Artificial Intelligence in Healthcare — Today vs. Tomorrow

September 09, 2022
Bridging the gap between what’s possible today and what could be possible tomorrow is what digital transformation is all about. Artificial intelligence (AI) in healthcare is one area in particular in which healthcare organizations are betting on. As new technologies emerge, the importance of properly using data is clearer than ever. We’re seeing a shift and now more than ever organizations want to assess the predictive power of their data. 

So, what does today and tomorrow look like for healthcare companies? Here are four key areas to pay attention to as everything unfolds. 

1. More Time Will Be Spent on Higher Value Initiatives 

Today, companies are taking a more manual approach to organizing and analyzing their data. They are being reactive versus proactive (and reactive data teams do not support data-driven decision making). Simply put – today, too much time is spent gathering and accessing data rather than focusing on higher value initiatives. 

In the future, more time will be spent on higher value initiatives as data-backed decisions are embedded into processes. In the past, data was only extracted and analyzed when necessary. In the future, data will be readily available in a way that answers critical business questions, looking at both historical data and future predictions. In healthcare, this means that data could help providers improve care, avoid harmful practices, and more. 

2. All Data Will Be Integrated to Eliminate Knowledge Silos 

Many organizations today are gathering data from different business lines across different databases. As a result, the data is not talking to each other. Reports become meaningless if you can’t connect them to each other and see the larger picture, considering all variables across various databases. 

Integrating data has multiple benefits and businesses are already starting to make the shift. By integrating your data, you can improve data quality, make it more readily available and make quick connections. Real-time business insights, augmented intelligence and analytics also make for stronger collaboration across the business. The result? Increased efficiency and ROI. It’s not a matter of should your company integrate data, it’s a matter of when you will do it. 

3. There Will Be a Shift to Prediction-Based Decision Making    

There are multiple versions of the truth right now. Organizations need to move to prediction-based decision making and make data-driven decisions based on the truth. If organizations aren’t moving towards data maturity, they won’t be able to answer the questions that executives within the business have. 

As we move the needle further, companies need to develop a culture of fact-based decision making. There are so many questions that executives can't answer to effectively run their business. There are multiple versions of the truth and a stack of siloed reports that only tells a partial story. There is a need to move to prediction-based decision making (make data-driven decisions based on future predictions).  

4. Improvements in Reporting Will Allow the Data to Tell a Story 

Nowadays, you can get reports, but data isn’t centralized to where you can get the answers you need. It could take three reports to answer one business question. But what if your data told a story? Unless you know what questions you’re trying to answer, who cares about all the data?   

With how fast technology moves, companies must adapt. The healthcare sector is no exception. In fact, healthcare companies will have to start taking full advantage of their data by adopting the latest AI technologies if they want to remain competitive. 

Data teams don’t exist just to put out fires. Instead, they should be seen as collaborators and true partners within the business. Times are changing, and it’s important that everyone knows the power of data and the importance of how to properly use it. Maybe your company hasn’t achieved data maturity yet, but eventually, all of us will be making more data-informed decisions.