Becker's Hospital Review

21 Your ACO just took on downside risk. Is your data strategy up for the task? By Brooke Murphy F or most accountable care organizations, the near future increasingly includes downside risk — which might catch some ACO's off guard. ACOs are care networks that can consist of independent physicians, physician groups, hospitals, health systems and payers that join with a broad spectrum of nonacute providers — rehabilitation clinics, behavioral health counselors, lab groups — to coordinate high-quality, low-cost care for specific patient populations. In the past eight years, ACOs have grown to cover more than 32 million patients across every state in the country, according to a 2017 Health Affairs study. At the top of ACOs' list of priorities: improved data analytics and reporting to help better manage chronic diseases, coordinate care and reduce practice variation, according to the Health Affairs study. With ACOs highlighting risk management as a top-most concern, it's no surprise organizations are searching for greater visibility into patient health data through investments in health IT and data management. is article examines the role data plays in improving risk management for young and veteran ACOs, as well as key considerations for organizations ramping up their population health analytics programs in preparation for downside risk. ACOs are eyeing risk-bearing contracts Approximately 26 percent of all Medicare ACOs participate in a downside risk model in January 2018. is is a 9 percent increase from 2017. Driving the movement to risk-bearing contracts, in part, is many ACOs' realization that returns on investment generated through MSSP Track 1 — a non-risk-bearing model — fell short of what organizations sought to recover upfront costs and remain profitable. "Effectively creating the infrastructure to manage a population is not something you do in a year," says Dan Underberger, MD, clinical solution executive and medical director of the clinical analytics team at Change Healthcare. "It takes several years and significant sunk costs to get the analysts, care management team, and technology in place. Many of these entities are two, three or four years into the [MSSP] program, when they begin to see what works and what doesn't. ey've got cost of care as low as they possibly can, and are starting to get a sense of what their capabilities are with their performance improvements." Mature ACOs aren't the only organizations eyeing risk-bearing contracts. Even historically risk-averse organizations are considering a downside risk strategy, largely driven to the table by CMS. Eighty-two ACOs in MSSP Track 1 since 2013 will decide between engaging in downside risk by 2019 or forfeiting their participation in the program. e most recent MSSP performance results indicate many remaining Track 1 ACOs are mature enough for downside risk. Approximately 91 percent of Track 1 ACOs would have financially benefited from assuming downside financial risk in the Track 1+ pathway based on 2016 performance data, according to a 2018 Avalere study. ACOs new to MSSP are also being pushed toward downside risk through MSSP Track 1+. e program, which builds on the first track iteration, is designed to encourage less risk-sophisticated, rural and smaller ACOs to experiment with risk by offering more limited downside models compared to tracks 2 and 3. e Track 1+ program boasts 55 ACOs in 2018, including major names like Cleveland Clinic. A crucial component to understanding operational needs in risk-based contracts is moving beyond EHR systems to incorporate population health management solutions. Eighty percent of ACOs reported using some type of population-based analytics solution in 2017, according to a poll by the National Association of ACOs and Leavitt Partners. Despite the near ubiquity of population health management systems, most ACOs have room to grow when it comes to laying the groundwork for population-based analytics. Integrating a population health management solution into an EHR is but a single component of an effective analytics initiative, especially if ACOs intend to use their analytics for predictive modeling down the line. Equally, if not more important than sophisticated IT solutions are high-quality, comprehensive data sources and standards that promote data integrity and foster physician trust in data insights. Because data analytics are only as valuable as the insights they yield, managing data to ensure it's secure, available, reliable and actionable is a top priority for organizations looking to use data in risk management. With ACOs highlighting risk management as a top-most priority, it's no surprise organizations are searching for greater visibility into patient health data through investments in health IT architecture and data management processes. State of HIT and data processes in ACOs Dr. Underberger discussed five considerations for ACOs looking to mature their data analytics programs in preparation for downside risk. 1. Data acquisition gaps. Acquiring data from each hospital, physician group and provider touch point within an ACO's network — from independent physicians practicing in multispecialty facilities to diagnostic labs — is key to building a valid, comprehensive snapshot of care management. "You can't fill patient care gaps until you fill the data acquisition gaps," Dr. Underberger says. The data necessary for ACOs to evaluate patient health risk lives in a range of disparate systems in a multitude of formats — including data found in EHR and practice management systems, claims data gathered from clearinghouses and health plans, and increasingly, patient-generated data from devices and even genomic tests. Executing this fundamental need for data acquisition brings ACOs face- to-face with one of health IT's greatest stumbling blocks: interoperability. 2. Interoperability challenges. Lack of interoperability standards across clinical and financial data sources adds enormous time and cost to data acquisition. Even without bringing financial data into the mix, exchanging data between discrete EHRs still presents technical difficulties. In fact, ACOs identified data extraction from EHRs as a leading problem due to poor interoperability standards, high labor costs and irreconcilable Sponsored by: SPONSORED CONTENT

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