8 min read

Big Data and Digital Evolution in Healthcare

Oct 4, 2021 8:00:00 AM

The term “digital transformation” is often heard on this blog, and it is happening around us. However, is that an accurate description of what is going on, or should we use “digital evolution” instead? Few companies can afford to completely overhaul their systems simultaneously with all the disruption it causes. Many businesses prefer an organized and structured approach towards digital maturity. 

One of the core benefits of a structured approach to digital evolution is operational continuity - and it is particularly apparent in sensitive industries, like healthcare. Health systems have been stretched to the limit during the global pandemic, and while many proved to be robust against all the odds, frailties have been exposed. 

The challenges health systems have faced worldwide have been unprecedented, bearing the brunt of the unfolding human tragedy. This has spurred on a new era where 81% of healthcare executives are experiencing an increased pace of digital transformation.  

Additionally, as the world begins to imagine post-pandemic life, 93% of executives say there is a renewed sense of urgency in the innovation of such companies. 

Digital Evolution of Healthcare 

Digital healthcare is more than just smartwatches, health apps, and rapid test devices. From a broader perspective, it encompasses all aspects of the health industry, including data management and systems. The evolutionary approach enables companies and other organizations to continue to provide critical services and products with minimal interruption. 

For instance, instead of transforming the whole system, digital evolution would see parts of the system being updated while other components pick up the slack.  

In healthcare, it is essential to maintain the quality of service while adhering to complex regulations that can vary across national and even state borders. By compartmentalizing digital transformation into an evolutionary process, companies and organizations will be able to meet each of the requirements while taking a step towards digital maturity. 

There are plenty of examples where overhauls to IT systems in healthcare have gone wrong. The UK’s NHS IT system failure, which cost the British government over £10 billion ($13.9 billion), is often cited as a prime example of where digital transformation can fail. There were several reasons behind its failure, but with a well-thought-out strategy, the right tools, and buy-in from stakeholders - such a scenario can be avoided. 

Managing “Big Data” 

The first step in any digital evolution is to look at what fuels the digital age: Data. We’ve heard a lot about Big Data, but what does it mean in the context of healthcare? 

In essence, it involves all the data involved in healthcare systems from all the various sources and formats. Here’s just some of them: 

  • Patient health records 
  • Inventory - including medicine, equipment, and PPE 
  • Government records - such as regulations and social care records 
  • Medical research - academic papers, journals, etc 
  • Smartphones and other wearable devices 

As you can imagine, each of these sources can generate a vast amount of data, which is increasing year on year. Health organizations and systems that 
can handle and process all this information as it comes in will be able to lay a solid platform to build its digitalization strategy. 

The key is to have the right tools in place to manage the data. 

One of these tools is APIs (which stands for application programming interface), which allow two programs to communicate with each other. It works by processing the information between two or multiple platforms so that the data can be used in different formats. APIs also act as a filter so that only the relevant information gets through to various programs. 

For example, if a doctor was looking for a patient’s medical records, which could come from the wider government database, they would only want to see the patient’s health history. APIs can be used as a communication tool between the government database and the medical records software, filtering out irrelevant details like education and tax history. 

This ability to filter out data is critical because it enables systems to avoid being overwhelmed with data. Without a mechanism to control the flow of data coming in or out, IT systems would simply collapse under its weight. 

Using Big Data to Implement Digital Evolution 

The possibilities of refined Big Data in the healthcare industry are endless. It allows providers to deliver more accurate diagnosis and personalized treatment. Patients can access doctors and other medical professionals remotely through smartphones. Wearable devices like Fitbits and other such watches can help people monitor their health in real-time, reducing pressures on health systems. 

The remarkable thing is that these possibilities are already a reality, and there is much more potential to come. 

From a macro perspective, having a system in place that efficiently manages data allows health systems - both private and public - to increase the accuracy of patient records, improve access to medicines, and identify the best treatment plans with the resources it has. 

By recording and tracking data in real-time, medical professionals will be able to treat patients better with individualized plans and monitor progress. 

The accessibility will also support faster processes, particularly in terms of diagnoses and treatments, where time can be the difference between life and death. Having already led the way to unprecedented advances in the field of medicine, the future also looks exciting: 

  • Wearable devices are not just gimmicks: There have been multiple studies on the potential of wearable devices. Apple Watch already can detect irregular heartbeat, which can be a sign of numerous heart issues. It has been working with a team from Stanford University to develop the product further, and such devices will become more accurate and complex in the future. 
  • AI and machine learning are set to be at the heart of healthcare: Harnessing the sheer power of Big Data with advanced software is a challenge in itself, but leading health companies, including the Mayo Clinic, have joined forces with IBM’s Watson Health computer system. The idea is to support doctors to reach better diagnoses more quickly by tapping into the vast reservoir of information, including academic journals and other medical records. 
  • Personalized healthcare: The most exciting part is all this Big Data can be distilled right down to the individual. It can deliver the best solutions and treatment for one patient, not just one or two strategies for specific conditions. Healthcare is already becoming increasingly personal, and it will become even more so in the future. 

Focus on Digital Evolution

The likelihood is that your healthcare organization is already digital to some extent. If you keep medical records in the cloud or carry out online consultations - then you have started to embrace the digital age. The reality, however, is that a complete overhaul to cutting-edge technology will not happen overnight. And nor is it particularly desirable. 

Trying to rush through digital transformation is likely to cause disruption and negatively impact your service to patients and stakeholders. 

Using tools like APIs and advanced API integration platforms, you can connect existing systems with new ones as you incrementally bring in the technology needed to achieve cutting-edge healthcare. Taking it step by step allows you to assess the performance, make the necessary tweaks and be ready for the next stage of development. 

Evolve your way to delivering healthcare that saves and enhances lives. 

Peter Edlund

Written by Peter Edlund