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Coforge | Blog | 8 ways Artificial Intelligence can harness the healthcare data explosion

Written by Kelli Bravo | Oct 9, 2023 6:30:00 PM

The exponential growth of healthcare data, ranging from electronic health records to genomic information, presents both opportunities and challenges. Artificial Intelligence (AI) is poised to address this data explosion by enabling population health analysis, personalized medicine, efficient data management, predictive analysis, accelerated drug discovery, clinician support, administrative efficiency, and enhanced data security. However, challenges like prediction accuracy, data privacy, regulatory compliance, and ethical considerations need to be addressed. With responsible development, AI can harness healthcare's massive data to improve patient care, advance research, and optimize operations. 

In 2020, it was projected that the doubling time of medical knowledge was 0.2 years—just 73 days compared to 2010 when it was 3.5 years. Medical students who graduated in 2020 would experience four doublings in knowledge by the time they completed the minimum length of training (7 years) needed to practice medicine . This ever-increasing volume of data is part of a data revolution that is generated daily, encompassing electronic health records (EHRs), medical imaging, genomic information, wearables, and more. This data deluge presents both unprecedented opportunities and significant challenges for clinicians and allied professionals to assimilate and apply new information effectively. Fortunately, with the advent of Artificial Intelligence (AI), the healthcare industry is poised to not only manage this data deluge but also leverage it for improved patient care, research, and operational efficiency. AI has the potential to be one of the most beautiful and transformative developments in the field.

In this blog, we explore how AI is set to address the healthcare data challenge and revolutionize the industry.

Population Health

AI is being used to study large population datasets, helping healthcare systems better understand disease prevalence, risk factors, and treatment outcomes. As a result, preventative actions can be taken earlier and more effectively to ensure the health of our populations.

Personalized Medicine

The healthcare data deluge enables AI to create highly personalized engagement strategies, outreach, population health programs, treatment plans, and so much more. By consuming a patient’s interaction information and background, AI can develop a personalized engagement program for outreach and omni-channel experiences. By analyzing a patient's genetic, clinical, socioeconomic and lifestyle data, AI can recommend treatments tailored to the individual, leading to more effective and efficient healthcare delivery as prescribed by clinicians.

Efficient Data Management

AI can streamline the storage, retrieval, and management of vast amounts of healthcare data. Through advanced algorithms, AI helps categorize and index data for easy access and retrieval, reducing the time and effort required to search for critical patient information. AI can also monitor patient vitals continuously, and in real-time, enabling early intervention. This ensures that healthcare professionals have the right data at their fingertips when making decisions and helps drive better patient outcomes.

Predictive Analysis

AI excels at predictive analysis, which is invaluable in healthcare. It can forecast patient readmissions, patient scheduling cancellation behaviors, prior authorization approvals, and even patient deterioration. By identifying high-risk individuals, healthcare providers can intervene proactively, reducing hospitalizations and improving resource allocation.

Drug Discovery and Development

The vast datasets generated during clinical trials and research can be effectively analyzed by AI, expediting drug discovery and development. AI can identify potential drug candidates, predict drug interactions, and optimize clinical trial designs, reducing costs and time-to-market for new medications.

Clinician Support

AI can help reduce clinician burnout by being an always-on virtual assistant. AI can support clinicians by delivering encounter summaries or automating charting such as voice to text, and AI as an automated assistant can do lookups and other research including drug interactions, patient summaries and referral templates. By supporting clinicians in their daily work, AI can be a welcome tool to not only increase efficiency but to also reduce burnout on already overworked and often understaffed clinicians.

Administrative Efficiency

Beyond clinical applications, AI can improve healthcare administration. It can automate administrative tasks like appointment scheduling, billing, and claims processing, and prior authorizations reducing administrative burdens on healthcare providers and streamlining operations for payers.  AI can handle complex scenarios that require interpretation of text, audio, and visual sources that historically have required human intervention – making the vision of real- time resolution a reality. Removing administrative barriers increases access to care while reducing the cost of care – a win/win scenario

Data Security and Privacy

AI can play a crucial role in improving data security and privacy. It can predict potential security weaknesses and breaches before they happen, detect subtle anomalies that may represent a breach, and adapt security defenses 24/7. AI can improve identity management and authentication to ensure data privacy and can easily de-identify health information to support large scale analysis without risk of privacy breaches. Applying AI for Data Security and Privacy is a must for all healthcare organizations managing critical patient data

Challenges and Considerations

Though AI promises a substantial role in addressing the healthcare data challenge, we cannot overlook several challenges on the way. These include concerns about prediction accuracy, data privacy, regulatory compliance (such as HIPAA in the United States and GDP in the EU), and hallucination, as well as the need for robust cybersecurity measures to protect patient data from cyberattacks. Moreover, it is critical to acknowledge the challenges and ethical considerations associated with AI.  Above all, we need to address equitable access to AI-based healthcare services while guarding against bias in the models themselves and preventing inaccurate information from informing care.  
 

In a Nutshell 

The healthcare data explosion is an inevitable outcome of the digital transformation of the industry. With the integration of AI, this massive growth in data availability can be harnessed and turned into a powerful asset for improving patient care, advancing medical research, and optimizing healthcare operations. AI's ability to efficiently manage, analyze, and derive insights from vast datasets is transforming healthcare into a more personalized, efficient, and effective industry, ultimately benefiting patients and healthcare providers alike. With responsible development and a strong ethical framework, AI in healthcare is all set to deliver improved health outcomes and reduce the cost of care for everyone around the globe.