Population Health Management eBook
Analysis Without Action Is A Recipe For Disaster
Our previous chapters described how important up-to-date, comprehensive aggregated data captured throughout the care continuum is for accurate and reliable population health management (PHM) analysis. Sophisticated PHM technology allows healthcare organizations to "crunch" data in seemingly endless ways, across any number of conditional, demographic, social or behavioral variables.
Those analytic capabilities, however, are also a risk, as they can deliver false confidence to providers. Analysis and reporting is enlightening but will not aid an organization to improve patient outcomes or reduce wasteful spending unless the information is acted upon. Moreover, advanced PHM technology must deliver analysis in a highly intuitive, actionable way to reduce clinician interpretation time and accelerate -- or automate -- interventions. Helping prioritize care interventions in this way can make the seemingly insurmountable task of helping large populations of patients achieve optimal outcomes much more attainable.
Establishing Data-driven Workflows
Intervening with patients based on the insight provided by data analytics needs to be strategic and efficient. Organizations must craft data-driven workflows that allow care managers to concentrate their limited time on the highest-risk, highest-need patient populations. Workflows would also depend on a healthcare organization's quality goals and the high-risk populations that are driving the organization's highest costs and care utilization.
Risk stratification capabilities of the PHM technology platform could help organizations design these workflows as well as implement automated interventions so care managers can focus on the most complex and challenging patients. Lower risk, easily managed patients would receive the same level of monitoring through up-to-date, comprehensive and aggregated data capture and analysis. However, these groups would receive more automated education, reminders and communications delivered through the PHM technology's rules-based engine.
Automated or manual intervention methods should be tailored to patients' preferences… Regardless of the method, the focus of the outreach for all populations must be preventive care and care-plan adherence support to nurture patient engagement and activation.
Automated or manual intervention methods should be tailored to patients' preferences, such as text messages to their mobile device, a secure message to a patient portal, or an interactive voice response phone call. Some patients, however, particularly senior populations, may prefer a phone call directly with a care manager. Regardless of the method, the focus of the outreach for all populations must be preventive care and care-plan adherence support to nurture patient engagement and activation. The PHM technology should support these targeted campaigns by delivering predictive modeling to enable more proactive outreach that helps overcome small care-plan adherence obstacles early, instead of after an adverse and costly health event has occurred.
Implementing Change Slowly To Improve Long-term Success
Implementing data-driven PHM outreach workflows needs to be as strategic as designing the process. It's recommended to implement the structure of the program in smaller pieces, making it more efficient and effective than managing all high-risk populations immediately. Rather, such an initiative should move forward incrementally focusing first on one high-risk, high-cost population and then learning and adjusting the course of action based on early experience. A gradual expansion across populations and care quality goals will help PHM-focused providers build confidence and mastery of these new processes while improving outcomes, setting the foundation for long-term success.
The next chapter of the eBook will describe automated interventions in greater detail and how patient-reported data can help fill in the data gaps caused when they visit other providers unaffiliated with your organization.
- 1: Cox, Cynthia and Sawyer, Bradley. "How does health spending in the U.S. compare to other countries?" Peterson-Kaiser Health System Tracker. February 13, 2018. Accessed May 15, 2018. https://www.healthsystemtracker.org/chart-collection/health-spending-u-s-compare-countries/?_sf_s=health+spending#item-start
- 2: Partnership to Fight Chronic Disease. "What Is The Impact Of Chronic Disease On America?" Fact Sheet. 2016. Accessed June 11, 2018 http://www.fightchronicdisease.org/sites/default/files/pfcd_blocks/PFCD_US.FactSheet_FINAL1%20%282%29.pdf