Abstract
In health-care, medical errors are quantified. Among them, wrong dose prescriptions occur. Drug dose titration (DT) is the process by which dosage is progressively adjusted to the patient till a steady dose is reached. Depending on the clinical disease, drug, and patient, dose titration can follow different procedures. Once modeled, these procedures can serve for clinical homogenization, standardization, decision support and retrospective analysis. Here, we propose a language to model dose titration procedures. The language was used to formalize single-drug titration of chronic and acute cases, and perform retrospective analysis of the drug titration processes on 1,000 cases treated with Bisoprolol and 2,430 cases treated with Ramipril, in order to identify different types of drug titration deviations from standard DT methods.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Al Hamid, A., Ghaleb, M., Aljadhey, H., Aslanpour, Z.: A systematic review of hospitalization resulting from medicine-related problems in adult patients. Br. J. Clin. Pharmacol. 78(2), 202–17 (2014). https://doi.org/10.1111/bcp.12293
Aronson, J.K.: Medication errors: definitions and classification. Br. J. Clin. Pharmacol. 67(6), 599–604 (2009). https://doi.org/10.1111/j.1365-2125.2009.03415.x
Buczak, A.L., Babin, S., Moniz, L.: Data-driven approach for creating synthetic electronic medical records. BMC Med. Inform. Decis. Mak. 10, 59 (2010). https://doi.org/10.1186/1472-6947-10-59
Carroll, R., Mudge, A., Suna, J., Denaro, C., Atherton, J.: Prescribing and up-titration in recently hospitalized heart failure patients attending a disease management program. Int. J. Cardiol. 216, 121–27 (2016). https://doi.org/10.1016/j.ijcard.2016.04.084
Corny, J., et al.: A machine learning-based clinical decision support system to identify prescriptions with a high risk of medication error. J. Am. Med. Inform. Assoc. 27(11), 1688–1694 (2020)
Gates, P.J., Meyerson, S.A., Baysari, M.T., Westbrook, J.I.: The prevalence of dose errors among paediatric patients in hospital wards with and without health information technology: a systematic review and meta-analysis. Drug Safety 42(1), 13–25 (2018). https://doi.org/10.1007/s40264-018-0715-6
Hickey, A., et al.: Improving medication titration in heart failure by embedding a structured medication titration plan. Int. J. Cardiol. 224, 99–106 (2016). https://doi.org/10.1016/j.ijcard.2016.09.001
Kamišalić, A., Riaño, D., Kert, S., Welzer, T., Nemec Zlatolas, L.: Multi-level medical knowledge formalization to support medical practice for chronic diseases. Data Knowl. Eng. 119, 36–57 (2019). https://doi.org/10.1055/s-0040-1702016
Landry, M., Lafrenière, S., Patry, S., Potvin, S., Lemasson, M.: The clinical relevance of dose titration in electroconvulsive therapy: a systematic review of the literature. Psychiat. Res. 294 (2020). https://doi.org/10.1016/j.psychres.2020.113497
Michel, M.C., Staskin, D.: Understanding dose titration: overactive bladder treatment with fesoterodine as an example. Eur. Urol. Suppl. 10, 8–13 (2011). https://doi.org/10.1016/j.eursup.2011.01.004
Miftahurrohmah, B., Iriawan, N., Wulandari, C., Dharmawan, Y.S.: Individual control optimization of drug dosage using individual Bayesian pharmacokinetics model approach. Proc. Comput. Sci. 161, 593–600 (2019). https://doi.org/10.1016/j.procs.2019.11.161
Mirinejad, H., Gaweda, A.E., Brier, M.E., Zurada, J.M., Inanc, T.: Individualized drug dosing using RBF-Galerkin method: case of anemia management in chronic kidney disease. Comput. Methods Progr. Biomed. 148, 45–53 (2017). https://doi.org/10.1016/j.cmpb.2017.06.008
Maxwell, S.: Chapter 2: therapeutics and good prescribing: choosing a dosing regime. In: Walker, B.R., Colledge, N.R., Ralston, S.H., Penman, I.D. (eds.) Davidson’s Principles and Practice of Medicine, p. 34. Elsevier Health Sciences (2013). ISBN 978-0-7020-5103-6
Medication Errors: Technical Series on Safer Primary Care. Geneva: World Health Organization (2016). Licence: CC BY-NC-SA 3.0 IGO
Riaño, D., Bohada, J.A., Collado, A., Lopez-Vallverdu, J.A.: MPM: a knowledge-based functional model of medical practice. J. Biomed. Inform. 46(3), 379–87 (2013). https://doi.org/10.1016/j.jbi.2013.01.007
Riaño, D., Fernández-Pérez, A.: Simulation-based episodes of care data synthetization for chronic disease patients. In: Riaño, D., Lenz, R., Reichert, M. (eds.) KR4HC/ProHealth -2016. LNCS (LNAI), vol. 10096, pp. 36–50. Springer, Cham (2017). https://doi.org/10.1007/978-3-319-55014-5_3
Riaño, D., Ortega, W.: Computer technologies to integrate medical treatments to manage multimorbidity. J. Biomed. Inform. 75, 1–13 (2017). https://doi.org/10.1016/j.jbi.2017.09.009
Schuck, R.N., Pacanowski, M., Kim, S., Madabushi, R., Zineh, I.: Use of titration as a therapeutic individualization strategy: an analysis of food and drug administration-approved drugs. Clin. Transl. Sci. 12(3), 236–39 (2019). https://doi.org/10.1111/cts.12626
Tariq, R. A., Vashisht, R., Sinha, A., et al.: Medication dispensing errors and prevention. In: StatPearls [Internet]. Treasure Island (FL): StatPearls. https://www.ncbi.nlm.nih.gov/books/NBK519065/. Accessed Jan 2021
Truda, G., Marais, P.: Evaluating warfarin dosing models on multiple datasets with a novel software framework and evolutionary optimisation. J. Biomed. Inform. (2019). https://doi.org/10.1016/j.jbi.2020.103634
Wang, Z., Myles, P., Tucker, A.: Generating and evaluating cross-sectional synthetic electronic healthcare data: preserving data utility and patient privacy. Comput. Intell. 1–33 (2021). https://doi.org/10.1111/coin.12427
Acknowledgements
The authors acknowledge financial support from the Slovenian Research Agency (Research Core Funding No. P2-0057) and the Spanish Ministry of Science and Innovation (Funding Code PID2019-105789RB-I00).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Switzerland AG
About this paper
Cite this paper
Riaño, D., Kamišalić, A. (2021). Modelling and Assessment of One-Drug Dose Titration. In: Tucker, A., Henriques Abreu, P., Cardoso, J., Pereira Rodrigues, P., Riaño, D. (eds) Artificial Intelligence in Medicine. AIME 2021. Lecture Notes in Computer Science(), vol 12721. Springer, Cham. https://doi.org/10.1007/978-3-030-77211-6_55
Download citation
DOI: https://doi.org/10.1007/978-3-030-77211-6_55
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-77210-9
Online ISBN: 978-3-030-77211-6
eBook Packages: Computer ScienceComputer Science (R0)