Files
Abstract
Development of an online warfarin dosing platform using R programming language to facilitate healthcare professional duties and limit medication related errors.
Monther Alsultan, Joshua M. Morriss, Daniel Contaifer Jr, Suad Alshammari; Silas Contaifer, Rachel W Flurie, Dayanjan S. Wijesinghe#
Department of Pharmacotherapy and Outcome Sciences
Objective: 1) Gain experience in developing platform agnostic, fully operational and clinically relevant web applications for effective pharmacist led patient care. 2) Create a decision- support tool using open source software to facilitate evidence-based management therapy of warfarin in clinical settings where it is available for everyone to use at anytime and anywhere.
Introduction: Healthcare is continuously growing and modern technologies provide opportunities for the creation of effective tools to manage multiple diseases. Mobile devices such as smartphones enable easy access to a variety of websites remotely and make data and information readily available for use. Additionally, mobile devices can offer healthcare providers with fast and easy access to essential medical information to support patient care. The profession of pharmacy is fast changing from one primarily focused on dispensing medicinal goods to one intensely focused on the delivery of patient care. This has led pharmacists to be involved in a diverse clinical service such as patient's education, Medication Therapy Management (MTM) and medications dose adjustment. Implementing such services often place additional stress on the daily routine of pharmacists. Therefore, there is a high need to find efficient ways to support healthcare related clinical services. One of the widely used anticoagulant medications is warfarin. Warfarin has been available on the market as effective therapy in management of thrombotic disorders. However, warfarin is frequently associated with medications errors which may lead to serious adverse events. The purpose of this paper is to demonstrate this fact fully via warfarin dosing web application to help support healthcare professionals in clinical settings.
Methods: Open-source programming language R in conjunction with RStudio version 1.2.5033 were used to develop and implement our warfarin dosing platform. Shiny packages for R with other packages were used to create our platform as a web-based app. We based our calculations and function of our platform on the UW health warfarin management- adult- ambulatory clinical practice guidelines.
Results: The platform contains three tools users can use:1) Calculating the warfarin maintenance dose,2) Selecting INR goals and duration of therapy,3) Assessment of Bleeding risk. Additionally, the app has a hyperlink to direct the users to the resource used in this app. On the first page of the app, the user can select their INR target and input a patients INR and weekly dose. Then, the app will immediately display the results. On the second page of the app, there is a feature for users helps to choose the INR target recommended based on patient conditions; There is a drop down menu contains different type of antithrombotic indications. Additionally, on the third page of the app, there is a feature for users helps to calculate the bleeding risk using HAS-BLED score. The users can answer “Yes” or “No” on multiple risk factors to stratify patients’ risk into low, moderate or high.
Conclusion: Our warfarin dosing platform demonstrates the feasibility of creating a free-tool for healthcare professionals to facilitate their daily practice and potential for reducing medication related errors. Additionally, we demonstrate that pharmacists can take advantage of open-sources resources available to develop any health-related application suitable to their needs.
Future Directions: The skills gained in the implementation of this full stack web application development will be further improved upon to develop additional clinical support tools for pharmacists. Further implementations will also incorporate fully or partially trained machine learning models. Our ultimate goal is to allow pharmacists to utilize data driven decision making strategies to implement fast and effective patient care.
Loading...
Publication Date
2021
Disciplines
Other Pharmacy and Pharmaceutical Sciences
Faculty Advisor/Mentor
Dayanjan S. Wijesinghe
Is Part Of
VCU Graduate Research Posters