Discover AI Use Cases in Healthcare
Leveraging AI to address healthcare challenges.
- AI in healthcare has not demonstrated value in analytics in the last ten years, despite rapid growth in investment and development.
- Healthcare organizations are challenged with inefficient business operations and are unsure of how to effectively address them.
- Adopting new technology requires a strategic approach and alignment between IT and healthcare administrators.
Our Advice
Critical Insight
Health organizations should approach AI adoption strategically and responsibly, with a clear understanding of the specific use cases and benefits and a plan for addressing the challenges associated with implementation and ongoing use. Before you start implementing any AI solutions, assess your organization’s readiness maturity level. With a very low maturity level, a new software solution will not improve your operations.
Impact and Result
Healthcare is a highly regulated industry, and many organizations are concerned about the risks associated with AI. It is imperative to approach AI strategically and responsibly. Those that are thriving are digitally mature and recognize that technology empowers people and processes.
Discover AI Use Cases in Healthcare
Leveraging AI to address healthcare challenges.
Analyst Perspective
AI has the potential to create value in your organization.
The potential of artificial intelligence (AI) in healthcare is significant, and health organizations should consider leveraging AI to improve patient outcomes and reduce costs. AI can be used for various purposes, including diagnosis and treatment, drug development, remote patient monitoring, and predictive analytics. By analyzing medical data, AI can help healthcare providers make more accurate diagnoses, develop more effective treatment plans, and monitor patients more effectively.
However, the adoption of AI in healthcare also poses some challenges. One of the main challenges is ensuring that the data used to train AI algorithms is accurate and representative of the population being served. Another challenge is ensuring that AI is used ethically and responsibly, with appropriate safeguards in place to protect patient privacy and prevent bias. Health organizations should approach AI adoption strategically, with a clear understanding of the specific use cases and benefits, and a plan for addressing the challenges associated with implementation and ongoing use. Despite these challenges, the potential benefits of AI in healthcare are significant, and healthcare organizations that invest in AI technology and expertise will foster innovation to improve operational efficiency and patient outcomes.
Sharon Auma-Ebanyat
Research Director, Healthcare
Industry Practice
Info-Tech Research Group
Executive Summary
Your Challenge
- AI in healthcare has not demonstrated value in analytics in the last ten years despite rapid growth in investment and development.
- Healthcare organizations are challenged with inefficient business operations and are uncertain how to effectively address them.
- Adopting new technology requires a strategic approach and alignment between IT and healthcare administrators.
Common Obstacles
- Healthcare leaders have a limited understanding of the benefits of AI, organizational impacts, and how to get started.
- Healthcare organizations are concerned about the risks of AI and compliance with privacy laws, regulations, and policies.
- Health IT leaders must continuously identify and prioritize feasible AI technology trends to foster innovative ways of addressing current operational challenges.
Info-Tech's Approach
- Help healthcare leaders understand and discover AI use cases that can address some of their business challenges.
- Guide healthcare leaders to start their AI journey by identifying and prioritizing AI use cases for their business capabilities through a benefits realization model.
- Leverage the output to gain executive buy-in. The approach will help you determine the most suitable problems (with the greatest value) to solve and meet all business criteria to implement AI responsibly.
Info-Tech Insight
Health organizations should approach AI adoption strategically and responsibly, with a clear understanding of the specific use cases and benefits and a plan for addressing the challenges associated with implementation and ongoing use. Healthcare organizations that invest in AI technology will foster innovation to improve operational efficiency and patient outcomes.
What is artificial intelligence (AI)?
There is no universally accepted definition of artificial intelligence (AI), but it generally refers to the development of computer systems that can perform tasks that would typically require human intelligence, such as learning, reasoning, perception, and problem-solving. AI can be characterized as a set of technologies that enable machines to process and analyze large amounts of data, identify patterns, and make predictions or decisions based on that data.
AI includes subfields such as machine learning, natural language processing, computer vision, and deep learning. Deep learning is a subset of machine learning that involves the use of neural networks to process and analyze large amounts of data. These subfields each focus on different aspects of AI, but they are all united by the goal of developing intelligent machines that can perform tasks without human intervention.
AI is a rapidly evolving field, and the definition of AI continues to evolve as new technologies and applications emerge. However, at its core, AI is about creating intelligent machines that can perform tasks that would typically require human intelligence.
Source: Dataconomy, 2023; Procedia Computer Science, 2023.
AI is driving automation in healthcare
The application of AI to automate repetitive tasks in healthcare has improved efficiency, accuracy, and productivity. As a result, 90% of healthcare organizations have adopted some form of automation in their operations. AI and automation are related concepts that are often used interchangeably, but they are distinct from each other. Automation refers to the use of technology to perform routine, repetitive tasks without human intervention. This can include tasks such as data entry, data processing, and other rule-based tasks. Robotic process automation (RPA) is a type of automation that uses software robots to automate these tasks.
On the other hand, AI involves the development of computer systems that can perform tasks that would typically require human intelligence, such as learning, reasoning, perception, and problem-solving. And while automation and AI are distinct concepts, they can be used together to create more efficient and effective systems. For example, RPA can be used to automate routine tasks, while AI can be used to analyze data and make predictions or decisions based on that data. This combination of automation and AI can lead to significant productivity gains, cost savings, and improved outcomes in many industries, including healthcare.
Benefits of automation in healthcare
- Better patient experience and satisfaction.
- Easy access to patient data and reduction of administrative errors.
- Lower staffing costs and less overtime.
Areas of healthcare organizations that are benefiting from automation worldwide (N=100)
Source: Statista, 2022.
Info-Tech Insight
RPA is typically the most feared application of automation in healthcare due to the assumption that by automating tasks, computers will replace humans in their jobs. However, it must be stressed that when implementing RPA technologies, it can lead to enhanced job creation, as seen with all disruptive technologies. It can also provide more value to existing jobs. Given the current healthcare staffing shortages and burnout, automation can reduce the administrative burden, and staff can be repurposed to focus on complex aspects of their work.
