Population health analytics and management tools are becoming essential for Community Health Centers (CHCs) and Federally Qualified Health Centers (FQHCs). These tools are taking on much greater importance as the healthcare delivery model for community-based care undergoes radical change.
Driving this change is the transition to value-based payment models. Medicaid’s adoption of value-based payment greatly affects CHCs and FQHCs. Medicaid often covers 35 to 90% percent of patients who receive care at CHCs and FQHCs, depending on state Medicaid expansion.
In response, the financial model for operating a CHC or FQHC is being transformed. As examples, many CHCs and FQHCs are merging and organizing into independent practice associations and joining accountable care organizations under the Medicaid 1115 waiver program.
Coping with change and taking on new administrative responsibility is never easy. At the heart of this change, CHCs and FQHCs are taking on greater risk for managing large numbers of patients—many of them from medically underserved communities. Population health analytics and management tools are needed to manage this new level of risk.
It starts with attribution
CHCs and FQHCs commonly are assigned to provide care for a specific patient population within a Medicaid managed care organization. The patients in this population are identified in a an “attribution” or “enrollment” list, panel, or roster.
The list is often delivered in an electronic spreadsheet. The challenge is how to manage these lists, which are outside of their practice management (PM) and electronic health record (EHR) systems.
Population analysis software provides a way to standardize, expand upon, and analyze data that originates from this list. The first step is to normalize data into standard format used to exchange healthcare information and import that list into the Population Health Management systems.
Next, additional information from outside sources may be integrated into the record, including claims data, health information exchange data, and data on social determinants of health. Over time, as patients receive care, the record deepens.
Identifying high users of care
Insights derived analyzing data on the patient population can be used to:
- Identify high risk patients and those who haven’t received preventive care (also known as identifying gaps in care)
- Perform predictive modeling using built-in algorithms; for example, estimating future costs of care
- Prioritize patient outreach – Given limitations of staffing and resources, who are the patients most in need of outreach and education?
- Analyze patient progress over time – Is their health improving or deteriorating? Is care effective?
A small percent of the patient population commonly drives a large percentage of healthcare costs. Patients with strong potential for becoming high users of care can be identified through analysis of clinical data, social determinants of health, and historical cost data. Their care can be better managed by using outreach tools.
Identifying these patients is essential to redirecting them to cost-effective services. It also helps prevent unnecessary emergency room visits, hospital admissions, and specialist care—and reduce total costs.
Essential to the viability of community-based health
Data analytics are essential to CHCs and FQHCs for managing overall utilization and expenses. Financial analytics can be used to identify and eliminate low-value care and monitor long-term financial viability.
CHCs and FQHCs do great work. They deliver high quality to more than 27 million people in the United States—that number is growing—many among the most vulnerable of the nation’s population. They are often the first line of defense in combatting the nation’s opioid epidemic.
For this great work to continue in the era of value-based care, CHCs and FQHCs need population health analysis and management tools. NextGen Healthcare is proud to provide solutions that will ensure the future well-being of community-based health.
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