Top five ways providers can leverage data to manage risk

Identifying and managing high-risk patients when they're not in a healthcare facility is still a relatively new process for providers.

For decades, and often to the chagrin of providers, payer organizations have attempted to manage high-risk patients and identify care gaps through claims data, provider-chart reviews and audits. This information was then presented to providers, who have historically resisted collaborating with payers on patient care for numerous reasons.

Providers, however, are now compelled to embrace risk management due to several value-based payment reform elements in the Patient Protection and Affordable Care Act. More evidence of the government's desire to transfer more risk to providers came in this year's announcement by the U.S. Department of Health and Human Services Secretary which stated that up to 50 percent of all Medicare payments by 2018 could be based on alternative payment models that reimburse for value.

Identifying and managing high-risk patients to avoid hospital admissions and improve outcomes have become essential for providers who want their organizations to transition successfully through these changing payment models. As such, instead of resisting payer involvement, provider organizations have begun embracing collaborations that include exchanging data or access to data-analytics tools that can help providers better identify high-risk patients, predict behaviors and intervene when necessary.

The following are five ways that providers can use their own claims and clinical data, as well as pharmacy and laboratory data and informatics tools to help manage risk and improve clinical performance under value-based payment programs.

1. Data collection. The first step in identifying and addressing risk is aggregating and analyzing as much relevant data as possible throughout the care continuum. CMS has made access to data sharing easier in its Medicare Shared Savings Program, allowing ACOs to access health information with patient's permission that will allow those providers to better care for the beneficiaries that they serve. Advancements in technology have more medical information available in electronic form than ever before, but there are still tremendous barriers from being able to share data effectively. The shift to value-based payments should also encourage providers to partner with payers to share information and work together to achieve the goal of high-quality care delivered in a cost effective way.

2. Identify high-risk patients. Once data is aggregated and analyzed, the provider organization needs data analytics tools to help identify and stratify high-risk or potentially high-risk patients based on intervention urgency. This is another area where payer experience can benefit providers. Health insurers have decades of experience in using claims, pharmacy, lab and limited data they could collect from provider charts to risk-stratify their members and form financial projections about expected medical losses. Over the years, across payer and provider organizations, sophisticated algorithms have been developed to stratify members and patients based on clinical data. However, socioeconomic and other data sources are also available which many provider organizations may not realize are accessible. These newer, complex algorithms have been proven to be more accurate at predicting patient behaviors and outcomes than traditional claims-and-chart-only data analysis.

3. Outreach. Once high-risk patients are identified based on analysis of available data, traditional patient outreach techniques, such as phone calls and letters, are common and often effective in encouraging patients to change behaviors and begin adhering to their prescribed care plans. Some progressive healthcare organizations are using electronic means of contacting patients, such as emails that direct the patient to view a message on a secure online patient portal, or even sending text messages to mobile devices. With smartphone ownership reaching 64 percent of the U.S. population, and 54 percent of Americans ages 50 to 64, the immediacy and ubiquity of mobile devices should be explored as an outreach opportunity. Other organizations are even interacting with patients through social media such as Facebook and Twitter. Although still rare and experimental, patients are nonetheless demanding to communicate with providers through social media, which can create engagement and risk management opportunities for organizations.

4. Point-of-care alerts. If the outreach was successful at scheduling a needed patient appointment, risk can be further reduced by using aggregated data to generate point-of-care alerts for the providers to support decision making during the office visit. These notifications can address the care quality metrics that the healthcare organization wants to improve, such as those that relate to a value-based payment contract or accountable care organization (ACO) program. However, configuring these notifications as to not overwhelm providers, which could lead to alert fatigue, should be considered.

5. Care coordination. Once patients' high-risk health concerns are addressed in the physician's practice, organizations must ensure patients continue to adhere to their care plan, such as completing subsequent specialist or physical rehabilitation appointments, performing routine testing or taking prescribed medications. To encourage adherence and reduce risk, data reconciliation and analysis and using intelligence to drive outreach and point-of-care alerts must be a continuous process throughout the organization.

In the coming years, improved data and information-system interoperability will hopefully make the data aggregation and analysis process more streamlined and timely. Until that day arrives though, healthcare organizations need to optimize existing health information technology systems and explore collaborative opportunities with other provider and payer organizations to help data flow faster and more efficiently.

About the author:
Jimmy Liu is vice president of Risk Analytics Services for Altegra Health.

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