Eight data analytics terms every healthcare executive should know

With so much going on in health IT, it can be difficult to keep track of all the buzzwords. Here’s your quick and easy guide. 

1. IoT –Internet of Things

This term encompasses the overall trend toward connectivity and computing in more and more devices. In healthcare, the increase in wearables and more use of smartphones and other mobile devices to connect with patients show that more everyday items will be connected to improve patient care. The goal of these devices and technology is to make healthcare a seamless part of consumers’ lives, says Ben Alexander, MD, chief medical information officer at WakeMed Health and Hospitals, a Raleigh, North Carolina-based not-for-profit health system.

“In healthcare, this will become more important as we try to keep patients healthy and away from the healthcare system, but are still responsible for their health outcomes,” Alexander says.

Continuous glucose monitors, fetal monitors, blood pressure and other health condition monitors are examples of how IoT technology has permeated healthcare. Ultimately, the goal of the increase in patient data will allow providers the opportunity to make better decision that lead to better outcomes, Alexander says.

“The rise and spread of wearables like the fitbit, smartwatches, and smartphones will give us a huge amount of data about our patient’s lives that we’ve never had access to,” Alexander says.

2. Data Mining

With all the different types of data being generated in healthcare, finding ways to interpret and analyze it is a very important part of the process. The amount of data generated from EHRs is just one source of the huge amount of data available in the healthcare system.

Data mining examines large databases to generate new information. As data increases, it will be important for healthcare organizations to be able to uncover patterns of patient behavior that can improve future outcomes, says David Martin, vice president of IT and operational systems at Guardian Pharmacy Services, which partners with independent pharmacies to utilize human capital management, revenue cycle management, financial reporting, and other business services.

“Modern healthcare businesses produce a tremendous amount of data on a daily basis,” he says. “Good data mining allows leaders to spot trends and predict behaviors, across almost every functional area.”

3. Artificial Intelligence

Artificial intelligence (AI) is a term that has been used in science fiction, but now has real world implications. In healthcare, it refers to devices and programs that use reasoning, natural language, processing, machine learning and human interaction to learn over time. AI technology in healthcare acts as an assistant to broader cognitive computing systems in determining processes and decisions, says Jaspinder Grewal, CEO of CareSkore, a population health management technology company that utilizes artificial intelligence.

“Cognitive computing acts as an advisor. Artificial intelligence takes that a step further by acting as an assistant.”

Healthcare organizations are already using AI technology to mine patient data, study genomics, and improve financial operations. A report by CB Insights released in February 2017 estimates there are more than 100 AI companies with a healthcare focus.

Next: Big Data

4. Big Data

Probably one of the most used terms in healthcare technology, big data describes the variety of information assets that can be used and analyzed through different methods.

“If used properly, big data allows leaders to link loosely associated data points to identify trends and make decisions not available under traditional analytics,” says Martin.

With all of the hype around big data, some experts caution against getting too caught up in the concept.

“Executives should not get distracted by thinking that ‘big data’ is something that they need to go make big investments in right now,” says Alexander. “Instead, focus on building a culture of data-driven decision making within your organization and develop your staff with basic skills in data analysis.”

5. The Cloud

When someone from your IT department brings up “the cloud,” it may sound like some nonexistent place where information is stored. Actually, the cloud is a way of storing and accessing data and programs over the Internet instead of on a hard drive.

There are many computer applications moving to the cloud, including EHRs, health information exchanges, human resources, and financial data applications. Some organizations use cloud-based applications to back up hard drives and other local (on-site) drives.

“It’s really just someone else’s computer,” Alexander says, meaning that though the information is accessible through computers, tablets, and other connected devices, it is housed in a place owned by another entity.

According to the 2016 HIMSS Analytics Cloud Survey, 84% of IT healthcare organizations are currently using cloud services. In addition, three-quarters are moving an existing or new workload to the cloud.

6. Predictive analytics

Being able to forecast and predict patient behavior can save money and improve patient outcomes. This is called predictive analytics: The practice of extracting information from existing data sets to identify patterns and predict future outcomes.

“Predictive analytics allows leaders to adjust strategies and tactics in marketing, sales, and customer service based on what customers will want in the future, based on historical behavior,” Martin says.

Reducing hospital readmissions is one of the most popular areas for predictive analytics, as data scientists look at a variety of factors and existing outcomes to make predictions on which patients are at higher-risk for being hospitalized repeatedly.

7.  Modern data management platforms

Healthcare organizations need to understand modern data management platforms to communicate with multiple stakeholders and bring together different operations in their business.

Modern data management can allow organizations to create patient profiles based on EHR information, lab results, claims, and reimbursements in one system. Because so much of the healthcare system operates in silos, finding ways to increase interoperability continues to be an important aspect of technology, says Ajay Khanna, vice president of product marketing at Reltio, a healthcare technology company.

“Healthcare organizations need a modern data management platform that brings together information from all internal, external, and third-party sources and helps create data-driven applications supporting all patient-centric initiatives,” says Khanna, adding that the 360-view technology also assists clinicians in reaching quality metrics through using graphics and other user-friendly features that patients, caregivers, clinicians, and business leaders can interpret.

“Beyond patients, it also helps in creating complete and reliable physician profiles as required by CMS and healthcare organization profiles,” Khanna says.

8. Data-driven applications

Healthcare organizations must start thinking like other consumer organizations to increase patient engagement and adherence. The increase in data-driven applications for healthcare makes it easy for patients as consumers to interact with health plans and systems. Data-driven applications can show relationships between people, places and activities, similar to Facebook, but using healthcare data from different silos in the system.

“Data-driven applications have the same power and ease of use of consumer applications, like LinkedIn, Google, and Facebook, but they're focused on your specific industry and business,” Khanna says.

These applications focus on being user friendly. Many include easy-to-read charts and graphs so that users can visualize the data, not just look at numbers. The visualization helps makes the data easy to interpret, and easier to make actionable, Khanna says. They enable a complete understanding of patients, physicians, payers, and other partners, with real-time visibility into relationships, health metrics, and resource utilization trends by the site of care.

“Data-driven applications also provide reliable information, enabling new healthcare models like pay-for-performance and helping healthcare organizations with improving treatment adherence and reducing readmission rates,” Khanna says.

Donna Marbury is a writer in Columbus, Ohio.