The survey data of patients, prescribers, and pharmacists' feedback on ePrescription systems security and privacy

Objective: To evaluate the attitudes of the parties (i.e. patients,
prescribers, and pharmacists) involved in the ePrescription systems toward
the new features and measure the potential benefits of introducing the use
of blockchain and machine learning (ML) to strengthen the in-place methods
for safely prescribing and dispensing medication. Methods: The survey
contains questions about the features introduced in the proposed approach
of using blockcahin and ML in the ePrescription system to evaluate the
security, privacy, reliability, and availability of the ePrescription
information in the system. The study population is comprised of 284
respondents in the patient group, 39 respondents in the pharmacist group,
and 27 respondents in the prescriber group, all of whom met the inclusion
criteria. The response rate was 80% (226/284) in the patient group, 87%
(34/39) in the pharmacist group, and 96% (26/27) in the prescriber group.
We removed the responses of participants who did not complete the surevy
questions. Conclusion: Our survey showed that a vast majority of
respondents in all groups had positive attitudes towards using blockchain
and ML algorithms to safely prescribe medications. However, a need for
minor improvements regarding the proposed features was identified, and a
post-implementation user study is needed to evaluate the proposed
ePrescription system in depth.