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Shue SA, Rowe E, Bell LA, Damush T, DeLong A, Gowan T, Skaar T, Haggstrom D. Pharmacogenomics implementation across multiple clinic settings: a qualitative evaluation. Pharmacogenomics 2023; 24:881-893. [PMID: 37975236 DOI: 10.2217/pgs-2023-0179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2023] Open
Abstract
Aim: To advance clinical adoption and implementation of pharmacogenomics (PGx) testing, barriers and facilitators to these efforts must be understood. This study identified and examined barriers and facilitators to active implementation of a PGx program across multiple clinic settings in an academic healthcare system. Materials & methods: 28 contributors to the PGx implementation (e.g., clinical providers, informatics specialists) completed an interview to elicit their perceptions of the implementation. Results: Qualitative analysis identified several barriers and facilitators that spanned different stages of the implementation process. Specifically, unclear test payment mechanisms, decision support tool development, rigid workflows and provider education were noted as barriers to the PGx implementation. A multidisciplinary implementation team and leadership support emerged as key facilitators. Furthermore, participants also suggested strategies to overcome or maintain these factors. Conclusion: Assessing real-world implementation perceptions and suggested strategies from a range of implementation contributors facilitates a more comprehensive framework and best-practice guidelines for PGx implementation.
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Affiliation(s)
- Sarah A Shue
- VA HSR&D Center for Health Information & Communication, Roudebush VA Medical Center, Indianapolis, IN 46202, USA
| | - Elizabeth Rowe
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Lauren A Bell
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Teresa Damush
- VA HSR&D Center for Health Information & Communication, Roudebush VA Medical Center, Indianapolis, IN 46202, USA
- Division of General Internal Medicine & Geriatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Alexis DeLong
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Tayler Gowan
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
| | - Todd Skaar
- Division of Clinical Pharmacology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - David Haggstrom
- VA HSR&D Center for Health Information & Communication, Roudebush VA Medical Center, Indianapolis, IN 46202, USA
- Division of General Internal Medicine & Geriatrics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Center for Health Services Research, Regenstrief Institute, Indianapolis, IN 46202, USA
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2
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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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Digital Future of Emergency Medical Services: Envisioning and Usability of Electronic Patient Care Report System. ADVANCES IN HUMAN-COMPUTER INTERACTION 2022. [DOI: 10.1155/2022/6012241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Despite the efforts of emerging technologies in the healthcare system, there is still a slower rate of acceleration in prehospital settings compared with the hospitals in digital transformation adaptation. The acknowledgment that digital transformation is significant to healthcare is reflected in planning for the future of digital healthcare. Thus, this study aimed to measure the usability of the electronic patient care report (ePCR) system among emergency medical services (EMS) staff who work in prehospital settings. A descriptive cross-sectional correlation study was used. Two hundred fifty EMS staff who are working in the prehospital setting at Saudi Red Crescent Authority in the Kingdom of Saudi Arabia were surveyed, and the response rate was 79.2% (198). An adapted tool of the Computer System Usability Questionnaire survey was used to collect data. The data were coded numerically and subjected to descriptive and inferential statistical analysis including Pearson’s correlation coefficient using the statistical software (SPSS 21). The majority of the participants rate their ePCR system as “useable” at a high level with a score of 3.41 (SD = 1.021). The overall mean of the ePCR system’s three subscales: system usefulness, information quality, interface quality, and overall satisfaction were 3.39 (SD = 1.152), 3.30 (SD = 1.052), 3.57 (SD = 1.064), and 3.37 (SD = 1.239), respectively. The least liked aspect of ePCR system software was information quality 81 (40.9%). Furthermore, there was a significant correlation between the age of EMS staff and the usability of the ePCR system (r = −0.150
,
). The results suggest that healthcare institutions’ policy and decision-makers pay close attention to performing standardized training for the staff on their ePCR system before going to the field to increase efficiency and productivity. Furthermore, the users in this study identified other system features that, if included, could have enhanced usability, and improved functions and capabilities of the design to meet the EMS staff’s expectations.
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4
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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: 23] [Impact Index Per Article: 11.5] [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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5
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O'Shea J, Ledwidge M, Gallagher J, Keenan C, Ryan C. Pharmacogenetic interventions to improve outcomes in patients with multimorbidity or prescribed polypharmacy: a systematic review. THE PHARMACOGENOMICS JOURNAL 2022; 22:89-99. [PMID: 35194175 PMCID: PMC8975737 DOI: 10.1038/s41397-021-00260-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Revised: 10/19/2021] [Accepted: 10/21/2021] [Indexed: 01/11/2023]
Abstract
Conventional medicines optimisation interventions in people with multimorbidity and polypharmacy are complex and yet limited; a more holistic and integrated approach to healthcare delivery is required. Pharmacogenetics has potential as a component of medicines optimisation. Studies involving multi-medicine pharmacogenetics in adults with multimorbidity or polypharmacy, reporting on outcomes derived from relevant core outcome sets, were included in this systematic review. Narrative synthesis was undertaken to summarise the data; meta-analysis was inappropriate due to study heterogeneity. Fifteen studies of diverse design and variable quality were included. A small, randomised study involving pharmacist-led medicines optimisation, including pharmacogenetics, suggests this approach could have significant benefits for patients and health systems. However, due to study design heterogeneity and the quality of the included studies, it is difficult to draw generalisable conclusions. Further pragmatic, robust pharmacogenetics studies in diverse, real-world patient populations, are required to establish the benefit of multi-medicine pharmacogenetic screening on patient outcomes.
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Affiliation(s)
- Joseph O'Shea
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
| | - Mark Ledwidge
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | - Joseph Gallagher
- School of Medicine and Medical Science, University College Dublin, Dublin, Ireland
| | | | - Cristín Ryan
- School of Pharmacy and Pharmaceutical Sciences, Trinity College Dublin, Dublin, Ireland.
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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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7
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Wake DT, Smith DM, Kazi S, Dunnenberger HM. Pharmacogenomic Clinical Decision Support: A Review, How-to Guide, and Future Vision. Clin Pharmacol Ther 2021; 112:44-57. [PMID: 34365648 PMCID: PMC9291515 DOI: 10.1002/cpt.2387] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Accepted: 07/28/2021] [Indexed: 02/06/2023]
Abstract
Clinical decision support (CDS) is an essential part of any pharmacogenomics (PGx) implementation. Increasingly, institutions have implemented CDS tools in the clinical setting to bring PGx data into patient care, and several have published their experiences with these implementations. However, barriers remain that limit the ability of some programs to create CDS tools to fit their PGx needs. Therefore, the purpose of this review is to summarize the types, functions, and limitations of PGx CDS currently in practice. Then, we provide an approachable step‐by‐step how‐to guide with a case example to help implementers bring PGx to the front lines of care regardless of their setting. Particular focus is paid to the five “rights” of CDS as a core around designing PGx CDS tools. Finally, we conclude with a discussion of opportunities and areas of growth for PGx CDS.
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Affiliation(s)
- Dyson T Wake
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
| | - D Max Smith
- MedStar Health, Columbia, Maryland, USA.,Georgetown University Medical Center, Washington, DC, USA
| | - Sadaf Kazi
- Georgetown University Medical Center, Washington, DC, USA.,National Center for Human Factors in Healthcare, MedStar Health Research Institute Washington, Washington, DC, USA
| | - Henry M Dunnenberger
- Mark R. Neaman Center for Personalized Medicine, NorthShore University HealthSystem, Evanston, Illinois, USA
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8
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Keeling NJ, Dunn TJ, Bentley JP, Ramachandran S, Hoffman JM, Rosenthal M. Approaches to assessing the provider experience with clinical pharmacogenomic information: a scoping review. Genet Med 2021; 23:1589-1603. [PMID: 33927377 DOI: 10.1038/s41436-021-01186-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2020] [Accepted: 04/11/2021] [Indexed: 11/09/2022] Open
Abstract
PURPOSE Barriers to the implementation of pharmacogenomics in clinical practice have been thoroughly discussed over the past decade. METHODS The objective of this scoping review was to characterize the peer-reviewed literature surrounding the experiences and actions of prescribers, pharmacists, or genetic counselors when using pharmacogenomic information in real-world or hypothetical research settings. RESULTS A total of 33 studies were included in the scoping review. The majority of studies were conducted in the United States (70%), used quantitative or mixed methods (79%) with physician or pharmacist respondents (100%). The qualitative content analysis revealed five major methodological approaches: hypothetical clinical case scenarios, real-world studies evaluating prescriber response to recommendations or alerts, cross-sectional quantitative surveys, cross-sectional qualitative surveys/interviews, and a quasi-experimental real-world study. CONCLUSION The findings of this scoping review can guide further research on the factors needed to successfully integrate pharmacogenomics into clinical care.
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Affiliation(s)
- Nicholas J Keeling
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - Tyler J Dunn
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA.
| | - John P Bentley
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - Sujith Ramachandran
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
| | - James M Hoffman
- Department of Pharmaceutical Sciences and Office of Quality and Patient Care, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Meagen Rosenthal
- Department of Pharmacy Administration, University of Mississippi School of Pharmacy, University, MS, USA
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9
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Farzandipour M, Sadeqi Jabali M, Nickfarjam AM, Tadayon H. Usability evaluation of selected picture archiving and communication systems at the national level: Analysis of users' viewpoints. Int J Med Inform 2020; 147:104372. [PMID: 33421687 DOI: 10.1016/j.ijmedinf.2020.104372] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Revised: 11/02/2020] [Accepted: 12/27/2020] [Indexed: 10/22/2022]
Abstract
BACKGROUND AND OBJECTIVES Picture Archiving and Communication System (PACS) can be considered as one of the most important information systems used in healthcare facilities and its usability problems can lead to delays in the acceptance of information systems, increased medical errors and also user dissatisfaction. The primary purpose of this study was to evaluate the usability of PACS from the perspective of its main users. METHODS This study used a combination of qualitative and quantitative methods and was carried out in 2019 where the research community consisted of PACS in five selected companies in Iran. The statistical sample included 200 individuals using the PACS in several hospitals across the country. Moreover, the sample was selected using the multistage random method. The data were then collected using the standard Computer System Usability Questionnaire (CSUQ) consisting of 5 sections and 19 items. Finally, the data were analyzed by SPSS software, version 18 using both descriptive and inferential methods. Content analysis was done for the qualitative data sets. RESULTS It was indicated that ease of use, as a category, was not significantly different from the perspective of various PACS users. However, the ANOVA test revealed that there were significant differences in terms of information quality, user interface quality, overall user satisfaction and usability of PACS from the users' perspectives. Furthermore, content analysis of users' comments showed that speeding up the image processing and frequent system failures were amongst the most positive and negative aspects of the PACS, respectively. CONCLUSIONS According to the perspective of the users of the investigated PACS in Iran, the usability of these PACS had a favorable status regarding ease of use while provided lower information quality. Generally, based on the users' viewpoints, the PACS from Company B were the most usable while the PACS provided by Company D were the least usable. It is suggested that the information quality and user interface of systems be improved by using appropriate analysis and needs assessment of the end users.
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Affiliation(s)
- Mehrdad Farzandipour
- Research Centre for Health Information Management, Kashan University of Medical Sciences, Kashan, Iran; Department of Health Information Management and Technology, Kashan University of Medical Sciences, Kashan, Iran
| | - Monireh Sadeqi Jabali
- Department of Health Information Management and Technology, Kashan University of Medical Sciences, Kashan, Iran
| | - Ali Mohammad Nickfarjam
- Research Centre for Health Information Management, Kashan University of Medical Sciences, Kashan, Iran
| | - Hamidreza Tadayon
- Department of Health Information Management and Technology, Kashan University of Medical Sciences, Kashan, Iran; Department of Health Information Technology, Neyshabur University of Medical Sciences, Neyshabur, Iran.
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10
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Yoon DY, Lee S, Ban MS, Jang IJ, Lee S. Pharmacogenomic information from CPIC and DPWG guidelines and its application on drug labels. Transl Clin Pharmacol 2020; 28:189-198. [PMID: 33425802 PMCID: PMC7781807 DOI: 10.12793/tcp.2020.28.e18] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Revised: 10/06/2020] [Accepted: 12/02/2020] [Indexed: 12/15/2022] Open
Abstract
There are several hurdles to overcome before implementing pharmacogenomics (PGx) in precision medicine. One of the hurdles is unawareness of PGx by clinicians due to insufficient pharmacogenomic information on drug labels. Therefore, it might be important to implement PGx that reflects pharmacogenomic information on drug labels, standard of prescription for clinicians. This study aimed to evaluate the level at which PGx was being used in clinical practice by comparing the Clinical Pharmacogenetics Implementation Consortium and Dutch Pharmacogenetics Working Group guidelines and drug labels of the US Food and Drug Administration (FDA) and the Korea Ministry of Food and Drug Safety (MFDS). Two PGx guidelines and drugs labels were scrutinized, and the concordance of the pharmacogenomic information between guidelines and drug labels was confirmed. The concordance of the label between FDA and MFDS was analyzed. In FDA labels, the number of concordant drug with guidelines was 24, while 13 drugs were concordant with MFDS labels. The number of drugs categorized as contraindication, change dose, and biomarker testing required was 7, 12 and 12 for the FDA and 8, 5 and 4 for the MFDS, respectively. The pharmacogenomic information of 9 drugs approved by both FDA and MFDS was identical. In conclusion, pharmacogenomic information on clinical implementation guidelines was limited on both FDA and MFDS labels because of various reasons including the characteristics of the guidelines and the drug labels. Therefore, more effort from pharmaceutical companies, academia and regulatory affairs needs to be made to implement pharmacogenomic information on drug labels.
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Affiliation(s)
- Deok Yong Yoon
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea
| | - Soyoung Lee
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea
| | - Mu Seong Ban
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea
| | - In-Jin Jang
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea
| | - SeungHwan Lee
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea
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11
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Carr DF, Turner RM, Pirmohamed M. Pharmacogenomics of anticancer drugs: Personalising the choice and dose to manage drug response. Br J Clin Pharmacol 2020; 87:237-255. [PMID: 32501544 DOI: 10.1111/bcp.14407] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 05/11/2020] [Accepted: 05/22/2020] [Indexed: 12/13/2022] Open
Abstract
The field of pharmacogenomics has made great strides in oncology over the last 20 years and indeed a significant number of pre-emptive genetic tests are now routinely undertaken prior to anticancer drug administration. Many of these gene-drug interactions are the fruits of candidate gene and genome-wide association studies, which have largely focused on common genetic variants (allele frequency>1%). Examples where there is clinical utility include genotyping or phenotyping for G6PD to prevent rasburicase-induced RBC haemolysis, and TPMT to prevent thiopurine-induced bone marrow suppression. Other associations such as CYP2D6 status in determining the efficacy of tamoxifen are more controversial because of contradictory evidence from different sources, which has led to variability in the implementation of testing. As genomic technology becomes ever cheaper and more accessible, we must look to the additional data our genome can provide to explain interindividual variability in anticancer drug response. Clearly genes do not act on their own and it is therefore important to investigate genetic factors in conjunction with clinical factors, interacting concomitant drug therapies and other factors such as the microbiome, which can all affect drug disposition. Taking account of all of these factors, in conjunction with the somatic genome, is more likely to provide better predictive accuracy in determining anticancer drug response, both efficacy and safety. This review summarises the existing knowledge related to the pharmacogenomics of anticancer drugs and discusses areas of opportunity for further advances in personalisation of therapy in order to improve both drug safety and efficacy.
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Affiliation(s)
- Daniel F Carr
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Richard M Turner
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
| | - Munir Pirmohamed
- Department of Molecular and Clinical Pharmacology, University of Liverpool, Liverpool, UK
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12
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Mukerjee G, Huston A, Kabakchiev B, Piquette-Miller M, van Schaik R, Dorfman R. User considerations in assessing pharmacogenomic tests and their clinical support tools. NPJ Genom Med 2018; 3:26. [PMID: 30210808 PMCID: PMC6133969 DOI: 10.1038/s41525-018-0065-4] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2018] [Revised: 08/10/2018] [Accepted: 08/13/2018] [Indexed: 12/18/2022] Open
Abstract
Pharmacogenomic (PGx) testing is gaining recognition from physicians, pharmacists and patients as a tool for evidence-based medication management. However, seemingly similar PGx testing panels (and PGx-based decision support tools) can diverge in their technological specifications, as well as the genetic factors that determine test specificity and sensitivity, and hence offer different values for users. Reluctance to embrace PGx testing is often the result of unfamiliarity with PGx technology, a lack of knowledge about the availability of curated guidelines/evidence for drug dosing recommendations, and an absence of wide-spread institutional implementation efforts and educational support. Demystifying an often confusing and variable PGx marketplace can lead to greater acceptance of PGx as a standard-of-care practice that improves drug outcomes and provides a lifetime value for patients. Here, we highlight the key underlying factors of a PGx test that should be considered, and discuss the current progress of PGx implementation.
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Affiliation(s)
| | - Andrea Huston
- GeneYouIn Inc., 156 Front St. W., Toronto, ON Canada
| | - Boyko Kabakchiev
- GeneYouIn Inc., 156 Front St. W., Toronto, ON Canada.,2Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, ON Canada
| | | | - Ron van Schaik
- 4International Expert Center Pharmacogenetics, Department of Clinical Chemistry, Erasmus University Medical Center, Rotterdam, The Netherlands
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13
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Mills R, Haga SB. Qualitative user evaluation of a revised pharmacogenetic educational toolkit. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2018; 11:139-146. [PMID: 30214267 PMCID: PMC6128278 DOI: 10.2147/pgpm.s169648] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
Introduction Pharmacogenetic (PGx) testing is a leading application for personalized and precision medicine; however, there are barriers, including limited provider and patient understanding, which affect its uptake. There is a need for tools that can enhance the patient and provider experience with testing and promoting the shared and informed decision-making. Materials and methods In this study, we sought to gather additional feedback on a PGx toolkit comprised of four educational tools that had been previously evaluated through an online survey by pharmacists. Specifically, we conducted semi-structured interviews with pharmacists and members of the public regarding their understanding and utility of the toolkit and its individual components. Results Participants found three of the four toolkit components, a test information sheet, flipbook, and results sheet, to be useful and important. The fourth component, results card, was viewed less favorably. Participants differed in their preference for medical jargon and detailed results nomenclature (namely star * alleles). Conclusion User input during the development of educational materials is essential for optimizing utilization, effectiveness, and comprehension.
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Affiliation(s)
- Rachel Mills
- Duke Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Durham, NC, USA,
| | - Susanne B Haga
- Duke Center for Applied Genomics and Precision Medicine, Duke University Medical Center, Durham, NC, USA,
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Blagec K, Koopmann R, Crommentuijn – van Rhenen M, Holsappel I, van der Wouden CH, Konta L, Xu H, Steinberger D, Just E, Swen JJ, Guchelaar HJ, Samwald M. Implementing pharmacogenomics decision support across seven European countries: The Ubiquitous Pharmacogenomics (U-PGx) project. J Am Med Inform Assoc 2018; 25:893-898. [PMID: 29444243 PMCID: PMC6016647 DOI: 10.1093/jamia/ocy005] [Citation(s) in RCA: 54] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 11/23/2017] [Accepted: 01/09/2018] [Indexed: 01/07/2023] Open
Abstract
Clinical pharmacogenomics (PGx) has the potential to make pharmacotherapy safer and more effective by utilizing genetic patient data for drug dosing and selection. However, widespread adoption of PGx depends on its successful integration into routine clinical care through clinical decision support tools, which is often hampered by insufficient or fragmented infrastructures. This paper describes the setup and implementation of a unique multimodal, multilingual clinical decision support intervention consisting of digital, paper-, and mobile-based tools that are deployed across implementation sites in seven European countries participating in the Ubiquitous PGx (U-PGx) project.
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Affiliation(s)
- Kathrin Blagec
- Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria
| | - Rudolf Koopmann
- bio.logis Genetic Information Management GmbH, Frankfurt am Main, Germany
| | | | - Inge Holsappel
- Medicines Information Centre; Royal Dutch Pharmacists Association (KNMP), The Hague, The Netherlands
| | | | - Lidija Konta
- bio.logis Center for Human Genetics, Frankfurt am Main, Germany
| | - Hong Xu
- Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria
| | - Daniela Steinberger
- bio.logis Genetic Information Management GmbH, Frankfurt am Main, Germany
- bio.logis Center for Human Genetics, Frankfurt am Main, Germany
- Institute for Human Genetics, Justus Liebig University, Giessen, Germany
| | - Enrico Just
- bio.logis Genetic Information Management GmbH, Frankfurt am Main, Germany
| | - Jesse J Swen
- Deptartment of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Deptartment of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Matthias Samwald
- Section for Artificial Intelligence and Decision Support; Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna, Vienna, Austria
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15
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Bank PCD, Swen JJ, Guchelaar HJ. Implementation of Pharmacogenomics in Everyday Clinical Settings. ADVANCES IN PHARMACOLOGY (SAN DIEGO, CALIF.) 2018; 83:219-246. [PMID: 29801576 DOI: 10.1016/bs.apha.2018.04.003] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Currently, germline pharmacogenomics (PGx) is successfully implemented within certain specialties in clinical care. With the integration of PGx in pharmacotherapy multiple stakeholders are involved, which are identified in this chapter. Clinically relevant pharmacogenes with their related PGx test are discussed, along with diagnostic test criteria to guide clinicians and policy makers in PGx test selection. The chapter further reviews the similarities and the differences between the guidelines of the Dutch Pharmacogenetics Working Group and the Clinical Pharmacogenetics Implementation Consortium which both support healthcare professionals in understanding PGx test results and help guiding pharmacotherapy by providing evidence-based dosing recommendations. Finally, clinical studies which provide scientific evidence and information on cost-effectiveness supporting clinical implementation of PGx in clinical care are discussed along with the remaining barriers for adoption of PGx testing by healthcare professionals.
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Affiliation(s)
- Paul C D Bank
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Jesse J Swen
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands
| | - Henk-Jan Guchelaar
- Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center, Leiden, The Netherlands.
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16
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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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Hinderer M, Boeker M, Wagner SA, Lablans M, Newe S, Hülsemann JL, Neumaier M, Binder H, Renz H, Acker T, Prokosch HU, Sedlmayr M. Integrating clinical decision support systems for pharmacogenomic testing into clinical routine - a scoping review of designs of user-system interactions in recent system development. BMC Med Inform Decis Mak 2017; 17:81. [PMID: 28587608 PMCID: PMC5461630 DOI: 10.1186/s12911-017-0480-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2016] [Accepted: 05/30/2017] [Indexed: 01/05/2023] Open
Abstract
Background Pharmacogenomic clinical decision support systems (CDSS) have the potential to help overcome some of the barriers for translating pharmacogenomic knowledge into clinical routine. Before developing a prototype it is crucial for developers to know which pharmacogenomic CDSS features and user-system interactions have yet been developed, implemented and tested in previous pharmacogenomic CDSS efforts and if they have been successfully applied. We address this issue by providing an overview of the designs of user-system interactions of recently developed pharmacogenomic CDSS. Methods We searched PubMed for pharmacogenomic CDSS published between January 1, 2012 and November 15, 2016. Thirty-two out of 118 identified articles were summarized and included in the final analysis. We then compared the designs of user-system interactions of the 20 pharmacogenomic CDSS we had identified. Results Alerts are the most widespread tools for physician-system interactions, but need to be implemented carefully to prevent alert fatigue and avoid liabilities. Pharmacogenomic test results and override reasons stored in the local EHR might help communicate pharmacogenomic information to other internal care providers. Integrating patients into user-system interactions through patient letters and online portals might be crucial for transferring pharmacogenomic data to external health care providers. Inbox messages inform physicians about new pharmacogenomic test results and enable them to request pharmacogenomic consultations. Search engines enable physicians to compare medical treatment options based on a patient’s genotype. Conclusions Within the last 5 years, several pharmacogenomic CDSS have been developed. However, most of the included articles are solely describing prototypes of pharmacogenomic CDSS rather than evaluating them. To support the development of prototypes further evaluation efforts will be necessary. In the future, pharmacogenomic CDSS will likely include prediction models to identify patients who are suitable for preemptive genotyping. Electronic supplementary material The online version of this article (doi:10.1186/s12911-017-0480-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Marc Hinderer
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany.
| | - Martin Boeker
- Medical Informatics, Institute of Medical Biometry and Statistics, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Sebastian A Wagner
- Department of Medicine, Hematology/Oncology, Goethe University, Frankfurt, Germany
| | - Martin Lablans
- Medical Informatics in Translational Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Stephanie Newe
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany
| | | | - Michael Neumaier
- Institute for Clinical Chemistry, Medical Faculty Mannheim, Ruprecht-Karls-University Heidelberg, Mannheim, Germany
| | - Harald Binder
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Harald Renz
- University of Marburg, Institute of Laboratory Medicine, Marburg, Germany
| | - Till Acker
- Institute of Neuropathology, University of Giessen, Giessen, Germany
| | - Hans-Ulrich Prokosch
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany
| | - Martin Sedlmayr
- Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Wetterkreuz 13, 91058, Erlangen, Germany
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Simoons M, Mulder H, Schoevers RA, Ruhé HG, van Roon EN. Availability of CYP2D6 genotyping results in general practitioner and community pharmacy medical records. Pharmacogenomics 2017; 18:843-851. [DOI: 10.2217/pgs-2017-0043] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: To investigate the availability of CYP450–2D6 (CYP2D6) genotyping results in general practitioner (GP) and/or community pharmacy records, and the influence thereof on psychotropic CYP2D6 substrate dosing. Materials & methods: Primary outcome was the percentage of patients genotyped for CYP2D6 with their genotype/phenotype registered in GP and/or pharmacy records. Secondary outcome was the number of defined daily doses of psychotropic CYP2D6 substrates prescribed after genotyping. Results: For 216 out of 1307 eligible patients, medication overviews could be obtained. Genotyping results were available at GPs for 3.1% and at pharmacies for 5.9%. The average psychotropic CYP2D6 substrate dose was not different between any non-extensive metabolizer group and extensive metabolizer group (all p ≥ 0.486). Conclusion: Valuable information for individualizing psychiatric pharmacotherapy is lost on a large scale.
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Affiliation(s)
- Mirjam Simoons
- Wilhelmina Hospital Assen, Department of Clinical Pharmacy, Assen, The Netherlands
- Department of Psychiatry, Interdisciplinary Center for Psychopathology & Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Pharmacy, Unit of Pharmacotherapy, –Epidemiology & –Economics, University of Groningen, Groningen, The Netherlands
| | - Hans Mulder
- Wilhelmina Hospital Assen, Department of Clinical Pharmacy, Assen, The Netherlands
- Psychiatric Hospital GGZ Drenthe, Assen, The Netherlands
| | - Robert A Schoevers
- Department of Psychiatry, Interdisciplinary Center for Psychopathology & Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Henricus G Ruhé
- Department of Psychiatry, Interdisciplinary Center for Psychopathology & Emotion regulation, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | - Eric N van Roon
- Department of Pharmacy, Unit of Pharmacotherapy, –Epidemiology & –Economics, University of Groningen, Groningen, The Netherlands
- Department of Clinical Pharmacy & Clinical Pharmacology, Medical Center Leeuwarden, Leeuwarden, The Netherlands
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Hinderer M, Boeker M, Wagner SA, Binder H, Ückert F, Newe S, Hülsemann JL, Neumaier M, Schade-Brittinger C, Acker T, Prokosch HU, Sedlmayr B. The experience of physicians in pharmacogenomic clinical decision support within eight German university hospitals. Pharmacogenomics 2017; 18:773-785. [PMID: 28593816 DOI: 10.2217/pgs-2017-0027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
Aim: The aim of this study was to assess the physicians’ attitude, their knowledge and their experience in pharmacogenomic clinical decision support in German hospitals. Materials & methods: We conducted an online survey to address physicians of 13 different medical specialties across eight German university hospitals. In total, 564 returned questionnaires were analyzed. Results: The remaining knowledge gap, the uncertainty of test reimbursement and the physicians’ lack of awareness of existing pharmacogenomic clinical decision support systems (CDSS) are the major barriers for implementing pharmacogenomic CDSS into German hospitals. Furthermore, pharmacogenomic CDSS are most effective in the form of real-time decision support for internists. Conclusion: Physicians in German hospitals require additional education of both genetics and pharmacogenomics. They need to be provided with access to relevant pharmacogenomic CDSS.
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Affiliation(s)
- Marc Hinderer
- Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Martin Boeker
- Faculty of Medicine & Medical Center, Institute of Medical Biometry & Statistics, University of Freiburg, Freiburg, Germany
| | - Sebastian A Wagner
- Department of Medicine, Hematology/Oncology, Goethe University, Frankfurt, Germany
| | - Harald Binder
- Institute of Medical Biostatistics, Epidemiology & Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Frank Ückert
- Department of Medical Informatics, Division of Translational Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Stephanie Newe
- Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Jan L Hülsemann
- Medical Directorate, University Hospital Magdeburg, Magdeburg, Germany
| | - Michael Neumaier
- Medical Faculty Mannheim, Institute for Clinical Chemistry, Ruprecht-Karls-University Heidelberg, Mannheim, Germany
| | | | - Till Acker
- Institute of Neuropathology, University of Giessen, Giessen, Germany
| | - Hans-Ulrich Prokosch
- Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Brita Sedlmayr
- Chair of Medical Informatics, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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van der Wouden CH, Cambon-Thomsen A, Cecchin E, Cheung KC, Dávila-Fajardo CL, Deneer VH, Dolžan V, Ingelman-Sundberg M, Jönsson S, Karlsson MO, Kriek M, Mitropoulou C, Patrinos GP, Pirmohamed M, Samwald M, Schaeffeler E, Schwab M, Steinberger D, Stingl J, Sunder-Plassmann G, Toffoli G, Turner RM, van Rhenen MH, Swen JJ, Guchelaar HJ. Implementing Pharmacogenomics in Europe: Design and Implementation Strategy of the Ubiquitous Pharmacogenomics Consortium. Clin Pharmacol Ther 2017; 101:341-358. [DOI: 10.1002/cpt.602] [Citation(s) in RCA: 186] [Impact Index Per Article: 26.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 12/12/2016] [Accepted: 12/13/2016] [Indexed: 12/14/2022]
Affiliation(s)
- CH van der Wouden
- Department of Clinical Pharmacy and Toxicology; Leiden University Medical Center; Leiden The Netherlands
| | - A Cambon-Thomsen
- UMR Inserm U1027 and Université de Toulouse III Paul Sabatier; Toulouse France
| | - E Cecchin
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico; National Cancer Institute; Aviano Italy
| | - KC Cheung
- Royal Dutch Pharmacists Association (KNMP); The Hague The Netherlands
| | - CL Dávila-Fajardo
- Department of Clinical Pharmacy, Granada University Hospital; Institute for Biomedical Research; Granada Spain
| | - VH Deneer
- Department of Clinical Pharmacy; St Antonius Hospital; Nieuwegein The Netherlands
| | - V Dolžan
- Pharmacogenetics Laboratory, Institute of Biochemistry, Faculty of Medicine; University of Ljubljana; Slovenia
| | - M Ingelman-Sundberg
- Department of Physiology and Pharmacology, Section of Pharmacogenetics; Karolinska Institutet; Stockholm Sweden
| | - S Jönsson
- Department of Pharmaceutical Biosciences; Uppsala University; Uppsala Sweden
| | - MO Karlsson
- Department of Pharmaceutical Biosciences; Uppsala University; Uppsala Sweden
| | - M Kriek
- Center for Clinical Genetics; Leiden University Medical Center; Leiden The Netherlands
| | | | - GP Patrinos
- University of Patras, School of Health Sciences, Department of Pharmacy; University Campus; Rion Patras Greece
| | - M Pirmohamed
- Department of Molecular and Clinical Pharmacology; Royal Liverpool University Hospital and University of Liverpool; Liverpool United Kingdom
| | - M Samwald
- Center for Medical Statistics, Informatics, and Intelligent Systems; Medical University of Vienna; Vienna Austria
| | - E Schaeffeler
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart; Germany and University of Tübingen; Tübingen Germany
| | - M Schwab
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart; Germany and University of Tübingen; Tübingen Germany
- Department of Clinical Pharmacology; University Hospital Tübingen; Tübingen Germany
- Department of Pharmacy and Biochemistry; University of Tübingen; Tübingen Germany
| | - D Steinberger
- Bio.logis Center for Human Genetics; Frankfurt am Main Germany
| | - J Stingl
- Research Division; Federal Institute for Drugs and Medical Devices; Bonn Germany
| | - G Sunder-Plassmann
- Division of Nephrology and Dialysis, Department of Internal Medicine III; Medical University of Vienna; Vienna Austria
| | - G Toffoli
- Experimental and Clinical Pharmacology, Centro di Riferimento Oncologico; National Cancer Institute; Aviano Italy
| | - RM Turner
- Department of Molecular and Clinical Pharmacology; Royal Liverpool University Hospital and University of Liverpool; Liverpool United Kingdom
| | - MH van Rhenen
- Royal Dutch Pharmacists Association (KNMP); The Hague The Netherlands
| | - JJ Swen
- Department of Clinical Pharmacy and Toxicology; Leiden University Medical Center; Leiden The Netherlands
| | - H-J Guchelaar
- Department of Clinical Pharmacy and Toxicology; Leiden University Medical Center; Leiden The Netherlands
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21
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Haga SB, Mills R, Moaddeb J. Evaluation of a pharmacogenetic educational toolkit for community pharmacists. Pharmacogenomics 2016; 17:1491-502. [PMID: 27533631 DOI: 10.2217/pgs-2016-0002] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
AIM Over the past several decades, the roles and services of community pharmacists have expanded beyond traditional medical dispensation and compounding, and include health services such as vaccinations, and clinical testing and screening. Incorporating pharmacogenetic (PGx) testing into the menu of pharmacy services is logical and feasible; however, few pharmacists have experience with PGx testing, and few educational resources about PGx are available to support the uptake of PGx testing in community pharmacies. METHODS We developed a toolkit of four resources to assist pharmacists to provide PGx testing. We conducted a survey of pharmacists in North Carolina to evaluate each component of the toolkit and the toolkit as a whole. RESULTS A total of 380 respondents completed the evaluation of one or more toolkit components (344 evaluated all four components and the overall toolkit). Most respondents (84%) have never ordered or used PGx test results. Though the usability of the toolkit overall was below average (65.1 on a range of 0-100), individual components were perceived as useful and more than 75% of pharmacists reported that they would use the toolkit components when offering testing, with the result summary sheet receiving the highest score (4.01 out of 5). Open-text comments highlighted the need for more patient-friendly language and formatting. CONCLUSION The majority of pharmacist respondents scored the components of the toolkit favorably. The next steps will be to revise and assess use of the toolkit in community pharmacy settings.
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Affiliation(s)
- Susanne B Haga
- Center for Applied Genomics & Precision Medicine, Duke University, School of Medicine, 304 Research Drive, Box 90141, Durham, NC 27708, USA
| | - Rachel Mills
- Center for Applied Genomics & Precision Medicine, Duke University, School of Medicine, 304 Research Drive, Box 90141, Durham, NC 27708, USA
| | - Jivan Moaddeb
- Center for Applied Genomics & Precision Medicine, Duke University, School of Medicine, 304 Research Drive, Box 90141, Durham, NC 27708, USA
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