How modern data platforms advance the quintuple objective

The Quintuple Objectives as Healthcare Goals Evolve

The quintuple aim is the latest iteration of a concept first described in 2008. Initially, the Triple Aim provided a framework for improving population health, enhancing the patient experience, and reducing the cost of care. As the Institute for Healthcare Improvement describes it, “the framework serves as a foundation for organizations and communities to successfully navigate the transition to a focus on health care for individuals and populations.”

Amid concerns that fatigue and job dissatisfaction in the health care workforce make 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 Went.

Similarly, the quintuple aim for 2022 arose in response to a previously unmet need. In this case, advocates cited health disparities among socially marginalized populations, older adults, and individuals living in poverty. While such disparities have existed for centuries, the global COVID-19 outbreak has raised awareness of these issues for healthcare leaders and the general public alike.

Watch: Find out how collecting the right data can improve health equity.

Measurable Improvement Under the Quintuple Objective

Broadly speaking, the Quintuple AIM provides a set of aspirations for healthcare. Like its predecessors, however, the Quintuple aims to serve as a framework for measurable improvements.

In a white paper, the Agency for Healthcare Research and Quality outlined a series of metrics that reflect an organization’s results. Some are likely already in use, whether it’s consumer evaluations of healthcare providers and results from systems surveys or internal data on emergency department use or hospitalizations. Other metrics may be less familiar, such as the Maslach Burnout Inventory to measure employee satisfaction or protocols for answering and assessing patients’ Assets, Risks, and Experiences surveys to identify social determinants of health.

Data on outcomes alone is insufficient to encourage improvement, however, because it captures a moment in time. As is happening, organizations also need to measure operational performance. For example, effectively addressing burnout means looking at how many nurses were scheduled for a shift, how many nurses are actually working, how many patients they have, and how to achieve the optimal nurse-to-patient ratio. Compares with, eg.

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,” says Gopalakrishnan. But organizations can quickly become overwhelmed with performance data from internal and external sources.

click on the banner below Read on to learn how a modern data analytics program can optimize care.