ABSTRACT
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.
ABSTRACT
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.
ABSTRACT
Background: To date, the COVID-19 pandemic does not appear to be overcome with new variants continuously emerging. The vaccination against COVID-19 has been the trend, but there are multiple systematic reviews on COVID-19 vaccines in patients with cancer, resulting in redundant and sub-optimal systematic reviews. There are still some doubts about efficacy and safety of the COVID-19 vaccine in cancer patients. Purpose: To identify, summarize and synthesize the available evidence of systematic reviews on response and COVID-19 vaccine safety in patients with cancer. Methods: Multiple databases were searched from their inception to May 1, 2022 to fetch the relevant articles. Study quality was assessed by AMSTAR2. The protocol of this study was registered on PROSPERO (CRD42022327931). Results: A total of 18 articles were finally included. The seroconversion rates after first dose were ranged from 37.30-54.20% in all cancers, 49.60-62.00% in solid cancers and 33.30-56.00% in hematological malignancies. The seroconversion rates after second dose were ranged from 65.30-87.70% in all cancers, 91.60-96.00% in solid cancers and 58.00-72.60% in hematological malignancies. Cancer types and types of therapy could influence vaccine response. COVID-19 vaccines were safe and well-tolerated. Conclusions: This study suggests COVID-19 vaccine response is significantly lower in cancer patients. Number of received doses, cancer types and treatment strategies could influence response of COVID-19 vaccine in cancer patients. COVID-19 vaccines are safe and well-tolerated. Considering the emergence of several new variants of SARS-CoV-2 with potential influence on ongoing vaccination programs, there is a need for booster doses to increase the effectiveness of COVID-19 vaccines. Systematic review registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022327931, identifier CRD42022327931.