Integrating AI into systems and workflows using a thoughtful hybrid IT strategy can help unlock productivity and collaboration among healthcare workers.
Key Takeaways:
- Siloed data and disparate technology significantly hamper healthcare collaboration and can lead to medical harm.
- AI helps glean meaningful data from all your sources and automates some administrative tasks. As a result, frontline workers spend more time with patients.
- A hybrid architecture lets you choose where AI runs, meaning you can match up data with AI for a cost-efficient, latency-optimized, secure, and scalable solution.
For many healthcare organizations, collaboration is hindered by existing processes, systems, and workplace solutions rather than individual clinicians’ practices. Data is scattered across disparate technology, making it difficult for health systems to derive meaningful insights. This lack of interoperability means those on the frontline can’t share patient information and report and analyze events seamlessly for continuous care improvement.
The right digital workplace solutions can reduce clinicians’ administrative burden and the likelihood of medical harm—a leading cause of death affecting roughly 25% of hospitalized patients. Artificial intelligence (AI) and hybrid IT strategies enable real-time access to patient insights for more informed decision-making.
This article explores how AI and hybrid IT strategies can power productivity and collaboration for frontline healthcare workers. Let’s dive in!
How AI Can Improve Clinicians’ Productivity and Collaboration
One of the biggest challenges in healthcare today is that workers don’t have efficient tools to report incidents and leverage existing data to deliver better medical care throughout a patient’s life cycle.
Here, AI can be the solution. It can help automate data extraction and analysis and the mundane aspects of incident reporting, considerably reducing the time and effort required while fostering a culture that empowers staff to voice safety concerns.
Every incident and near-miss can be extensively reported and shared across the organization. Now, with a single source of truth about patient risk factors, clinicians can work together to prevent similar harm incidents from occurring in the future.
Another way AI boosts productivity is by handling routine administrative tasks so that clinicians spend more time with patients. According to McKinsey, nurses spend only 58% of their time delivering direct care. Documentation, scheduling, and other day-to-day tasks occupy the remaining 42%. AI can reduce some of that administrative burden. For example, it can help take and transcribe patient notes during appointments or respond to questions so that patients get the information they need whenever they need it.
Generally, the idea behind incorporating AI into healthcare workflows is to automate tasks and speed up data extraction and analysis so that frontline workers can be more productive and collaborate better with colleagues.
Leveraging Hybrid IT for Better AI Use
Most healthcare businesses today run on legacy technology. Depending on the organization, this could include old applications, mainframes, or uncoordinated instances of public cloud usage. These can hinder innovation, drain IT budgets, and make it challenging to embrace AI.
Yet, completely overhauling legacy systems isn’t the solution to evolving the digital workplace. Your existing technology holds your data, and your data is the basis for your AI. AI requires both historical information and current and instantaneous data to work effectively. Breaking down data silos and creating consistent environments across the IT estate is key to realizing the true potential of AI. That’s where a hybrid infrastructure comes in.
To use an analogy, imagine your employees are on a road trip trying to get from point A to point B, but there are big ink blots all over the map, obscuring critical information and making it impossible to decipher the roads that connect to the destination.
In this situation, your team lacks the information needed to work effectively and efficiently. Failing to integrate data and systems or modernize legacy IT is like removing interstates from the map. Without a clear, fast route, your team must navigate backroads, slowing progress and increasing the risk of getting lost. They can’t leverage the latest technologies or fully utilize your data, leaving your operations stuck in the past.
By choosing an intentional hybrid architecture, you can bring AI to wherever your data and applications already reside. Your team can analyze the data in an optimized, organized, and secure way in the cloud and on-premise with governance built-in and integrated across this landscape from day one. In other words, healthcare organizations can tackle AI confidently and consistently, significantly improving productivity and collaboration.
Strategies for AI and Hybrid IT Adoption
There are a few considerations to keep in mind when modernizing your digital workplace. First, your systems must be stable and ready for AI. The most critical elements for system stability include:
- Elasticity: Having the appropriate capacity for expansion.
- Resilience: Having high availability and disaster recovery in place.
- Security: Having robust controls that prevent leakage and unauthorized access to patient data.
CoreAIR (Application Infrastructure Readiness) can comprehensively assess your existing infrastructure to quickly determine the best path to evolving your digital core capabilities.
It’s time to modernize operations once systems are stable and ready for AI. Leverage infrastructure as code, compliance as code, modern application observability, and automated workload rebalancing to speed up AI creation and deployment.
Be sure to provide seamless access to data. Regardless of whether your organization has been through multiple rounds of data management efforts in the past, the time is genuinely now to put in place robust data cataloging and data governance systems. API-based modernization can help you insert points into your applications where data and capabilities can easily be accessed.
Optimize end-to-end deployment. AI deployment is often feared to cause cost increases. However, it can have the opposite effect when approached strategically. For instance, automated workload optimization can help reduce GPU usage by better managing system resources. Similarly, using smaller, tailor-made AI models and rolling out implementation in small, manageable chunks can help reduce overall implementation costs.
As you embark on this journey, consider tapping an external resource with a track record of successfully deploying healthcare technology solutions to maximize your AI and hybrid IT investments.
Leverage Cutting-Edge Digital Workplace Solutions with Expert Help from NRI
Modernizing your healthcare organization’s digital workspace improves productivity and collaboration among frontline workers while reducing medical harm to patients. Integrating AI into existing systems and workflows with hybrid IT as a foundation is crucial to making this happen. When you power your enterprise with hybrid IT capabilities, tailor-fit models, governance, and best practices, you can drive real value with AI.
As a leading healthcare digital transformation consultancy, NRI is here to help you embrace cutting-edge technologies that match your medical expertise. Through CoreAIR, our pros can evaluate your infrastructure and recommend practical steps to quickly evolve the digital workspace without negatively disrupting existing routines.
Get in touch now to set up a new digital core where collaboration thrives.
