The Institute for Healthcare Improvement recommends best practices for data analytics to better population health management across a variety of health systems.
Population health management has become increasingly important for health systems as the industry shifts its focus towards value-based care. Because health systems have large amounts of data at their disposal, utilizing that data effectively to inform population health management strategies is critical.
“Population health is the various determinants that affect the health and well-being of individuals and populations on an everyday basis,” Niñon Lewis, MS, head of content portfolios at the Institute for Healthcare Improvement told HealthITAnalytics.com. “We embrace the definition that includes the various determinants of health, including genetics, healthcare delivery, environment, social determinants, and behavior.”
Typically, Lewis said, organizations define population health based on where they fit in the care delivery system.
“Hospitals that are thinking about population health management rarely think about it outside their own walls. They might be thinking about patient-centered medical homes, patient registries, and implementing health-related questions into their EMR,” Lewis explained. “I tend to have a broader view of the total pie including what influences decisions, the ecosystem around you, and whether you’re going to thrive on a daily basis.”
Lewis encouraged health systems to leverage community organizations and work with a coalition of many stakeholders towards better health and well-being for the community.
But for some health systems, large-scale community health strategies are not feasible. These partnerships are labor-intensive, and some smaller organizations may not have the personnel to manage them. Others may not yet have made the community connections necessary for forging meaningful partnerships.
No matter the resources available to a health system, population health management should start with a three-party data review strategy, Lewis said. This helps health system leaders understand the pulse of their population and inform future strategies.
The first step is to look at big, health system-wide data on utilization metrics and outcomes for the population.
“This is what we tend to think about when we say, ‘Let’s look at the data.’ You pull all the quantitative stuff that’s available to your practitioners,” Lewis added.
The second and third parts of the data review require a more qualitative analysis.
“You have to actually talk to people,” Lewis emphasized.
For part two, Lewis recommended interviewing patients who are receiving services from the health system while part three requires interviewing providers about their needs.
“Don’t think you have to survey 100 people when you can find out about 80 percent of what you need to know from interviewing just five clients,” Lewis noted. “Use open-ended questions or motivational interviewing techniques.”
The IHI says health systems only need to talk to five patients as a best practice. Lewis explained that this method is a low-cost analytic strategy. It does not cost anything to talk to five patients and case managers often have the ability to talk and identify high-risk populations.
“You can put those questions into a normal patient conversation, during discharge planning, or admission appointments. That doesn’t cost any money,” Lewis said.
“They are the ones at the frontlines seeing what the actual needs are,” stated Lewis. “It’s understanding what their life is like and getting their perspective on the needs and assets of the population.”
Providers are the ones who understand the needs of the population and what resources they do, or don’t, have to help their patients. They are also the ones who most closely interact with patients to understand their complex health needs, so talking with providers helps build a complete picture of a patient population.
“The three-part data review is golden because oftentimes you look at the numbers and there’s no story behind that data. You can extrapolate some things, but it’s actually in the qualitative gathering of the information that you start to see. It’s data that comes to life,” argued Lewis.
After the data review is completed, the results of the review can inform population health strategy. When developing that strategy, Lewis noted that it’s important to think outside of traditional outcome measures and data sources from which to extrapolate those measures.
“One project I’ve seen a health system do isn’t actually care delivery related. It’s about figuring out how to negotiate with the county to get data to come out at a faster interval,” she said. “Oftentimes, this data is collected on a monthly or quarterly basis but it’s only released on a yearly basis. They’re seeing what they could do to get ahold of it. People will do that for you but they haven’t been asked because they’re not mandated to release it faster.”
Lewis also recommended organizations look at patient-reported measures to understand the well-being of a patient population and chronic disease management to help move the needle on one disease that affects the population’s health overall.
“There are loads of ways to get very scrappy with your data collection when you put in the hands of the people that are serving your population. Knowing that this data collection is for learning, not to publish a study, people get creative,” Lewis noted.
Lewis also discussed the importance of promoting equity at every level of the population health management strategy from data analytics to implementation.
“Whenever you’re looking at the data, stratify it,” she recommended. “You’d be surprised how hard it is to get the culture to change. When it becomes just the way you do business, you’re never not looking at the data through an equity lens.”
When data is always stratified, it becomes second nature for analysts and decision-makers to integrate equity into the conversation and focus on promoting equity in their solutions. These solutions help promote addressing equity and make it a priority in each of the organization’s projects.
At an institutional level, Lewis recommended integrating equity into an organization’s strategic development and planning.
“It becomes not just a rule somebody’s thinking about, but it’s talked about at the board level and the C-suite,” said Lewis. “They’re looking at hiring practices and professional dress codes and seeing in what ways they are inadvertently perpetuating inequity in their organization with their own employees and patients.”
“To address equity is to use all the levers that you have at your disposal to be a force for change,” Lewis concluded. “You need to be able to see it at all those different levels from looking at the data differently, strategic priority, addressing the clinical care, and looking at your own practices.”
Translating best analytic practices into routine population health assessment can help promote more equitable care within a patient population and the broader community.
Date: September 13, 2019