Building CCWIS is as Easy as 1, 2, 3

This is part of a series on the Comprehensive Child Welfare Information System (CCWIS), which states can build with federal funding help to replace an antiquated data and management process.

There are three main expectations for states in building a new Comprehensive Child Welfare Information System (CCWIS):

  • Improve quality data collection.
  • Share such efforts and access to data across agencies.
  • Tailor the new technology systems to each state’s unique needs.

Although accountability movements are not often viewed as all too wonderful by those being held accountable, these three main CCWIS expectations actually hold great potential to significantly improve child welfare services.

In this part of the series I also want to share why I think CCWIS might just be the secret to your overall future success with the Family First Prevention Services Act, a recent and major shift of federal funding that prioritizes preventing the use of group homes and foster care in more cases.

First Things First

One of the first signs I saw suggesting that those at the federal level might be on to something, was when I read the Q&A portion of the final CCWIS ruling. It was in here that I saw the importance they placed upon improving the quality of case management data collected by encompassing efforts ranging from intake to discharge, or finding that forever home. As the final ruling clarifies, without improving the quality of formative and summative data collected along each youth’s arduous path throughout the systems of care, no matter how impressive the technology is, it will not have the evidence needed to successfully guide your efforts, or possibly pass the rigor of annual reviews.

Efforts during the last decade to find an “algorithm” for child welfare failed largely because we need better data. Operational and predictive analytics will not calculate consistent or accurate recommendations without reliable and valid formative data collected on the true nature of the traumatized youths’ circumstances and the level of care provided, as well as reliable and valid measurement of the summative outcomes experienced by the youth.

How can we perform ongoing analysis predicting the best outcome or next steps needed for a specific youth, if we are not actually tracking the many variables tied to the support and level of care being provided to such youth? And how can we perform these predictive analyses, if we have not combined and analyzed a larger collection of data tracking the care provided with the outcomes experienced by youth (i.e. collecting comprehensive information)?

For that matter, how can we increase this collection of quality data needed to inform our analyses, if we are not having the clinicians, educators, drug addiction specialists and so many others provide us with measurements of the differing levels of treatment provided and response to treatment outcomes experienced?

This is why in order to capture a wider net of quality data across child welfare, CCWIS also seeks to increase agency collaboration using a tailored system which works for all across the systems of care. The secrets to improving your overall success, and better ensuring your new technology actually delivers, rest within the three main steps CCWIS is requesting. So, let’s take a closer look at these three steps.

Step 1: Collect Essential, Quality Data

The quality and quantity of data collected and fed into your new CCWIS could mean the difference between life and death for your co-workers and the youth you serve. Being that too many of you have probably experienced situations where lack of accurate information contributed to a crisis or tragic ending, most probably would agree that making avoidable mistakes in child welfare is not an option.

The bottom line is that if your new technology system is not fed an adequate amount of high quality data, then the limited evidence captured and the recommendations delivered (via operational or predictive analytics) will leave ample room for error putting agencies, staff, families and children at increased risk.

There is a long list of what are called required methodological and statistical assumptions. These essential caveats to perform operational and predictive analysis must be met before any software can perform and deliver sound, reliable (consistent) and valid (accurate) results and recommendations. Common challenges encountered in child welfare to meet such assumptions include sampling bias, the quality and quantity of measurement tools used, statistically controlling for other variables impacting outcomes (covariates), missing data violations, and the variability which comes along with serving a sample of youth one would often describe as extreme outliers.

Without quality data, there is a 50/50 chance your data is not providing a reliable and valid approach to consistently measuring what you think you are measuring. Moreover, you could be missing critical data pieces related to a youth’s previous challenges and experiences, which are essential to reducing the duration and breadth of services needed.

Step 2: Truly Share Data Collection Across Agencies

Case management systems designed to only support case managers with initial intake and placement decisions is not enough to improve the support and care provided to children, shorten the duration of services, or reduce the number of children in the system. Adopting a system which only provides a small fraction of your workforce with new technology falls far short of what CCWIS was designed to accomplish and what you need to rise above the current challenges. To improve high quality data collection comprehensively, we need to collect, connect and share information across the entire child welfare workforce.

In order to take a more holistic and systemic approach, you need to adopt technology which helps all of your agencies collectively gather information essential to creating and quickly accessing integrated care passports detailing each youth’s challenges and treatment history, no matter where they land in the systems of care.

In order to produce Automated Information Driven (AID) recommendations, we need to know if previous attempts with similarly challenged youth led to positive or negative short- and long-term outcomes. And if we are not focused on collecting comprehensive data beyond the initial risk and safety assessment administered by an investigator, case manager or social worker, we are not going to have an adequate collection of formative and summative outcome scores to perform the more precise predictive analytics or predictive modeling needed to augment decision making.

The hard-to-find hard copies, faxes, scans and emails documenting Child Protective Services and clinical records scattered across different facilities, offices and disparate Statewide Automated Child Welfare Information System SACWIS , need to become a thing of the past. Every stakeholder in the child welfare system should be connected in real time on one platform. By adopting technology that allows all to enter, share and access data, the amount of missing information can be greatly reduced.

Why buy a system to only support case workers, a small fraction of your workforce, when you know that after a few months of use the rest of the workforce is going to ask when their new technology is coming? At the price tag some are charging for such CCWIS products, that answer might be never. What you need in order to simultaneously tackle CCWIS, and the Family First Act, is one system, one solution, one platform for all to share.

Step 3: Personally Tailoring the System to Your State’s Needs

New systems must allow for you to tailor data collection, analysis and reporting to your state’s and county region’s strengths and challenges. You cannot and should not assume that because technology claiming their artificial intelligence or supposed “algorithm” had success in one location, it will work in yours.

Services and resources differ greatly across state lines and even within your state’s communities. As a result of these differing agencies’ assets and unique populations of families and youth, response to treatment can differ among individuals. What works in the capitol of your state might not work in your rural area. Your time, resources, and efforts are valuable and should be guided by realistic, personalized operational and predictive analytic recommendations.

Also, if you are hoping to determine the best preventative approaches, new systems should avoid putting a heavy reliance exclusively on warning signs. The New York Times highlighted an effort in Pennsylvania that seemed to be mainly focused on warning signs to guide the decisions of removing a child from the home. This was an interesting endeavor, and of course safety is essential.

With the Family First Act’s aims to limit the use of group homes and a shortage of foster parents existing nationwide, however, just removing a child from the home will be more than slightly limited in the years to come. Therefore, more data personalized to your county, region and agency strengths and challenges is needed so we can have higher quality data essential to figuring out how to help the child if they stay in their home.

Basing predictive analytics on warning signs will only lead to creating alert systems that warn you of bad things to come.But by building predictive recommendations on data documenting your agencies’ quality of care, effectiveness of treatment and successful outcomes, you will be able to better determine more fruitful preventative approaches. Thus, improving decision-making to select placements as well as treatments which lead to more successful outcomes and less services needed.

Deep Breaths and Baby Steps

Understandably, many agencies are feeling overwhelmed by the cost and work needed to pursue CCWIS and the Family First Act. Many also are tired of the endless sad headlines and the revolving door of high-turnover. I know I am, that is why I dedicated my research focus to help child welfare and juvenile justice develop better systems to improve the lives of youth nationwide.

Evidence suggests that nationwide staff, children and families need more than a minimal solution. For those who see these new laws as an opportunity to not only upgrade technology but also improve data collection and evidence-driven decision-making, rest assured there is a tech solution and team ready to help you.

By taking the high road and empowering your entire workforce with a quality data-focused, tailored solution essential to improving outcomes for all, streamlining and exceeding accountability can be quick, affordable and effective. And as a result of truly embracing these three steps to CCWIS compliance, receiving the 50 percent development costs match from the federal government and more proactively being reimbursed for Title IV-E, becomes a more likely reality.

 This series is written by Dr. Michael Corrigan, associate professor at, Marshall University and vice president of Multi-Dimensional Education. Corrigan and his team are the architects of VitalChild’s MDYA360 Outcomes Monitoring System, a CCWIS solution developed by Helix Business Solutions and Powered by Oracle Cloud.

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