chacartegui
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
| | - Miriam Saiz-Rodríguez
- Research Unit, Fundación Burgos por la Investigación de la Salud (FBIS), Hospital Universitario de Burgos, 09006 Burgos, Spain;
| | - Dolores Ochoa
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
| | - Francisco Abad-Santos
- Clinical Pharmacology Department, La Princesa University Hospital, Instituto Teófilo Hernando, Instituto de Investigación Sanitaria La Princesa (IP), Universidad Autónoma de Madrid (UAM), 28029 Madrid, Spain; (G.M.-A.); (M.N.-G.); (G.V.-G.); (P.S.-C.); (D.O.)
- UICEC Hospital Universitario de La Princesa, Plataforma SCReN (Spanish Clinical Research Network), Instituto de Investigación Sanitaria La Princesa (IP), 28006 Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, 28200 Madrid, Spain
- Correspondence: (P.Z.); (F.A.-S.); Tel.: +34-915-202-425 (P.Z. & F.A.-S.); Fax: +34-915-202-540 (P.Z. & F.A.-S.)
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14
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Acceptance of clinical decision support systems in Saudi healthcare organisations. INFORMATION DEVELOPMENT 2021. [DOI: 10.1177/02666669211025076] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Applications of clinical decision support systems (CDSS) have become essential for physicians seeking to make appropriate decisions. The implementation of CDSS, however, is complicated if the factors affecting physician’s acceptance are not recognised. This study aims to explore the various factors that may influence the acceptance of CDSS in Saudi Arabia. A qualitative method was used to collect data from interviews with 54 GPs, with interviews conducted in three stages. The study then integrated the Unified Theory of Acceptance and Use of Technology (UTAUT) and Task-Technology Fit (TTF) models to communicate the findings. It is suggested that all factors of both UTAUT and TTF influence acceptance of CDSS by GPs, with the sole exception of the social influence factor. Some additional factors were also discovered by means of in-depth interviews, including accessibility, patient satisfaction, informativeness (increased knowledge), connectedness (informing patients), communication and shared knowledge, privacy and security, and perceived risk (functional performance risk and time risk). The study thus offers a new insight of the factors influencing GPs’ acceptance of CDSS.
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15
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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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16
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Christensen KD, Bell M, Zawatsky CLB, Galbraith LN, Green RC, Hutchinson AM, Jamal L, LeBlanc JL, Leonhard JR, Moore M, Mullineaux L, Petry N, Platt DM, Shaaban S, Schultz A, Tucker BD, Van Heukelom J, Wheeler E, Zoltick ES, Hajek C. Precision Population Medicine in Primary Care: The Sanford Chip Experience. Front Genet 2021; 12:626845. [PMID: 33777099 PMCID: PMC7994529 DOI: 10.3389/fgene.2021.626845] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 02/11/2021] [Indexed: 01/10/2023] Open
Abstract
Genetic testing has the potential to revolutionize primary care, but few health systems have developed the infrastructure to support precision population medicine applications or attempted to evaluate its impact on patient and provider outcomes. In 2018, Sanford Health, the nation's largest rural nonprofit health care system, began offering genetic testing to its primary care patients. To date, more than 11,000 patients have participated in the Sanford Chip Program, over 90% of whom have been identified with at least one informative pharmacogenomic variant, and about 1.5% of whom have been identified with a medically actionable predisposition for disease. This manuscript describes the rationale for offering the Sanford Chip, the programs and infrastructure implemented to support it, and evolving plans for research to evaluate its real-world impact.
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Affiliation(s)
- Kurt D Christensen
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States.,Department of Population Medicine, Harvard Medical School, Boston, MA, United States.,Broad Institute of MIT and Harvard, Cambridge, MA, United States
| | - Megan Bell
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Carrie L B Zawatsky
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Ariadne Labs, Boston, MA, United States
| | - Lauren N Galbraith
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Robert C Green
- Broad Institute of MIT and Harvard, Cambridge, MA, United States.,Department of Medicine, Brigham and Women's Hospital, Boston, MA, United States.,Ariadne Labs, Boston, MA, United States.,Department of Medicine, Harvard Medical School, Boston, MA, United States
| | | | - Leila Jamal
- National Cancer Institute, Bethesda, MD, United States.,Department of Bioethics, National Institutes of Health, Bethesda, MD, United States
| | - Jessica L LeBlanc
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | | | - Michelle Moore
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Lisa Mullineaux
- Mayo Clinic Genomics Laboratory, Rochester, MN, United States
| | - Natasha Petry
- Sanford Health Imagenetics, Fargo, ND, United States.,Department of Pharmacy Practice, North Dakota State University, Fargo, ND, United States
| | - Dylan M Platt
- Sanford Health Imagenetics, Sioux Falls, SD, United States
| | - Sherin Shaaban
- Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, United States.,ARUP Laboratories, Salt Lake City, UT, United States
| | - April Schultz
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | | | - Joel Van Heukelom
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
| | | | - Emilie S Zoltick
- Center for Healthcare Research in Pediatrics, Department of Population Medicine, Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Catherine Hajek
- Sanford Health Imagenetics, Sioux Falls, SD, United States.,Sanford School of Medicine, University of South Dakota, Sioux Falls, SD, United States
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17
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Caspar SM, Schneider T, Stoll P, Meienberg J, Matyas G. Potential of whole-genome sequencing-based pharmacogenetic profiling. Pharmacogenomics 2021; 22:177-190. [PMID: 33517770 DOI: 10.2217/pgs-2020-0155] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Pharmacogenetics represents a major driver of precision medicine, promising individualized drug selection and dosing. Traditionally, pharmacogenetic profiling has been performed using targeted genotyping that focuses on common/known variants. Recently, whole-genome sequencing (WGS) is emerging as a more comprehensive short-read next-generation sequencing approach, enabling both gene diagnostics and pharmacogenetic profiling, including rare/novel variants, in a single assay. Using the example of the pharmacogene CYP2D6, we demonstrate the potential of WGS-based pharmacogenetic profiling as well as emphasize the limitations of short-read next-generation sequencing. In the near future, we envision a shift toward long-read sequencing as the predominant method for gene diagnostics and pharmacogenetic profiling, providing unprecedented data quality and improving patient care.
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Affiliation(s)
- Sylvan Manuel Caspar
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland.,Department of Health Sciences & Technology, Laboratory of Translational Nutrition Biology, ETH Zurich, Schwerzenbach 8603, Switzerland
| | - Timo Schneider
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland
| | - Patricia Stoll
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland
| | - Janine Meienberg
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland
| | - Gabor Matyas
- Center for Cardiovascular Genetics & Gene Diagnostics, Foundation for People with Rare Diseases, Schlieren-Zurich 8952, Switzerland.,Zurich Center for Integrative Human Physiology, University of Zurich, Zurich 8057, Switzerland
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18
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Malsagova KA, Butkova TV, Kopylov AT, Izotov AA, Potoldykova NV, Enikeev DV, Grigoryan V, Tarasov A, Stepanov AA, Kaysheva AL. Pharmacogenetic Testing: A Tool for Personalized Drug Therapy Optimization. Pharmaceutics 2020; 12:E1240. [PMID: 33352764 PMCID: PMC7765968 DOI: 10.3390/pharmaceutics12121240] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 12/15/2020] [Accepted: 12/17/2020] [Indexed: 12/14/2022] Open
Abstract
Pharmacogenomics is a study of how the genome background is associated with drug resistance and how therapy strategy can be modified for a certain person to achieve benefit. The pharmacogenomics (PGx) testing becomes of great opportunity for physicians to make the proper decision regarding each non-trivial patient that does not respond to therapy. Although pharmacogenomics has become of growing interest to the healthcare market during the past five to ten years the exact mechanisms linking the genetic polymorphisms and observable responses to drug therapy are not always clear. Therefore, the success of PGx testing depends on the physician's ability to understand the obtained results in a standardized way for each particular patient. The review aims to lead the reader through the general conception of PGx and related issues of PGx testing efficiency, personal data security, and health safety at a current clinical level.
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Affiliation(s)
- Kristina A. Malsagova
- Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (T.V.B.); (A.T.K.); (A.A.I.); (A.A.S.); (A.L.K.)
| | - Tatyana V. Butkova
- Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (T.V.B.); (A.T.K.); (A.A.I.); (A.A.S.); (A.L.K.)
| | - Arthur T. Kopylov
- Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (T.V.B.); (A.T.K.); (A.A.I.); (A.A.S.); (A.L.K.)
| | - Alexander A. Izotov
- Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (T.V.B.); (A.T.K.); (A.A.I.); (A.A.S.); (A.L.K.)
| | - Natalia V. Potoldykova
- Institute of Urology and Reproductive Health, Sechenov University, 119992 Moscow, Russia; (N.V.P.); (D.V.E.); (V.G.)
| | - Dmitry V. Enikeev
- Institute of Urology and Reproductive Health, Sechenov University, 119992 Moscow, Russia; (N.V.P.); (D.V.E.); (V.G.)
| | - Vagarshak Grigoryan
- Institute of Urology and Reproductive Health, Sechenov University, 119992 Moscow, Russia; (N.V.P.); (D.V.E.); (V.G.)
| | - Alexander Tarasov
- Institute of Linguistics and Intercultural Communication, Sechenov University, 119992 Moscow, Russia;
| | - Alexander A. Stepanov
- Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (T.V.B.); (A.T.K.); (A.A.I.); (A.A.S.); (A.L.K.)
| | - Anna L. Kaysheva
- Biobanking Group, Branch of Institute of Biomedical Chemistry “Scientific and Education Center”, 109028 Moscow, Russia; (T.V.B.); (A.T.K.); (A.A.I.); (A.A.S.); (A.L.K.)
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19
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Vassy JL, Gaziano JM, Green RC, Ferguson RE, Advani S, Miller SJ, Chun S, Hage AK, Seo SJ, Majahalme N, MacMullen L, Zimolzak AJ, Brunette CA. Effect of Pharmacogenetic Testing for Statin Myopathy Risk vs Usual Care on Blood Cholesterol: A Randomized Clinical Trial. JAMA Netw Open 2020; 3:e2027092. [PMID: 33270123 PMCID: PMC7716196 DOI: 10.1001/jamanetworkopen.2020.27092] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
Abstract
IMPORTANCE Nonadherence to statin guidelines is common. The solute carrier organic anion transporter family member 1B1 (SLCO1B1) genotype is associated with simvastatin myopathy risk and is proposed for clinical implementation. The unintended harms of using pharmacogenetic information to guide pharmacotherapy remain a concern for some stakeholders. OBJECTIVE To determine the impact of delivering SLCO1B1 pharmacogenetic results to physicians on the effectiveness of atherosclerotic cardiovascular disease (ASCVD) prevention (measured by low-density lipoprotein cholesterol [LDL-C] levels) and concordance with prescribing guidelines for statin safety and effectiveness. DESIGN, SETTING, AND PARTICIPANTS This randomized clinical trial was performed from December 2015 to July 2019 at 8 primary care practices in the Veterans Affairs Boston Healthcare System. Participants included statin-naive patients with elevated ASCVD risk. Data analysis was performed from October 2019 to September 2020. INTERVENTIONS SLCO1B1 genotyping and results reporting to primary care physicians at baseline (intervention group) vs after 1 year (control group). MAIN OUTCOMES AND MEASURES The primary outcome was the 1-year change in LDL-C level. The secondary outcomes were 1-year concordance with American College of Cardiology-American Heart Association and Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines for statin therapy and statin-associated muscle symptoms (SAMS). RESULTS Among 408 patients (mean [SD] age, 64.1 [7.8] years; 25 women [6.1%]), 193 were randomized to the intervention group and 215 were randomized to the control group. Overall, 120 participants (29%) had a SLCO1B1 genotype indicating increased simvastatin myopathy risk. Physicians offered statin therapy to 65 participants (33.7%) in the intervention group and 69 participants (32.1%) in the control group. Compared with patients whose physicians did not know their SLCO1B1 results at baseline, patients whose physicians received the results had noninferior reductions in LDL-C at 12 months (mean [SE] change in LDL-C, -1.1 [1.2] mg/dL in the intervention group and -2.2 [1.3] mg/dL in the control group; difference, -1.1 mg/dL; 90% CI, -4.1 to 1.8 mg/dL; P < .001 for noninferiority margin of 10 mg/dL). The proportion of patients with American College of Cardiology-American Heart Association guideline-concordant statin prescriptions in the intervention group was noninferior to that in the control group (12 patients [6.2%] vs 14 patients [6.5%]; difference, -0.003; 90% CI, -0.038 to 0.032; P < .001 for noninferiority margin of 15%). All patients in both groups were concordant with CPIC guidelines for safe statin prescribing. Physicians documented 2 and 3 cases of SAMS in the intervention and control groups, respectively, none of which was associated with a CPIC guideline-discordant prescription. Among patients with a decreased or poor SLCO1B1 transporter function genotype, simvastatin was prescribed to 1 patient in the control group but none in the intervention group. CONCLUSIONS AND RELEVANCE Clinical testing and reporting of SLCO1B1 results for statin myopathy risk did not result in poorer ASCVD prevention in a routine primary care setting and may have been associated with physicians avoiding simvastatin prescriptions for patients at genetic risk for SAMS. Such an absence of harm should reassure stakeholders contemplating the clinical use of available pharmacogenetic results. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT02871934.
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Affiliation(s)
- Jason L. Vassy
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - J. Michael Gaziano
- VA Boston Healthcare System, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Robert C. Green
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Ariadne Labs, Boston, Massachusetts
| | - Ryan E. Ferguson
- VA Boston Healthcare System, Boston, Massachusetts
- Department of General Internal Medicine, Boston University School of Medicine, Boston, Massachusetts
- Department of Epidemiology, Boston University School of Public Health, Boston, Massachusetts
| | | | | | - Sojeong Chun
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Anthony K. Hage
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | - Soo-Ji Seo
- Massachusetts College of Pharmacy and Health Sciences, Boston
| | | | | | - Andrew J. Zimolzak
- VA Boston Healthcare System, Boston, Massachusetts
- Baylor College of Medicine, Houston, Texas
- Michael E. DeBakey VA Medical Center, Houston, Texas
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20
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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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21
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Schutijser BCFM, Jongerden I, Klopotowska JE, Moesker M, Langelaan M, Wagner C, de Bruijne M. Nature of adverse events with opioids in hospitalised patients: a post-hoc analysis of three patient record review studies. BMJ Open 2020; 10:e038037. [PMID: 32998923 PMCID: PMC7528356 DOI: 10.1136/bmjopen-2020-038037] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
Abstract
OBJECTIVE Opioids are increasingly prescribed and frequently involved in adverse drug events (ADEs). The underlying nature of opioid-related ADEs (ORADEs) is however understudied. This hampers our understanding of risks related to opioid use during hospitalisation and when designing interventions. Therefore, we provided a description of the nature of ORADEs. DESIGN A post-hoc analysis of data collected during three retrospective patient record review studies (in 2008, 2011/2012 and 2015/2016). SETTING The three record review studies were conducted in 32 Dutch hospitals. PARTICIPANTS A total of 10 917 patient records were assessed by trained nurses and physicians. OUTCOME MEASURES Per identified ORADE, we described preventability, type of medication error, attributable factors and type of opioids involved. Moreover, the characteristics of preventable and non-preventable ORADEs were compared to identify risk factors. RESULTS Out of 10 917 patient records, 357 ADEs were identified, of which 28 (8%) involved opioids. Eleven ORADEs were assessed as preventable. Of these, 10 were caused by dosing errors and 4 probably contributed to patients' death. Attributable factors identified were mainly on patient and organisational levels. Morphine and oxycodone were the most frequently involved opioids. The risk for ORADEs was higher in elderly patients. CONCLUSIONS Only 8% of ADEs identified in our sample were related to opioids. Although the frequency is low, the risk of serious consequences is high. We recommend to use our findings to increase awareness among physicians and nurses. Future interventions should focus on safe dosing of opioids when prescribing and administering, especially in elderly patients.
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Affiliation(s)
| | - Irene Jongerden
- Public and Occupational Health, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | | | - Marco Moesker
- Public and Occupational Health, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
| | | | - Cordula Wagner
- Public and Occupational Health, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
- NIVEL, Utrecht, The Netherlands
| | - Martine de Bruijne
- Public and Occupational Health, Amsterdam UMC Locatie VUmc, Amsterdam, The Netherlands
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22
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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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23
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Olakotan OO, Yusof MM. Evaluating the alert appropriateness of clinical decision support systems in supporting clinical workflow. J Biomed Inform 2020; 106:103453. [PMID: 32417444 DOI: 10.1016/j.jbi.2020.103453] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 05/08/2020] [Accepted: 05/09/2020] [Indexed: 02/06/2023]
Abstract
The overwhelming number of medication alerts generated by clinical decision support systems (CDSS) has led to inappropriate alert overrides, which may lead to unintended patient harm. This review highlights the factors affecting the alert appropriateness of CDSS and barriers to the fit of CDSS alert with clinical workflow. A literature review was conducted to identify features and functions pertinent to CDSS alert appropriateness using the five rights of CDSS. Moreover, a process improvement method, namely, Lean, was used as a tool to optimise clinical workflows, and the appropriate design for CDSS alert using a human automation interaction (HAI) model was recommended. Evaluating the appropriateness of CDSS alert and its impact on workflow provided insights into how alerts can be designed and triggered effectively to support clinical workflow. The application of Lean methods and tools to analyse alert efficiencies in supporting workflow in this study provides an in-depth understanding of alert-workflow fit problems and their root cause, which is required for improving CDSS design. The application of the HAI model is recommended in the design of CDSS alerts to support various levels and stages of alert automations, namely, information acquisition and analysis, decision action and action implementation.
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Affiliation(s)
| | - Maryati Mohd Yusof
- Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia.
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24
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Kostyuk GP, Zakharova NV, Reznik AM, Surkova EI, Ilinsky VV. [Perspectives of the use of pharmacogenetic tests in neurology and psychiatry]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 119:131-135. [PMID: 31626230 DOI: 10.17116/jnevro2019119091131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
The review is devoted to the analysis of the current state of pharmacogenetic research and their use in psychiatric practice. The main genes responsible for the pharmacodynamics and pharmacokinetics of drugs used in psychiatry are listed. Foreign pharmacogenetic clinical recommendations and progress on their implementation in medical practice in various countries of Europe and the USA are analyzed. The need to create Russian clinical guidelines on pharmacogenomics to improve the effectiveness of patient care and to implement a personalized approach to therapy is discussed.
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Affiliation(s)
- G P Kostyuk
- Alekseev Psychiatric Clinical Hospital #1, Moscow, Russia
| | - N V Zakharova
- Alekseev Psychiatric Clinical Hospital #1, Moscow, Russia
| | - A M Reznik
- Medical Institute of Ongoing Education of 'Moscow National University of Food Production', Moscow, Russia
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25
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Nguyen KA, Patel H, Haggstrom DA, Zillich AJ, Imperiale TF, Russ AL. Utilizing a user-centered approach to develop and assess pharmacogenomic clinical decision support for thiopurine methyltransferase. BMC Med Inform Decis Mak 2019; 19:194. [PMID: 31623616 PMCID: PMC6798472 DOI: 10.1186/s12911-019-0919-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 09/20/2019] [Indexed: 11/10/2022] Open
Abstract
Background A pharmacogenomic clinical decision support tool (PGx-CDS) for thiopurine medications can help physicians incorporate pharmacogenomic results into prescribing decisions by providing up-to-date, real-time decision support. However, the PGx-CDS user interface may introduce errors and promote alert fatigue. The objective of this study was to develop and evaluate a prototype of a PGx-CDS user interface for thiopurine medications with user-centered design methods. Methods This study had two phases: In phase I, we conducted qualitative interviews to assess providers’ information needs. Interview transcripts were analyzed through a combination of inductive and deductive qualitative analysis to develop design requirements for a PGx-CDS user interface. Using these requirements, we developed a user interface prototype and evaluated its usability (phase II). Results In total, 14 providers participated: 10 were interviewed in phase I, and seven providers completed usability testing in phase II (3 providers participated in both phases). Most (90%) participants were interested in PGx-CDS systems to help improve medication efficacy and patient safety. Interviews yielded 11 themes sorted into two main categories: 1) health care providers’ views on PGx-CDS and 2) important design features for PGx-CDS. We organized these findings into guidance for PGx-CDS content and display. Usability testing of the PGx-CDS prototype showed high provider satisfaction. Conclusion This is one of the first studies to utilize a user-centered design approach to develop and assess a PGx-CDS interface prototype for Thiopurine Methyltransferase (TPMT). This study provides guidance for the development of a PGx-CDS, and particularly for biomarkers such as TPMT.
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Affiliation(s)
- Khoa A Nguyen
- Department of Pharmacotherapy and Translational Research, University of Florida, College of Pharmacy, 1225 Center Drive, Gainesville, FL, 32610, USA. .,Center for Health Services Research, Regenstrief Institute Inc., 1101 W 10th St, Indianapolis, IN, USA. .,Center for Health Information and Communication, Department of Veterans Affairs (VA), Veterans Health Administration, Health Services Research and Development Service (CIN 13-416), Richard L. Roudebush VA Medical Center, 1481 W 10th St, Indianapolis, IN, 46202, USA. .,Department of Pharmacy Practice, College of Pharmacy, Purdue University, 640 Eskenazi Avenue, Indianapolis, IN, USA.
| | - Himalaya Patel
- Center for Health Information and Communication, Department of Veterans Affairs (VA), Veterans Health Administration, Health Services Research and Development Service (CIN 13-416), Richard L. Roudebush VA Medical Center, 1481 W 10th St, Indianapolis, IN, 46202, USA
| | - David A Haggstrom
- Center for Health Services Research, Regenstrief Institute Inc., 1101 W 10th St, Indianapolis, IN, USA.,Center for Health Information and Communication, Department of Veterans Affairs (VA), Veterans Health Administration, Health Services Research and Development Service (CIN 13-416), Richard L. Roudebush VA Medical Center, 1481 W 10th St, Indianapolis, IN, 46202, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alan J Zillich
- Department of Pharmacy Practice, College of Pharmacy, Purdue University, 640 Eskenazi Avenue, Indianapolis, IN, USA
| | - Thomas F Imperiale
- Center for Health Services Research, Regenstrief Institute Inc., 1101 W 10th St, Indianapolis, IN, USA.,Center for Health Information and Communication, Department of Veterans Affairs (VA), Veterans Health Administration, Health Services Research and Development Service (CIN 13-416), Richard L. Roudebush VA Medical Center, 1481 W 10th St, Indianapolis, IN, 46202, USA.,Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alissa L Russ
- Center for Health Information and Communication, Department of Veterans Affairs (VA), Veterans Health Administration, Health Services Research and Development Service (CIN 13-416), Richard L. Roudebush VA Medical Center, 1481 W 10th St, Indianapolis, IN, 46202, USA.,Department of Pharmacy Practice, College of Pharmacy, Purdue University, 640 Eskenazi Avenue, Indianapolis, IN, USA
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26
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Krebs K, Milani L. Translating pharmacogenomics into clinical decisions: do not let the perfect be the enemy of the good. Hum Genomics 2019; 13:39. [PMID: 31455423 PMCID: PMC6712791 DOI: 10.1186/s40246-019-0229-z] [Citation(s) in RCA: 95] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Accepted: 07/31/2019] [Indexed: 12/14/2022] Open
Abstract
The field of pharmacogenomics (PGx) is gradually shifting from the reactive testing of single genes toward the proactive testing of multiple genes to improve treatment outcomes, reduce adverse events, and decrease the burden of unnecessary costs for healthcare systems. Despite the progress in the field of pharmacogenomics, its implementation into routine care has been slow due to several barriers. However, in recent years, the number of studies on the implementation of PGx has increased, all providing a wealth of knowledge on different solutions for overcoming the obstacles that have been emphasized over the past years. This review focuses on some of the challenges faced by these initiatives, the solutions and different approaches for testing that they suggest, and the evidence that they provide regarding the benefits of preemptive PGx testing.
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Affiliation(s)
- Kristi Krebs
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
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27
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Primary Care Physicians' Knowledge, Attitudes, and Experience with Personal Genetic Testing. J Pers Med 2019; 9:jpm9020029. [PMID: 31137623 PMCID: PMC6617198 DOI: 10.3390/jpm9020029] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 05/21/2019] [Accepted: 05/22/2019] [Indexed: 02/07/2023] Open
Abstract
Primary care providers (PCPs) will play an important role in precision medicine. However, their lack of training and knowledge about genetics and genomics may limit their ability to advise patients or interpret or utilize test results. We evaluated PCPs’ awareness of the role of genetics/genomics in health, knowledge about key concepts in genomic medicine, perception/attitudes towards direct-to-consumer (DTC) genetic testing, and their level of confidence/comfort in discussing testing with patients prior to and after undergoing DTC testing through the 23andMe Health + Ancestry Service. A total of 130 PCPs completed the study. Sixty-three percent were board-certified in family practice, 32% graduated between 1991 and 2000, and 88% had heard of 23andMe prior to the study. Seventy-two percent decided to participate in the study to gain a better understanding about testing. At baseline, 23% of respondents indicated comfort discussing genetics as a risk factor for common diseases, increasing to 59% after undergoing personal genetic testing (PGT) (p < 0.01). In summary, we find that undergoing PGT augments physicians’ confidence, comfort, and interest in DTC testing.
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28
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FARMAPRICE: A Pharmacogenetic Clinical Decision Support System for Precise and Cost-Effective Therapy. Genes (Basel) 2019; 10:genes10040276. [PMID: 30987397 PMCID: PMC6523070 DOI: 10.3390/genes10040276] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Revised: 03/26/2019] [Accepted: 04/01/2019] [Indexed: 01/02/2023] Open
Abstract
Pharmacogenetic (PGx) guidelines for the precise dosing and selection of drugs remain poorly implemented in current clinical practice. Among the barriers to the implementation process is the lack of clinical decision support system (CDSS) tools to aid health providers in managing PGx information in the clinical context. The present study aimed to describe the first Italian endeavor to develop a PGx CDSS, called FARMAPRICE. FARMAPRICE prototype was conceived for integration of patient molecular data into the clinical prescription process in the Italian Centro di Riferimento Oncologico (CRO)-Aviano Hospital. It was developed through a coordinated partnership between two high-tech companies active in the computerization of the Italian healthcare system. Introducing FARMAPRICE into the clinical setting can aid physicians in prescribing the most efficacious and cost-effective pharmacological therapy available.
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29
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Romero Lagunes ML, Vera Badillo FE. Design and Implementing Pharmacogenomics Study in Cancer. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2019; 1168:43-77. [DOI: 10.1007/978-3-030-24100-1_4] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/04/2022]
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30
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Vassy JL, Chun S, Advani S, Ludin SA, Smith JG, Alligood EC. Impact of SLCO1B1 Pharmacogenetic Testing on Patient and Healthcare Outcomes: A Systematic Review. Clin Pharmacol Ther 2018; 106:360-373. [PMID: 30137643 DOI: 10.1002/cpt.1223] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Accepted: 08/14/2018] [Indexed: 12/22/2022]
Abstract
Demonstrated improvements in patient outcomes will facilitate the clinical implementation of pharmacogenetic testing. Using the association between solute carrier organic anion transporter family member 1B1 (SLCO1B1) and statin-associated muscle symptoms (SAMSs) as a model, we conducted a systematic review of patient outcomes after delivery of SLCO1B1 results. Using PubMed and Embase searches through December 19, 2017, we identified 37 eligible records reporting preliminary or final outcomes, including six studies delivering only SLCO1B1 results and five large healthcare system-based implementation projects of multipharmacogene panels. Two small trials have demonstrated at least short-term improvements in low-density lipoprotein cholesterol after SLCO1B1 testing among previously statin intolerant patients. Evidence from large implementation projects suggests that SLCO1B1 results may change prescribing patterns for some high-risk patients. No study has reported improvements in SAMSs or cardiovascular events or tracked the economic outcomes of SLCO1B1 testing. Ongoing studies should collect and report outcomes relevant to pharmacogenetics stakeholders.
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Affiliation(s)
- Jason L Vassy
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA.,Division of General Internal Medicine and Primary Care, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Sojeong Chun
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA.,Massachusetts College of Pharmacy and Health Sciences University, Boston, Massachusetts, USA
| | - Sanjay Advani
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Sophie A Ludin
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA.,Cornell University, Ithaca, New York, USA
| | - Jason G Smith
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Elaine C Alligood
- Veterans Affairs (VA) VA Boston Healthcare System, Boston, Massachusetts, 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] [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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Prokosch HU, Acker T, Bernarding J, Binder H, Boeker M, Boerries M, Daumke P, Ganslandt T, Hesser J, Höning G, Neumaier M, Marquardt K, Renz H, Rothkötter HJ, Schade-Brittinger C, Schmücker P, Schüttler J, Sedlmayr M, Serve H, Sohrabi K, Storf H. MIRACUM: Medical Informatics in Research and Care in University Medicine. Methods Inf Med 2018; 57:e82-e91. [PMID: 30016814 PMCID: PMC6178200 DOI: 10.3414/me17-02-0025] [Citation(s) in RCA: 57] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2017] [Accepted: 04/13/2018] [Indexed: 01/05/2023]
Abstract
INTRODUCTION This article is part of the Focus Theme of Methods of Information in Medicine on the German Medical Informatics Initiative. Similar to other large international data sharing networks (e.g. OHDSI, PCORnet, eMerge, RD-Connect) MIRACUM is a consortium of academic and hospital partners as well as one industrial partner in eight German cities which have joined forces to create interoperable data integration centres (DIC) and make data within those DIC available for innovative new IT solutions in patient care and medical research. OBJECTIVES Sharing data shall be supported by common interoperable tools and services, in order to leverage the power of such data for biomedical discovery and moving towards a learning health system. This paper aims at illustrating the major building blocks and concepts which MIRACUM will apply to achieve this goal. GOVERNANCE AND POLICIES Besides establishing an efficient governance structure within the MIRACUM consortium (based on the steering board, a central administrative office, the general MIRACUM assembly, six working groups and the international scientific advisory board), defining DIC governance rules and data sharing policies, as well as establishing (at each MIRACUM DIC site, but also for MIRACUM in total) use and access committees are major building blocks for the success of such an endeavor. ARCHITECTURAL FRAMEWORK AND METHODOLOGY The MIRACUM DIC architecture builds on a comprehensive ecosystem of reusable open source tools (MIRACOLIX), which are linkable and interoperable amongst each other, but also with the existing software environment of the MIRACUM hospitals. Efficient data protection measures, considering patient consent, data harmonization and a MIRACUM metadata repository as well as a common data model are major pillars of this framework. The methodological approach for shared data usage relies on a federated querying and analysis concept. USE CASES MIRACUM aims at proving the value of their DIC with three use cases: IT support for patient recruitment into clinical trials, the development and routine care implementation of a clinico-molecular predictive knowledge tool, and molecular-guided therapy recommendations in molecular tumor boards. RESULTS Based on the MIRACUM DIC release in the nine months conceptual phase first large scale analysis for stroke and colorectal cancer cohorts have been pursued. DISCUSSION Beyond all technological challenges successfully applying the MIRACUM tools for the enrichment of our knowledge about diagnostic and therapeutic concepts, thus supporting the concept of a Learning Health System will be crucial for the acceptance and sustainability in the medical community and the MIRACUM university hospitals.
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Affiliation(s)
- Hans-Ulrich Prokosch
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Till Acker
- Institute of Neuropathology, Justus-Liebig-University Giessen, Giessen, Germany
| | - Johannes Bernarding
- Chair of Medical Informatics, Institute for Biometry and Medical Informatics, Otto-von-Guericke-University Magdeburg, Magdeburg, Germany
| | - Harald Binder
- Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center – University of Freiburg, Freiburg, Germany
| | - Martin Boeker
- Institute of Medical Biometry and Statistics, Medical Faculty and Medical Center – University of Freiburg, Freiburg, Germany
| | - Melanie Boerries
- Institute of Molecular Medicine and Cell Research and Comprehensive Cancer Center Freiburg (CCCF), University Medical Center, Faculty of Medicine, University of Freiburg; German Cancer Research Center (DKFZ), Heidelberg and German Cancer Consortium (DKTK) partner site Freiburg, Freiburg, Germany
| | | | - Thomas Ganslandt
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
- Department of Biomedical Informatics, University Medicine Mannheim, Ruprecht-Karls-University Heidelberg, Mannheim, Germany
| | - Jürgen Hesser
- Experimental Radiation Oncology Department, University Medical Center Mannheim, Central Institute for Scientific Computing (IWR), Central Institute for Computer Engineering (ZITI), Heidelberg University, Mannheim, Germany
| | - Gunther Höning
- Department of Information Technology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Michael Neumaier
- Chair for Clinical Chemistry, Medical Faculty Mannheim of Heidelberg University, Mannheim, Germany
| | - Kurt Marquardt
- University Hospital of Giessen and Marburg, Giessen, Germany
| | - Harald Renz
- Chair for Clinical Chemistry, Philipps University Marburg, Medical Director of the University Clinic Marburg, Marburg, Germany
| | - Hermann-Josef Rothkötter
- Institute of Anatomy, Otto-von-Guericke-University Magdeburg, Dean of the Medical Faculty, Magdeburg, Germany
| | - Carmen Schade-Brittinger
- Chair of the Coordinating Centre for Clinical Trials, Philipps University Marburg, Marburg, Germany
| | - Paul Schmücker
- University of Applied Sciences Mannheim, Institute for Medical Informatics, Mannheim, Germany
| | - Jürgen Schüttler
- Department of Anesthesiology, University of Erlangen-Nürnberg, Dean of the Medical Faculty, Erlangen, Germany
| | - Martin Sedlmayr
- Chair of Medical Informatics, Department of Medical Informatics, Biometrics and Epidemiology, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
- Institute of Medical Informatics and Biometrics, Carl Gustav Carus Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
| | - Hubert Serve
- Department of Hematology and Oncology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
| | - Keywan Sohrabi
- Faculty of Health Sciences, University of Applied Sciences – THM, Giessen, Germany
| | - Holger Storf
- Medical Informatics Group, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany
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Baskys A. Application of pharmacogenetics in clinical practice: problems and solutions. J Neural Transm (Vienna) 2018; 126:109-113. [PMID: 29922908 DOI: 10.1007/s00702-018-1894-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Accepted: 06/12/2018] [Indexed: 12/16/2022]
Abstract
This paper discusses difficulties of pharmacogenomic data integration into clinical practice. It emphasizes the need for developing simple and easy to use bioinformatics tools to help prescribers to rapidly access and use genetic data in clinical decision-making at the point of encounter.
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Affiliation(s)
- Andrius Baskys
- Graduate College of Biomedical Sciences, Western University of Health Sciences, Pomona, CA, USA. .,Memory Disorders Clinic, Riverside Psychiatric Medical Group, Riverside, CA, USA. .,World Association of Genomic Medicine, A Coruña, Spain.
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Butler MG. Pharmacogenetics and Psychiatric Care: A Review and Commentary. JOURNAL OF MENTAL HEALTH & CLINICAL PSYCHOLOGY 2018; 2:17-24. [PMID: 30556062 PMCID: PMC6291002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Grants] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Affiliation(s)
- Merlin G. Butler
- Departments of Psychiatry & Behavioral Sciences and Pediatrics, University of Kansas Medical Center, Kansas City, Kansas, USA
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Haga SB. Integrating pharmacogenetic testing into primary care. EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2017; 2:327-336. [PMID: 31853504 DOI: 10.1080/23808993.2017.1398046] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction Pharmacogenetic (PGx) testing has greatly expanded due to enhanced understanding of the role of genes in drug response and advances in DNA-based testing technology development. As many primary care visits result in a prescription, the use of PGx testing may be particularly beneficial in this setting. However, integration of PGx testing may be limited as no uniform approach to delivery of tests has been established and providers are ill-prepared to integrate PGx testing into routine care. Areas covered In this paper, the readiness of primary care practitioners are reviewed as well as strategies to address these barriers based on published research and ongoing activities on education and implementation of PGx testing. Expert Commentary Widespread integration of PGx testing will warrant continued education and point-of-care decisional support. Primary care providers may also benefit from consultation services or team-based care with laboratory medicine specialists, pharmacists, and genetic counselors.
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Affiliation(s)
- Susanne B Haga
- Center for Applied Genomics & Precision Medicine, Duke University School of Medicine, 304 Research Drive, Durham, NC 27708, USA,
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