Framework to enable pharmacist access to health care data using Blockchain technology and artificial intelligence

Roosan, Don; Wu, Yanting; Tatla, Vineet; Li, Yawen; Kugler, Anne; Chok, Jay; Roosan, Moom R.

doi:10.1016/j.japh.2022.02.018

Cited by 28 publications

(13 citation statements)

References 33 publications

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“…For example, during the COVID-19 epidemic prevention and control, to better meet the demand of residents seeking medical and pharmacy services, the “health cloud” platform ( An, 2022 ) launched medical and pharmacy services online in April 2022 with joint efforts of the Shanghai municipal commission of health and family planning, the medical insurance platform, and a majority of hospitals in Shanghai that have launched internet hospitals. Similarly, AI enabled pharmacists to access the medical data across different health care providers ( Roosan et al, 2022 ). Moreover, it provides people the flexibility to choose a certain doctor and pharmacist in the internet hospital to consult.…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study

Sun

et al. 2022

Front. Pharmacol.

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Background: Recently, internet hospitals have been emerging in China, saving patients time and money during the COVID-19 pandemic. In addition, pharmacy services that link doctors and patients are becoming essential in improving patient satisfaction. However, the existing internet hospital pharmacy service mode relies primarily on manual operations, making it cumbersome, inefficient, and high-risk.Objective: To establish an internet hospital pharmacy service mode based on artificial intelligence (AI) and provide new insights into pharmacy services in internet hospitals during the COVID-19 pandemic.Methods: An AI-based internet hospital pharmacy service mode was established. Initially, prescription rules were formulated and embedded into the internet hospital system to review the prescriptions using AI. Then, the “medicine pick-up code,” which is a Quick Response (QR) code that represents a specific offline self-pick-up order, was created. Patients or volunteers could pick up medications at an offline hospital or drugstore by scanning the QR code through the window and wait for the dispensing machine or pharmacist to dispense the drugs. Moreover, the medication consultation function was also operational.Results: The established internet pharmacy service mode had four major functional segments: online drug catalog search, prescription preview by AI, drug dispensing and distribution, and AI-based medication consultation response. The qualified rate of AI preview was 83.65%. Among the 16.35% inappropriate prescriptions, 49% were accepted and modified by physicians proactively and 51.00% were passed after pharmacists intervened. The “offline self-pick-up” mode was preferred by 86% of the patients for collecting their medication in the internet hospital, which made the QR code to be fully applied. A total of 426 medication consultants were served, and 48.83% of them consulted outside working hours. The most frequently asked questions during consultations were about the internet hospital dispensing process, followed by disease diagnosis, and patient education. Therefore, an AI-based medication consultation was proposed to respond immediately when pharmacists were unavailable.Conclusion: The established AI-based internet hospital pharmacy service mode could provide references for pharmacy departments during the COVID-19 pandemic. The significance of this study lies in ensuring safe/rational use of medicines and raising pharmacists’ working efficiency.

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Section: Discussionmentioning

confidence: 99%

Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study

Sun

et al. 2022

Front. Pharmacol.

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Section: Simulation Studymentioning

confidence: 99%

“…The simulation was modified by considering the metabolism as a chemical reaction to predict the drug diffusion in this situation. In the studies performed by Baert and De Backer, [28] Salamah et al, [29] and Roosan and Sharma, [30] the half-life of MLX was reported to be about 20 h. Pseudo-ternary phase diagrams of oil-surfactant-water systems were obtained based on the experimental data. The ME area in the phase diagrams should be large enough to achieve an adequate formulation, therefore the diagrams with a large area of the ME zone were labelled as acceptable, and those with an inadequate ME area were labelled as not acceptable.…”

Section: Prediction Of the Effect Of Metabolism On Drug Diffusionmentioning

confidence: 99%

“…The metabolism rate of MLX as a constant value is needed in the simulation. To find this value, the half-life of MLX in the natural skin tissue was reported to be about 20 h. [28][29][30] Since the metabolism rate of MLX was approximated as a constant value, the rate of MLX metabolism was considered to be À0.05%/h in the simulation. By adding this metabolism rate to validate the simulation of the membrane, the drug release of formulation 1 in the natural tissue of the skin was simulated.…”

Section: Prediction Of Drug Release In the Natural Tissue Of The Skinmentioning

confidence: 99%

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Preparation of nano‐micelles of meloxicam for transdermal drug delivery and simulation of drug release: A computational supported experimental study

et al. 2022

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Meloxicam (MLX) is a generic drug with a wide range of pharmaceutical applications in the world. In this study, the nanostructural form of MLX was prepared using the microemulsion (ME) method. The size distribution of droplets was measured by dynamic light scattering (DLS). Among several substances, oleic acid was chosen as the oily phase, and Tween 80/PEG 400 (1/1) and Tween 80/ethanol (2/1) were selected as surfactants and co-surfactants to create a stable and large area of the ME zone. The droplet sizes for MEs created for Tween/ethanol and Tween/PEG 400 were about 13 and 800 nm, respectively. This shows that the ME is in the form of nanomicelles. Despite the small size of Tween/ethanol, the release amount of the drug from Tween/PEG 400 was higher. The release rate of the drug formulation and its variation were experimentally investigated in the Franz diffusion cell using UV spectroscopy detection. In addition, the simulation of the drug release was carried out. The diffusion coefficient of Tween 80/ethanol (1/1), calculated using the simulation, was about 16.8 Â 10 À13 cm 2 /s, and it was predicted that the maximum percentage of release after 24 h would be about 70%. Finally, the release of MLX in the skin tissue was predicted by applying the rate of metabolism in the simulation. The results showed that the maximum percentage of MLX released into the skin was about 40%.

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“…As a result of this high rate of computerized device adoption, electronic prescriptions, EHRs, and e-pharmacies are just a few of the mainstream digital solutions that will continue to be widely used in the healthcare industry [ 52 ]. Furthermore, it is envisaged that in the recent wake of artificial intelligence systems, the potentials for electronic prescribing will greatly expand, towards ultimately minimizing the number of errors committed in medical prescribing [ 53 ].…”

Section: Ehealth: An Overviewmentioning

confidence: 99%

eHealth: A Survey of Architectures, Developments in mHealth, Security Concerns and Solutions

Alenoghena

Onumanyi

Ohize

et al. 2022

IJERPH

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The ramifications of the COVID-19 pandemic have contributed in part to a recent upsurge in the study and development of eHealth systems. Although it is almost impossible to cover all aspects of eHealth in a single discussion, three critical areas have gained traction. These include the need for acceptable eHealth architectures, the development of mobile health (mHealth) technologies, and the need to address eHealth system security concerns. Existing survey articles lack a synthesis of the most recent advancements in the development of architectures, mHealth solutions, and innovative security measures, which are essential components of effective eHealth systems. Consequently, the present article aims at providing an encompassing survey of these three aspects towards the development of successful and efficient eHealth systems. Firstly, we discuss the most recent innovations in eHealth architectures, such as blockchain-, Internet of Things (IoT)-, and cloud-based architectures, focusing on their respective benefits and drawbacks while also providing an overview of how they might be implemented and used. Concerning mHealth and security, we focus on key developments in both areas while discussing other critical topics of importance for eHealth systems. We close with a discussion of the important research challenges and potential future directions as they pertain to architecture, mHealth, and security concerns. This survey gives a comprehensive overview, including the merits and limitations of several possible technologies for the development of eHealth systems. This endeavor offers researchers and developers with a quick snapshot of the information necessary during the design and decision-making phases of the eHealth system development life cycle. Furthermore, we conclude that building a unified architecture for eHealth systems would require combining several existing designs. It also points out that there are still a number of problems to be solved, so more research and investment are needed to develop and deploy functional eHealth systems.

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Framework to enable pharmacist access to health care data using Blockchain technology and artificial intelligence

Cited by 28 publications

References 33 publications

Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study

Artificial intelligence-based internet hospital pharmacy services in China: Perspective based on a case study

Preparation of nano‐micelles of meloxicam for transdermal drug delivery and simulation of drug release: A computational supported experimental study

eHealth: A Survey of Architectures, Developments in mHealth, Security Concerns and Solutions

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