How Modern Data Platforms Advance the Quintuple Aim

The Quintuple Aim as an Evolution of Healthcare Goals

The Quintuple Aim is the latest iteration of a concept first described in 2008. Initially, the Triple Aim provided a framework to improve population health, enhance the patient experience and reduce the costs of care. As the Institute for Healthcare Improvement described it, “the framework serves as the foundation for organizations and communities to successfully navigate the transition from a focus on health care to optimizing health for individuals and populations.”

Amid concerns that burnout and job dissatisfaction in the healthcare workforce made it difficult for organizations to achieve the Triple Aim, advocates proposed the Quadruple Aim in 2014, adding a fourth goal of improving the work life of clinical staff.

Similarly, the Quintuple Aim arose in 2022 in response to a previously unmet need. In this case, advocates cited health inequity among socially marginalized populations, older adults and individuals living in poverty. Though such inequities have existed for centuries, the global COVID-19 outbreak heightened awareness of these issues for healthcare leaders and ordinary people alike.

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Measurable Improvement Under the Quintuple Aim

Viewed broadly, the Quintuple Aim provides a set of aspirations for healthcare. Like its predecessors, though, the Quintuple Aim is meant to serve as a framework for measurable improvement.

In a white paper, the Agency for Healthcare Research and Quality outlined a range of metrics that illustrate an organization’s outcomes. Some are likely already in use, whether it’s Consumer Assessment of Healthcare Providers and Systems survey results or internal data on emergency department utilization or hospital readmissions. Other metrics may be less familiar, such as the Maslach Burnout Inventory for measuring staff satisfaction or the Protocol for Responding to and Assessing Patients’ Assets, Risks and Experiences survey for identifying social determinants of health.

Data on outcomes alone is insufficient to spur improvement, however, as it captures a single moment in time. Organizations also need to measure operational performance as it’s happening. Effectively addressing burnout, for example, means knowing how many nurses were scheduled for a shift, how many nurses are actually working, how many patients they have and how that compares with optimal nurse-to-patient ratios, for example.

Improving patient outcomes, meanwhile, requires monitoring patients both in the hospital and at home. “You need to be able to connect the dots across the continuum of care,” Gopalkrishnan says. But organizations can quickly become overwhelmed with performance data from internal and external sources.

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The Modern Data Platform and the Quintuple Aim

In traditional environments, this data remains siloed, stored and maintained on-premises by the business unit that collects and therefore “owns” it. Data also largely remains in its native format, unreadable by business intelligence or analytics software. This hinders Quintuple Aim improvement efforts, as decision-makers across the organization are forced to act with only a fraction of the data that would be beneficial to them.

Enter the modern data platform, which allows organizations to embrace an agile approach to optimizing data. The modern data platform makes it possible for organizations to store and manage data from a centralized, cloud-based location. Doing this removes the silos that previously made data inaccessible, reduces the resources devoted to on-premises data center management and offers the flexibility to add resources where needed.

In addition, the modern data platform provides the computing power necessary for running real-time analytics — essential for the clinical decision support that contributes to better outcomes and patient experiences. Finally, the platform makes it easy to add homegrown or third-party modules that contribute to performance improvement initiatives, such as tools that track survey results and flag responses that may benefit from a follow-up.

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There are four important questions healthcare organizations should ask before implementing a modern data platform:

1. What are the desired business outcomes? Defining these goals should involve clinical stakeholders, not just IT leadership. This will ensure that efforts are directly tied to Quintuple Aim improvement efforts and not initiatives with little business value.
2. What challenges currently stand in the way? Business and IT leaders should assess existing data assets and infrastructure. Among other steps, this process should identify opportunities to improve data quality or define new policies for data governance so data is more accessible and usable once the data platform is in place.
3. What people, processes and technology are necessary? A modern data platform isn’t a server that can be plugged in and turned on. Every organization has unique improvement goals tied to the Quintuple Aim, and that means implementing a modern data platform with the right features and modules to meet those needs.
4. How will data needs evolve? The modern data platform should be flexible enough to accommodate emerging technologies as well as new business goals that come with new data management needs.

In looking at ways to layer technology atop the modern data platform, Gopalkrishnan recommends prioritizing third-party partners that emphasize outcomes over product features. To address an issue such as the impact of staffing levels on patient outcomes, for example, an organization should project staffing shortages over a period of several years. In turn, that model can help determine which technology investments — ICU monitoring, tele-triage or process automation, for instance — can maintain the level of care necessary to meet Quintuple Aim goals.

“You need to work backward from your desired end state to build the right solution,” Gopalkrishnan says. “For the problem in front of you, you need to know the most efficient and effective and scalable models, along with what sources of data you need to build those models.”