| Insights
● Healthcare systems are weighed down by aging legacy applications, causing integration issues, higher costs, and operational inefficiencies. ● Modernization across the data value chain is the need of the hour, wherein the budget constraints can be met with regulatory compliance and value-based care. ● The convergence of AI with low-code platforms can create a synergy capable of enhanced integration capabilities, agile development, and real-time data analysis, paving the way for a future defined by efficient, predictive, and personalized care delivery. |
According to recent reports, nearly 90% of healthcare executives identify digital transformation as a top priority, but most still struggle to allocate the necessary resources for modernization. Therefore, the need for healthcare modernization, particularly addressing outdated legacy systems, is more critical than ever, as organizations aim to boost agility and innovation in an increasingly digital environment.
At the heart of this paradigm lie low-code platforms and artificial intelligence (AI)—the catalysts of change. By streamlining the modernization process, these technologies empower healthcare providers to tackle technical and operational challenges head-on.
They facilitate a transition from reactive to proactive care, prioritizing predictive and personalized models. Therefore, by upgrading legacy systems, healthcare organizations can enhance operational agility, improve patient engagement, and provide more affordable care.
Modernization: An Industry Imperative
According to Gartner, over 70% of Fortune 500 companies still use legacy systems. For decades, the healthcare sector has struggled with fragmented solutions and inadequate integration, resulting in reduced productivity, patient care bottlenecks, escalating costs, and increasing physician burnout.
Thus, it’s no surprise that current industry trends intensify the urgent need for modernization:
Predictive and Personalized Care: There is an increasing push toward using predictive analytics to make personalized healthcare decisions, improving patient care and operational efficiency.
Integration and Interoperability: Systems working in silos need to be integrated to enhance the patient experience through connected care.
Regulatory compliance: Modernization efforts must comply with ever-evolving regulations, and there are challenges with updating systems while maintaining efficiency. Having said that, healthcare providers must also address the key roadblocks to advance their modernization efforts.
Budget constraints: Healthcare providers face challenges in modernization due to budget constraints, inefficient planning, and inadequate development methods, which hinder timely investments in technology and infrastructure.
The complexity of data migration: Transitioning to new systems involves significant data migration challenges, including ensuring that data is accurately transferred and accessible across different tech stacks.
Technology fitment: Choosing the right technology to enable the integration of multiple systems effectively, as incompatibilities can lead to inefficiencies and hinder the desired outcomes of modernization efforts.
Low-code Platforms: The Key To Digital Transformation
Today, low-code platforms are emerging as a compelling solution for tackling some of the biggest underlying challenges in legacy modernization efforts. Low code is critical for managing complexity in healthcare with scalable applications, allowing for faster development and flexibility. It supports legacy modernization without requiring complete system overhauls, preserving existing investments while enhancing interoperability across systems.
AI: Unlocking The Power of Intelligent Automation and Insights
Alongside the advent of low-code platforms, the emergence of artificial intelligence promises a paradigm shift for the healthcare industry. The technology is already making its presence felt across critical areas like predictive analysis and decision-making, process improvements, and key aspects of patient care.
Here’s how:
Diagnostics: The ability to accurately evaluate medical images through the use of AI algorithms significantly increases the speed and precision of diagnosing numerous conditions.
Personalized Surgery: With the help of patient information analysis, AI assists in tailoring treatments to the patient and predicting future health complications along with the most effective care pathways.
Illness Management: AI systems and wearable technology can continuously monitor and analyze patients’ wellness information, letting healthcare providers take action proactively.
Management of Revenue Cycles: AI can help with automating manual tasks in revenue cycles, minimizing claim denials, and enhancing billing practices.
The real magic happens when the capabilities of AI and low-code unite seamlessly on platforms created to manage complex integrations and support millions of users, ensuring both scalability and efficiency in enterprise healthcare environments.
Interoperability across platforms (e.g., Epic or Cerner) is one of the key benefits, allowing for efficient coordination of patient care and hospital operations. AI platforms with built-in security controls can also address data protection, infrastructure protection, and compliance with healthcare regulations (e.g., HIPAA, FedRAMP).
AI-Powered Low-code Platforms: Bringing the Vision to Fruition
We have covered the exciting potential of low-code and AI and how a platform combining these technologies can usher in an era of transformative change in healthcare. Now, let’s examine what this potential means for real-world scenarios.
Healthcare organizations are accelerating their modernization efforts, especially in telemedicine and remote care solutions. One notable success story is of a large cancer center that, during the pandemic, urgently needed a telemedicine platform.
The center was able to develop and launch its platform within six weeks, allowing the organization to go from zero to 50,000 appointments, scaling eventually to hundreds of thousands per month.
This story underscores the platform’s ability to provide quick, scalable solutions for healthcare organizations during critical times, demonstrating speed and flexibility. The success is also attributed to the platform’s ability to integrate with existing Electronic Health Record (EHR) systems without requiring a complete overhaul, allowing for a smooth digital transformation.
Capabilities that Accelerate Transformation
To boost modernization efforts, organizations need help in enhancing integration, simplifying processes, and improving efficiency. So, these AI or low-code platforms need to have capabilities that address complex data and integration challenges, bridge system gaps, and enable rapid, scalable solutions with accelerated development.
For instance, organizations often try to improve efficiency by enhancing automation and partner collaboration; that is best achieved with functionalities that simplify and automate healthcare-specific HIPAA Electronic Data Interchange (EDI) transformation, enabling smooth data exchange, compliance with X12, HIPAA, and 005010 standards, and efficient workflows. This approach allows seamless data transformation across the healthcare ecosystem without the need for specialized EDI expertise, while also promoting accurate and efficient information exchange, reducing errors, and minimizing rework.
Furthermore, healthcare organizations need capabilities to simplify secure connections and perform essential tasks such as creating, searching for, and retrieving patient information, as well as managing appointments. In this regard, AI platforms with seamless access to Electronic Privacy Information Center (EPIC) EHR data can streamline data integration and facilitate collaboration across healthcare systems. The ability to do this while staying compliant with standards such as Substitutable Medical Applications, Reusable Technologies (SMART) on Fast Healthcare Interoperability Resources (FHIR) also helps reduce costs and drive efficiency.
The Way Forward
As we look to the future, the evolution of low-code platforms and AI in healthcare promises to enhance integration capabilities, facilitate agile development, and enable real-time data analysis. These advancements will empower healthcare organizations to deliver care that is not only more efficient but also increasingly predictive, proactive, and personalized.
In this modernization journey, the healthcare sector stands on the brink of transformative change, ready to embrace the innovations that will shape the future of patient care.
