Digital Transformation Dissertations

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    Evaluating the Impact of Electronic Prescription Services on Workflow Efficiencies in Community Pharmacies of Dublin, Ireland.
    (2024) Vattamkandathil Tomy, Ardra
    The integration of Electronic Prescription Services (EPS) represents a significant advancement in the healthcare sector, designed to enhance the accuracy and efficiency of prescription management. By enabling the electronic transmission of prescriptions from healthcare providers to pharmacies, EPS aims to reduce the errors associated with traditional paper-based prescriptions and streamline pharmacy operations. Despite its potential benefits, the implementation of EPS presents various challenges, including technical integration and the need for comprehensive staff training. This research investigates the impact of Electronic Prescription Services (EPS) on community pharmacies in Dublin, Ireland, examining areas such as prescription accuracy, workflow efficiency, pharmacist satisfaction, and implementation challenges. EPS, an advancement in healthcare, facilitates the electronic transmission of prescriptions from healthcare providers to pharmacies, aiming to enhance patient safety, streamline operations, and reduce errors compared to traditional paper prescriptions. Despite EPS’s potential benefits, including improved prescription accuracy and operational efficiency, community pharmacies face challenges such as technical integration issues and the need for effective staff training. This study employs a quantitative methodology, using surveys distributed to pharmacists and pharmacy staff, to evaluate these impacts comprehensively. Adopting a pragmatic research philosophy and an inductive approach, the study collects and analyzes primary data to understand the operational changes brought about by EPS. Data analysis, performed using JASP software, involved descriptive and inferential statistical techniques, including Chi-square and Kendall’s Tau tests, to assess relationships between EPS implementation and various performance metrics. The findings reveal significant associations: improved communication with prescribers correlates moderately with reduced prescription errors, and overall pharmacist satisfaction is strongly associated with the ease of EPS use and improvements in medication inventory management. Workflow efficiency showed notable improvements in prescription processing time, daily volume, patient waiting time, and counselling ability, though increased processing time was linked to reduced efficiency. Confidence in EPS is high, particularly regarding its role in identifying potential medication interactions. The study concludes that EPS positively impacts several facets of pharmacy operations, enhancing prescription accuracy, workflow efficiency, and pharmacist satisfaction, while increasing confidence in the system. Nonetheless, further attention is needed to address training and technical challenges associated with EPS implementation.
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    Assessing Perception and Adoption of Robotics Among Healthcare Professionals in Kerala : A Quantitative Study on Acceptance of Robotics Within Healthcare Sector.
    (2024) Mathew, Christeena
    Robotics, initially developed for automation and precision tasks across various industries, have now established a vital role in healthcare by alleviating burdens for both patients and medical professionals. This study primarily seeks to investigate how healthcare professionals in Kerala perceive robotics and to assess the extent of their adoption of these technologies. It aims to understand the acceptance of robotics in the healthcare sector, providing insights into potential barriers and facilitators for integrating robotics into medical practice in Kerala. Utilizing the Technology Acceptance Model (TAM) and employing structured surveys and statistical analysis, the study delivers robust insights into the current state of robotics integration in healthcare by assessing the perceptions of professionals employed in hospitals, clinics, and other healthcare facilities across Kerala. Surveying 70 healthcare professionals, the research unveils significant enthusiasm, particularly among younger professionals aged 24-34. Overall, 67% of the respondents recognize the benefits of robotics in automating routine tasks, enhancing surgical precision, and improving operational efficiency through error reduction. The study highlights key challenges: 49% of respondents report a lack of comprehensive training as a major barrier to training, while 38% cite financial constraints as major challenge to broader adoption. Despite these challenges, 53% of professionals express strong support for integrating robotics, showcasing their readiness to leverage technology for enhanced patient care and surgical outcomes.Additionally, the study identifies a positive relationship between increased awareness of robotics and greater comfort in using this technology, suggesting that enhancing knowledge could significantly improve comfort levels and adoption rates among healthcare professionals. These findings underscore a generational shift towards embracing advanced technologies and emphasize the need for targeted training programs and strategic policy development to facilitate the adoption of robotics, aiming to make healthcare services in Kerala more precise, efficient, and cost-effective.
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    The Knowledge, Attitude And Practice Of Pharmacists Towards the Use And Development Of Robotics Pharmacies In Hospital Pharmacies Settings In India
    (2024-05) Biju Kumar, Devika
    This study explores the knowledge, attitudes, and behaviours of Indian pharmacists on the adoption and usage of robotic pharmacies in hospital settings. It aims to determine the advantages, disadvantages, and accuracy of robotic pharmacy systems in terms of medication administration and patient safety. Using a pragmatic research mindset and a deductive technique, the study gathered qualitative and quantitative data from 85 pharmacists via an online survey. The findings show that, while there is considerable interest and positive feedback regarding robotic pharmacies, significant limitations such as financial restrictions, regulatory compliance, and labor adaptability prevent widespread implementation. The research's results show that there is a positive correlation between the perceived benefits of robotic pharmacy and their current and future use in hospitals. Pharmacists understand whether these technologies may reduce drug errors, increase operational efficiency, and improve patient safety. However, concerns regarding job displacement, machine dependability, and managing complex medication remain. The study emphasizes the importance of extensive training programs, cost-benefit analyses, and staff transition management measures in order to optimize the benefits of robotic pharmacies. The study's hypotheses testing indicated beneficial connections between knowledge, attitudes, and the use of robotic systems, emphasizing the relevance of education and training in fostering acceptance and successful implementation. Despite the limitations, the promise for robotic pharmacies to transform healthcare delivery by enhancing medication management is clear. Future advances in artificial intelligence and machine learning are projected to improve these systems capabilities.To summarize, while robotic pharmacies provide considerable benefits, overcoming the previously mentioned challenges through strategic planning, regulatory compliance, and education is critical for their successful integration into Indian hospital pharmacies. The study offers useful information for stakeholders and policymakers seeking to develop best practices and promote the effective implementation of robotic pharmacies, eventually increasing patient care and operational efficiency.
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    Utilizing Artificial Intelligence (Machine learning algorithms) for Process Optimization in Pharmaceutical Manufacturing Processes
    (2024-05) Adelodun Johnson, Arafat
    Digital transformation has introduced smart manufacturing, artificial intelligence, IoT, and advanced computerization to the pharmaceutical industry to drive Process Optimization. This plays a crucial role in the pharmaceutical industry as the complexity of manufacturing processes presents multidimensionality of product design, process development and product manufacturing data. While statistical techniques such as multivariate data analysis has made significant contribution to the pharmaceutical sector, its application can only be subjected to one process at a time in terms of providing support for quality-by-design based development and manufacturing of pharmaceuticals, limiting the enormous potential for automation. By leveraging machine learning, manufacturing processes can be streamlined to mitigate challenges associated with variability and complexity through predictive analysis of the large volume of data generated by PAT. This paper aims to provide a critical overview of how ML can be applied during various stages of the manufacturing process through a comprehensive analysis of existing literature from peer-reviewed journals, books, academic papers with illustrative examples applied in the context of pharmaceutical formulation development and related technologies as well as future trends. The study also aims to gain objective insights regarding the use of ML in pharmaceutical dosage manufacturing by exploring the opinions and perspectives of professionals actively involved in pharmaceutical manufacturing processes. With an estimated sample size of 90 participants, the study utilised an online survey-questionnaire that was administered to process managers, operators, industry experts, quality assurance and control officers to gather quantitative data in Ireland. An overall response rate of 69% was obtained and their opinion was evaluated in line with reviewed literature. The outcome of the study demonstrated the potential benefits that ML had to offer the pharmaceutical industry, the current applications, the limitations, and regulatory issues surrounding the adoption of ML in pharmaceutical manufacturing from both primary and secondary data sources.
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    The impact of Smart Manufacturing on the Digital Maturity of Medical Device Industry
    (2024-05) Dattaram Solkar, Ankita
    The study explores the impact of smart manufacturing on the digital maturity of the medical device industry. The research aims to assess smart manufacturing technologies contributions to digital maturity, focusing on technological advancements, connectivity features, and overall industry improvements. The literature review highlights the importance of operational efficiency, quality improvement, product customization, and regulatory compliance as primary drivers for adopting digital technologies in the medical device industry. Additionally, the study emphasizes the significance of a robust data strategy, seamless digital integration, and smart manufacturing practices. The study adopts a mixed-methods approach, combining qualitative and quantitative data to understand the impact of smart manufacturing on digital maturity, involving a comprehensive literature review and a survey of industry professionals from India and Ireland. Findings suggest that digital maturity positively impacts operational efficiency and product quality, with potential benefits including enhanced quality, efficiency, and innovation through advanced technologies like AI, IoT, and big data analytics. However, challenges such as data security and system interoperability need to be addressed. The research recommends a supportive organizational culture, leadership commitment, and continuous employee training to drive digital maturity, ultimately fostering innovation and competitiveness.