Jerod Johnson on the Big Data transformation in healthcare

Jerod Johnson, technology evangelist at CData, sees Big Data rapidly transforming healthcare. He’s how to check if your data strategy can keep up

Big Data is intrinsic to today’s healthcare system. In fact, nearly a third of the world’s data volume is generated by the healthcare industry. 

But whether healthcare organisations can effectively manage all this data — let alone extract actionable insights and tangible value — is another question. The simple reality is that almost 90% of organisations aren’t prepared for the mass volume of data that lies ahead. 

The healthcare industry has historically lagged behind other sectors when it comes to digital innovation, but many in the sector are discovering they can no longer operate without a connected, cohesive data analytics strategy. Recent innovations in telehealth, advancements in AI and machine learning, and the accelerated pace of digital transformation have only added fuel to the fire — and organisations that don’t move with urgency will only fall further behind.  


More healthcare data, more challenges 

From patient portals and EHRs to wearables and ER wait-time tracking, healthcare organisations have more data at their fingertips than ever. But if they can’t effectively access this influx of information and capture meaningful insights, what’s the point of even collecting it?

While lagging data strategies hamstring organisations, advanced data analytics offer extraordinary opportunities that positively impact patients, providers, and organisations. Here's just a handful of the many benefits: 

  • Medical practitioners can speed up the time it takes to make accurate diagnoses, enhance treatment options, and improve patient care
  • Health providers can measure patient outcomes and the efficacy of treatment plans, increase healthcare access and equity, and upgrade patient experiences
  • Hospitals, clinics, and other healthcare facilities can lower re-admittance rates, manage disease outbreaks, and optimise resource use
  • Organisations can increase operational efficiencies, reduce costs, and ensure the best quality of care alongside a strong bottom line

Managing the volume, variety, and velocity of data is a formidable job for any organisation. But it’s made even more challenging by the unique privacy and security requirements present in healthcare. In particular, healthcare organisations must extract insights from data without compromising or exposing patient information as required under HIPAA. 

Unlike other industries, it’s not enough for healthcare organisations to simply collect and organise data in a warehouse. They also must anonymise, while still maintaining, useful data points. Without the proper practices and technology tools in place to analyse data without exposing patient information, all of the organisation’s data essentially goes unused and meaningful insights go undiscovered. 


Building better data operations in 2023

The volume (and value) of data is poised to grow even faster in the coming years. Yet, despite the impending deluge of data, six in 10 health systems are halfway or less from their ideal digital state.

The year ahead will prove crucial for organisations to make progress toward building better, more comprehensive data practices. As you reevaluate and refine your data analytics operations, consider the following steps to keep up with the trajectory of Big Data: 


Break down data siloes

Four in ten organisations say data is highly fragmented and siloed. Currently, nearly all health systems are in need of greater interoperability among their healthcare data. However, these findings underscore the need to open and expand access to data sources throughout the organisation. 

Take one of our customers at CData, an in-home healthcare provider that acquired a smaller company. While the smaller company predominantly operated on Salesforce, our customer standardised on a homegrown CRM, requiring them to replicate and share data between the different systems and structures. 

As the depth and breadth of data sources and analytics tools continue to grow, dismantling data siloes and ensuring interoperability becomes even more important. For example, continuous data replication solutions that seamlessly move data from different systems to a common data store allow organisations to extract and move anonymous or sensitive data into HIPPA compliant systems.


Find greater value from AI

Advancements in AI models and training have led to more accurate diagnoses, better predictions, and more effective treatment plans. In fact, AI and machine learning have delivered more value than expected for the majority of healthcare and life sciences companies.

Still, nearly three-quarters of organisations struggle to select the best AI technologies, and only one in three say their AI capabilities are sufficient in supporting digital transformation. If you fall into the category of those struggling with AI, you may have bit off more than you can chew. Be sure to develop the necessary skills and expertise by starting with small initiatives that you can scale up as you mature. 


Strengthen cybersecurity practices

Healthcare unfortunately remains the top target for cyberattacks — and resulting data breaches are more expensive than any other industry. 

These threats underscore the need for organisations to prioritise secure and intelligent data management technologies and practices. Robust, continuous backups and rapid data restoration solutions are a good place to start. From there, implement ongoing updates and improvements to your data security configuration, such as adopting the latest encryption protocols, hosting on-going employee education, or implementing simple practices like multi-factor authentication and regular software and systems updates. 


Connect real-time analytics 

Data insights have an expiration date. If data isn’t timely, relevant, or accessible then it won’t provide much value. Real-time data connectivity solutions allow teams across your organisation to seamlessly connect to data sources, obtain live data from those sources to collect accurate insights and optimise decision-making.

The possibilities are evident in the modern drug discovery and development lifecycle. For example, pharmaceutical companies gain more rapid, efficient insights into research findings, drug testing and trials, and treatment efficacy with real-time data. The high-speed delivery of the COVID-19 vaccine is a prime illustration of what’s possible. Going forward, real-time analytics will enable the pace of drug development to continue to accelerate along with many other uses across the healthcare industry. 

The healthcare industry has entered a new era of data analytics. Whether it’s AI-enhanced diagnostics, financial figures, or patient feedback via an online portal, all of the data is interconnected. Organisations that can access, analyse, and act upon data insights are positioned to thrive in today’s data-driven healthcare landscape. 

With more data sources, higher volumes of data, and better technology to support advanced analytics, there are greater opportunities for healthcare organisations to adapt, innovate, and find new value, if they are willing to embrace change. Are you ready to set your data operations up for success?


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