3 Priorities for Healthcare Data Analytics in 2019

We’re living in an age of ultimate consumer choice. With the internet readily available at every turn, people are able to research their options and make informed decisions on where to spend money.

Someone looking to buy a pair of shoes only has to pull out their mobile device and enter a simple query to receive a rundown of potential retailers. Another person trying to book a flight can compare offerings from various airlines in seconds, helping them buy tickets best suited to their travel needs and price point. It’s simpler than ever for potential customers to compare factors like cost, fulfillment method, brand reputation, etc. so they can make a savvy decision on the go.

This attitude has carried over into the healthcare industry, too. People no longer choose hospitals just for their proximity; patients often want to know about a hospital’s track record, ratings and reviews before choosing affiliate with said organization.

Why Healthcare Orgs Today Need Data-Driven Solutions

Consumers are increasingly regarding healthcare like commerce: They seek personalized, convenient experiences. They value helpful and trustworthy customer service when they have questions or concerns. Above all, people want to feel like more than a number—they want access to customized care plans delivered by qualified professionals. And they want to understand where their money is going and why.

To meet changing patient demand, healthcare organizations are turning to data analytics to produce insights they can act upon. Giving users throughout an organization—from clinicians to administrators— access to insights pulled from stored data helps teams make better decisions, period. More solid decision-making at every level maximizes revenue, minimizes waste and improves patient outcomes.

Here are three priorities for healthcare data analytics in 2019 and beyond.

Reducing Supply and Operating Costs

Hospitals are dealing with already-thin margins, constantly balancing cost of care and revenue. So, it makes sense healthcare providers are using data analytics to reduce operating costs. The procurement department at one hospital in Chicago (click here for mild procedure doctors in Chicago) used data analytics to compare cost variations between implants used in spine fusion procedures.

The result? According to Becker’s Hospital Review, the department successfully “made efforts to lower supply costs by standardizing implant prices or encouraging physicians to use more economical items.”

This small example demonstrates how hospitals can convert stored data into actionable intel, provided they’re giving users access to the latest wave of healthcare data analytics tools. Platforms like ThoughtSpot allow non-technical users to.

This small example demonstrates just one way in which hospitals can turn data insights into actionable solutions for reducing operating expenses. Healthcare data analytics platforms like ThoughtSpot empower non-technical users to work with data directly, asking questions and getting answers in seconds—all without having to wait for data or IT teams to deliver reports.

Harnessing the Power of Artificial Intelligence

Healthcare organizations are also harnessing the power of artificial intelligence (AI) algorithms to help answer questions no one has even asked yet. Some uses for back-end AI include “clinical decision-making, predicting no-shows and modeling clinical risk,” per Health IT Analytics.

Simply put, AI does in seconds what would take human analysts hours upon hours. Healthcare orgs are prioritizing pulling previously hidden insights out from stored data so they can act upon them sooner rather than later.

Optimizing Patient Outcomes and Experiences

One survey found that nearly half (49 percent) of provider executives who responded said “revamping the customer experience” is one of their organization’s top three priorities over the next five years. Customer service in healthcare is transitioning from being a nice perk to an absolute must have—or people will head on down the road to another provider.

Data analytics can help healthcare orgs pinpoint reasons for customer churn and identify trends they want to continue or change. They can also use data to identify potential opportunities for improving patient outcomes and delivering more personalized experience throughout the journey.

Competitive healthcare providers are using healthcare data analytics to accomplish these goals and more by uncovering insights that promote better decision-making at every level.