Modern technology is changing the world in so many ways, it’s become difficult to quantify all the different transformations that are happening, especially considering a lot of them are occurring simultaneously. From new and various forms of technology including AI, machine learning, big data, and IoT to new applications of it, big things are happening.
One area that is seeing a lot of change yet doesn’t get as much coverage is the long-term care industry, effectively described as the nursing home field. Residential and elderly care programs are being upgraded for modern times.
It makes a lot of sense why, especially when one understands the benefits afforded by going digital. In general, a digital transformation can offer cost savings, higher efficiency ratings, more eco-friendly processes, better customer or care experiences and much more.
Benefits aside, the real question is how these data-oriented technologies are changing the field? What new opportunities do they provide and how are they improving or restructuring legacy operations?
In any medical or health-related field, patient care is a concept that is constantly evolving or adapting over time. This is because there are two timelines essentially playing out in parallel. The first is the application of certain treatments and care programs, which health professionals are using to enrich the lives of their patients. The second is the research and development application where scientists are constantly pushing the envelope to discover new treatments and solutions.
As some of the newly discovered solutions are rolled into the mainstream field, there’s a merger between old and new mirroring what’s happening thanks to the introduction of new technologies.
Data-oriented systems and programs can help even out this entire scenario, providing seamless integration of the new treatment plans and solutions. A multitude of data about active patients, past experiences and future solutions can be digested by data analytics tools to discover potential uses. Many of the newer systems — machine learning provides the power — can discover new opportunities faster, better and oft-overlooked by their human counterparts.
The result is a more successful and efficient industry where long-term patients are getting exactly the kind of personalized care they need.
As organizations and teams make the conversion to digital platforms, all existing resources and documentation must make the leap, as well. This is an incredible challenge in healthcare simply because of how much documentation it involves. Even just a single patient’s records and history can include a massive collection of data points and documents.
This presents something called data overload, where there is just too much digital information and content for the average professional to process. Even with incredibly skilled and devoted teams of analysts, databases can be just way too big to deal with.
The solution is to implement credible and trustworthy platforms that can help ingest, organize, process and spit out useful insights. Machine learning and AI will be the drivers behind such technologies, but there are other solutions that will be necessary to make it work including cloud computing, big data and advanced analytics.
As these systems come online, they will need to be both vetted and secured in order to keep up with the stringent healthcare policies and regulations — HIPAA compliance is a great example. But at the same time, technology will help transform the use of data and digital content in the field. It goes well beyond simple data entry and allows for remarkable applications. Real-time insights about a patient, for example, can help ensure they are being provided the right care.
Even something that seems unrelated, like legal documentation, would benefit from data solutions in the industry. Most long-term care facilities need legal representation to deal with potential problems, the least of which requires extensive documentation collection and storage. That information when stored, processed and handled in digital form suddenly becomes much more manageable, and trackable.
In a hospital or medical facility, there are often varying professionals that either provide care or support patients. It’s not always the case where a patient is assigned a single doctor or nurse. This creates some challenges in terms of logistics, as each professional must first weigh what the previous caregivers were doing, how that might have affected the patient, or even how that might influence potential future treatments.
The same thing happens in long-term care and nursing home situations. You can’t have nurses manning a single patient all day every day, there are always going to be shift changes. There’s also a point to be made for turnover rates, where one professional might leave the industry entirely taking a lot of their patient familiarity and expertise with them.
But data-based solutions can help prevent issues that occur with these trade-offs. One nurse can pass the torch, so to speak, in a much faster, more efficient and more reliable way simply by sharing access to patient data with those who need it.
Everything from existing and prior treatments to patient reactions and even recommended solutions can all be recorded and factored into a data system. This allows subsequent caregivers to view and assess the full brevity of a patient’s care.
It’s true that healthcare data and related systems, as a whole, are in their adolescent phase, which means regulatory bodies are still trying to iron out how and what to do with them. That doesn’t mean the technology doesn’t have its uses. More importantly, it’s not necessarily a reason to avoid implementing such solutions, especially when there are a lot of advantages they can provide.
In long-term and elderly care especially, documentation plays a huge role in the care and treatment of certain patients. It’s about more than just their medication or daily schedules, it also includes their entire medical history, genetics, current health, and much more.
Data solutions can help provide the necessary automation, efficiency improvements, clinical and financial support and even a reduction in manual or clinical errors.
Kayla Matthews writes about data centers and big data for several industry publications, including The Data Center Journal, Data Center Frontier and insideBIGDATA. To read more posts from Kayla, you can follower her personal tech blog at ProductivityBytes.com.