Maximize the value of CHF population management programs with advanced analytics PLAYBOOK

Maximize the value of CHF population management programs with advanced analytics PLAYBOOK

STEP ONE: Analyze your patient population Bend the cost curve: Learning more about your patients can lead to higher-quality care As providers increasingly assume more risk, population health management (PHM) is being looked to as a way to improve the quality and delivery of health care and control costs. As part of this strategy, providers are expanding their chronic disease management programs into their communities and proactively monitoring and interacting with the populations they serve. Underlying the success of these programs is the effective use of advanced analytics. With the help of sophisticated tools that scrutinize longitudinal claims and clinical data, for instance, providers are getting a more robust view of their patients with congestive heart failure (CHF). They are identifying patients who haven t been seen regularly or whose health metrics are outside acceptable limits and finding ways to more intensely manage them. PHM IMPROVE HEALTH CARE QUALITY IMPROVE HEALTH CARE DELIVERY CONTROL COSTS Foster change leadership and a culture of data before launching initiatives Population health management starts with building a coalition of leaders to lead PHM initiatives. Such leaders may include a steering committee and the engagement of a range of disciplines spanning areas that are critical to success. For example, before tackling chronic disease management, Cornerstone Health Care a multispecialty clinic in the Piedmont Triad region of North Carolina convened workgroups to design processes and define measures. They focused on an automated system for outreach and patient engagement. The physician-led group began by educating and aligning its entire staff on the same clinical pathway. For population health management to succeed, organizations need to do more than lead from the top down. They also need to cultivate a bottom-up cultural change by encouraging trust in their data. The Mayo Clinic Health System (MCHS), for instance, has engendered trust among physicians by offering training for those who use data to improve decision making. The integrated system has also established governance mechanisms to ensure that priorities are aligned with capabilities and that data are used properly. Leveraging advanced analytics With the help of sophisticated tools that scrutinize longitudinal claims and clinical data providers are: Getting a more robust view of their CHF population Identifying patients who haven t been seen regularly Identifying patients whose health metrics are outside acceptable limits Finding ways to more intensely manage these metrics 2

STEP TWO: Predict the future. Are your patients at risk of being hospitalized? Better managing patients with CHF means having a fuller picture of their health including predicting their risk for future complications and more accurately targeting interventions. About 5.1 million people in the United States have CHF, which costs the nation an estimated $32 billion each year. This includes the cost of health care services, medications to treat CHF and missed days of work. The mean cost of hospitalization alone is $23,077. But much of the cost and harm to quality of life caused by CHF can be mitigated. For example, by using natural language processing to analyze echocardiogram results, which renders notes on ejection fractions structured and reportable, physicians can better assess their CHF patients risk. The Mayo Clinic Health System is piloting a CHF predictive model that brings together in-depth clinical, diagnostic and demographic data to identify patients at highest risk for admission within the next six months. Mayo Clinic users review and export lists of these patients for outreach and coordination. They can then track the impact of this work by comparing benchmark hospitalization rates for the CHF population to the true outcomes for the coordinated population. $23,077 MEAN COST OF HOSPITALIZATION In addition to identifying and acting on gaps in care, organizations can use analytics to track clinical, operational and financial performance. Dashboard reports, for instance, can provide valuable insight into clinical performance, laying the groundwork for initiatives designed to promote physician practice of evidence-based medicine and drive improvements in quality, safety and efficiency. Gaining access to comprehensive longitudinal data can also help providers benchmark their practices against other practices across the country. $32 BILLION HEALTH CARE SERVICES MEDICATIONS ANNUAL COSTS OF CHF Organizations can use longitudinal data to: IDENTIFY AND ACT ON GAPS IN CARE TRACK CLINICAL, OPERATIONAL AND FINANCIAL PERFORMANCE MISSED DAYS OF WORK BENCHMARK THEIR PRACTICES AGAINST OTHER PRACTICES ACROSS THE COUNTRY 3

STEP THREE: Stratify patients by risk to more effectively coordinate care Segmenting a patient population lays the groundwork for devising effective care management and patient engagement programs. Many organizations have retooled their care management approach from a reactive model to one that is driven by predictive, proactive intervention and care. Working with clinicians and care coordinators, provider practice alone, 44 patients were identified physician practice leaders at Sentara Medical as high risk. Of this group, only one of those Group, for example, used risk scores to identify patients had been part of previous high-risk CHF and other chronically ill patients who patient lists. The practice reviewed the other were at highest risk for hospitalization. Their patients and has since been able to engage more data were then reviewed with their primary than 50 percent of the eligible group in care care physicians in order to provide an in-depth coordination programs. understanding of the populations at risk. San Francisco Bay Area group Brown & Toland Sentara, which has 380 primary care and Physicians has used its data to create a working specialty care physicians in Virginia and North registry that in-house care coordinators use to Carolina, chose to focus first on patients who target outreach to high-risk patients. Thirty to 40 fell within the 90th percentile of risk for CHF, as percent of each day s schedule is held for same-day well as chronic obstructive pulmonary disease or next-day appointments so that patients identified and diabetes. SMG s quality team was then able as having gaps in care can be seen quickly. Patients to expand the threshold to also include patients with uncomplicated problems can be seen in within the 80th percentile of risk to increase 10-minute quick sick appointments. As a result, opportunities for intervention. By using the wait times for patients have dramatically improved. information in their patients profiles, physicians Providers who use PHM principles to manage their were able to identify patients for outreach, as patients with CHF will be ahead of the curve as the well as recognize and act on changes in critical industry continues its march toward value-based disease-related parameters such as BMI, blood reimbursement. Leveraging advanced analytics to pressure or ejection fraction. create more comprehensive risk profiles for patients To date, Sentara s efforts around proactive will better position providers to make the transition intervention have been successful. At one three- from treating illness to managing health. PREDICT PATIENT RISK TO PREVENT HIGH-COST CARE AND COMPLICATIONS Use population analytics to separate those in need of intervention from those whose chronic illness is well-managed. Segment by Clinical Risk SENTARA MEDICAL GROUP Used predictive analytics to stratify patient-centered medical home (PCMH) patients by risk of future hospitalization Shifted care management program from reactive to proactive BROWN & TOLAND HEALTH SERVICES One of the first medical groups in U.S. to deploy integrated EHR in a private practice setting Selected as a Pioneer Accountable Care Organization (ACO) in 2011 Leading primary care transformation through its PCMH TREATING ILLNESS leveraging advanced analytics MANAGING HEALTH 4

SOURCES 1 U.S. Department of Health and Human Services. Centers for Disease Control and Prevention. Fact Sheet, n.d. http://www.cdc.gov/dhdsp/data_statistics/fact_sheets/docs/fs_heart_failure.pdf. Accessed Jan. 27, 2014. 2 G. Wang, Z. Zhang, C. Ayala, H.K. Wall and J. Fang, Costs of heart failure-related hospitalizations in patients aged 18 to 64 years, American Journal of Managed Care, 2010 Oct 16 (10): 769-76. CONTACT 800.765.6619 discover@optum.com optum.com/analytics All Optum trademarks and logos are owned by Optum, Inc. All other brand or product names are trademarks or registered marks of their respective owners. Because we are continuously improving our products and services, Optum reserves the right to change specifications without prior notice. Optum is an equal opportunity employer. OPTPRJ4944 2014 Optum, Inc. All Rights Reserved. 5