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Enabling better patient care with AI automation

Thanks to Hollywood blockbusters like iRobot and The Terminator, many of us believe that Artificial Intelligence (AI) is all about robots. While there are examples of this, like the use of robots in surgery, AI for the most part isn’t about attention-grabbing humanoid bots.  

Automation is actually one of the most common and biggest benefits of AI in its current form. For the healthcare industry, being able to automate basic tasks in operations and administration can result in an improved patient experience, quality of service, better project implementation and lower costs.  

Advances in AI and machine learning are driving a shift in how technology is applied and data is utilised in everyday healthcare environments. The opportunities these emerging technologies present is critical as practitioners and business and IT leaders work to enable improved improve clinical outcomes, patient experience and hospital operations.

Through AI and machine learning, computers can learn to recognise patterns in unstructured data - information that comes in many different forms and is therefore difficult to store with traditional databases – in a way that enables automation to be applied. Over the next two to three years, innovations in electronic health records (EHR), revenue cycle, and operations will see AI enabled throughout the healthcare industry, both public and private. AI will be integrated into the clinical workflows in existing tools like EHRs and medical imagery technology such as picture archiving and communication systems (PACS), empowering practitioners with real-time data at the point of care.

Unlocking opportunity

AI is levelling the playing field as projects and innovations that were previously thought to be out of reach as either too costly or time-consuming are now possible. If the cost of a new project can be reduced by 50 percent through the use of AI to automate key aspects, the project now becomes feasible. Additionally, cost-savings in one area can free up funds to invest in other areas. 

As waiting times increase and staffing continues to be an issue in the NHS, putting AI to use in the automation of basic tasks and processes can result in a better overall quality of care. 

In radiology, PACS systems are using AI to automate tasks like worklist optimisation and hanging protocols – critical applications that can improve workflow and productivity for radiologists and radiology administrators. That has a positive impact on patient care, but also on productivity and therefore waiting times.  

Impact of automation

As these new tools are implemented, having the right infrastructure to support high performance – fast, dependable, and capable of handling lots of data – is paramount. Outside of radiology, automation can have a big impact in many operational and administrative areas: 

Faster data to enrich EHRs

The NHS is working to modernise the capabilities of EHRs to generate and extract data in as close to real-time as possible. Technology providers can now implement systems with new APIs and new ways to harness data. Such efforts could reduce physician frustration and enhance patient care as doctors and nurses get the information they need at the right time, in the right setting.  

Improved ordering 

One of the most time-consuming processes for physicians is the prescription request process within the EHR. Ten years ago, a physician could write an order onto a prescription pad in seconds, compared to the multiple clicks in takes to complete a prescription now. However, medical processes have moved on since then, and prescriptions must be requested and logged digitally. Predictive technologies and AI can make a real impact to drive efficiencies in this area. Tools such as voice-activated virtual assistants are emerging to enhance the prescription and patient scheduling processes.  

Adaptive staffing 

Health systems are beginning to use machine learning to adjust staffing to support fluctuating emergency department patient volumes and reduce wait times in ambulatory services. By using historical data across multiple sources, NHS Trusts can understand when to scale up staff to handle an influx of patients for the upcoming flu season or ramp up other support staff during warm weather to ensure a smooth patient experience in A&E.

Conclusion

It is clear that AI has vast potential to improve healthcare, an industry that has long felt the pressure of budgetary and resource constraints. AI will facilitate innovative and transformative technologies, helping to achieve improved outcomes whilst helping reduce operating costs. Contrary to popular belief this doesn’t just revolve around robots supporting humans in surgeries. It has already started on the administrative side, and the possibilities for the future are boundless.

Peter Gadd, VP Northern EMEA at Pure Storage



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