Is 2023 The Right Year To Invest In AI And Transform Clinical Operations?

Updated on August 26, 2023

Johns Hopkins announced they will improve the health of older adults and help them live longer independently by identifying early signs of diseases with new technologies. Mid-last year, experts from the same hospital developed a system that can decrease mortality rates caused by sepsis by 20% through rapid detection. Turning our attention to Taiwan, doctors at China Medical University Hospital (CMUH) are using a new innovative solution that can cut down test diagnosis times from 72 hours to just one hour. 

What do these new health technologies have in common? Artificial intelligence (AI). 

AI has come a long way, and not only has technology matured, but also organizations that were early to embrace the tech have learned to master it to reap benefits. Additionally, market conditions and trends in the industry reveal that the AI transformation is in full swing. 

Here’s how leading organizations in 2023 use AI, and how do they overcome risks and challenges that range from data security, ethical issues, and adoption barriers?  

A Bull Market: Indicators and Operation Areas

March 2023 saw an AI healthcare bull market taking over Wall Street, with companies like GE HealthCare Technologies investing strongly in the trend. Simultaneously, NASDAQ reported on the rising AI healthcare trend highlighting how industry giants, such as NVIDIA (NVDA), Medtronic (MDT), and Microsoft (MSFT), are increasing their stock value as they dip their toes into the market. 

The 2023 Vantage Market Research says that the global AI healthcare market is projected to reach $95.65 billion by 2028—a dramatic increase from its 2021 valuation of just $6.6 billion. Stanford’s 2023 AI Index explains that AI investments in healthcare exceed those made in other sectors like fintech, data management, and cloud technology. 

AI’s potential and flexibility is a driving force in healthcare. It can be applied in a wide range of sectors within health. AI is transforming healthcare with applications for everything, from diagnosis and treatment to drug discovery and patient monitoring. 

Here’s how top industry leaders are using AI. 

Healthcare Operations and Administration

A recent paper of experts from Harvard University and McKinsey found that broader adoption of AI could lead to savings of five to 10% in U.S. healthcare spending—roughly up to $360 billion annually. The report also highlighted that this technology can improve healthcare quality, increase access, improve patient experience, and increase clinician satisfaction.

AI is helping managers in healthcare facilities optimize resources, streamline processes, reduce waste and energy, and improve performance. Moreover, AI is scheduling medical appointments, automating billing and coding, detecting fraud, monitoring the quality of care provided, and providing holistic data-driven analytics. 

Medical Image Analysis 

Radiologists and other specialists leverage AI to interpret medical images faster and more accurately, reducing errors and improving outcomes. Through the use of AI solutions combined with X-ray imagery, healthcare professionals can detect cancer, pneumonia, and other respiratory affections. 

Clinical Decision Support 

Clinicians are also making more informed decisions based on evidence and guidelines leveraging new platforms that are powered by AI. For example, IBM Watson Health, a leading AI platform, can analyze patient data and provide personalized recommendations for diagnosis and treatment.

Data-driven platforms can enable clinicians to diagnose diseases, prescribe treatments, monitor patients’ conditions, predict outcomes, and provide decision support. 

Population Health Management and Medical Devices 

Using data platforms and AI, healthcare organizations can identify high-risk patients and predict outcomes and end-to-end operational costs. 

Medical devices have been evolving and maturing for several years. Back in 2018, Google Health developed an AI system that can predict heart diseases in the blink of an eye using retina scans. In recent years, health wearables, such as smartwatches, have become mainstream. Medical devices, which need to meet standards and regulations, and go through lengthy approval processes, are also gaining momentum. 

As of January 2023, the U.S. Food and Drug Administration (FDA) has cleared more than 520 AI medical algorithms. These include 396 for radiology, 58 for cardiology, 14 for hematology, 10 for neurology, seven for clinical chemistry, and four for pathology, microbiology, and anesthesiology. 

Drug Discovery and Research Development  

AI is also being leveraged to accelerate the process of finding new drugs and testing their efficacy and safety. A recent example is DeepMind’s AI technology that can develop a tiny ‘syringe’ that can inject gene therapy and tumor-killing drugs. 

Researchers are utilizing AI to develop new drugs, design clinical trials, analyze data, and generate evidence. Leading organizations are seizing competitive advantages, utilizing AI to screen potential drug candidates, optimize trial protocols, identify biomarkers, synthesize literature, and generate hypotheses.

AI Privacy And Security: Overcoming Risks And Challenges 

AI offers many benefits for healthcare. But it also poses some risks and challenges. As AI solutions require large amounts of information to train and validate their algorithms, they increase the exposure and vulnerability of data. Moreover, some AI applications may involve sharing or transferring data across different entities or platforms, raising legal and ethical issues.

To ensure data security and privacy in the AI era, healthcare organizations need to adopt some best practices. These include but are not limited to, encrypting data at rest, in use, and in transit and implementing access control policies. Access control policies set rules that define who can access data and for what purpose—and complying with regulations. 

Furthermore, numerous international, federal, and state laws apply to health organizations. These also govern how data should be collected, stored, shared, or deleted. The laws are in place to protect the rights and interests of data owners and individuals, and breaching them has severe legal and economic consequences. 

Healthcare organizations should comply with relevant regulations and standards in their jurisdiction or domain, such as the U.S. Federal Health Insurance Portability and Accountability Act (HIPAA), European General Data Protection Regulation (GDPR), or standards like the Fast Healthcare Interoperability Resources (FHIR).

The Way Forward 

While healthcare providers and organizations can apply AI across various healthcare settings and scenarios, promising benefits and results, only those that have embraced a culture of innovation are reaping the benefits. 

Moving projects from pilot to implementation requires engagement from across the entire organization, from all level workers to executives, decision-makers, and boards. 

AI is critically more than a buzzword. In health, it has the potential to save and improve billions of lives, break down gaps, accelerate diagnosis and treatments, help caregivers, and enable professionals. 

With the potential to augment humans’ capacity and uncover insights and patterns in data, organizations turn to AI to slash costs, increase organizational sustainability, reduce errors, and automate operations. Driving innovation with AI in healthcare, aligned with best practices, ethics, and compliance, is the way forward in 2023. 

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Sajid Mohamedy

Sajid Mohamedy is Nisum's EVP of Growth and Development with a successful track record in creating and expanding enterprises. He is skilled in entrepreneurship, marketing analytics, mergers and acquisitions, venture capital, and international growth. Sajid has a background in management consulting and launched a solar industry startup (Kolibri) before joining Nisum. He is a mentor at UCLA Anderson Venture Accelerator and advises and invests in multiple startups. Sajid holds an MBA from UCLA Anderson and dual degrees in Economics and Political Science from UCLA.