Experts explain how mindshifts and new technologies can lead to smarter, accessible healthcare services.
Reports show global healthcare IT could become a $200 billion industry by 2020, but experts say these are challenging times for healthcare organizations navigating regulations and a wave of digital health data technologies.
Using technology to improve healthcare quality, safety and efficiency has been an uphill battle. Experts say there’s a need for better cooperation, interoperability and a shift from reactive to proactive use of patient data.
This shift could lead to what’s being called “automated care,” where computers analyze tremendous amounts of health and lifestyle data, then use artificial intelligence to deliver data-driven options that help doctors treat patients.
If the U.S. healthcare industry used big data to drive efficiency and quality, the sector could create more than $300 billion in value every year, according to research firms MGI and McKinsey.
But for the most part, the healthcare industry remains in an era of little data, according to Kenneth Laliberte, a products solutions manager at Meditech, which sells information systems for health care organizations.
“We have yet to really unleash the power of big data,” Laliberte says.
He said harnessing the power of big data requires healthcare organizations to move from a mindset of hindsight to foresight. The ability to collect, manage and access a wide array of patient data will help keep people well, rather than just address health needs when illness occurs.
Data Systems That Work Together
Patient data is often fragmented, not captured in a uniform manner, and inaccessible by providers when they need it. Managing and using patient data require interoperable systems, and this is a big challenge, according to Andy Bartley, a senior solutions architect for the Health & Life Sciences Group at Intel.
He said Health Level Seven International and other standards organizations advocate for consistent protocols for sharing data between protected health devices.
“It’s not an easy issue to solve, and even with national and international standards bodies, there’s still a lot of work to do to try and solve those problems,” said Bartley.
About 80 percent of health data is unstructured, which means it is captured but not organized in a pre-defined manner, according to Laliberte. That means this important information is not categorized, making it difficult to find.
“That’s all data needed to get an accurate picture of a patient population,” said Laliberte.
Plus, other information could be considered useful, too, including lifestyle and behavior data, neighborhood conditions or even personal health tracker data.
Laliberte said categorizing data more thoroughly can help healthcare organizations and clinicians identify hot spots of high-cost patients and chronic disease.
Even without a universal healthcare data system in place, organizations still need to use all the patient information available, according to Mark Wagar, president of Heritage Medical Systems, which manages patient care through physician groups and independent practices.
“The fact that we don’t have perfect information is not new,” said Wagar. “Everybody is concerned that [big data] is not perfect so you wait and tweak, but the patient cannot wait. You need to take the pieces of the information you can get and consolidate it.”
Wagar said without well-categorized data running on inter-operable systems, organizations collate data from multiple information platforms, including hard copies and hand-written forms — all of which can be inefficient and compromise health outcomes.
New Payment Approach
The U.S. outspends any other country in the world when it comes to healthcare, according to the World Data Bank. Spending on healthcare in the U.S. has increased by nearly 25 percent in the past decade, and now exceeds 17 percent of the GDP.
“There’s enough money spent on healthcare. We have to repurpose it,” said Mary Cooke, DHA, RN, vice president of strategic military alliances and of the Johns Hopkins US Family Health Plan.
“More important is the human cost of not providing targeted and effective care. How can we have an architecture that provides an analytics platform that meets our needs?”
It’s not an easy time to be a healthcare organization, said Bartley.
“It’s getting harder and harder to be a small independent practice,” he said. “New regulations are changing the way that healthcare is paid for. Even large health systems are having to look at how they vertically integrate and increase the number of covered lives that they’re responsible for in order to manage risk.”
One new approach is the shift away from a fee-for-service payment model to pay-for-performance or value-based care system that offers healthcare systems incentives based on their ability to improve patient outcomes. Bartley said this emphasizes managing patient populations and overall health rather than focusing on medically coded billing and reimbursement transactions.
“That starts to align the various market participants in the healthcare system,” he said. “You need everybody, from healthcare providers, pharmaceutical companies, medical device makers and payers to evolve their business models to streamline the financial process of the whole healthcare system. Patients play a critical role in this transformation as well. Value-based care encourages wellness, which means increasing engagement with healthy behaviors and managing chronic conditions.”
Regulations like the Medicare Prescription Drug Improvement and Modernization Act of 2003 and the Affordable Care Act in 2010 — and the current administration considering changes to the law — brought greater awareness to these complexities, according to Bartley.
“It’s not as simple as just knowing how to reimburse the healthcare providers,” he said. “There are many moving pieces and a different places where money flows.”
Predictive and Automated Care
Bartley said leveraging big data technology can increase access to care. One example is what he calls care automation.
“Imagine getting self-service healthcare based on your history and your specific symptoms without having to come in and see anybody, he said. “And you do that from the convenience of your home or from your mobile phone.”
He said this is at the intersection of evidence-based medicine, big data and artificial intelligence. Technology can help automate care for many common conditions, and eventually more complex conditions.
He said a hot topic in healthcare tech now is predicative analytics, the ability to take data, apply machine learning to it and build a system for predictive recommendations. This technology can help predict the number of patients that will visit an office on any given day or identify patients with the highest risk of getting a certain disease.
“It’s about using historical data to help predict the future,” said Bartley. “It’s one of the next big waves of analytics in healthcare.”
Putting the data infrastructure in place and building analytics capabilities are only part of the challenge. A massive mindset and cultural shift needs to happen in order for health organizations to embrace data-driven decision processes.
“The technology is a small part of what’s needed to implement predictive analytics,” said Bartley. It requires new processes and methods for delivering care.
”Putting data to use will help healthcare providers improve patient access to quality care and control costs. Having a handle on the data can point the way.”