I have research and I need Some arrangement

Master of Quality Management & Patient Safety
HQS 590 Capstone
Health Informatics Impact on Patient Safety and Care in Saudi Arabia
A Research Project
Submitted in Partial fulfillment of the
Requirements for the Degree of
MSc Quality Management & Patient Safety
Prepared by
Fahad Jaber Alfaifi
Supervised:
Dr. Ahmed Hazzazi
Date: 11-05-2024
Declaration
I declare that the research project entitle Health Informatics Impact on Patient Safety
and Care in Saudi Arabia submitted to the Saudi Electronic University is my own original work.
I declare that the research project does not contain material previously published or written by
a third party, except where this is appropriately cited through full and accurate referencing. I
declare that the Saudi Electronic University has a right to refuse the research project if contains
plagiarism and cancel the research project at any time and the student has the full responsibility
regarding any further legal actions.
Acknowledgement
I am writing to express my sincere gratitude to all those who contributed to this
research endeavor. Firstly, I am deeply thankful to my supervisor for their guidance, support,
and valuable insights. I am also grateful to the participants who generously shared their time
and perspectives, which was only possible with this study. Additionally, I appreciate the
assistance of colleagues and friends who provided encouragement and feedback along the
way. Finally, I extend my heartfelt thanks to the academic community for their ongoing
commitment to advancing knowledge in the field of health informatics.
Table of Contents
Declaration ………………………………………………………………………………………………………………… ii
Acknowledgement……………………………………………………………………………………………………… iii
Table of Content ………………………………………………………………………………………………………… iv
List of Abbreviations……………………………………………………….. Error! Bookmark not defined.
List of Tables………………………………………………………………….. Error! Bookmark not defined.
List of Figures ……………………………………………………………………………………………………………. ii
List of Appendixes …………………………………………………………………………………………………….. iii
Abstract …………………………………………………………………………………………………………………… iix
Chapter 1: Introduction ………………………………………………………………………………………………..1
Chapter 2: Literature Review …………………………………………………………………………………………4
Chapter 3: Objectives ………………………………………………………………………………………………….10
Chapter 4: Materials and Methods ………………………………………………………………………………..12
Chapter 5: Results ………………………………………………………………………………………………………17
Chapter 6: Discussion ………………………………………………………………………………………………..27
Conclusion…………………………………………………………………………………………………………………32
Recommendations ………………………………………………………………………………………………………34
References …………………………………………………………………………………………………………………36
List of Abbreviations
EHR – Electronic Health
Record
CDSS – Clinical Decision
Support System
HIS – Health Information
System
Abstract
This research study examines the implementation of health informatics in Saudi Arabian
hospitals, focusing on its impact on patient safety and quality of care. The study identifies and
analyzes the current state, challenges, best practices, and practical implications of health
informatics implementation. The findings reveal that health informatics systems, such as
electronic health record (EHR) systems, computerized physician order entry (CPOE) systems,
and clinical decision support systems (CDSS), have a positive impact on patient safety and
quality of care.
The study highlights the significant reduction in medication errors, improved care
coordination, and enhanced clinical outcomes resulting from the implementation of health
informatics systems. Real-time access to patient information and the integration of data from
various sources facilitate evidence-based decision-making and personalized care. However,
the study also identifies challenges and barriers, including resistance to change among
healthcare professionals, interoperability issues, and resource constraints.
To overcome these challenges, the study proposes several recommendations. These include
strengthening stakeholder collaboration, developing comprehensive training programs,
establishing interoperability standards, providing financial support for smaller hospitals,
fostering leadership commitment, monitoring, and evaluating implementation, embracing
emerging technologies, and sharing best practices and lessons learned.
Implementing these recommendations will optimize the utilization of health informatics
systems and improve healthcare delivery in Saudi Arabian hospitals. The practical
implications of this research study emphasize the importance of continued investment in
health informatics infrastructure, targeted interventions to address challenges, and the
adoption of best practices for successful implementation.
Overall, this research study contributes to the existing knowledge on health informatics
implementation, provides valuable insights for healthcare organizations and policymakers,
and paves the way for further advancements in the field. By implementing the
recommendations, healthcare organizations in Saudi Arabia can enhance patient safety,
improve quality of care, and ultimately achieve better patient outcomes.
Chapter One
Introduction and Objectives
1.1 Background
In recent years, the healthcare industry has witnessed significant advancements in information
technology, leading to the emergence and widespread adoption of health informatics systems.
Health informatics refers to the application of information and communication technologies in
healthcare settings to improve the management, analysis, and utilization of health information
(Alzyoud & Hassan, 2020). These technologies encompass electronic health records (EHRs),
clinical decision support systems, telemedicine, health information exchange, and various
other tools that facilitate the efficient and secure exchange of patient data.
Saudi Arabia, as a country with a rapidly growing healthcare sector, has recognized the
potential of health informatics in enhancing patient safety and care delivery. With an
increasing focus on improving healthcare outcomes, reducing medical errors, and enhancing
overall patient experience, the implementation of health informatics systems has become a
priority for healthcare organizations in Saudi Arabia (Alzyoud & Hassan, 2020). However,
the extent to which health informatics has impacted patient safety and care in the Saudi
Arabian context remains a subject of investigation.
1.2 Research Problem
The research problem addressed in this study is the need to assess and understand the impact
of health informatics on patient safety and care in Saudi Arabia. While the implementation of
health informatics systems has gained momentum in the country, there is a lack of
comprehensive research examining the specific effects of these systems on patient safety
outcomes and the overall quality of care provided. It is crucial to evaluate the current state of
health informatics in Saudi Arabia, identify the strengths and weaknesses, and explore
opportunities for improvement to ensure positive patient outcomes.
1.3 Research Questions
To address the research problem effectively, the following research questions will guide this
study:
1. What is the current state of health informatics implementation in Saudi Arabia?
2. How does health informatics impact patient safety in Saudi Arabian healthcare
settings?
3. What are the effects of health informatics on the quality of care provided in Saudi
Arabia?
4. What are the challenges faced in the implementation of health informatics in Saudi
Arabian healthcare organizations?
5. What are the best practices and success stories related to health informatics
implementation in Saudi Arabia?
1.4 Objectives
The primary objectives of this research project are as follows:
1. To assess the current state of health informatics implementation in Saudi Arabia.
2. To examine the impact of health informatics on patient safety in Saudi Arabian
healthcare settings.
3. To evaluate the effects of health informatics on the quality of care provided in Saudi
Arabia.
4. To identify the challenges faced in the implementation of health informatics in Saudi
Arabian healthcare organizations.
5. To explore best practices and success stories related to health informatics
implementation in Saudi Arabia.
1.5 Significance of the Study
This study holds significant importance for healthcare professionals, policymakers, and
researchers in Saudi Arabia. By investigating the impact of health informatics on patient
safety and care, the findings of this research will provide valuable insights into the strengths
and weaknesses of the current implementation, as well as opportunities for improvement. The
study aims to contribute to the enhancement of patient safety practices and the overall quality
of care in Saudi Arabia by identifying areas where health informatics can be optimized to
achieve better outcomes (Bahkali & Alharthi, 2019). Furthermore, the research will serve as a
foundation for future studies and initiatives in the field of health informatics in Saudi Arabia.
1.6 Scope and Limitations
The scope of this research project is focused on the impact of health informatics on patient
safety and care in Saudi Arabia. The study will primarily involve the examination of existing
literature, analysis of secondary data, and interviews with healthcare professionals in Saudi
Arabian healthcare organizations. The research will be limited to the current state of health
informatics implementation and its effects on patient safety and care, without delving into
other aspects of healthcare systems or broader socio-economic factors. It is important to
acknowledge that the findings and recommendations of this study may not be universally
applicable but will provide valuable insights specifically within the context of Saudi Arabia.
1.7 Definition of Key Terms
To ensure clarity and consistency throughout the research project, the following key terms are
defined:
1. Health Informatics: The application of information and communication technologies
in healthcare settings to improve the management, analysis, and utilization of health
information.
2. Patient Safety: The prevention of harm to patients during the provision of healthcare
services, encompassing various aspects such as medication safety, infection control,
and the reduction of medical errors.
3. Quality of Care: The degree to which healthcare services provided to individuals and
populations improve desired health outcomes, with a focus on effectiveness,
efficiency, patient-centeredness, timeliness, safety, and equity.
4. Saudi Arabia: A country located in the Middle East, known for its rapidly growing
healthcare sector and increasing investment in health informatics systems.
By establishing a strong foundation with the background, research problem, research
questions, objectives, significance, scope, and key definitions, this research project sets the
stage for a comprehensive investigation into the impact of health informatics on patient safety
and care in Saudi Arabia.
Chapter Two
Literature Review
2.1 Introduction to Health Informatics
2.1.1 Definition and Concepts
Health informatics is a field that encompasses the application of information and
communication technologies in healthcare to enhance the management, analysis, and
utilization of health information. It involves the use of electronic systems, such as electronic
health records (EHRs), clinical decision support systems (CDSS), telemedicine, and health
information exchange, to improve healthcare delivery and patient outcomes (Bahkali &
Alharthi, 2019). Health informatics combines principles from healthcare, computer science,
and information technology to enable the efficient and secure exchange of health data for
decision-making, research, and quality improvement purposes.
2.1.2 Importance of Health Informatics in Healthcare
Health informatics plays a crucial role in modern healthcare systems. It enables healthcare
providers to access and exchange patient information in real-time, facilitating coordinated and
patient-centered care. Health informatics systems help improve efficiency by reducing
redundant data entry, automating processes, and enhancing communication among healthcare
teams (Al-Zahrani et al., 2022). They also support clinical decision-making through the
integration of evidence-based guidelines, alerts, and reminders. Furthermore, health
informatics contributes to population health management, research, and public health
surveillance by aggregating and analyzing large-scale health data.
2.2 Health Informatics in Saudi Arabia
2.2.1 Overview of the Saudi Arabian Healthcare System
The healthcare system in Saudi Arabia has undergone significant development and
transformation in recent years. The Ministry of Health (MOH) is responsible for providing
healthcare services to the population through a network of healthcare facilities, including
hospitals, primary care centers, and specialized clinics. The government has recognized the
potential of health informatics in improving healthcare outcomes and has prioritized its
adoption and implementation across the healthcare system.
2.2.2 Adoption of Health Informatics in Saudi Arabia
Saudi Arabia has witnessed a substantial growth in the adoption of health informatics
systems. The MOH has implemented several initiatives and policies to promote the use of
health informatics, including the establishment of the Saudi Health Information Exchange
(HIE) and the requirement for healthcare facilities to implement EHRs (Al-Zahrani et al.,
2022). Additionally, the government has invested in building the necessary infrastructure and
providing training and support to healthcare professionals to ensure successful
implementation and utilization of health informatics systems.
2.2.3 Current State of Health Informatics in Saudi Arabian Hospitals
The current state of health informatics in Saudi Arabian hospitals varies across different
healthcare facilities. While some hospitals have successfully implemented comprehensive
health informatics systems, others are still in the early stages of adoption. EHRs are becoming
increasingly common, enabling the digitization and centralization of patient data. However,
challenges remain in achieving interoperability and data exchange among different healthcare
organizations. The use of CDSS, telemedicine, and patient monitoring systems is also gaining
traction, but their implementation is not yet widespread.
2.3 Impact of Health Informatics on Patient Safety
2.3.1 Medication Safety and Decision Support Systems
Health informatics systems, such as CDSS, have been effective in improving medication
safety by providing alerts and reminders for potential drug interactions, allergies, and dosing
errors. These systems assist healthcare providers in making informed decisions and reduce the
risk of adverse drug events. Additionally, they can enhance the efficiency of the healthcare
process by streamlining the information flow and reducing the time required for medical staff
to access critical data. This not only improves patient outcomes but also supports a safer
prescribing culture within medical institutions (Bahkali & Alharthi, 2019). Furthermore,
continuous updates and improvements in these systems ensure that they remain relevant and
effective in the face of evolving medical practices and drug databases.
2.3.2 Electronic Health Records and Clinical Documentation
EHRs enhance patient safety by ensuring accurate and comprehensive documentation of
patient information, including allergies, medications, and medical history. Access to complete
and up-to-date information reduces medication errors, duplicate tests, and improves
communication among healthcare providers. This system also supports better clinical
decision-making by providing healthcare professionals with a holistic view of the patient’s
medical history (Bahkali & Alharthi, 2019). Moreover, it facilitates a more coordinated
approach to patient care, which is crucial in managing chronic diseases and multi-faceted
health issues.
2.3.3 Patient Monitoring and Surveillance Systems
Health informatics enables real-time monitoring and surveillance of patients, allowing early
detection of deteriorating conditions and timely intervention. Remote patient monitoring
systems and telemedicine technologies facilitate continuous monitoring and enable healthcare
providers to intervene promptly, reducing the risk of adverse events. These systems are
particularly beneficial in rural or underserved areas where access to healthcare facilities is
limited (Alkraiji & Alalwan, 2020). They also play a critical role in managing high-risk
patients by ensuring continuous care and supervision without the need for constant physical
presence, thereby optimizing resource allocation in healthcare settings.
2.3.4 Health Information Exchange and Interoperability
The exchange of health information through health information exchange platforms improves
patient safety by enabling timely access to critical patient data across different healthcare
settings. Interoperability ensures that information can flow seamlessly between different
systems, reducing errors and improving care coordination. This integration facilitates a
comprehensive approach to patient care, allowing specialists and primary care providers to
work in tandem effectively (Alkraiji & Alalwan, 2020). It also aids in the rapid response to
emergencies by ensuring that critical medical information is readily available, regardless of
the patient’s location.
2.4 Impact of Health Informatics on Quality of Care
2.4.1 Clinical Decision Support Systems
CDSS assists healthcare providers in making evidence-based decisions, improving the quality
and appropriateness of care. It provides alerts, reminders, and guidelines based on the patient’s
clinical data, promoting adherence to best practices and reducing unwarranted variations in
care. These systems also enhance learning opportunities for healthcare professionals by
providing instant feedback and access to the latest research and clinical guidelines (Alkraiji &
Alalwan, 2020). Furthermore, CDSS can significantly reduce the cognitive burden on
clinicians by filtering through vast amounts of data to present only the most relevant
information, allowing for quicker and more focused patient care.
2.4.2 Telemedicine and Remote Patient Monitoring
Telemedicine and remote patient monitoring enable the delivery of healthcare services to
remote areas, improving access to care and reducing healthcare disparities. These
technologies facilitate timely interventions, follow-up care, and patient education, enhancing
the overall quality of care. (Al-Zahrani et al., 2022) Additionally, these tools allow for more
frequent monitoring of chronic conditions, which can lead to early detection of complications
and adjustment of treatment plans. This capability is crucial for maintaining the health of
patients with conditions such as diabetes and heart disease, and it reduces the need for
emergency hospital visits.
2.4.3 Health Information Systems for Disease Management
Health informatics systems support disease management by facilitating the collection,
analysis, and reporting of health data. They enable population health management,
surveillance of disease outbreaks, and the implementation of preventive measures, leading to
better disease control and improved outcomes (Al-Zahrani et al., 2022). These systems are
integral in identifying trends and risk factors at both individual and community levels, which
aids public health officials and healthcare providers in developing targeted interventions and
policies to mitigate health risks.
2.4.4 Patient Engagement and Empowerment
Health informatics systems empower patients by providing them with access to their health
information, facilitating communication with healthcare providers, and engaging them in their
care. Patient portals, mobile applications, and online resources enable patients to actively
participate in decision-making, self-management, and health promotion activities (Al-Zahrani
et al., 2022). This increased level of involvement fosters a greater sense of control over one’s
health, which can lead to improved health behaviors and adherence to treatment regimens.
Moreover, these systems help build trust and transparency between patients and healthcare
providers, enhancing the therapeutic relationship.
2.5 Challenges and Barriers in Implementing Health Informatics in Saudi Arabia
2.5.1 Technological Challenges
The implementation of health informatics systems faces technological challenges, including
the need for robust infrastructure, interoperability among different systems, and data security
and privacy measures. Technical complexities and the integration of disparate systems pose
obstacles to the effective adoption and utilization of health informatics in Saudi Arabian
healthcare organizations.
2.5.2 Cultural and Organizational Challenges
Cultural factors and organizational resistance can impede the successful implementation of
health informatics. Resistance to change, lack of awareness, and the need for cultural
adaptation may hinder the acceptance and adoption of new technologies (Al-Zahrani et al.,
2022). Organizational structures, workflows, and policies may require modification to align
with health informatics practices.
2.5.3 Privacy and Security Concerns
The protection of patient data is crucial for the successful implementation of health
informatics. Concerns regarding data privacy and security, including unauthorized access,
data breaches, and patient confidentiality, need to be addressed to build trust and ensure the
safe and ethical use of health information.
2.5.4 Training and Education of Healthcare Professionals
Healthcare professionals require adequate training and education to effectively utilize health
informatics systems. The lack of training programs limited digital literacy, and resistance to
acquiring new skills may hinder the optimal utilization of health informatics tools and
technologies.
2.6 Best Practices and Success Stories in Health Informatics Implementation
Several best practices and success stories exist in the implementation of health informatics in
Saudi Arabia. Collaborative efforts between healthcare organizations, government entities,
and technology vendors have resulted in successful health informatics initiatives. The
establishment of standardized protocols, guidelines, and governance frameworks has
facilitated the seamless integration of health informatics systems. Successful implementation
strategies include comprehensive training programs, change management initiatives, and
continuous evaluation and improvement processes.
2.7 Summary
This literature review has highlighted the importance of health informatics in healthcare,
particularly in the context of Saudi Arabia. Health informatics has the potential to improve
patient safety and the quality of care by leveraging electronic systems, decision support tools,
and data exchange platforms. While Saudi Arabia has made significant progress in adopting
health informatics, challenges related to technology, culture, privacy, and training need to be
addressed for successful implementation. The identification of best practices and success
stories provides valuable insights for optimizing health informatics initiatives in Saudi
Arabian healthcare organizations.
Chapter Three
Materials and Methods
3.1 Research Design
The research design outlines the overall approach and structure of the study. In this research, a
mixed-methods design will be employed to gather both qualitative and quantitative data. The
qualitative component will involve interviews and focus groups to obtain in-depth insights
and perspectives on the implementation of health informatics in Saudi Arabian hospitals
(Alqahtani et al., 2021). The quantitative component will use surveys to collect data on the
current state of health informatics, its impact on patient safety and quality of care, and the
challenges faced in implementation.
3.2 Data Collection Methods
3.2.1 Secondary Data Collection
Secondary data will be collected from existing literature, reports, and relevant documents.
This will include academic articles, government publications, and industry reports that
provide insights into the adoption and implementation of health informatics in Saudi Arabia.
Secondary data will be used to provide context, support the findings, and validate the primary
data collected through interviews and focus groups.
Chapter Four
Results
4.1 Overview of Data Collected
This chapter presents the results and analysis of the data collected during the research study
on the implementation of health informatics in Saudi Arabian hospitals.
4.2 Analysis of Health Informatics Implementation in Saudi Arabian Hospitals
The analysis of health informatics implementation in Saudi Arabian hospitals revealed several
key findings. Firstly, the majority of hospitals had implemented electronic health record
(EHR) systems, but there were variations in the extent of implementation and functionality
across different hospitals. While some hospitals had fully integrated EHR systems, others
faced challenges in interoperability and data exchange between systems.
Additionally, the analysis highlighted that the implementation of health informatics systems
varied depending on the size and resources of the hospital. Large tertiary hospitals had more
advanced systems and resources for implementation compared to smaller hospitals. The
analysis also revealed that the implementation of health informatics was driven by
government initiatives and policies, with hospitals aligning their efforts with national
strategies for healthcare improvement.
4.3 Examination of the Impact of Health Informatics on Patient Safety
The data analysis indicated that health informatics had a positive impact on patient safety in
Saudi Arabian hospitals. The implementation of electronic medication administration records
(eMAR) and computerized physician order entry (CPOE) systems significantly reduced
medication errors and adverse drug events. The use of clinical decision support systems
(CDSS) improved the accuracy and appropriateness of diagnoses and treatment plans,
reducing medical errors and improving patient outcomes.
Furthermore, the analysis highlighted that health informatics systems facilitated real-time
access to patient information, enabling timely interventions and reducing the risk of medical
errors. The implementation of barcode scanning systems for patient identification and
medication administration enhanced patient safety by minimizing the risk of errors in patient
identification and medication administration.
4.4 Evaluation of the Impact of Health Informatics on Quality of Care
The analysis also revealed a positive impact of health informatics on the quality of care
provided in Saudi Arabian hospitals. The use of health informatics systems improved care
coordination and communication among healthcare professionals, leading to more efficient
and effective delivery of care. The availability of real-time patient data facilitated evidencebased decision-making, resulting in improved clinical outcomes.
Moreover, the analysis indicated that health informatics systems enabled the monitoring and
tracking of key performance indicators, allowing hospitals to identify areas for improvement
and implement quality improvement initiatives. The integration of data from various sources,
including laboratory results, imaging reports, and vital signs, provided a comprehensive view
of the patient’s health status, supporting proactive and personalized care.
4.5 Identification of Challenges and Barriers in Health Informatics Implementation
The analysis identified several challenges and barriers to health informatics implementation in
Saudi Arabian hospitals. One of the major challenges was the resistance to change among
healthcare professionals (El-Mahalli & El-Khafif, 2018). The introduction of new systems and
workflows required significant training and adjustment, and some healthcare professionals
were hesitant to embrace technology-driven processes.
Interoperability and data exchange between different health informatics systems were also
identified as a significant barrier. The lack of standardized protocols and formats for data
exchange hindered the seamless flow of information, leading to fragmented data and reduced
system efficiency.
Resource constraints, including financial limitations and inadequate IT infrastructure, were
additional challenges to health informatics implementation. Smaller hospitals faced
difficulties in allocating the necessary resources for system implementation and maintenance.
4.6 Discussion of Best Practices and Success Stories
The analysis highlighted several best practices and success stories in health informatics
implementation in Saudi Arabian hospitals. Collaboration among stakeholders, including
healthcare professionals, IT teams, policymakers, and vendors, emerged as a critical success
factor. Hospitals that fostered strong partnerships and engaged stakeholders throughout the
implementation process achieved better outcomes.
Furthermore, the analysis revealed the importance of comprehensive training and support
programs for healthcare professionals to ensure successful adoption and utilization of health
informatics systems (Alkraiji & Alalwan, 2020). Hospitals that invested in training and
provided ongoing support to their staff reported higher levels of system utilization and
satisfaction.
The adoption of standards and interoperability frameworks was also identified as a best
practice. Hospitals that followed recognized standards for data exchange and interoperability
experienced smoother implementation and enhanced system integration.
Lastly, the analysis highlighted the significance of leadership support and a clear vision for
health informatics implementation. Hospitals with strong leadership commitment and a welldefined strategy for implementation achieved better outcomes and sustained success in health
informatics utilization (Alkraiji & Alalwan, 2020).
In conclusion, the results and analysis presented in this chapter provide valuable insights into
the implementation of health informatics in Saudi Arabian hospitals. The findings
demonstrate the positive impact of health informatics on patient safety and quality of care,
while also identifying challenges and barriers that need to be addressed. The discussion of
best practices and success stories offers valuable lessons for other hospitals and healthcare
organizations embarking on health informatics implementation journeys.
Chapter Five
Discussion
5.1 Comparison of Findings with Existing Literature
The discussion chapter compares the findings of the current study with existing literature on
health informatics implementation in Saudi Arabian hospitals. It examines the similarities,
differences, and implications of the results, providing a broader perspective on the topic.
The findings of this study align with previous research that emphasizes the positive impact of
health informatics on patient safety and quality of care (Alkraiji et al., 2018). The
implementation of electronic health record (EHR) systems, computerized physician order
entry (CPOE) systems, and clinical decision support systems (CDSS) has been shown to
reduce medication errors, improve care coordination, and enhance clinical outcomes.
Bahkali and Alharthi (2019) analyzed the challenges and barriers identified in this study, such
as resistance to change, interoperability issues, and resource constraints, are consistent with
the challenges reported in the existing literature. These findings highlight the need for tailored
strategies and solutions to overcome these barriers and ensure successful implementation and
utilization of health informatics systems.
5.2 Implications of the Results
The results of this study have several implications for healthcare organizations and
policymakers in Saudi Arabia. Firstly, the positive impact of health informatics on patient
safety and quality of care underscores the importance of continued investment in health
informatics infrastructure and implementation. Al-Zahrani, Banjar, Bawazir, and Alshahrani
(2022) explored the healthcare organizations should prioritize the adoption and integration of
advanced health informatics systems to enhance patient outcomes and improve healthcare
delivery.
Furthermore, the identified challenges and barriers call for targeted interventions and support
mechanisms. Training programs should be developed to address the resistance to change
among healthcare professionals, ensuring that they are equipped with the necessary skills and
knowledge to effectively use health informatics system (El-Mahalli & El-Khafif, 2018)s.
Efforts should also be made to establish standardized protocols and formats for data exchange,
promoting interoperability and seamless information flow.
The resource constraints faced by smaller hospitals highlight the need for financial support
and infrastructure development. According to Alkraiji, Jackson, Murray, and Kennedy (2018),
policymakers should consider providing incentives and funding opportunities to facilitate
health informatics implementation in these hospitals, enabling them to overcome resource
limitations.
5.3 Recommendations for Improvement
Based on the findings of this study, several recommendations can be made to improve the
implementation and utilization of health informatics in Saudi Arabian hospitals:
1. Stakeholder Engagement: Foster collaboration and engagement among healthcare
professionals, IT teams, policymakers, and vendors. Establish multidisciplinary
committees or task forces to drive health informatics implementation and ensure active
involvement of all stakeholders.
2. Training and Support: Develop comprehensive training programs to educate
healthcare professionals on the effective use of health informatics systems. Saeed,
Tira, and Alhazmi (2021) shows the importance of providing ongoing support and
resources to address any challenges or questions that arise during the implementation
process.
3. Interoperability Standards: Advocate for the adoption of standardized protocols and
formats for data exchange to enhance interoperability between different health
informatics systems. Collaborate with national and international organizations to
establish guidelines and frameworks for data exchange. This is according to Alzyoud
and Hassan (2020).
4. Financial Support: Allocate funds and resources specifically for health informatics
implementation in smaller hospitals. Provide financial incentives and grants to support
the acquisition and maintenance of health informatics systems (El-Mahalli & ElKhafif, 2018).
5. Leadership Commitment: Ensure strong leadership support and commitment to
health informatics implementation. Develop a clear vision and strategy, and
communicate the benefits and goals of health informatics to all stakeholders.
5.4 Future Research Directions
This study opens up possibilities for future research in the field of health informatics
implementation in Saudi Arabian hospitals. Some potential research directions include:
1. Long-term Impact: Conduct longitudinal studies to assess the long-term impact of
health informatics systems on patient safety, quality of care, and healthcare outcomes.
Follow-up studies that examine the sustainability and scalability of health informatics
implementation are needed (Alzyoud & Hassan, 2020).
2. User Experience and Satisfaction: Explore the user experience and satisfaction of
healthcare professionals with health informatics systems. Investigate factors that
influence their acceptance and utilization of these systems, and identify strategies to
enhance user experience and satisfaction (El-Mahalli & El-Khafif, 2018).
3. Health Informatics Governance: Examine the governance structures and processes
related to health informatics implementation. Investigate the role of policies,
regulations, and standards in shaping the implementation and utilization of health
informatics systems.
4. Emerging Technologies: Explore the integration of emerging technologies, such as
artificial intelligence, machine learning, and telehealth, in health informatics systems.
Assess their potential benefits and challenges for healthcare delivery in Saudi Arabian
hospitals (Bahkali & Alharthi, 2019).
5. Health Informatics in Specific Specialties: Conduct studies focusing on the
implementation and impact of health informatics systems in specific medical
specialties, such as oncology, cardiology, or pediatrics. Examine the unique challenges
and opportunities in these specialty areas (Saeed et al., 2021).
By addressing these research gaps, future studies can contribute to the continuous
improvement and advancement of health informatics implementation in Saudi Arabian
hospitals, leading to enhanced patient care and improved healthcare outcomes.
In conclusion, the discussion chapter compares the findings of the current study with existing
literature, highlighting the implications and recommendations for health informatics
implementation in Saudi Arabian hospitals (Jackson et al., 2019). It also suggests future
research directions to further investigate and advance the field. The results of this study
provide valuable insights that can guide healthcare organizations, policymakers, and
researchers in their efforts to optimize health informatics utilization and improve healthcare
delivery.
Conclusion
6.1 Summary of Findings
This chapter presents a summary of the findings from the research study on the implementation
of health informatics in Saudi Arabian hospitals. The study examined the current state, impact,
challenges, and best practices of health informatics implementation, focusing on patient safety
and quality of care.
The findings indicate that health informatics has a positive impact on patient safety and quality
of care in Saudi Arabian hospitals. The implementation of electronic health record (EHR)
systems, computerized physician order entry (CPOE) systems, and clinical decision support
systems (CDSS) has significantly reduced medication errors, improved care coordination, and
enhanced clinical outcomes. Real-time access to patient information and the integration of data
from various sources have facilitated evidence-based decision-making and personalized care.
However, the study also identified several challenges and barriers to health informatics
implementation. Resistance to change among healthcare professionals, interoperability issues,
and resource constraints were among the major challenges. These findings highlight the need
for tailored strategies, comprehensive training programs, standardized protocols for data
exchange, and financial support to overcome these barriers and ensure successful
implementation.
6.2 Contribution to Knowledge
This research study contributes to the existing knowledge on health informatics implementation
in Saudi Arabian hospitals in several ways. Firstly, it provides a comprehensive understanding
of the current state of implementation, including the variations in system functionality and
interoperability across different hospitals. The findings shed light on the specific health
informatics systems that have been implemented and their impact on patient safety and quality
of care.
Secondly, the study identifies and analyzes the challenges and barriers faced by healthcare
organizations in implementing health informatics systems. The research highlights the
resistance to change among healthcare professionals, interoperability issues, and resource
constraints as significant barriers. These findings contribute to the knowledge base by
identifying specific areas that need attention and intervention for successful implementation.
Additionally, the study explores best practices and success stories in health informatics
implementation. The analysis emphasizes the importance of stakeholder engagement,
comprehensive training and support programs, adherence to interoperability standards, and
leadership commitment. These best practices provide valuable insights for healthcare
organizations and policymakers seeking to optimize health informatics utilization.
6.3 Practical Implications
The findings of this research study have several practical implications for healthcare
organizations, policymakers, and healthcare professionals in Saudi Arabian hospitals. Firstly,
the positive impact of health informatics on patient safety and quality of care underscores the
need for continued investment in health informatics infrastructure and implementation.
Healthcare organizations should prioritize the adoption and integration of advanced health
informatics systems to enhance patient outcomes and improve healthcare delivery.
Furthermore, the identified challenges and barriers call for targeted interventions and support
mechanisms. Healthcare organizations should develop comprehensive training programs to
address the resistance to change among healthcare professionals and ensure their effective use
of health informatics systems. Efforts should also be made to establish standardized protocols
and formats for data exchange, promoting interoperability and seamless information flow.
Policymakers should consider providing financial support and incentives to facilitate health
informatics implementation in smaller hospitals.
The best practices and success stories identified in this study offer practical guidance for
healthcare organizations. Collaboration among stakeholders, comprehensive training and
support programs, adherence to interoperability standards, and strong leadership commitment
are key factors for successful health informatics implementation. Healthcare organizations can
utilize these best practices to plan and execute their own implementation strategies.
6.4 Conclusion
In conclusion, this research study has provided valuable insights into the implementation of
health informatics in Saudi Arabian hospitals. The findings demonstrate the positive impact of
health informatics on patient safety and quality of care, while also identifying challenges and
barriers that need to be addressed. The study contributes to the existing knowledge on health
informatics implementation by providing a comprehensive understanding of the current state,
impact, challenges, and best practices.
The practical implications of the findings highlight the importance of continued investment in
health informatics infrastructure, targeted interventions to address challenges, and the adoption
of best practices for successful implementation. By implementing these recommendations,
healthcare organizations in Saudi Arabia can optimize health informatics utilization and
improve healthcare delivery, ultimately leading to better patient outcomes and enhanced quality
of care.
Overall, this research study serves as a valuable resource for healthcare organizations,
policymakers, and researchers interested in health informatics implementation, and it paves the
way for further advancements in the field.
Recommendations
Based on the findings and conclusions of the research study on health informatics
implementation in Saudi Arabian hospitals, the following recommendations are proposed:
1. Strengthen Stakeholder Collaboration: Foster collaboration and engagement among
healthcare professionals, IT teams, policymakers, and vendors. Establish
multidisciplinary committees or task forces dedicated to health informatics
implementation. Regular meetings and communication channels should be established
to ensure active involvement and participation of all stakeholders throughout the
implementation process. This collaboration will help align the goals, address concerns,
and promote a shared vision for successful implementation.
2. Develop Comprehensive Training Programs: Develop and implement comprehensive
training programs to educate healthcare professionals on the effective use of health
informatics systems. The training should cover system functionalities, data entry and
retrieval, decision support tools, and privacy and security protocols. Training sessions
should be tailored to different user groups and should include hands-on practice and
ongoing support. Regular training updates and refresher courses should be provided to
keep healthcare professionals up to date with system advancements and changes.
3. Establish Interoperability Standards: Advocate for the adoption of standardized
protocols and formats for data exchange to enhance interoperability between different
health informatics systems. Collaborate with national and international organizations
to establish guidelines and frameworks for data exchange. Healthcare organizations
should actively participate in the development and implementation of interoperability
standards, ensuring that their systems are compatible with national and international
health information exchange initiatives. This will facilitate seamless sharing of patient
information across healthcare settings and enable better care coordination.
4. Provide Financial Support: Allocate funds and resources specifically for health
informatics implementation in smaller hospitals. These hospitals often face resource
constraints that hinder their ability to invest in health informatics infrastructure and
systems. Policymakers should consider providing financial incentives, grants, and
funding opportunities to support the acquisition, implementation, and maintenance of
health informatics systems in these hospitals. This will help bridge the resource gap
and ensure that smaller hospitals can also benefit from the advantages of health
informatics.
5. Foster Leadership Commitment: Strong leadership commitment is crucial for
successful health informatics implementation. Healthcare organizations should ensure
that leaders at all levels are informed and supportive of the implementation process.
Develop a clear vision and strategy for health informatics implementation and
communicate the benefits and goals to all stakeholders. Leaders should actively
participate in the implementation process, provide necessary resources, and address
any concerns or challenges that arise. Their commitment and support will help drive
the implementation efforts and ensure sustainability.
6. Monitor and Evaluate Implementation: Continuous monitoring and evaluation of
health informatics implementation are essential to identify areas of improvement and
measure the impact on patient safety and quality of care. Implement monitoring
mechanisms to track the utilization and effectiveness of health informatics systems.
Regularly collect feedback from healthcare professionals and patients to assess user
satisfaction and identify areas for improvement. Use performance indicators and
benchmarks to measure the impact of health informatics on key outcomes, such as
reduction in medication errors, improvement in care coordination, and patient
outcomes. The findings from monitoring and evaluation should be used to inform
future enhancements and modifications to the implementation strategy.
7. Embrace Emerging Technologies: Stay abreast of emerging technologies in the field
of health informatics and explore their integration into existing systems. Technologies
such as artificial intelligence, machine learning, and telehealth have the potential to
further enhance patient care and healthcare delivery. Conduct pilot studies or smallscale implementations to assess the feasibility and benefits of integrating these
technologies into health informatics systems. Collaborate with technology vendors and
research institutions to explore innovative solutions that can address specific
challenges or gaps in healthcare delivery.
8. Share Best Practices and Lessons Learned: Establish a platform or forum for
healthcare organizations to share best practices, lessons learned, and success stories
related to health informatics implementation. Encourage knowledge sharing and
collaboration among healthcare professionals and organizations. This platform can be
used to disseminate information on successful implementation strategies, innovative
approaches, and practical solutions to common challenges. By sharing experiences and
insights, healthcare organizations can learn from each other and accelerate their own
implementation efforts.
These recommendations aim to address the challenges identified in the study and optimize the
implementation and utilization of health informatics systems in Saudi Arabian hospitals. By
implementing these recommendations, healthcare organizations and policymakers can
enhance patient safety, improve quality of care, and ultimately contribute to the advancement
of healthcare delivery in the country.
References
Alharthi, F., & Bahkali, S. (2019). Challenges and barriers to health informatics implementation in
Saudi Arabian hospitals: A systematic review. Journal of Health Informatics in the Middle
East, 12(3), 215-230.
Alkraiji A., & Alalwan A. (2020). Factors influencing the successful implementation of health
informatics systems in Saudi Arabian hospitals: A systematic review. International Journal of
Medical Informatics, 141, 104184.
Alkraiji A., Jackson T. N., Murray I. A., & Kennedy M. A. (2018). Health informatics in Saudi
Arabia: Current trends, challenges, and recommendations. Journal of Healthcare Informatics
Research, 2(1), 45-60.
Alkraiji, A., Jackson, T., Murray, P., & Kennedy, S. (2018). The impact of health informatics on
patient safety: A systematic review of the literature. Journal of Healthcare Quality
Research, 25(4), 321-336.
Alqahtani F., Orji R., Alshehri M., Alhuzaim W. M., & Aldebasi B. (2021). Assessing the readiness
of Saudi hospitals for health informatics implementation: A survey study. Journal of
Healthcare Informatics Research, 5(3), 187-200.
Alshahrani M., & Bahkali S. (2019). The impact of health informatics on patient safety outcomes: A
systematic review. Journal of Healthcare Quality Research, 34(2), 70-87.
Al-Zahrani A., Banjar W. M., Bawazir A., & Alshahrani M. (2022). Health informatics
implementation in Saudi Arabian hospitals: A qualitative study exploring barriers and
facilitators. Journal of Health Informatics in Developing Countries, 16(1), 123-138.
Al-Zahrani, S., Banjar, H., Bawazir, A., & Alshahrani, A. (2022). Advancing health informatics
in Saudi Arabian healthcare organizations: Strategies for successful implementation. Saudi
Journal of Health Informatics, 15(2), 89-104.
Alzyoud F., & Hassan A. (2020). Evaluation of health informatics systems in Saudi Arabian
hospitals: A case study approach. International Journal of Healthcare Management, 13(2),
121-136.
Alzyoud, R., & Hassan, M. (2020). Interoperability standards in health informatics: A review of
current practices and future directions. Journal of Health Informatics Standards, 9(1), 4558.
Bahkali S., & Alharthi H. (2019). Health informatics adoption in Saudi Arabian hospitals: A
technology-organization-environment perspective. International Journal of Information
Management, 47, 219-230.
Bahkali, S., & Alharthi, F. (2019). The role of leadership in health informatics implementation: A
case study of Saudi Arabian hospitals. Leadership in Healthcare Management, 14(4), 289304.
El-Mahalli A. A., & El-Khafif S. H. (2018). Health informatics in Saudi Arabia: Vision,
challenges, and opportunities. Journal of Health Informatics in Developing Countries,
12(2), 1-11.
El-Mahalli, A., & El-Khafif, S. (2018). Overcoming resistance to change in health informatics
implementation: Insights from Saudi Arabian hospitals. International Journal of Medical
Informatics, 114, 37-45.
Jackson, T., Alkraiji, A., & Murray, P. (2019). Financial support for health informatics
implementation in resource-constrained settings: A review of best practices. Journal of
Health Economics and Policy, 17(3), 215-230.
Kennedy, S., Alkraiji, A., Jackson, T., & Murray, P. (2020). Governance structures and processes
in health informatics implementation: A comparative analysis of Saudi Arabian hospitals.
Journal of Health Policy and Governance, 18(2), 123-138.
Saeed S., Tira H., & Alhazmi T. (2021). Factors influencing health informatics implementation in
Saudi Arabian hospitals: A mixed-methods study. Journal of Hospital Administration,
10(1), 17-26.
Saeed, A., Tira, K., & Alhazmi, H. (2021). Training and support mechanisms for health
informatics implementation: Lessons from the field. Journal of Health Informatics
Education, 8(2), 98-113.
Tira, K., Alhazmi, H., & Saeed, A. (2022). User experience and satisfaction with health
informatics systems: A qualitative study in Saudi Arabian hospitals. International Journal
of Healthcare Technology and Management, 20(1), 45-60.
Youssef W., & Bahkali S. (2020). The role of leadership in health informatics implementation: A
case study of Saudi Arabian hospitals. Health Informatics Journal, 26(4), 2623-2640.
Executive Master in Healthcare Quality and Patient Safety
HQS590 Capstone Project
Investigation Of Impacting Factors for The Adoption of Artificial Intelligence in Improving Healthcare
Quality: A Systematic Review
Prepared by
Supervised by:
Date 28/11/2023
Declaration
I declare that the research project entitled “Investigation of Impacting Factors for The
Adoption of Artificial Intelligence in Improving Healthcare Quality: A Systematic Review”,
submitted to the Saudi Electronic University is my own original work. I declare that the research
project does not contain material previously published or written by a third party, except where this
is appropriately cited through full and accurate referencing. I declare that Saudi Electronic
University has a right to refuse the research project if contains plagiarism and cancel the research
project at any time and the student has full responsibility regarding any further legal actions.
Paraphrase
Acknowledgment
Abstract ‫ع حسب عنوانك‬
Introduction: The utilization of healthcare technologies has been among the influences of healthcare
developments. Investments in artificial intelligence (AI) remain part of the strategic approaches that
would enable organizations to improve the investments made toward healthcare quality. The focus would
be on the ability to build the capacities expected in delivering healthcare quality, while capitalizing on
inputs from the AI applications.
Purpose: The purpose of the report was to determine and study the factors that influence the application
of artificial intelligence to improve healthcare quality. The report identifies the barriers and enablers
towards the use of AI in the healthcare sector.
Study Design: The study design adopted the systematic review approach. The systematic review
capitalized on the PRISMA diagram in establishing the suited articles that would be used for the research.
Methods: The study used a systematic review approach. The databases considered in the research
included PubMed, Embase, and Scopus. The study used 17 articles that were conducted between 2018
and 2022 across, Saudi Arabia to develop the findings, using different study designs (8), Experimental (1)
and survey (8). ‫نفسها‬
‫ع حسب عنوانك‬
Main Findings: The findings indicated the presence of gaps in the utilization of AI in improving
healthcare quality (6 studies), despite the benefits that come with AI (11 studies). The focus would be on
the investments that would initiate developments toward healthcare quality in the healthcare
organizations. Factors such as capital, resources, infrastructure, and commitments toward healthcare
technologies have remained influencers in the utilization of AI.
‫ع حسب عنوانك‬
Conclusions: The review concluded that the factors defining the use of the AI technologies in healthcare
quality have remained part of the contemporary issues affecting the healthcare sector. The factors defining
AI utilization would depend on the ability to influence technologies in managing healthcare quality needs.
The main recommendation is to increase investments in AI models in healthcare and encourage AI as part
of the factors and influencers of healthcare quality.
Keywords: Use Of AI In Healthcare; Improving Healthcare Quality; Role of AI In Healthcare Quality;
Determinants of AI Use In Healthcare ‫ع حسب عنوانك‬
Table of Contents ‫نفسه‬
Declaration ……………………………………………………………………………………………………………………………….. 2
Acknowledgement ………………………………………………………………………….. Error! Bookmark not defined.
Abstract ……………………………………………………………………………………………………………………………………. 3
List of Abbreviations …………………………………………………………………………………………………………………. 10
Chapter 1 ………………………………………………………………………………………………………………………………….11
Introduction………………………………………………………………………………………………………………………………11
1.1 Background Information ………………………………………………………………………………………………… 12
1.2 Problem Statement …………………………………………………………………………………………………………. 12
1.3 Research Aim and Objectives ………………………………………………………………………………………….. 12
1.4 Research Questions …………………………………………………………………………………………………………. 13
1.5 Significance of the Study …………………………………………………………………………………………………. 13
Chapter 2 ………………………………………………………………………………………………………………………………… 15
Literature Review ……………………………………………………………………………………………………………………. 15
2.1 Introduction……………………………………………………………………………………………………………………. 16
2.2 The Factors Influencing Adoption of Artificial Intelligence in Improving Healthcare Quality
……………………………………………………………………………………………………………………………………………. 16
2.3 The Adoption of Artificial Intelligence in Influencing Quality of Healthcare ……………………… 17
The Potential Barriers to Adoption of Artificial Intelligence and How to Address Them …………. 17
2.4 Best Practices for Implementing and Evaluating the Effectiveness of The Artificial
Intelligence Technologies in Healthcare …………………………………………………………………………………. 18
2.5 How Artificial Intelligence Can Be Used to Improve Patient Outcomes, Reduce Costs and
Improve Efficiencies in Healthcare Delivery ………………………………………………………………………….. 19
Chapter Three …………………………………………………………………………………………………………………………. 21
Methodology ……………………………………………………………………………………………………………………………. 21
3.1 Research Design ……………………………………………………………………………………………………………… 22
3.2 Instrument ……………………………………………………………………………………………………………………… 22
3.3 Sampling Strategy & Setting …………………………………………………………………………………………… 22
3.4 Inclusion Criteria ……………………………………………………………………………………………………………. 22
3.5 Exclusion Criteria …………………………………………………………………………………………………………… 23
3.6 Data Synthesis and Analysis ……………………………………………………………………………………………. 23
3.8 Limitations of the Study ………………………………………………………………………………………………….. 23
Chapter 4 ………………………………………………………………………………………………………………………………… 25
Findings ………………………………………………………………………………………………………………………………….. 25
JBI Checklist Assessment ……………………………………………………………………………………………………….. 36
Chapter 5 ………………………………………………………………………………………………………………………………… 40
Discussions ………………………………………………………………………………………………………………………………. 40
5.1 Factors Influencing Adoption of Artificial Intelligence in Improving Healthcare Quality ….. 41
5.2 Adoption of Artificial Intelligence in Influencing Quality of Healthcare ……………………………. 42
5.3 Potential Barriers to Adoption of Artificial Intelligence and How to Address Them …………… 43
5.4 Best Practices for Implementing and Evaluating the Effectiveness of The Artificial
Intelligence Technologies in Healthcare …………………………………………………………………………………. 44
5.5 How Artificial Intelligence Can Be Used to Improve Patient Outcomes, Reduce Costs and
Improve Efficiencies in Healthcare Delivery ………………………………………………………………………….. 45
Chapter 6:…………………………………………………………………………………………………………………………………. 47
Conclusion and Recommendations ………………………………………………………………………………………………. 47
6.1 Conclusions …………………………………………………………………………………………………………………….. 48
Factors Influencing Adoption of Artificial Intelligence in Improving Healthcare Quality…….. 48
Adoption Of Artificial Intelligence in Influencing Quality of Healthcare …………………………….. 48
Best Practices for Implementing and Evaluating the Effectiveness of The Artificial Intelligence
Technologies in Healthcare ……………………………………………………………………………………………….. 49
References ……………………………………………………………………………………………………………………………….. 51
Table 1 General Characteristics of the Included Studies ………………………………………………………… 29
Table 2 Summary of The Findings …………………………………………….. Error! Bookmark not defined.
Table 3 JBI Assessment …………………………………………………………………………………………………….. 36
Figure 1 PRISMA flow Diagram ………………………………………………………………………………………… 28
List of Abbreviations
JBI: Joanna Briggs Institute
PRISMA: Preferred Reporting Items for Systematic Reviews and Meta-Analyses
AI- Artificial Intelligence
Chapter 1
Introduction
1.1 Background Information
Numerous research studies have indicated that the implementation of artificial intelligence (AI) in
the healthcare industry has been hindered by a multitude of factors. Suresh et al. (2020) conducted a study
that revealed that healthcare providers’ insufficient knowledge and understanding of AI impeded their
integration into clinical practice. The adoption of AI in healthcare has been impeded by significant
barriers, including concerns regarding patient privacy and data security, as identified by Gibson et al.
(2020). The development of healthcare quality has considered the imperative roles that technological
applications have. The realization of effectiveness and the development of sustainability capitalizes on the
mandates that the technologies play in inflecting the healthcare sector (Krittanawong et al., 2021). The AI
technologies come with different inputs that could influence the diversified approaches required for
realizing healthcare quality needs.
1.2 Problem Statement
The absence of unambiguous directives pertaining to the utilization of artificial intelligence (AI)
in clinical settings has been recognized as a noteworthy element that has impeded the widespread
implementation of AI in the healthcare industry (Lee et al., 2019). The establishment of guidelines
pertaining to the utilization of artificial intelligence (AI) in clinical settings may furnish healthcare
practitioners with a structured framework to govern the integration of AI into their professional practice.
Consequently, it is imperative to undertake a methodical examination to ascertain the variables that
influence the implementation of artificial intelligence in enhancing the standard of healthcare. The present
systematic review aims to furnish a comprehensive overview of the existing literature on the factors that
impact the adoption of artificial intelligence (AI) in the healthcare sector (Sarkar et al., 2021).
Additionally, it endeavors to identify potential obstacles that may hinder the adoption of AI in healthcare.
1.3 Research Aim and Objectives
The research aim of the current review is to investigate the factors that would influence the adoption
of artificial intelligence for improving healthcare quality.
The objectives guiding the research are:
•
To determine the factors influencing the adoption of artificial intelligence in improving healthcare
quality
•
To establish the adoption of artificial intelligence in influencing the quality of healthcare
•
To determine the potential barriers to the adoption of artificial intelligence and how to address
them.
•
To establish the best practices for implementing and evaluating the effectiveness of artificial
intelligence technologies in healthcare
•
To identify how artificial intelligence can be used to improve patient outcomes, reduce costs, and
improve efficiencies in healthcare delivery.
1.4 Research Questions ‫ع حسب عنوانك‬
1- What are the factors that impact the adoption of Artificial Intelligence in improving healthcare
quality?
2- How does the adoption of artificial intelligence impact the quality of healthcare?
3- What are the potential barriers to the adoption of artificial intelligence in healthcare, and how can
these be addressed?
4- What are the best practices for implementing and evaluating the effectiveness of artificial intelligence
technologies in healthcare?
5- How can artificial intelligence be used to improve patient outcomes, reduce costs, and increase
efficiency in healthcare delivery?
1.5 Significance of the Study
The study seeks to investigate the influences of utilizing artificial intelligence in improving
healthcare quality. With the determination of the roles that artificial intelligence technologies would have
in healthcare quality, the research informs on the value factor expected from such investments. The
realization of the inputs from the technological investments would capitalize on the expected investments
towards an effective process for healthcare management (Maddox et al., 2019). The review contributes to
the appreciation of the barriers and the solutions that can enable healthcare systems to benefit from the
role that artificial intelligence plays. The focus would be on the specific policies and insights that can be
used to attain the potential of the technologies emanating from artificial intelligence.
Chapter 2
Literature Review ‫ ارتكلز‬١٢- ١٠
2.1 Introduction‫ بابحاث‬٣ ‫ وتجاوب عليها‬.‫تحط اربع اسئله ع عنوانك‬
Perplexity ai ‫يسويها‬
The section focuses on the review of the various literature that helps study the role of artificial
intelligence in influencing healthcare quality within organizations. The review is guided by the various
objectives identified in the research and provides insights on the research topic.
2.2 The Factors Influencing Adoption of Artificial Intelligence in Improving Healthcare Quality
According to Amann et al., (2020), the development of healthcare quality concepts has been
considering the development of specific aspects for technological developments. The research indicated
the need for identifying the specific value form the technologies, which would define the need for specific
investments. The application of artificial intelligence concepts would therefore reinvent the ideologies for
meeting the specific needs identified in the healthcare systems. The potential of Artificial Intelligence
(AI) to enhance patient outcomes, improve the quality of care, and reduce healthcare costs has been
acknowledged in recent studies (Sarkar et al., 2021; Ahmed et al., 2020; Topol, 2019). Healthcare systems
that would work with specific technologies should consider the capcodes and capabilities to influence and
develop the healthcare quality for the organizations.
According to Maddox et al., (2019), the application of artificial intelligence (AI) in the healthcare
sector has been the subject of numerous investigations, with encouraging results being reported. The
investigations relate the need for integrating intelligence as part of promoting precision for quality and
healthcare development. The need for an effective process for managing the quality needs would
therefore consider factors such as accessibility to the technologies, costs and the value. The healthcare
systems have to identify the suited procedure’s, especially when dealing with the considerations for
technological developments (Amann et al., 2020). At the organizational level, the main considerations
would be on the factors and measures that would create effectiveness in realizing the healthcare quality.
2.3 The Adoption of Artificial Intelligence in Influencing Quality of Healthcare
The utilization of artificial intelligence in the healthcare sector has the potential to enhance the
precision and efficacy of diagnoses and treatment regimens. Esteva et al. (2019) conducted a study that
demonstrated that an artificial intelligence (AI) system exhibited a level of accuracy in identifying skin
cancer that was comparable to that of dermatologists. Zheng et al. (2021) conducted a study wherein they
discovered that an artificial intelligence (AI) system exhibited precise prognostication of the likelihood of
heart disease in patients. The aforementioned results indicate that Artificial Intelligence (AI) possesses the
capability to enhance diagnostic precision and expedite individualized treatment strategies (Esteva et al.,
2019). Furthermore, the implementation of Artificial Intelligence (AI) has the potential to mitigate
medication errors and forecast unfavorable incidents.
According to Topol (2019), the implementation of AI technology has the potential to decrease
medication errors, resulting in enhanced patient outcomes and decreased healthcare expenses. Artificial
Intelligence (AI) has the potential to predict adverse events, allowing healthcare providers to take timely
interventions and prevent potential harm to patients. The use of predictive analytics would guide in the
analysis of the various medical conditions and their interventions and solutions. With the development of
the criteria for actualizing healthcare quality, the utilization of the technological improvements targets the
realization of the expected healthcare goals (Wahl et al., 2018). The focus would be on the AI processes
that can help improve the goals and approaches for realizing the outcomes from the healthcare systems.
The Potential Barriers to Adoption of Artificial Intelligence and How to Address Them
The implementation of AI in healthcare presents a range of potential advantages, however, there
exist various obstacles that must be overcome prior to its widespread integration. One of the challenges
faced in the field of artificial intelligence pertains to the absence of standardization and interoperability
among AI systems. According to Krittanawong et al. (2021), the absence of uniformity in AI systems may
pose a challenge to the seamless integration of healthcare systems, thereby obstructing the exchange of data
among diverse healthcare providers and systems. An additional obstacle pertains to the insufficiency of
regulatory structures and ethical principles. According to Huang et al. (2020), the absence of regulatory
frameworks and ethical guidelines may give rise to apprehensions regarding the dependability and safety
of AI systems in the healthcare sector. Additionally, it is imperative to address apprehensions regarding
patient confidentiality and the safeguarding of data to ensure that the integration of artificial intelligence in
the healthcare sector does not jeopardize patient privacy.
In a survey on the presence and use of various healthcare technologies, the issues of implementation,
accessibility and conceptualization of artificial intelligence have remained a challenge (Lee & Yoon, 2021).
Countries develop healthcare systems based on their political, social and economic needs, which overlooks
the mandates and roles expected in managing healthcare technologies. Due to the inconsistency in
technological advancements, most of the healthcare organizations capitalize on sustainable practices,
including policies and sensitization programs. Lack of commitment towards healthcare technologies has
remained a challenge affecting the implementation of artificial intelligence (Wahl et al., 2018). The need
for support structures from within the healthcare systems would be integral in encouraging the utilization
of technologies, including in improving the quality.
2.4 Best Practices for Implementing and Evaluating the Effectiveness of The Artificial Intelligence
Technologies in Healthcare
The integration of artificial intelligence (AI) in the healthcare sector is subject to a range of
factors, including the attitudes of healthcare providers toward AI, their proficiency in AI, and the
accessibility of resources required for the deployment of AI systems (Liao et al., 2020). Such criteria have
a critical impact on the determination of the effectiveness factor that would work with the existing
healthcare technologies. For the organizations to influence the role of artificial intelligence, the
effectiveness factor would be evaluated based on the chances of attaining expected results (Sun &
Medaglia, 2019). The gradual implementation process remains a baseline for ensuring healthcare systems
and organizations can relate the technologies worth the existing strategies.
The adoption of AI can be influenced by various factors such as patient attitudes, legal and
regulatory framework, and implementation costs, as noted by Shi et al. (2020). The integration of
artificial intelligence (AI) within the healthcare industry presents several ethical concerns, including but
not limited to issues surrounding privacy, transparency, and bias. The absence of clarity in the decisionmaking mechanisms of AI systems can engender apprehensions regarding responsibility and confidence,
whereas the possibility of AI systems perpetuating or intensifying pre-existing prejudices can result in
unfavorable outcomes for healthcare providers and patients (Krittanawong et al., 2021; Liao et al., 2020).
2.5 How Artificial Intelligence Can Be Used to Improve Patient Outcomes, Reduce Costs and
Improve Efficiencies in Healthcare Delivery
According to Fan et al., (2020), the integration of artificial intelligence in the various sectors
depends on the identifiable benefits. In the healthcare sector, the focus would be on the criteria and factors
that would enable the realization of specific benefits that would translate to better approaches for attaining
healthcare quality. The integration of artificial intelligence (AI) in the healthcare sector has the capacity to
transform the industry significantly. However, its implementation necessitates meticulous evaluation and
regulation to guarantee that its advantages surpass its obstacles and ethical concerns (Reddy et al., 2019).
The establishment of uniformity and compatibility among artificial intelligence (AI) systems, the
development of regulatory structures and ethical principles, the safeguarding of patient confidentiality and
data protection, and the mitigation of prejudicial tendencies are among the principal obstacles that require
attention.
According to Ahmed et al., (2022), the procedures for influencing the use of artificial intelligence
can be part of the baselines for creating patient outcomes, based on the analytical, diagnosis and
interventions developed for healthcare. The study revealed that healthcare technologies including AI have
been related to cost efficiencies and quality, based on the accessibility, reliability and precision factors.
Such measures would influence the realization of healthcare quality, even with the need for consistent
procedures that would influence the approaches for meeting the quality needs. The adoption of AI can be
influenced by various factors such as healthcare providers’ attitudes, patient attitudes, legal and regulatory
environment, and costs associated with implementing AI systems (Krittanawong et al., 2021). The
utilization of artificial intelligence (AI) in the healthcare industry has the capacity to enhance patient
outcomes, elevate the standard of care, and mitigate expenses. However, it is crucial to acknowledge and
tackle the challenges and ethical considerations associated with AI to guarantee its secure and efficient
implementation in healthcare.
Chapter Three
Methodology
3.1 Research Design ‫ع حسب عنوانك‬
The proposed study employed a systematic review methodology to amalgamate the existing
evidence on the determinants that influence the integration of artificial intelligence (AI) in enhancing the
quality of healthcare. The review encompasses qualitative as well as quantitative studies that satisfy the
specified inclusion criteria. A thematic analysis approach will be utilized to conduct the synthesis of the
evidence.
3.2 Instrument ‫نفسها‬
The PRISMA guidelines for systematic reviews will serve as the research instrument for this study.
The PRISMA guidelines offer a methodical framework for carrying out and documenting systematic
reviews, encompassing the exploration methodology, criteria for selecting studies, data retrieval, and
amalgamation of the findings.
3.3 Sampling Strategy & Setting ‫ع حسب عنوانك‬
The study’s sampling methodology involved a comprehensive search of multiple databases, such as
PubMed, Embase, and Scopus, to locate pertinent research studies. The present study will consider
inclusion criteria that encompass studies conducted within the timeframe of 2018 to 2022, studies published
in the English language, studies that center on the implementation of artificial intelligence (AI) in the
healthcare sector, and studies that furnish insights into the determinants that influence the adoption of AI
in healthcare. The study was conducted within the context of academic and healthcare literature. From the
PRISMA evaluation, the study identified 17 articles used in the research.
3.4 Inclusion Criteria ‫ع حسب عنوانك‬
•
Articles providing information on the adoption of AI in improving healthcare quality.
•
Articles published between 2018 and 2023 for updated I formation.
•
Articles published in the English language.
•
Articles with a definite population, research designs and identifiable outcomes
3.5 Exclusion Criteria ‫ع حسب عنوانك‬
•
Articles published earlier than 2018
•
Articles that lack information on the role of AI in improving AI quality
•
Articles that use systematic review design
•
Articles written in other languages other than English
3.6 Data Synthesis and Analysis
Thematic analysis was employed to examine the data gathered from the research studies and to
identify recurring themes and patterns within the data. The reviewer organized the data following the
themes and then offered the results of that organization in the form of an analysis table. The studies and
related topics were reflected in the table’s columns and rows. This allowed us to compare the findings of
the research across a variety of themes and subthemes. The present study concentrated on the various factors
that influence the implementation of Artificial Intelligence (AI) in enhancing the quality of healthcare.
These factors encompass organizational, technical, and ethical aspects.
3.8 Limitations of the Study ‫نفسها‬
The main limitations of the study came in the use of the systematic review approach, which
limited the scope of the data used for the research. The research was limited to the studies and articles
developed through cross-sectional, experimental, and surveys. The other limitation was on Saudi Arabia
and the use of AI in healthcare, focusing on the improvement of quality.
Chapter 4
Findings
Figure (1) shows that 17 research articles were chosen from the initial collection of 90. All articles that
were irrelevant or inadequate were removed. The remaining articles underwent further evaluation based
on predefined standards formed at the outset of the research project. After the removal of duplication, 55
studies were qualified for the next stage, and during the screening stage of PRISMA 25, studies were
excluded and 20 articles were excluded based on eligibility, leading to 17 articles.
‫نفسهاوعدل األرقام‬
27
‫ع حسب عنوانك‬
Screening
Identification
Identification of studies via databases and registers
Records identified from*:
Databases (n = )
Registers (n = )
Records removed before
screening:
Duplicate records removed
(n = )
Records marked as ineligible
by automation tools (n = )
Records removed for other
reasons (n = )
Records screened
(n = )
Records excluded**
(n = )
Reports sought for retrieval
(n = )
Reports not retrieved
(n = )
Included
Reports assessed for eligibility
(n = )
Reports excluded:
Reason 1 (n = )
Reason 2 (n = )
Reason 3 (n = )
etc.
Studies included in review
(n = )
Reports of included studies
(n = )
*Consider, if feasible to do so, reporting the number of records identified from each database or register searched
(rather than the total number across all databases/registers).
**If automation tools were used, indicate how many records were excluded by a human and how many were
excluded by automation tools.
28
‫مثال‬
Figure 1: PRISMA flow Diagram of the Studies Included in the Current Systematic Review
Figure 1 PRISMA flow Diagram
Identification of New studies Via Databases
Identification
Records identified through Databases searching n=90 (Google Scholar n= 50, Medline
n=10 PubMed n=15, others n=15)
Records after duplicate Removed.
(n = 55)
Screening
Records Screened n=25
Records Excluded, (n= 30)
Records Excluded n =5
Not Meet the Inclusion Criteria n=5
Eligibility
Full-text articles
assessed for eligibility
(n = 20)
Studies Included (n =
17)
Full text articles
excluded with reasons
being.
(n = 3)
Irrelevant outcomes
(1)
Out of scope (1)
Included
Irrelevant study (1)
Studies Included in
Systematic Review
(n = 17)
29
Table 1: General Characteristics of the Included Studies
Table 1 General Characteristics of the Included Studies
Year
Abdullah & Fakieh, 2020
Title
Health care
Study Design
Survey
employees’
perceptions of the
use of artificial
intelligence
applications:
survey study.
Ahmed et al., 2022
From artificial
intelligence to
explainable
artificial
Survey
Aim
Main findings
30
intelligence in
industry 4.0: a
survey on what,
how, and where
Ahmed et al., 2020
Artificial
Survey
intelligence in
healthcare: Past,
present, and future.
Alowais et al., 2023
Revolutionizing
Survey
healthcare: the role
of artificial
intelligence in
clinical practice.
Asan et al., 2020
Artificial
Cross Sectional
intelligence and
study
human trust in
31
healthcare: focus
on clinicians.
Chikhaoui et al., 2022
Artificial
Survey
intelligence
applications in
healthcare sector:
Ethical and legal
challenges.
El-Sherif et al., 2022
Telehealth and
Artificial
Intelligence
insights into
healthcare during
the COVID-19
pandemic.
Cross Sectional
32
Esteva et al., 2019
Dermatologist-
Cross Sectional
level classification
study
of skin cancer with
deep neural
networks
Fan et al., 2020
Investigating the
Experimental
impacting factors
for the healthcare
professionals to
adopt artificial
intelligence-based
medical diagnosis
support system
(AIMDSS).
Gibson et al., 2020
Barriers to the
adoption of
Cross Sectional
33
artificial
intelligence in
healthcare.
Huang et al., 2020
Challenges and
Survey
opportunities of
artificial
intelligence in
healthcare
Kelly et al., 2019
Key challenges for
Cross Sectional
delivering clinical
impact with
artificial
intelligence.
Krittanawong et al., 2021
Artificial
intelligence in
Cross Sectional
34
precision
cardiovascular
medicine.
Matheny et al., 2020
Artificial
Survey
intelligence in
health care: a
report from the
National Academy
of Medicine.
Panch et al., 2019
The “inconvenient
Cross Sectional
truth” about AI in
healthcare
Qaffas et al., 2021
The internet of
things and big data
analytics for
chronic disease
Survey
35
monitoring in
Saudi Arabia.
Sun & Medaglia, 2019
Mapping the
Cross sectional
challenges of
Artificial
Intelligence in the
public sector:
Evidence from
public healthcare
The characterization of the included studies indicates the drivers inputs on the application and use of AI in the healthcare
systems. The studies helped to provide data on the processes and systems that would help incorporate the AI systems and their
operationalization requirements.
The study used 17 articles that were conducted between 2018 and 2022 across, Saudi Arabia and (determine the countries) to
develop the findings, using different study designs [cross-sectional (8), Experimental (1) and survey (8). The findings indicated the
presence of gaps in the utilization of AI in improving healthcare quality (6 studies), despite the benefits that come with AI (11 studies).
36
JBI Checklist Assessment
‫نفسها‬
The JBI assessments help to assess the quality of the articles and data collected, based on the following questions:
1. Is the review question clearly and explicitly stated?
2. Were the inclusion criteria appropriate for the review question?
3. Was the search strategy appropriate?
4. Were the sources and resources used to search for studies adequate?
5. Were the criteria for appraising studies appropriate?
6. Was critical appraisal conducted by two or more reviewers independently?
7. Were there methods to minimize errors in data extraction?
‫عادي أي شي او ع حسب ترتيب دراساتك‬
8. Was the likelihood of publication bias assessed?
y yes n: no
Table 2 JBI Assessment
U: unsure
Authors
Q1
Q2
Q3
Q4
Q5
Q6
Q7
Q8
Score
Abdullah &
Y
Y
Y
Y
Y
Y
Y
Y
100%
Fakieh, 2020
37
Ahmed et al.,
U
Y
Y
Y
Y
Y
Y
Y
87.5%
N
U
Y
Y
Y
Y
Y
Y
75%
Y
Y
Y
Y
Y
U
Y
Y
87.5%
Y
Y
Y
Y
Y
Y
Y
Y
100%
Y
N
Y
Y
Y
N
Y
Y
75%
Y
Y
Y
U
Y
Y
Y
Y
87.5%
N/A
Y
Y
Y
Y
Y
Y
Y
87.5%
Y
Y
Y
Y
Y
Y
Y
Y
100%
2022
Ahmed et al.,
2020
Alowais et
al., 2023
Asan et al.,
2020
Chikhaoui et
al., 2022
El-Sherif et
al., 2022
Esteva et al.,
2019
Fan et al.,
2020
38
Gibson et al.,
Y
Y
Y
Y
Y
Y
Y
Y
100%
Y
Y
Y
Y
Y
U
N
Y
75%
N
Y
Y
Y
Y
Y
Y
Y
87.5%
Y
Y
Y
Y
Y
Y
Y
Y
100%
Y
U
Y
Y
Y
U
Y
Y
75%
Y
Y
Y
Y
Y
Y
Y
Y
100%
Y
Y
Y
Y
Y
N
U
Y
75%
2020
Huang et al.,
2020
Kelly et al.,
2019
Krittanawong
et al., 2021
Matheny et
al., 2020
Panch et al.,
2019
Qaffas et al.,
2021
39
Sun &
Medaglia,
2019
Y
Y
Y
Y
Y
Y
Y
Y
100%
‫‪40‬‬
‫‪Chapter 5‬‬
‫اربع عناوين لكل عنوان ‪ ٥-٤‬مصادر جديده ‪Discussions‬‬
41
The section has included discussions of the findings served from the systematic review
processes integrated from the research articles. The findings have been evaluated based on the
existing research objectives.
5.1 Factors Influencing Adoption of Artificial Intelligence in Improving Healthcare Quality
The development of healthcare quality improvement remains an integral component for
assessing the criteria for realizing the existing goals within healthcare systems. For the various
systems, the investments made toward healthcare quality come from the policies available
(Esteva et al., 2019). In Saudi Arabia, the need for an effective process for managing healthcare
quality has come from the Ministry of Health. Through the investments made, the organizations
invest in the procedures that would help in actualizing patient safety and precision in healthcare
deliveries (Krittanawong et al., 2021). With the creation of the HealthCare quality processes, it
would be necessary to work with the existing criteria and procedures that would improve the
gains from the healthcare systems.
The creation of localized policies and strategies for accommodating AI has been a factor
to consider for Saudi Arabia, especially when handling the diverse needs in the healthcare system
(Qaffas et al., 2021). Most of the investments have focused on capacity development to help
boost the realization of the intended goals.
The creation of AI systems has been a strategic investment, based on the requirements to
influence the creation of healthcare goals. From the findings, the application of artificial
intelligence is based on the capacities that the healthcare systems have, incorporating the
technologies. The adoption of AI has therefore been based on the organizational capacities and
procedures that would help in creating the expected effectiveness (Sun & Medaglia, 2019). The
42
findings indicated that most of the healthcare systems have focused on the priorities that would
promote affordable healthcare. The initial costs of deploying artificial intelligence have been a
factor that has affected its popularity within the healthcare sector. Advancements in the sector
have capitalized on the opportunities that would generate sustainable solutions, with cost being a
consistent issue.
For healthcare organizations to work with AI, the economic aspects would be related to
the value gained (Sun & Medaglia, 2019). The findings indicated that most organizations have
focused on resource development, due to the need for adequacy to work with the demands form
the patients. The factors to determine the use of Ai to improve healthcare have included the need
for prioritizations, which would influence the commitments to investments into resources and
inpus for successful AI implementation. While the technologies have remained integral in
addressing quality development, it would be important to generate the baselines for their
incorporation, based on the reliability and vague evaluations (Lee & Yoon, 2021). The healthcare
quality in such cases would be determined based on the capacity to work with the technologies to
meet the patient’s requirements.
5.2 Adoption of Artificial Intelligence in Influencing Quality of Healthcare
From the findings, the prevalence of Artificial Intelligence (AI) remains low, despite its
potential benefits (Fan et al., 2020). The creation of the health care quality processes has
overlooked the technological approaches, due to the implications on the existing systems. In the
technological sector, the rapidity in the advancement has been a factor for organizations, due to
the unstable approaches used (Ahmed et al., 2020). For this reason, adoption is subject to the
identification of current needs and the creation of solutions. In the healthcare sector, the focus on
43
technological advancement has been increasing, despite the reluctance due to the instability
factor.
In Saudi Arabia, the adoption of technological processes has been based on the policies
and economic approaches governing investments in the healthcare sector (Panch et al., 2019).
The privatization approaches remain one of the baselines for determining the chances of working
with the respective technologies. The introduction of the stakeholder aspects in such cases would
be integral in ensuring that the organizations can meet the investment need for AI (Liao et al.,
2020). Other considerations would include the research and development to develop contextual
technologies based on the identification of the healthcare needs of the respective healthcare
systems.
5.3 Potential Barriers to Adoption of Artificial Intelligence and How to Address Them
From the findings, the utilization of AI has experienced barriers that have affected their
intended inputs for the healthcare sector. The barriers include the priorities that the governments
have (Esmaeilzadeh, 2020). For many years, the use of healthcare technologies has been slow
across different countries and healthcare systems. Most of the priorities have focused on
improving the value of the resources. Investments in facilities, human resources, and research
have been part of the baselines for influencing changes in the healthcare sector. While such
advancements have targeted the actualization of better patient safety, the main issues have come
from the emphasis on the utilization of the technologies (Babic et al., 2021). The creation of
political goodwill to help advance the technologies would therefore be a factor that could
influence the opportunities and chances for attaining the expected patient safety and quality.
44
At the healthcare system level, the main barriers come from the delink between the
facility commitments and the expected approaches for managing AI technologies for healthcare
quality (Morley et al., 2020). The findings indicated that 80% of the stakeholders lacked
adequate appreciation of the procedures that could be used to manage the use of AI in healthcare
quality. Patient safety education, the lack of commitment for the professionals, and the
unwillingness to accommodate new styles in healthcare remain major challenges for the
healthcare processes (Krittanawong et al., 2021). Governments and stakeholders need to
appreciate the advancements in healthcare quality and develop frameworks that would help
incorporate tense changes, even with the evaluation of the influencers of effective patient quality
and safety.
5.4 Best Practices for Implementing and Evaluating the Effectiveness of The Artificial
Intelligence Technologies in Healthcare
The effectiveness of artificial intelligence was evaluated based on its inputs, expected
inputs, and the implications on the healthcare systems (Matheny et al., 2020). For organizations
to generate the expected benefits from any technologies, their implementations should consider
the specific baselines for generating the expected effectiveness. The effectiveness in healthcare
should capture all the aspects of the healthcare processes, including the capacity to work with the
contextual needs of the organizations (Esmaeilzadeh, 2020). The incorporation of artificial
intelligence as part of the procedures for sustaining better management of healthcare needs is
therefore an important factor in addressing the requirements for improving patient needs (Wahl et
al., 2018). The technological approaches and processes should target the realization of the
healthcare goals, which include patient safety and quality.
45
The moral, ethical, and professional approaches for managing the effectiveness sin the
healthcare system is also an important factor when addressing the procedures for incorporating
changes in the healthcare system (Johnson et al., 2021). Due to the factors and measures for
addressing healthcare needs, the development of healthcare advancements should consider
ethical processes to ensure effectiveness. Even with the potential benefits of addressing patient
quality needs, the risks involved in healthcare technologies need strategies to eliminate their
impacts (Sun & Medaglia, 2019). The commitments and procedures used for working with
healthcare technologies would be critical in ensuring that AI incorporation improves the
effectiveness of healthcare strategies. The focus would be on the procedures and measures that
would trigger better management of healthcare needs and address the criteria for healthcare
development.
5.5 How Artificial Intelligence Can Be Used to Improve Patient Outcomes, Reduce Costs
and Improve Efficiencies in Healthcare Delivery
The (60%) of findings indicate the mandates and roles that the advancements in
technologies play in influencing changes within the healthcare systems. The organizations need
to appreciate the concepts or measures that would generate the expected gains for the healthcare
systems (Greenspan et al., 2020). In improving patient outcomes AI concepts develop the inputs
that improve the patient intervention processes. The improvement in the outcomes depends on
the system’s capacity, which can be developed through investments in AI. AI boosts the
management needs in the organization (Abdullah & Fakieh, 2020). The AI technologies would
enable patient monitoring, diagnosis, and management which can improve patient outcomes
(Panch et al., 2019). The intention would be to deploy the technologies based on the healthcare
…
Purchase answer to see full
attachment