Fahmi Y. Al-Ashwal

Fahmi Y. Al-Ashwal

orcid

Research Focus & Metrics

Academic Career Length

10Years (2017-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

View All Publications
1 September 2023 in Drug, Healthcare and Patient Safety
Verified
Journal Article
Open access
PDF file
FAFahmi Y. Al-Ashwal
Fahmi Y. Al-Ashwal
MZMohammed Zawiah
Mohammed Zawiah
LGLobna Gharaibeh
Lobna Gharaibeh
RFRana Abu Farha
Rana Abu Farha
ABAhmad Bitar
Ahmad Bitar
Background: AI platforms are equipped with advanced ‎algorithms that have the potential to offer a wide range of ‎applications in healthcare services. However, information about the accuracy of AI chatbots against ‎conventional drug-drug interaction tools is limited‎. This study aimed to assess the sensitivity, specificity, and accuracy of ChatGPT-3.5, ChatGPT-4, Bing AI, and Bard in predicting drug-drug interactions. Methods: AI-based chatbots (ie, ChatGPT-3.5, ChatGPT-4, Microsoft Bing AI, and Google Bard) were compared for their abilities to detect clinically relevant DDIs for 255 drug pairs. Descriptive statistics, such as specificity, sensitivity, accuracy, negative predictive value (NPV), and positive predictive value (PPV), were calculated for each tool. Results: When a subscription tool was used as a reference, the specificity ranged from a low of 0.372 (ChatGPT-3.5) to a high of 0.769 (Microsoft Bing AI). Also, Microsoft Bing AI had the highest performance with an accuracy score of 0.788, with ChatGPT-3.5 having the lowest accuracy rate of 0.469. There was an overall improvement in performance for all the programs when the reference tool switched to a free DDI source, but still, ChatGPT-3.5 had the lowest specificity (0.392) and accuracy (0.525), and Microsoft Bing AI demonstrated the highest specificity (0.892) and accuracy (0.890). When assessing the consistency of accuracy across two different drug classes, ChatGPT-3.5 and ChatGPT-4 showed the highest ‎variability in accuracy. In addition, ChatGPT-3.5, ChatGPT-4, and Bard exhibited the highest ‎fluctuations in specificity when analyzing two medications belonging to the same drug class. Conclusion: Bing AI had the highest accuracy and specificity, outperforming Google’s Bard, ChatGPT-3.5, and ChatGPT-4. The findings highlight the significant potential these AI tools hold in transforming patient care. While the current AI platforms evaluated are not without limitations, their ability to quickly analyze potentially significant interactions with good sensitivity suggests a promising step towards improved patient safety.

11 December 2020 in PLOS ONE
Verified
Journal Article
Open access
PDF file
FAFahmi Y. Al-Ashwal
Fahmi Y. Al-Ashwal
MKMohammed Kubas
Mohammed Kubas
MZMohammed Zawiah
Mohammed Zawiah
ABAhmad Bitar
Ahmad Bitar
RSRamzi Mukred Saeed
Ramzi Mukred Saeed
SGSiti Maisharah Sheikh Ghadzi
Siti Maisharah Sheikh Ghadzi
Background: The coronavirus disease of 2019 (COVID-19) represents a difficult challenge and could have devastating consequences for the healthcare system and healthcare workers in war-torn countries with poor healthcare facilities such as Yemen. Our study aimed to evaluate the knowledge, preparedness, counselling practices of healthcare workers regarding COVID-19, and the perceived barriers to adequately prevent and control COVID-19 in Yemen. Methods: Healthcare workers (HCWs) from major healthcare facilities participated in this cross-sectional study. A self-administered questionnaire comprising of five main domains (demographics, knowledge, self-preparedness, counselling practice, perceived barriers) was distributed among HCWs after obtaining informed consent. A convenient sampling technique was used. Descriptive and inferential analyses were applied using SPSS software. Results: A total of 1000 participants were initially targeted to participate in the study with 514 (51.4%) responding, of which 55.3% were female. Physicians and nurses constituted the largest proportion of participants, with 39.5% and 33.3%, respectively. The median scores for knowledge, self-preparedness, and counselling practice were 8 (out of 9), 9 (out of 15), and 25 (out of 30), respectively. The physician group showed a statistically significant association with better knowledge compared to the nurse group only, P<0.001. Males had higher preparedness scores than females, p<0.001. Also, the intensive care unit (ICU) and emergency departments presented a statistically significant difference by which the participants from these departments were more prepared compared to the others (e.g. outpatients, paediatrics and surgery) with P < 0.0001. The lack of awareness among the general population about COVID-19 preventive measures was perceived as the most common barrier for the adequate prevention and control of COVID-19 in Yemen (89.1%). Conclusion: The major highlight of this study is that HCWs have, overall, good knowledge, suboptimal preparedness, and adequate counselling practices prior to the outbreak of COVID-19 in Yemen, despite the high number of perceived barriers. However, urgent action and interventions are needed to improve the preparedness of HCWs to manage COVID-19. The perceived barriers also need to be fully addressed by the local healthcare authorities and international organisations working in Yemen for adequate prevention and control measures to be in place in managing COVID-19.

1 December 2023 in Journal of Multidisciplinary Healthcare
Verified
Journal Article
Open access
PDF file
MZMohammed Zawiah
Mohammed Zawiah
FAFahmi Y. Al-Ashwal
Fahmi Y. Al-Ashwal
LGLobna Gharaibeh
Lobna Gharaibeh
RFRana Abu Farha
Rana Abu Farha
KAKarem Alzoubi
Karem Alzoubi
FAFahd Abrah
Fahd Abrah
Background: The emergence of Chat-Generative Pre-trained Transformer (ChatGPT) by OpenAI has revolutionized AI technology, demonstrating significant potential in healthcare and pharmaceutical education, yet its real-world applicability in clinical training warrants further investigation. Methods: A cross-sectional study was conducted between April and May 2023 to assess PharmD students’ perceptions, concerns, and experiences regarding the integration of ChatGPT into clinical pharmacy education. The study utilized a convenient sampling method through online platforms and involved a questionnaire with sections on demographics, perceived benefits, concerns, and experience with ChatGPT. Statistical analysis was performed using SPSS, including descriptive and inferential analyses. Results: The findings of the study involving 211 PharmD students revealed that the majority of participants were male (77.3%), and had prior experience with artificial intelligence (68.2%). Over two-thirds were aware of ChatGPT. Most students (n= 139, 65.9%) perceived potential benefits in using ChatGPT for various clinical tasks, with concerns including over-reliance, accuracy, and ethical considerations. Adoption of ChatGPT in clinical training varied, with some students not using it at all, while others utilized it for tasks like evaluating drug-drug interactions and developing care plans. Previous users tended to have higher perceived benefits and lower concerns, but the differences were not statistically significant. Conclusion: Utilizing ChatGPT in clinical training offers opportunities, but students’ lack of trust in it for clinical decisions highlights the need for collaborative human-ChatGPT decision-making. It should complement healthcare professionals’ expertise and be used strategically to compensate for human limitations. Further research is essential to optimize ChatGPT’s effective integration.

31 December 2023 in Journal of Pharmaceutical Policy and Practice
Verified
Journal Article
Open access
PDF file
KHKhawla Abu Hammour
Khawla Abu Hammour
HAHamza Alhamad
Hamza Alhamad
FAFahmi Y. Al-Ashwal
Fahmi Y. Al-Ashwal
Abdulsalam M HalboupAbdulsalam M Halboup
Abdulsalam M Halboup
RFRana Abu Farha
Rana Abu Farha
AHAdnan Abu Hammour
Adnan Abu Hammour
The purpose of this study is to find out how much pharmacists know and have used ChatGPT in their practice. We investigated the advantages and disadvantages of utilizing ChatGPT in a pharmacy context, the amount of training necessary to use it proficiently, and the influence on patient care using a survey. This cross-sectional study was carried out between May and June 2023 to assess the potential and problems that pharmacists observed while integrating chatbots powered by AI (ChatGPT) in pharmacy practice. The correlation between perceived benefits and concerns was evaluated using Spearman's rho correlation due to the data's non-normal distribution.Any pharmacists licensed by the Jordanian Pharmacists Association were included in the study. A convenient sampling technique was used to choose the participants, and the study questionnaire was distributed utilizing an online medium (Facebook and WhatsApp). Anyone who expressed interest in taking part was given a link to the study's instructions so they may read them before giving their electronic consent and accessing the survey. The potential advantages of ChatGPT in the pharmacy practice were widely acknowledged by the participants. The majority of participants (69.9%) concurred that educational material about pharmacy items or therapeutic areas can be provided using ChatGPT, with 66.9% of respondents believing that ChatGPT is a machine learning algorithm. Concerns about the accuracy of AI-generated responses were also prevalent. More than half of the participants (55.7%) raised the possibility that AI systems such as ChatGPT could pick up on and replicate prejudices and discriminatory patterns from the data they were trained on. Analysis shows a statistically significant positive link, albeit a minor one, between the perceived advantages of ChatGPT and its drawbacks (r = 0.255, p < 0.001). However, concerns were strongly correlated with knowledge of ChatGPT. In contrast to those who were either unsure or had not heard of ChatGPT (64.2%), individuals who had heard of it were more likely to have strong concerns (79.8%) (p = 0.002). Finally, the results show a statistically significant association between the frequency of ChatGPT use and positive perceptions of the tool (p < 0.001). Although ChatGPT has shown promise in health and pharmaceutical practice, its application should be rigorously regulated by evidence-based law. According to the study's findings, pharmacists support the use of ChatGPT in pharmacy practice but have concerns about its use due to ethical reasons, legal problems, privacy concerns, worries about the accuracy of the data generated, data learning, and bias risk.

17 June 2020 in PLOS ONE
Verified
Journal Article
Open access
PDF file
MZMohammed Zawiah
Mohammed Zawiah
AYAl-Motassem Yousef
Al-Motassem Yousef
Amer Hayat KhanAmer Hayat Khan
Amer Hayat Khan
FAFahmi Y. Al-Ashwal
Fahmi Y. Al-Ashwal
AMAmal Matar
Amal Matar
AAAbdullah Abdulmajid Abdo Ahmed
Abdullah Abdulmajid Abdo Ahmed
Pharmacists have crucial role in providing drug information and medication counseling to patients. This survey aimed to benchmark the current knowledge of the pharmacists concerning food-drug interactions (FDIs) in Jordan. A cross-sectional study was conducted in Amman, the capital and largest city of Jordan, using a validated questionnaire. It was distributed to pharmacists working in community and hospital pharmacies using a convenience sampling technique. Descriptive and inferential statistics were performed in this study. A total of 340 questionnaires distributed, 300 (88%) pharmacists responded. Over 50% of pharmacists claimed that they have sufficient knowledge regarding FDI. Virtually, the overall median (interquartile range) knowledge score was 18 (15–21), approximately 60%. The highest knowledge scores were for alcohol-drug interactions section (66.6%) followed by both common food-drug interactions and the timing of drug intake to food consumption sections with a score of (58.3%) for each, reflecting a suboptimal knowledge of FDIs among the pharmacists. Pharmacists had unsatisfactory knowledge about common FDIs, with no significant difference between hospital and community pharmacists. Therefore, more attention and efforts should be played to improve awareness about potential food-drug interactions.

29 October 2021 in PLOS ONE
Verified
Journal Article
Open access
PDF file
ABAhmad Bitar
Ahmad Bitar
MZMohammed Zawiah
Mohammed Zawiah
FAFahmi Y. Al-Ashwal
Fahmi Y. Al-Ashwal
MKMohammed Kubas
Mohammed Kubas
RSRamzi Mukred Saeed
Ramzi Mukred Saeed
AKAmer Hayat Khan
Amer Hayat Khan
Background: Since the beginning of the COVID-19 outbreak, many pharmaceutical companies have been racing to develop a safe and effective COVID-19 vaccine. Simultaneously, rumors and misinformation about COVID-19 are still widely spreading. Therefore, this study aimed to investigate the prevalence of COVID-19 misinformation among the Yemeni population and its association with vaccine acceptance and perceptions. Methods: A cross-sectional online survey was conducted in four major cities in Yemen. The constructed questionnaire consisted of four main sections (sociodemographic data, misinformation, perceptions (perceived susceptibility, severity, and worry), and vaccination acceptance evaluation). Subject recruitment and data collection were conducted online utilizing social websites and using the snowball sampling technique. Descriptive and inferential analyses were performed using SPSS version 27. Results: The total number of respondents was 484. Over 60% of them were males and had a university education. More than half had less than 100$ monthly income and were khat chewers, while only 18% were smokers. Misinformation prevalence ranged from 8.9% to 38.9%, depending on the statement being asked. Men, university education, higher income, employment, and living in urban areas were associated with a lower misinformation level (p <0.05). Statistically significant association (p <0.05) between university education, living in urban areas, and being employed with perceived susceptibility were observed. The acceptance rate was 61.2% for free vaccines, but it decreased to 43% if they had to purchase it. Females, respondents with lower monthly income, and those who believed that pharmaceutical companies made the virus for financial gains were more likely to reject the vaccination (p <0.05). Conclusion: The study revealed that the acceptance rate to take a vaccine was suboptimal and significantly affected by gender, misinformation, cost, and income. Furthermore, being female, non-university educated, low-income, and living in rural areas were associated with higher susceptibility to misinformation about COVID-19. These findings show a clear link between misinformation susceptibility and willingness to vaccinate. Focused awareness campaigns to decrease misinformation and emphasize the vaccination’s safety and efficacy might be fundamental before initiating any mass vaccination in Yemen.