How Snowflake Helps Confront Data Challenges and Ensure Program Integrity in Healthcare and Human Services

U.S. Health and Human Services agencies can solve data issues to break down data silos, improve disease surveillance and lower costs

From February 2020 to the end of March 2023, Congress’s Families First Coronavirus Response Act (FFCRA) required the provision of continuous enrollment for people with Medicaid throughout the COVID-19 public health emergency (PHE), causing enrollment in Medicaid to grow by 23.2 million to nearly 95 million.

As of today, however, Congress has stopped matching funding for this enrollment increase. With Medicaid being the primary program providing comprehensive nationwide healthcare coverage for low-income Americans, over 90 million people are expected to lose enrollment and become uninsured.

Medicaid isn’t the only agency facing immense challenges. Other U.S. Department of Health and Human Services agencies are tasked with providing health equity and whole-person care for millions of citizens while also improving program integrity. In the midst of funding cuts, enrollment benefit fraud or improper billing can pervade the healthcare industry, whether by illegitimate recipients or by predatory healthcare providers and agencies. 

In addition to policy changes, there are major modernization efforts underway. From integrated eligibility programs and Medicaid enterprise systems to child welfare information systems and other human service program modernizations, money has been set aside to ensure federal, state and local governments are keeping up with the ever-changing tech landscape.

Both policy changes and modernization efforts present challenges, but they also create opportunities to build a solid data foundation to drive collaboration and break out of data silos in each agency. 

Let’s dive into each of these kinds of organizations—Medicaid, public health and human services agencies—to discuss some of the recent trends and issues they face as it relates to data. 

Medicaid and its challenges with siloed data

To prevent rising uninsurance rates, state governments need to pull large amounts of data from multiple agencies to verify eligibility requirements. The challenge is that much of this data is fragmented across clinical, financial and administrative organizations, resulting in a host of issues including:

  • A significant loss of timeliness during public health emergencies
  • Improper classification of disparate, siloed data
  • A lack of confidence in making data-informed decisions

The problem of siloed data presents another significant roadblock: ensuring program integrity. According to a recent Thomson Reuters survey aimed at local and state government workers, only 59% of responders feel confident they have the right resources to fight fraud, waste and abuse (FWA). For instance, analysts and investigators of FWA claims don’t have insight into a Medicaid recipient’s change in benefit status (for example, when they get a new job that covers health insurance and no longer need Medicaid coverage).
To make things worse, with the American Recovery and Reinvestment Act of 2009, States must process claims within 30 days of receipt, which means they have 30 days to not only uncover fraud but also report on it. For investigators and claims processing agents, for example, this is a significant time constraint. And in times of high demand (as in a public health emergency), the problem of aggregating this fragmented data worsens both accuracy and timeliness in detecting FWA.

Creating a 360-degree view of a recipient through reliable aggregation of scattered inter-departmental data is key to addressing the issue of rising uninsurance rates among low-income Americans, along with ensuring program integrity in Medicaid. 

Data modernization efforts targeted toward integrated eligibility systems (IES) can be helpful in addressing these issues. IESs are the technological backbone for U.S. state-level Medicaid and human services programs, providing rule automation, case management and workflow systems to ensure timely and accurate determination of eligibility requirements across various human services programs. As individuals and families qualify for multiple programs, states tend to use the same technology for combined eligibility determinations. Modernizing these systems using the latest cloud computing capabilities can not only save costs, but also drive interagency collaboration on critical data sets. 

Public health and limitations in disease surveillance

When it comes to reliably monitoring the state of public health, we need fast, accurate access to data so that public health agencies can recognize and track developing health threats, from preterm births to drug overdoses to COVID-19. However, public health is continually facing new demands and expectations for data about our nation’s evolving health challenges.

To further highlight the issues, let’s look at the critical job of disease surveillance. 

To be successful, organizations need to:

  • Quickly evaluate the effectiveness of current preventive measures
  • Support health planning and allocate appropriate resources in the healthcare system
  • Identify high-risk populations or areas to target interventions
  • Develop a valuable archive of disease activity for future references

With the CDC monitoring over 4 million health messages from emergency rooms every day, this is incredibly difficult.

To execute on this, the following capabilities are critical:

  • Reliable access to data
  • Speedy collection, analysis, feedback and action taken on insights
  • Easy and secure collaboration across different data collection agencies and countries
  • A self-managing data platform to compensate for the lack of technical resources and government funding

Given the challenge of navigating millions of health cases and facilitating collaboration between a multitude of health agencies, the need for reliable collection and analysis of aggregated data is crucial in addressing urgent public health demands and preventing drug overdose crises or COVID-19 outbreaks.

Data needs in human services

Efficient, centralized technologies are indispensable when addressing basic human needs like food and shelter as well as general social welfare. Integrated eligibility systems, for example, provide the enrollment technology for America’s safety net programs such as SNAP, which provides food vouchers for families and children in need. Unfortunately, IES technologies are outdated and built on a monolithic system that significantly reduces health agencies’ ability to generate data-informed insights and provide benefits to citizens. 

To be successful, states will need to:

  • Minimize application backlogs that delay benefits to citizens and complicate processing of claims, including difficult formats such as federal tax forms, pay stubs, PDFs and images
  • Break down data silos across the organization to generate insights about how successful specific programs are and what merits their additional funding
  • Keep costs low given the limited resources and technical talent available for maintaining infrastructure

Along with Medicaid and public health agencies, human services not only benefits from but also requires these capabilities to improve and ensure public welfare. Despite the numerous challenges and their growing urgency, Snowflake can help.

Helping to solve health and human services issues with the Data Cloud

At the onset of the COVID-19 epidemic, the overnight explosion of data surrounding collapsing public health overwhelmed disease-surveillance systems. To effectively collect data in the deluge, the California Dept. of Technology enlisted Snowflake’s help to deliver a secure, centralized location for all COVID-19 data, including information about positive cases, testing, deaths and California Hospital Association data (for example, the number of available hospital beds).

Snowflake integrated with ErsiGIS software and Tableau, the state’s chosen dashboard and analytics solutions. In addition, Snowflake Marketplace was used to enable secure data sharing with other state agencies, departments and health partners for downstream planning. The data is available now as a Snowflake Marketplace listing.

Looking broadly across the US, eight states use Snowflake as part of their Medicaid modernization program and the Centers for Medicare and Medicaid Services (CMS) has deployed multiple projects across Snowflake to date.

Discover how customer Covered California uses Snowflake to tackle their data challenges.

The post How Snowflake Helps Confront Data Challenges and Ensure Program Integrity in Healthcare and Human Services appeared first on Snowflake.

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