The importance of real-time data processing in healthcare lies in its ability to deliver instant insights, which can significantly improve patient outcomes by enabling timely interventions, accurate decision-making, and optimizing operations.
However, the sheer volume and complexity of healthcare data pose significant challenges that hinder its widespread implementation despite its potential benefits. In this blog, we will look at how artificial intelligence (AI) techniques can be leveraged to overcome these challenges and unlock the full potential of real-time data processing.
The Challenge of Real-Time Data Processing
One major issue faced by real-time data processing in healthcare is the enormous volume and velocity of data generated from diverse sources such as electronic health records, medical imaging, and wearable devices, which require robust infrastructure and advanced algorithms for timely analysis.
Today, approximately 30% of the world’s data volume is being generated by the healthcare industry. By 2025, the compound annual growth rate of healthcare data is expected to grow by 36%, further exacerbating the challenge of real-time data processing. Traditional data processing methods struggle to handle the sheer volume and variety of healthcare data, leading to delays in analysis and decision-making.
Additionally, data integration and interoperability are complex, as healthcare information is often stored in incompatible formats across disparate systems. Regulatory challenges, including stringent data privacy and security requirements, further complicate real-time data processing.
Lastly, the high costs associated with the necessary IT infrastructure and the shortage of skilled professionals in data science and IT management pose significant barriers. These technical, regulatory, and organizational hurdles must be addressed to fully leverage the potential of real-time data processing in healthcare.
And AI is the way to do it…
Addressing the Challenge with Healthcare AI Techniques
AI-powered solutions offer innovative ways to process and analyse healthcare data in real-time, enabling medical professionals to extract actionable insights and drive informed decision-making. These valuable insights into patient conditions, treatment efficacy, and disease progression contribute to early disease detection, personalized treatment plans, and improved patient outcomes, among other such key parameters.
Natural language processing (NLP) techniques can extract relevant information from unstructured clinical notes and documents, further enhancing the richness of available data for analysis.
Felix’s EOB Digitization tool that is known to works 250% faster than manual processes, offers patented document intelligence solutions that leverage AI, ML, and NLP to extract data from unstructured documents with an accuracy rate of 99%. Felix Solutions stands at the forefront of healthcare AI innovation, offering advanced solutions designed to address the challenges of real-time data processing effectively.
With features like Contract Ingestion and EOB Digitization, Felix Solutions equips healthcare providers to streamline operations, optimize revenue management, and enhance patient care in real-time. Moreover, Felix Solutions’ HIPAA-compliant deployment options ensure that patient data remains protected and secure throughout the real-time data processing workflow.
Expected Outcomes and Business Impact
AI-powered real-time insights offer significant benefits to healthcare organizations by enhancing a few key parameters of medical practice and administration.
Let’s take a quick look:
Operational Efficiency
By predicting patient admissions, optimizing staff schedules, and accurately managing inventory, AI helps streamline hospital operations which ultimately leads to better resource allocation. Additionally, administrative tasks like billing, coding, and scheduling can be automated using AI, freeing up healthcare professionals to focus more on patient care.
The AMA’s Augmented Intelligence Research conducted in 2023 found that enthusiasm was highest among physicians for AI tools that help reduce administrative burdens, including documentation (54%) and prior authorization (48%).
Cost Saving
Similar to the above-mentioned point, by forecasting patient admissions and optimizing staff schedules, AI ensures that healthcare facilities are adequately staffed without overstaffing. This reduces labour costs while maintaining high-quality patient care. Enhanced resource management through AI also cuts down on waste and storage costs.
Furthermore, the automation of administrative tasks like billing, coding, and appointment scheduling reduces the likelihood of costly manual errors. These efficiencies cumulatively result in significant financial savings for healthcare providers, allowing resources to be allocated more effectively towards patient care and innovation.
Early Detection & Improved Diagnostics
AI can analyze medical images, lab results, and patient data with amazing precision to detect diseases like cancer, heart conditions, and neurological disorders at earlier stages than traditional methods. For instance, AI algorithms can identify subtle patterns in imaging studies that can easily be missed by human radiologists. By 2025, it has been estimated that 90% of hospitals will rely on AI-powered technology for early diagnosis.
In the same vein, AI systems provide highly accurate and consistent diagnostic results, reducing the variability and potential errors associated with human analysis. This ensures that patients receive reliable diagnoses regardless of where they are treated.
Personalized Treatment
AI analyzes individual patient data, including highly intricate genetic information, to tailor personalized treatment plans for each patient’s unique needs. This can lead to more effective therapies and better patient outcomes, especially in complex diseases like cancer. AI algorithms can also predict how patients respond to specific treatments based on historical data and current health status, and help select the most effective treatment options, adjusting them as needed along the way.
Enhanced Patient Engagement and Outcomes (Population Health Management, Remote Monitoring & Virtual Health Assistance)
By analysing large datasets, AI. An identify trends and patterns in public health, helping healthcare providers and policymakers to implement preventive measures and improve overall population health.
AI-powered devices also continuously monitor patients’ vital signs and health metrics in real-time, alerting healthcare providers to any concerning changes. This is particularly beneficial for managing chronic conditions and reducing hospital readmissions.
According to the University of Pittsburgh Medical Center, RPM helped to reduce its readmission rate by an astounding 76%! Additionally, AI chatbots and virtual assistants provide patients with real-time health information, reminders for medication, and assistance with appointment scheduling, enhancing patient engagement and adherence to treatment plans
Conclusion
This much is certain…the future of healthcare is powered by AI.
As healthcare organizations strive to harness the power of real-time data processing, partnering with Felix Solutions offers a compelling opportunity to achieve these goals effectively and efficiently.
By leveraging Felix Solutions’ AI-driven solutions, healthcare providers can unlock the full potential of real-time data processing to deliver superior patient care, optimize operations, and drive strategic growth.