When the press writes about failures in the child welfare system, the tragedies are unique, but the pattern is often all too familiar. A family has been involved with the agency multiple times, signs of risk were missed, and the result is significant harm or even death. It’s hard to read about a set of facts that seem so clear in hindsight. We could have known, we should have known, we just didn’t connect the dots from the available data and the risk it entailed.
Quality assurance reviews following a tragedy often indicate it was prevent.able and, unfortunately, attribute the tragedy to a people problem, further singling out the caseworker or supervisor. In reality, however, the cause of a tragedy is often driven by a capacity problem that is disguised as a people problem. While there is much information gathered about the families we serve, finding and tracking everything presents a monumental challenge to caseworkers. The short list of obstacles includes handoffs, multiple agencies and providers, staff turnover, and overwhelming workloads. We leave this problem to the caseworkers, who have dozens of cases, hundreds of interactions each month, and just minutes to absorb and react to new information on each case. On top of that, we implement new technologies that inundate workers with hundreds of alerts, reminders, and notifications telling them what to remember and what needs to be done now … and be sure to complete it all by Friday. It requires staff to be super human.
The dream, of course, is that caseworkers can do all those things. We want “eyes” on these kids all the time and we expect staff to notice every detail. Each child deserves the right attention and the right services. It’s up to staff to find a way to get that done. If they just review everything or if the supervisors dig hard enough, they can find the “blind spots” that might be missed. Unfortunately, the dream and the reality are far apart, and there is no safety net when things go wrong.
One way we might reduce risk involves predictive analytics, using a model, for example, to determine which children are at greatest risk of harm in the future and “screening in” those families when allegations are raised. These analytical solutions are maturing and show some long-term promise, but they have generated inconsistent results. The algorithms are error prone when applied to historical and potentially biased data, the improvements in accuracy have been modest, and the downside when they fail is just as problematic as the problem they are addressing. Fundamentally they just don’t focus on this key issue facing child welfare. The problem is not the judgment of intake workers; rather we need to augment casework with insights. We need to remove the blind spots to help workers see the signs we can’t afford to miss. But how?
If we had access to data that told us when a known sexual predator moved into a home with a child receiving preventive services, we could direct a worker to visit and determine if new intervention is required, today.
Instead of using algorithms to replace social worker judgment at a point in time, we could leverage digital eyes to augment the caseworker’s ability to keep up with everything happening in a case and notify an agency to real-time changes in circumstances that could otherwise be missed. It’s the perfect intersection where good process and technology meet. By bringing together the data we know for the children we serve, we can identify when a situation has actually changed and determine the response based on the new insight. For example, if we had access to data that told us when a known sexual predator moved into a home with a child receiving preventive services, we could direct a worker to visit and determine if new intervention is required, today. If a foster parent is involved in criminal activity, we should reassess. If a single mom receiving services stops getting child support, we should evaluate how to assist. It isn’t about scoring or weighing risk, rather it’s about new information driving action through a social worker.
These digital eyes could act as an ongoing monitoring tool, leveraging case, government agency, and third-party data to look for important changes — eviction, police called to the home, job loss—on a daily basis, not just when a caseworker has scheduled time to visit. Then, a unit of staff evaluating the significance of changing data can coordinate to take immediate action from this insight. With the right digital eyes, caseworkers can do today what we’ve previously only dreamed of them doing.
While no approach can protect every child in every situation, we have to act on the data we know to be true to our mission. The risky events are real, and the right tools can help make you aware and let you take action. This approach allows you to monitor the risks you could know for the children you do know. Getting more eyes, more often, on these kids can move us closer than ever to that dream of not missing a thing.
[fusion_separator style_type=”single solid” hide_on_mobile=”small-visibility,medium-visibility,large-visibility” class=”” id=”” sep_color=”#606060″ top_margin=”25px” bottom_margin=”1px” border_size=”” icon=”” icon_circle=”” icon_circle_color=”” width=”45%” alignment=”left” /][fusion_text]
*Originally published as Eliminate Blind Spots to Improve Safety: More Eyes More Often (Policy & Practice, August 2019)
