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DOI: 10.1055/s-0040-1708050
Design and Usability of an Electronic Health Record—Integrated, Point-of-Care, Clinical Decision Support Tool for Modeling and Simulation of Antihemophilic Factors
Publikationsverlauf
18. November 2019
04. Februar 2020
Publikationsdatum:
08. April 2020 (online)
Abstract
Background With the consequences of inadequate dosing ranging from increased bleeding risk to excessive drug costs and undesirable administration regimens, the antihemophilic factors are uniquely suited to dose individualization. However, existing options for individualization are limited and exist outside the flow of care. We developed clinical decision support (CDS) software that is integrated with our electronic health record (EHR) and designed to streamline the process for our hematology providers.
Objectives The aim of this study is to develop and examine the usability of a CDS tool for antihemophilic factor dose individualization.
Methods Our development strategy was based on the features associated with successful CDS tools and driven by a formal requirements analysis. The back-end code was based on algorithms developed for manual individualization and unit tested with 23,000 simulated patient profiles created from the range of patient-derived pharmacokinetic parameter estimates defined in children and adults. A 296-item heuristic checklist was used to guide design of the front-end user interface. Content experts and end-users were recruited to participate in traditional usability testing under an institutional review board approved protocol.
Results CDS software was developed to systematically walk the point-of-care clinician through dose individualization after seamlessly importing the requisite patient data from the EHR. Classical and population pharmacokinetic approaches were incorporated with clearly displayed estimates of reliability and uncertainty. Users can perform simulations for prophylaxis and acute bleeds by providing two of four therapeutic targets. Testers were highly satisfied with our CDS and quickly became proficient with the tool.
Conclusion With early and broad stakeholder engagement, we developed a CDS tool for hematology provider that affords seamless transition from patient assessment, to pharmacokinetic modeling and simulation, and subsequent dose selection.
Keywords
software design - therapeutic drug monitoring - usability testing - factor VII - factor VIII - factor IXAuthors' Contributions
S.M.A.R. conceived of the application, developed the initial algorithm around which the software was based, led the development of the decision support tool, and conducted the usability testing. S.L.C. and B.W. coordinated the requirements analysis for the clinical aspects of this tool. H.G., P.G., and A.K. were involved in coding of the back-end analytics. S.M.A.R., H.G., and P.G. undertook unit testing and validation. M.B. and A.G. were responsible for the design and coding of the UI. H.G. was responsible for integration of the software with the electronic health record. A.K. was responsible for supervising all informatics activities. All authors reviewed and approved the manuscript.
Protection of Human and Animal Subjects
The study was performed in compliance with the World Medical Association Declaration of Helsinki on Ethical Principles for Medical Research Involving Human Subjects. All participants were enrolled with informed consent under a protocol that was reviewed and approved by the Institutional Review Board at Children's Mercy Hospital (IRB# 00000285).
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References
- 1 Carlsson M, Björkman S, Berntorp E. Multidose pharmacokinetics of factor IX: implications for dosing in prophylaxis. Haemophilia 1998; 4 (02) 83-88
- 2 Blowey DL, Kearns GL. Congenital nephrotic syndrome alters antithrombin-III disposition in children. Clin Pharmacol Ther 1998; 63: 76
- 3 Shapiro AD, Korth-Bradley J, Poon MC. Use of pharmacokinetics in the coagulation factor treatment of patients with haemophilia. Haemophilia 2005; 11 (06) 571-582
- 4 Shakhnovich V, Daniel J, Wicklund B, Kearns G, Neville K. Use of pharmacokinetic modelling to individualize FFP dosing in factor V deficiency. Haemophilia 2013; 19 (02) 251-255
- 5 Brown JT, Wicklund BM, Abdel-Rahman SM. Individualized factor IX dosing: application of pharmacokinetic modeling to optimize pharmacodynamic activity. Haemophilia 2015; 21: e125-e127
- 6 Durieux P, Trinquart L, Colombet I. , et al. Computerized advice on drug dosage to improve prescribing practice. Cochrane Database Syst Rev 2008; 3 (03) CD002894
- 7 Buclin T, Gotta V, Fuchs A, Widmer N, Aronson J. Monitoring drug therapy. Br J Clin Pharmacol 2012; 73 (06) 917-923
- 8 Sheiner LB, Rosenberg B, Melmon KL. Modelling of individual pharmacokinetics for computer-aided drug dosage. Comput Biomed Res 1972; 5 (05) 411-459
- 9 Proost JH, Meijer DK. MW/Pharm, an integrated software package for drug dosage regimen calculation and therapeutic drug monitoring. Comput Biol Med 1992; 22 (03) 155-163
- 10 Buffington DE, Lampasona V, Chandler MHH. Computers in pharmacokinetics. Choosing software for clinical decision making. Clin Pharmacokinet 1993; 25 (03) 205-216
- 11 Lacarelle B, Pisano P, Gauthier T. , et al. Abbott PKS system: a new version for applied pharmacokinetics including Bayesian estimation. Int J Biomed Comput 1994; 36 (1-2): 127-130
- 12 Nieuwlaat R, Connolly SJ, Mackay JA. , et al; CCDSS Systematic Review Team. Computerized clinical decision support systems for therapeutic drug monitoring and dosing: a decision-maker-researcher partnership systematic review. Implement Sci 2011; 6: 90
- 13 Fuchs A, Csajka C, Thoma Y, Buclin T, Widmer N. Benchmarking therapeutic drug monitoring software: a review of available computer tools. Clin Pharmacokinet 2013; 52 (01) 9-22
- 14 Wallach D, Scholz SC. User-Centered Design: Why and How to Put Users First in Software Development. In Software for People. Heidelberg, Germany: Springer Berlin Heidelberg; 2012: 11-38
- 15 Gould JD, Lewis C. Designing for usability: key principles and what designers think. Commun ACM 1985; 28: 300-311
- 16 Lobach D, Sanders GD, Bright TJ. , et al. Enabling Health Care Decision making Through Clinical Decision Support and Knowledge Management. Evidence Report No. 203. (Prepared by the Duke Evidence-based Practice Center under Contract No. 290–2007–10066-I.) AHRQ Publication No. 12–E001-EF. Rockville, MD:Agency for Healthcare Research and Quality. Evid Rep Technol Assess (Full Rep) 2012; 203: 1-784
- 17 Wiegers K, Beatty J. Software Requirements. 3rd ed. Redmond, Washington: Microsoft Press; 2013
- 18 Highsmith J, Cockburn A. Agile Software Development: the business of innovation. IEEE Computer 2001; 34: 120-127
- 19 Abdel-Rahman SM, Breitkreutz ML, Bi C. , et al. Design and testing of an EHR-integrated, busulfan pharmacokinetic decision support tool for the point-of-care clinician. Front Pharmacol 2016; 7: 65
- 20 Weiss E. Making Computers People-Literate. San Francisco: Jossey-Bass Publishers; 1993
- 21 LePage P. Responsive web design basics. Available at: https://developers.google.com/web/fundamentals/design-and-ux/responsive . Accessed January 16, 2020
- 22 Angular. Available at: https://angular.io/ . Accessed January 16, 2020
- 23 Bootstrap. Available at: https://getbootstrap.com/ . Accessed January 16, 2020
- 24 Gavin HP. The Levenberg-Marquardt algorithm for nonlinear least squares curve-fitting problems (August 3, 2019). Available at: http://people.duke.edu/~hpgavin/ce281/lm.pdf . Accessed January 9, 2019
- 25 Thron CD. Linearity and superposition in pharmacokinetics. Pharmacol Rev 1974; 26 (01) 3-31
- 26 What Is REST. Available at: https://restfulapi.net/ . Accessed January 16, 2020)
- 27 Sauro J, Lewis JR. Quantifying the User Experience Practical Statistics for User Research. Waltham, MA: Morgan Kaufmann; 2012
- 28 myPKFiT for ADVATE. 510(k) Number BK170028. Decision date 12/14/17. Available at: https://www.fda.gov/vaccines-blood-biologics/substantially-equivalent-510k-device-information/bk170028-mypkfit-advate . Accessed May 25, 2019
- 29 Iorio A, Keepanasseril A, Foster G. , et al; WAPPS-Hemo co-investigator network. Development of a web-accessible population pharmacokinetic service-hemophilia (WAPPS-Hemo): study protocol. JMIR Res Protoc 2016; 5 (04) e239
- 30 Preijers T, van Moort I, Fijnvandraat K, Leebeek FWG, Cnossen MH, Mathôt RAA. ; ‘OPTI-CLOT’ Study Group. Cross-evaluation of pharmacokinetic-guided dosing tools for factor VIII. Thromb Haemost 2018; 118 (03) 514-525
- 31 Manco-Johnson MJ, Abshire TC, Brown D. Randomized, controlled, multi-year study to evaluate joint outcomes in young children using recombinant factor VIII (Kogenate® FS). Haemophilia 2006; 12: 17-18
- 32 du Treil S, Rice J, Leissinger CA. Quantifying adherence to treatment and its relationship to quality of life in a well-characterized haemophilia population. Haemophilia 2007; 13 (05) 493-501
- 33 García-Dasí M, Aznar JA, Jiménez-Yuste V. , et al. Adherence to prophylaxis and quality of life in children and adolescents with severe haemophilia A. Haemophilia 2015; 21 (04) 458-464
- 34 Hacker MR, Geraghty S, Manco-Johnson M. Barriers to compliance with prophylaxis therapy in haemophilia. Haemophilia 2001; 7 (04) 392-396
- 35 Lindvall K, Colstrup L, Wollter IM. , et al. Compliance with treatment and understanding of own disease in patients with severe and moderate haemophilia. Haemophilia 2006; 12 (01) 47-51
- 36 Duncan N, Kronenberger W, Roberson C, Shapiro A. VERITAS-Pro: a new measure of adherence to prophylactic regimens in haemophilia. Haemophilia 2010; 16 (02) 247-255
- 37 De Moerloose P, Urbancik W, Van Den Berg HM, Richards M. A survey of adherence to haemophilia therapy in six European countries: results and recommendations. Haemophilia 2008; 14 (05) 931-938
- 38 Armstrong EP, Malone DC, Krishnan S, Wessler MJ. Adherence to clotting factors among persons with hemophilia A or B. Hematology 2015; 20 (03) 148-153
- 39 Razzaboni E, Toss A, Cortesi L. , et al. Acceptability and adherence in a chemoprevention trial among women at increased risk for breast cancer attending the Modena Familial Breast and Ovarian Cancer Center (Italy). Breast J 2013; 19 (01) 10-21
- 40 Will JC, Zhang Z, Ritchey MD, Loustalot F. Medication adherence and incident preventable hospitalizations for hypertension. Am J Prev Med 2015; 50 (04) 489-499
- 41 Liu AY, Hessol NA, Vittinghoff E. , et al. Medication adherence among men who have sex with men at risk for HIV infection in the United States: implications for pre-exposure prophylaxis implementation. AIDS Patient Care STDS 2014; 28 (12) 622-627