Data Optimization

Administrative Data in Health and Human Services – Episode 1

September 2019

Join us as we take a look at our recent podcast series inspired by the PEW Charitable Trusts report, How States Use Data to Inform Decisions: A national review of the use of administrative data to improve state decision-making.

Episode 1

Listen on Spotify    Listen on iHeartRadio

Click here to listen to the full interview on SoundCloud.

Edited excerpts of the interview are available in the transcript below.

In our first episode of the series, we talk with Amber Ivy, one of the researchers who contributed to the PEW report, Dr. Bill Hazel, Virginia 's former Secretary of Health and Human Resources, and Tony Fung, Virginia 's former Deputy Secretary of Technology as they discuss challenges and opportunities they faced and the solutions they created to positively impact the health and well-being of their communities.

In their preliminary research to find how states used data to inform decisions, PEW found a lack of any comprehensive studies that identified the variety of ways administrative data was being used by health and human service agencies. For the PEW study, over 350 leaders representing offices including budget, auditing, legislative, technology, and performance management were interviewed, as well as leaders focused in HHS services in SNAP, TANF, Medicaid, and Child Welfare. Researchers found that states traditionally collected administrative data mostly for compliance reasons, yet were starting to look at data differently in ways that were more strategic and that allowed them to look at new uses, like improving service delivery, examining policy and program effectiveness, and crafting policy responses to complex problems.

Researcher Amber Ivy shared, "Policy makers in Massachusetts used data to better understand why people were dying from drug overdoses at such a high rate. By being able to integrate data together, they were able to identity factors leading to opioid policies and began to use legislative policies to inform treatment." Key actions included setting up goals and structures, writing formal data strategy, data governance structures, and inventory datasets. Next steps included building the state 's capacity to use data, hiring or training staff, dedicating funding to support projects, and ensuring data quality can be accessed and used by relevant stakeholders. The final step is to use analytical techniques to extract meaningful information from data. Ivy relays, "We need to look at data as a collective resource, not just "my data for my department," and establish protocols to ensure data can be shared. It 's not enough just to analyze—you need to give them the story behind the data and help stakeholders to better interpret that. And none of this will work without encouraging leaders to commit to data driven initiatives, enact legislation and policies that supports different data use and create a culture that supports data as a strategic asset to guide decision making." There are challenges to the process, yet they can be overcome, as we hear from the following VA leaders.

We are joined by Anthony Fung, who served as Deputy Secretary of Technology for the Commonwealth of Virginia, and is now the CEO of a company named GovInsight.

How was data sharing in VA done and implemented? How has it evolved? What were some of the public to public, and public to private partnerships you pursued?

Fung relays that data sharing has been a process of building blocks and that it has taken decades to change the laws, culture and technology to make data sharing available. He says, "The opioid crisis is a multifaceted problem and the ability to share data and help connect the dots was challenging. We looked at laws, policies and culture to find ways to make it easier and we wanted to ensure privacy laws were adhered to." Changing the process was truly a team effort with the Governor 's office, Office of the Attorney General, private industry and academia. As a group they proved value and presented a strong case for change, having the right tone and leadership support. Initiatives included youth cases where they worked with agency resources, data scientists and graduate students from universities like University of Virginia, Virginia Tech and Virginia Commonwealth University. Fung shares, "We leveraged non sensitive data to turn the VA economy around. We quickly realized the data was messy and came in different kinds of conditions. Yet it was more Important to understand the value of the data and how you can govern it to improve quality. We also focused on executive action and created the groundwork for law changes." The team enhanced transparency and created the first open data portal in VA, streamlining processes, increasing operational efficiency and effectiveness. The groundwork was laid for increased capacity, use of data and analytics and policy change, ensuring that future administrations could derive value from the efforts.

Tell us a little about the contracting vehicle Virginia created for analytics.

Fung shares that they wanted to create an agile contract vehicle with the ability for no-cost pilots to "try before you buy" and reduce the risk of project failure. They found that having a smaller scope and offering a no-risk pilot increased results. "Part of the vision was to identify cost savings. It is extremely important for funding and government looking to find resources for these projects. We wanted agencies to have the latest and greatest technology and tools that help facilitate the sharing of data without potential risks. One pilot identified millions of dollars in costs savings to leverage data analytics and improve processes."

We are now joined by Dr. Bill Hazel, who served as Virginia 's Secretary for Health and Human Resources for 8 years and is now a Senior Advisor for Strategic Initiatives and Community Engagement at George Mason University.

The work you do now at GMU, and what you had to focus on as Secretary, is fighting the opioid epidemic in Virginia and elsewhere. You 've talked about not being able to do that when agencies or programs exist in siloes, and how having a newly created Chief Data Officer position helped to address the opioid issue from an enterprise perspective. How have you seen data sharing be a help and hinderance in the fight against the addiction crisis?

Dr. Hazel relays that pilot projects paved the way for the general assembly to see that sharing information was useful. With 2.7 million individuals enrolled in eligibility programs, they realized that a large percentage were enrolled in multiple programs and that by sharing information and enrolling once, they saved $20 million in work hours. Examples like this were helpful to make the case for making government more efficient. Dr. Hazel shares, "In Virginia we identified that in 2016 we spent $6.19 billion on kids aged 0-21, with multiple funding agencies. You can 't deal with these complexities without some degree of sharing. In the opioid crisis, people could easily understand it wasn 't just behavioral health issues, law enforcement etc. We had to share actionable data, to understand patterns in the community so we can intervene before people overdose. It used to be that data could only be used for the purpose it was collected for. We were able to draft bills to open up that data, which should be shared for a variety of purposes, like providing services, determining eligibility, managing programs and oversight research." They were able to now study the social determinants of the opioid crisis and how to promote prevention. By creating relationships, they were able to help people stay in recovery.

When it comes to funding data sharing work, what are some ways to explain the importance of IT to the legislature? What are some funding streams from federal partners that helped to create things like the Shenandoah Valley model?

Dr. Hazel shared that with funding, you have to not just show the potential for savings but also how you reengineer processes and procedures. Grants are very useful and using funding to build connections and trust is important. To create collective impact working between multiple organizations you have to create common goals, measures for those goals and get to the data piece quickly. Using funding like that to begin to build those connections and trust is important. "Then when a grant does come available to create a data sharing program, we have a community that has built the trust and is willing to take that on. We have a useful tool to help understand what has happened and predict what will happen in the region. The combination of funding sources that we blend and braid together to make this work is important."

This episode and more available on our podcast page. Go to Episode 2. Go to Episode 3.

Podcast Episode One

Additional Data Optimization Posts

The Health and Human Services Workforce: Igniting the Potential Part 2

Posted on 10/1/2018
Minnesota is one of a handful of states whose child welfare system is structured as a state-supervised and county-administered model. Minnesota’s system spans a large geographical area made up of 87 counties and 11 federally recognized tribes. In 201

Data Optimization | The Catalyst

Posted on 1/1/2014
Find additional posts on Data Optimization.

Browse Impact Areas

Productive National Narrative

Modern H/HS Policy

Evidence-Informed Investments

Data Optimization

Agile H/HS Workforce

Healthier Ecosystem

The Catalyst Home