Clinician Response to Pharmacogenetic Clinical Decision Support Alerts.
Journal
Clinical pharmacology and therapeutics
ISSN: 1532-6535
Titre abrégé: Clin Pharmacol Ther
Pays: United States
ID NLM: 0372741
Informations de publication
Date de publication:
Dec 2023
Dec 2023
Historique:
received:
09
05
2023
accepted:
09
08
2023
medline:
17
11
2023
pubmed:
17
9
2023
entrez:
16
9
2023
Statut:
ppublish
Résumé
The objective of this study was to characterize clinician response following standardization of pharmacogenetic (PGx) clinical decision support alerts at University of Florida (UF) Health. A retrospective analysis of all PGx alerts that fired at a tertiary academic medical center from August 2020 through May 2022 was performed. Alert acceptance rate was calculated and compared across six gene-drug pairs, patient care setting, and clinician specialty. The disposition of the triggering medication was compared with the alert response and evaluated for congruence. There were a total of 818 alerts included for analysis of alert response, 557 alerts included in acceptance rate calculations, and 392 alerts with sufficient information to assess clinical response. The overall acceptance rate was 63%. The alert response and clinical response were congruent for 47% of alerts. Alert response was influenced by the triggering gene-drug pair, clinician specialty, patient care setting, and specialty of the provider who initially ordered the PGx test. Clinical response was mostly incongruent with alert response. Alert acceptance is influenced by the triggering gene-drug pair, clinician specialty, and care setting. Alert response is not a reliable surrogate marker for clinical action. Any future research into the impact of clinical decision support (CDS) alerts should focus on clinical response rather than alert response. Given the reliance on CDS alerts to enhance uptake of PGx, it is worthwhile to further investigate their impact on prescribing and patient outcomes.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1350-1357Subventions
Organisme : NCATS NIH HHS
ID : UL1 TR001427
Pays : United States
Informations de copyright
© 2023 The Authors. Clinical Pharmacology & Therapeutics © 2023 American Society for Clinical Pharmacology and Therapeutics.
Références
HealthIT.gov. Clinical decision support <https://www.healthit.gov/topic/safety/clinical-decision-support>.
Kuperman, G.J. et al. Medication-related clinical decision support in computerized provider order entry systems: a review. J. Am. Med. Inform. Assn. 14, 29-40 (2007).
Topić, E. Pharmacogenomics and personalized medicine. EJIFCC 19, 31-41 (2008).
Galli, M. et al. Comparative effects of guided vs. potent P2Y12 inhibitor therapy in acute coronary syndrome: a network meta-analysis of 61 898 patients from 15 randomized trials. Eur. Heart J. 43, 959-967 (2022).
Rosenblat, J.D., Lee, Y. & McIntyre, R.S. The effect of pharmacogenomic testing on response and remission rates in the acute treatment of major depressive disorder: a meta-analysis. J. Affect. Disord. 241, 484-491 (2018).
Xiang, Q. et al. Association between SLCO1B1 T521C polymorphism and risk of statin-induced myopathy: a meta-analysis. Pharmacogenomics J. 18, 721-729 (2018).
Perlis, R.H., Mehta, R., Edwards, A.M., Tiwari, A. & Imbens, G.W. Pharmacogenetic testing among patients with mood and anxiety disorders is associated with decreased utilization and cost: a propensity-score matched study. Depress. Anxiety 35, 946-952 (2018).
Driest, S.L. et al. Clinically actionable genotypes among 10,000 patients with preemptive pharmacogenomic testing. Clin. Pharmacol. Ther. 95, 423-431 (2014).
Bush, W. et al. Genetic variation among 82 pharmacogenes: the PGRNseq data from the eMERGE network. Clin. Pharmacol. Ther. 100, 160-169 (2016).
Hicks, J.K. et al. Opportunity for genotype-guided prescribing among adult patients in 11 US health systems. Clin. Pharmacol. Ther. 110, 179-188 (2021).
Samwald, M. et al. Incidence of exposure of patients in the United States to multiple drugs for which pharmacogenomic guidelines are available. PloS One 11, e0164972 (2016).
Luczak, T., Brown, S.J., Armbruster, D., Hundertmark, M., Brown, J. & Stenehjem, D. Strategies and settings of clinical pharmacogenetic implementation: a scoping review of pharmacogenetics programs. Pharmacogenomics 22, 345-364 (2021).
Garg, A.X. et al. Effects of computerized clinical decision support systems on practitioner performance and patient outcomes: a systematic review. JAMA 293, 1223-1238 (2005).
Page, N., Baysari, M.T. & Westbrook, J.I. A systematic review of the effectiveness of interruptive medication prescribing alerts in hospital CPOE systems to change prescriber behavior and improve patient safety. Int. J. Med. Inform. 105, 22-30 (2017).
Cerqueira, O., Gill, M., Swar, B., Prentice, K.A., Gwin, S. & Beasley, B.W. The effectiveness of interruptive prescribing alerts in ambulatory CPOE to change prescriber behaviour & improve safety. BMJ Qual. Saf. 30, 1038-1046 (2021).
Reckmann, M.H., Westbrook, J.I., Koh, Y., Lo, C. & Day, R.O. Does computerized provider order entry reduce prescribing errors for hospital inpatients? A systematic review. J. Am. Med. Inform. Assoc. 16, 613-623 (2009).
Kaushal, R., Shojania, K.G. & Bates, D.W. Effects of computerized physician order entry and clinical decision support systems on medication safety: a systematic review. Arch. Intern. Med. 163, 1409-1416 (2003).
van der Sijs, H., Aarts, J., Vulto, A. & Berg, M. Overriding of drug safety alerts in computerized physician order entry. J. Am. Med. Inform. Assoc. 13, 138-147 (2006).
Cavallari, L.H. et al. Institutional profile: University of Florida Health Personalized Medicine Program. Pharmacogenomics 18, 421-426 (2017).
Arwood, M.J. et al. Design and early implementation successes and challenges of a pharmacogenetics consult clinic. J. Clin. Med. 9, 2274 (2020).
Shah, S.N., Amato, M.G., Garlo, K.G., Seger, D.L. & Bates, D.W. Renal medication-related clinical decision support (CDS) alerts and overrides in the inpatient setting following implementation of a commercial electronic health record: implications for designing more effective alerts. J. Am. Med. Inform. Assoc. 28, 1081-1087 (2021).
Weingart, S.N., Toth, M., Sands, D.Z., Aronson, M.D., Davis, R.B. & Phillips, R.S. Physicians' decisions to override computerized drug alerts in primary care. Arch. Intern. Med. 163, 2625-2631 (2003).
Topaz, M. et al. Rising drug allergy alert overrides in electronic health records: an observational retrospective study of a decade of experience. J. Am. Med. Inform. Assn. 23, 601-608 (2016).
Taylor, L.K. & Tamblyn, R. Reasons for physician non-adherence to electronic drug alerts. Stud. Health Technol. Inform. 107, 1101-1105 (2004).
Ariosto, D. Factors contributing to CPOE opiate allergy alert overrides. AMIA Annu. Symp. Proc. 2014, 256-265 (2014).
Wong, A. et al. Evaluation of medication-related clinical decision support alert overrides in the intensive care unit. J. Crit. Care 39, 156-161 (2017).
Nanji, K.C. et al. Medication-related clinical decision support alert overrides in inpatients. J. Am. Med. Inform. Assoc. 25, 476-481 (2018).
Nanji, K.C. et al. Overrides of medication-related clinical decision support alerts in outpatients. J. Am. Med. Inform. Assoc. 21, 487-491 (2014).
Lin, C.-P., Payne, T.H., Nichol, W.P., Hoey, P.J., Anderson, C.L. & Gennari, J.H. Evaluating clinical decision support systems: monitoring CPOE order check override rates in the Department of Veterans Affairs' computerized patient record system. J. Am. Med. Inform. Assoc. 15, 620-626 (2008).
Bryant, A., Fletcher, G. & Payne, T. Drug interaction alert override rates in the meaningful use era: no evidence of progress. Appl. Clin. Inform. 5, 802-813 (2014).
Isaac, T. et al. Overrides of medication alerts in ambulatory care. Arch. Intern. Med. 169, 305-311 (2009).
Herr, T.M., Peterson, J.F., Rasmussen, L.V., Caraballo, P.J., Peissig, P.L. & Starren, J.B. Pharmacogenomic clinical decision support design and multi-site process outcomes analysis in the eMERGE network. J. Am. Med. Inform. Assoc. 26, 143-148 (2019).
Kleindorfer, D.O. et al. 2021 guideline for the prevention of stroke in patients with stroke and transient ischemic attack: a guideline from the American Heart Association/American Stroke Association. Stroke 52, e364-e467 (2021).
Lee, C.R. et al. Clinical pharmacogenetics implementation consortium guideline for CYP2C19 genotype and clopidogrel therapy: 2022 update. Clin. Pharmacol. Ther. 112, 959-967 (2022).
Payne, T.H. et al. Recommendations to improve the usability of drug-drug interaction clinical decision support alerts. J. Am. Med. Inform. Assoc. 22, 1243-1250 (2015).
Hsieh, T.C. et al. Characteristics and consequences of drug allergy alert overrides in a computerized physician order entry system. J. Am. Med. Inform. Assn. 11, 482-491 (2004).
Breu, A.C., Allen-Dicker, J., Mueller, S., Palamara, K., Hinami, K. & Herzig, S.J. Hospitalist and primary care physician perspectives on medication management of chronic conditions for hospitalized patients. J. Hosp. Med. 9, 303-309 (2014).
Bloss, C.S., Schork, N.J. & Topol, E.J. Direct-to-consumer pharmacogenomic testing is associated with increased physician utilisation. J. Med. Genet. 51, 83-89 (2014).
Elchynski, A.L. et al. Determining the potential clinical value of panel-based pharmacogenetic testing in patients with chronic pain or gastroesophageal reflux disease. Pharmacogenomics J. 21, 657-663 (2021).
Beitelshees, A.L. et al. Evaluating the extent of reusability of CYP2C19 genotype data among patients genotyped for antiplatelet therapy selection. Genet. Med. 22, 1898-1902 (2020).
Black, R.M. et al. Projected impact of pharmacogenomic testing on medications beyond antiplatelet therapy in percutaneous coronary intervention patients. Pharmacogenomics 21, 431-441 (2020).
Centers for Medicare & Medicaid Services. <Chronic conditions overview https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Chronic-Conditions> (2021).
Hicks, J.K., Dunnenberger, H.M., Gumpper, K.F., Haidar, C.E. & Hoffman, J.M. Integrating pharmacogenomics into electronic health records with clinical decision support. Am. J. Health Syst. Pharm. 73, 1967-1976 (2016).
Caraballo, P.J. et al. Integrating pharmacogenomics into the electronic health record by implementing genomic indicators. J. Am. Med. Inform. Assoc. 27, 154-158 (2020).
Goldspiel, B.R. et al. Integrating pharmacogenetic information and clinical decision support into the electronic health record. J. Am. Med. Inform. Assoc. 21, 522-528 (2014).
Smith, M.D., Wake, D.T. & Dunnenberger, H.M. Pharmacogenomic clinical decision support: a scoping review. Clin. Pharmacol. Ther. 113, 803-815 (2023).
Manzi, S.F. et al. Creating a scalable clinical pharmacogenomics service with automated interpretation and medical record result integration - experience from a pediatric tertiary care facility. J. Am. Med. Inform. Assoc. 24, 74-80 (2017).