Healthcare Unbound episode recap:

• There’s never been more healthcare data (or access to it). Data on various aspects of patients’ journeys through the healthcare system are particularly powerful for both providers and payers.
• Healthcare data can reveal critical insights and actionable steps toward improving the quality, efficiency, and affordability of care. 
• On this episode of Healthcare Unbound, Clarify Health Solutions Senior Director Sapna Prasad, PhD, shares how healthcare data has evolved and why understanding patient journeys is so relevant now. 

Today, revolutionary ways of compiling, processing, and analyzing healthcare data are transforming the industry, but context is still everything. 

For physicians, that can mean taking a holistic approach to patient care. For healthcare organizations, it might be a matter of collecting data on patients’ ZIP codes, education levels, and incomes — and even whether they rent or own their homes. Those aren’t clinically necessary, but they’re vital to understanding how to better serve all patients, regardless of their demographic markers.

In public health, the mantra is that “it’s not just about the physical; it’s about the mental, the social, and the psychological,” says Sapna Prasad, Ph.D., senior director and head of Clarify Insights at Clarify Health Solutions. “Being able to see that in data sources we wouldn’t traditionally use is very powerful and still untapped. There’s a lot we have to learn about how we use that data, but it is helping us widen our lens and think about things differently than we have in the past.”

At Clarify, Dr. Prasad leads a team of analysts and clinical informaticists who deliver data-driven insights to payers and providers. She says that one of the best ways to understand the healthcare system at large, as well as individual medical groups, hospitals, and other healthcare organizations, is to understand the patient journey. In many ways, any given patient’s journey is a microcosm of these institutions.

“Patient journeys are not new in healthcare,” Dr. Prasad says. “But they have evolved over time.”

The biggest catalyst for this evolution is the internet. WebMD and “Dr. Google” are often an individual’s first interactions with the healthcare system. Patients find healthcare providers, schedule appointments, and even rate doctors and hospitals online. 

“We see patients, in some cases, who have moved from being passive users of healthcare to coming into their doctor’s offices … advocating for themselves,” Dr. Prasad adds. 

That has changed the game for providers and payers, who now want to analyze patient journeys so they can improve quality and patient outcomes — while maintaining efficiency and profitability. 

Data in healthcare and the power of the patient journey

Today, there’s an unprecedented amount and variety of data available to us. Even everyday consumers can access healthcare price transparency data. Certainly, healthcare providers have a bigger appetite for consuming that data — a dynamic in which “the patient journey is more powerful than it ever has been before,” Dr. Prasad says. That massive data can be overwhelming, though. It has to be segmented, organized, and analyzed — which is a daily struggle for insurance companies and providers. 

Traditionally, tracking the patient journey took a “clinically focused, episode-based yet siloed approach” that included timelines and courses of care, says Dr. Prasad. Ultimately, the power of patient journey data is unlocking patterns and uncovering areas for improvement. Clarify aims to understand how patients access and seek care alongside insights into their experiences and outcomes. The ways patients are transported to hospitals, for example, are among the factors affecting whether they can access care quickly and efficiently. 

That’s why Dr. Prasad sees the patient journey as a building block of initiatives like value-based care, which requires benchmarks to understand inflection points and figure out how to drive change.

What healthcare data can teach us 

Dr. Prasad says there are two distinct approaches to working with healthcare data:

1. “Sometimes you want to let the data speak for itself,” she says. We can map millions of claims data into “tactical” touchpoints like diagnosis type, time to diagnosis, and other clinical facets of the patient experience. That’s useful both on both individual provider and institutional levels. 
2. The other approach is to ask targeted questions about specific patient populations, like how quickly they can access procedures and whether that affects their outcomes.

No matter which tactic they take, Dr. Prasad thinks it’s necessary for executives at provider and payer organizations to look at data with a clinical lens. 

“Data can tell you lots of stories,” she explains. “You can make a data set say anything, but you ultimately want the patient journey to be relevant to the physician, to the executive, to the payer system — so they can understand how to use it for change.”

Again, context is key: Data itself doesn’t tell us what constitutes appropriate care or what good outcomes should look like. We also need to determine how to measure data against clinical benchmarks. 

“Ultimately, we want our patients to get better care,” says Dr. Prasad. “We want them to get that care faster and most efficiently and in the most affordable way. That really does require, in addition to the data, having that clinical lens for what’s important.”

The evolution of healthcare analytics

Once upon a time, patient charts were on paper. Doctors and nurses made handwritten notes. Now, technology has made that data widely available and accessible. “You don’t even have to work for a healthcare organization necessarily,” Dr. Prasad points out. “If you’re interested in consuming healthcare data, there are so many ways to access it, and there are so many types of data, so many millions of records of data, which I think is really amazing.”

Even more amazing is that we can link data sets and make even deeper insights. That ability widens healthcare professionals’ perspectives to include what happens to patients beyond clinic walls. And because machine learning empowers us to identify patterns in data sets, we can predict what might happen next. For example, healthcare providers can estimate the effects of changing time-focused metrics like how quickly patients can get appointments or what might happen if patients come in for follow-ups after 15 days instead of 30 days. Would those things improve patient outcomes — or perhaps lower costs?

Armed with these kinds of insights, providers can move forward with a better understanding of the optimal journey for a particular type of patient. They can work toward better outcomes, increased efficiency, and more affordable care by making the right changes at the right times. 

That’s often a challenge in healthcare, says Dr. Prasad. Providers can’t use current patients as case studies. 

“Intentionally changing levers without knowing the outcome — I think a lot of us would pause at the thought of that, especially if it was ourselves or a loved one,” she says. 

However, predictive models enable healthcare professionals to identify likely outcomes with some certainty. “In addition to the patient being important, it’s also about how physicians want to interact with the system,” Dr. Prasad notes. “Hospitals are always on a mission to be more efficient. So I think there’s a lot of reason for an interest in knowing what you’re getting into, if you will, with some informed decision-making before you actually go out on a limb and change something in your institution.”

Why go beyond clinical data?

At first blush, tracking patient demographics like income and education might seem invasive. However, these data can reveal critical realities about patient populations and their barriers to accessing care, especially in historically underserved communities. Often, data can pinpoint the best solutions, too.

“Maybe we didn’t even know why they weren’t coming in to seek care or why they weren’t able to seek care,” says Dr. Prasad. As an example, she talks about how Clarify has helped its provider customers work toward improving cancer patients’ outcomes by identifying nearby infusion centers for those who need treatment every two to three weeks. 

“Big cancer institutions exist, but they’re often very far from patients in regions where that’s tough to access,” she explains. “If a physician can provide a patient with information on an infusion center within five miles, that patient will be more likely to keep up with frequent treatments.” 

She adds that “data can really help you understand, even at the singular patient level, the types of interventions many health systems are already offering.” 

For instance, case managers and social workers can facilitate rides to appointments, home health aides, and other invaluable resources for patients who otherwise might not be able to access healthcare. Sometimes, medication can be delivered to patients’ homes. Telemedicine visits might be the best option for patients in remote areas. 

Healthcare providers don’t need to invent anything new; they just need to direct that social worker to the right patient at the right time. 

“Really use the data” is Dr. Prasad’s parting advice to healthcare professionals.

 “We have so much data at our fingertips,” she explains. “It can help the patient, it can help the physician, it can help the hospital system. Ultimately, all of those things can transform the way our healthcare system works today. But it all starts with being open to asking the questions of the data and to letting the data show things that maybe we don’t expect to see.”

This article is based on an episode of the Healthcare Unbound podcast, which provides front-row access to healthcare visionaries discussing advancements and groundbreaking solutions — subscribe for free and get future episodes delivered to your preferred platform.