"From Kilobytes to Kilodaltons": A Novel Algorithm for Medical Image Encryption based on the Central Dogma of Molecular Biology.

With the continued integration of technology in medicine, large amounts of patient data are often vulnerable to cyber-attacks. Medical data must be secured, however traditional cryptographic algorithms are inapplicable to medical images due to factors such as bulk data capacity, strong correlation among adjacent pixels, and high redundancy. To address the need for new medical image encryption algorithms, a novel approach based on the central dogma of molecular biology is proposed. The resulting algorithm has a linear runtime complexity, and is resistant to brute force, differential and statistical attacks. The algorithm advances the state-of-the-art in DNA-based image encryption and surpasses recent approaches in medical image encryption in its defence against cyber-attacks. Clinical Relevance- Secure data transmission and storage is critical for patient privacy. This algorithm increases the security of patient imaging when compared to image encryption algorithms in literature.

Patients', pharmacists', and prescribers' attitude toward using blockchain and machine learning in a proposed ePrescription system: online survey.

OBJECTIVE: To evaluate the attitudes of the parties involved in the system 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 medication. The proposed blockchain will strengthen the security and privacy of the patient's prescription information shared in the network. Once the ePrescription is submitted, it is only available in read-only mode. This will ensure there is no alteration to the ePrescription information after submission. In addition, the blockchain will provide an improved tracking mechanism to ensure the originality of the ePrescription and that a prescriber can only submit an ePrescription with the patient's authorization. Lastly, before submitting an ePrescription, an ML algorithm will be used to detect any anomalies (eg, missing fields, misplaced information, or wrong dosage) in the ePrescription to ensure the safety of the prescribed medication for the patient. METHODS: The survey contains questions about the features introduced in the proposed 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. KEY FINDINGS: The vast majority of the respondents in all groups had a positive attitude toward the proposed ePrescription system's security and privacy using blockchain technology, with 72% (163/226) in the patient group, 70.5% (24/34) in the pharmacist group, and 73% (19/26) in the prescriber group. Moreover, the majority of the respondents in the pharmacist (70%, 24/34) and prescriber (85%, 22/26) groups had a positive attitude toward using ML algorithms to generate alerts regarding prescribed medication to enhance the safety of medication prescribing and prevent medication errors. CONCLUSION: Our survey showed that a vast majority of respondents in all groups had positive attitudes toward 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.

A framework to lower the risk of medication prescribing and dispensing errors: A usability study of an NFC-based mobile application.

BACKGROUND: Wrong medication and wrong dosage are major risks in the pharmaceutical industry, as many medication errors occur when dispensing medication. The dispensing process in its current form is limited in verifying the patient's identity before dispensing the medication. Furthermore, this process does not offer a robust method for providing accurate medication intake instructions. Therefore, we have developed a framework to accurately and securely overcome issues associated with transferring patient credentials and prescription information. The long-term goal of this research is to develop a framework to mitigate medication dispensing errors. One of the framework components is the mobile application that uses near-field communication (NFC) to transfer information. Therefore, in this paper, we designed a user study to assess the proposed NFC-based mobile application in terms of usefulness and ease of use compared with the traditional method of picking up a prescribed medication. METHODS: We conducted a usability study with 21 participants to perform four tasks to simulate the process of picking up a prescribed medication using the proposed NFC application method and the traditional method of picking up medication. Then, we asked the participants to complete two post-questionnaires after using each method to evaluate the participants' experience of the process. Next, we asked the participants to complete an additional questionnaire about the usefulness of the NFC application method. Finally, we conducted semi-structured interviews with the participants to get more evidence to back up the questionnaire answers. RESULTS: Our findings show that 91% of the participants believe using the NFC application method will improve patient safety during the medication pickup process. Nearly 97% of participants found the NFC application method easy to use. Our findings show that the participants scored lower when using the NFC application method compared with the traditional method when trying to identify the wrong medication after dispensing. In addition, 90% of the participants successfully identified the wrong medication when using the NFC application method, compared to only 38% when using the traditional method. Finally, the results show that the participants preferred using the NFC application method in terms of information availability, security, and privacy. CONCLUSIONS: The study findings show that the proposed NFC application for managing patients' prescriptions and picking up medication might improve patient safety. The results show that the participants believe the NFC application will mitigate medication dispensing errors, at least from their end. The participants believe the application will provide a fast and accurate method of verifying dispensed medication from the patient end. Moreover, the application will help the patient to track their current prescription, which also helps them remember the medication intake instructions. Finally, the study indicates that the application will provide a secure, private, and accurate method to help verify the patient's identity, thus minimizing medication errors during the medication dispensing process.

Digital Health in Physicians' and Pharmacists' Office: A Comparative Study of e-Prescription Systems' Architecture and Digital Security in Eight Countries.

e-Prescription systems are key components and drivers of digital health. They can enhance the safety of the patients, and are gaining popularity in health care systems around the world. Yet, there is little knowledge on comparative international analysis of e-Prescription systems' architecture and digital security. We report, in this study, original findings from a comparative analysis of the e-Prescription systems in eight different countries, namely, Canada, United States, United Kingdom, Australia, Spain, Japan, Sweden, and Denmark. We surveyed the databases related to pharmacies, eHealth, e-Prescriptions, and related digital health websites for each country, and their system architectures. We also compared the digital security and privacy protocols in place within and across these digital systems. We evaluated the systems' authentication protocols used by pharmacies to verify patients' identities during the medication dispensing process. Furthermore, we examined the supporting systems/services used to manage patients' medication histories and enhance patients' medication safety. Taken together, we report, in this study, original comparative findings on the limitations and challenges of the surveyed systems as well as in adopting e-Prescription systems. While the present study was conducted before the onset of COVID-19, e-Prescription systems have become highly relevant during the current pandemic and hence, a deeper understanding of the country systems' architecture and digital security that can help design effective strategies against the pandemic. e-Prescription systems can help reduce physical contact and the risk of exposure to the virus, as well as the wait times in pharmacies, thus enhancing patient safety and improving planetary health.

Trends in Persuasive Technologies for Physical Activity and Sedentary Behavior: A Systematic Review.

Persuasive technology (PT) is increasingly being used in the health and wellness domain to motivate and assist users with different lifestyles and behavioral health issues to change their attitudes and/or behaviors. There is growing evidence that PT can be effective at promoting behaviors in many health and wellness domains, including promoting physical activity (PA), healthy eating, and reducing sedentary behavior (SB). SB has been shown to pose a risk to overall health. Thus, reducing SB and increasing PA have been the focus of much PT work. This paper aims to provide a systematic review of PTs for promoting PA and reducing SB. Specifically, we answer some fundamental questions regarding its design and effectiveness based on an empirical review of the literature on PTs for promoting PA and discouraging SB, from 2003 to 2019 (170 papers). There are three main objectives: (1) to evaluate the effectiveness of PT in promoting PA and reducing SB; (2) to summarize and highlight trends in the outcomes such as system design, research methods, persuasive strategies employed and their implementaions, behavioral theories, and employed technological platforms; (3) to reveal the pitfalls and gaps in the present literature that can be leveraged and used to inform future research on designing PT for PA and SB.

Energy-Balancing Unequal Clustering Approach to Reduce the Blind Spot Problem in Wireless Sensor Networks (WSNs).

Wireless Sensor Networks (WSNs) have become a significant part of surveillance techniques. With unequal clustering approaches and multi-hop communication, WSNs can balance energy among the clusters and serve a wide monitoring area. Recent research has shown significant improvements in unequal clustering approaches by forming clusters prior to the selection of cluster heads. These improvements adopt different geometric fractals, such as the Sierpinski triangle, to divide the monitoring area into multiple clusters. However, performance of such approaches can be improved further by cognitive partitioning of the monitoring area instead of adopting random fractals. This paper proposes a novel clustering approach that partitions the monitoring area in a cognitive way for balancing the energy consumption. In addition, the proposed approach adopts a two-layered scrutinization process for the selection of cluster heads that ensures minimum energy consumption from the network. Furthermore, it reduces the blind spot problem that escalates once the nodes start dying. The proposed approach has been tested in terms of number of alive nodes per round, energy consumption of nodes and clusters, and distribution of alive nodes in the network. Results show a significant improvement in balancing the energy consumption among clusters and a reduction in the blind spot problem.

Butterfly Encryption Scheme for Resource-Constrained Wireless Networks.

Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID) and Wireless Body Area Networks (WBAN) that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG), and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis.