This report is based on a 2019 Healthcare Analytics Summit presentation given by Susan Seidensticker, BSIE, MSHAI, CPHQ, CSSBB, PMP, Director, Waiver Quality Operations, The University of Texas Medical Branch, and Andrew T. Herndon, MHA, CSSGB, Senior Business Manager, Office of the President, The University of Texas Medical Branch, titled, “Serving the Traditionally Underserved with Population Health Improvements.”
To improve care in a value-based market, health systems must become competent in population health management (PHM). PHM, however, can be complicated with organizational barriers including information silos and limited resources. To succeed, health systems need multidisciplinary and cross-functional stakeholder support that ensures standard PHM work occurs across the organization. Earning this backing relies on real-time, actionable data and analytics to measure the effectiveness of population health improvements.
An analytics-driven PHM program that engages the stakeholders achieves the following:
PHM comprises strategies that guide transformation across the continuum of care to help organizations achieve sustainable outcomes improvement—versus focusing improvement resources on limited populations and acute care. Population health covers the full spectrum of individual and population health (health behaviors, clinical care, social and economic factors, and the physical environment), making PHM strategies key to ensuring improvement initiatives comprehensively impact healthcare delivery across organizations.
How urgent is the need for PHM among U.S. health systems? By the statistics, PHM is a healthcare imperative, as the nation’s rates of serious medical conditions and associated costs are substantial:
By guiding transformation across the continuum of care, PHM strategies help health systems manage concerns they know their populations are at risk for (e.g., addressing the above conditions proactively and reducing reliance on acute care). As well, under PHM’s value-based model (e.g., at-risk contracting and pay-for-performance arrangements), organizations receive enhanced financial incentives for delivering preventive services and tracking patients across the care continuum.
To manage these patients and succeed in PHM, organizations must rely on a new set of data-driven, team-based skills. To address the following broad scope of common population health challenges, organizations must have systemwide stakeholder engagement:
In certain states (including California, Texas, Massachusetts, New York, and others), the Delivery System Reform Incentive Payment (DSRIP) program offers performance-based incentives for improving care delivery to Medicaid and other uninsured (underserved) individuals. Under DSRIP, states have millions of dollar available for reinvestment annually, most of which are tied to clinical outcomes.
DSRIP goals tied to PHM include reducing the total medical spend, improving patient outcomes, and establishing a direct link between provider performance and payment.
In Texas, for example, DSRIP ties payments to performance in 30 measures tied to 32 rates for traditionally underserved populations. DSRIP gives health systems in Texas the opportunity to earn millions of dollars in incentives, which can drive stakeholder interest in improving care for underserved populations—especially when organizational objectives align, and real-time data measures improvement.
Improvement teams can earn stakeholder engagement in PHM programs, such as DSRIP, by choosing measures that align with strategic objectives (e.g., reducing emergency department visits). In Texas, for example, the University of Texas Medical Branch (UTMB) picked primary care measures for DSRIP and identified opportunities for improvement to earn incentives while also supporting organizational goals.
Achieving PHM, and DSRIP incentives, requires health systems to select strategic improvement opportunities to maximize quality care and revenue:
From securing stakeholder engagement to achieving PHM goal, organizations must leverage real-time data and analytics. VBC is the new norm, and it requires real-time analytics to measure performance and measures as needed to succeed in PHM.
An advanced analytics tool for PHM must be capable of compound measure stratification and proactive (versus reactive) patient outreach. It must also trend data over time to gauge intervention effectiveness, show historical context (e.g., whether trending up or down), support attribution models, and refresh daily.
Example capabilities of an advanced PHM application include: filtering by disease, location, department, and provider; displaying composite scores and individual measure scores; and graphing individual measure performance over time. This insight helps organizations improve clinical processes by improving pre-visit planning and proactive patient outreach; implementing standardize clinic workflows; and sharing ongoing, timely feedback with clinics and providers.
With the breadth and depth of PHM challenges comprising the continuum of care from frontline clinician engagement to real-time actionable data, health systems must have organizationwide stakeholder engagement to impact population-based improvement. Organizations in DSRIP states may more clearly illustrate the challenges and opportunities in PHM, but any health system stands to benefit from a real-time data and analytics approach to stakeholder engagement.
Would you like to learn more about this topic? Here are some articles we suggest:
Would you like to use or share these concepts? Download the presentation highlighting the key main points.