MCHB/EPI Miami Conference — December 7 - 9, 2005

Child Development: The New Public Health Frontier — Transcript

LA VERNE JONES: Good morning. I'd like to thank you all for this opportunity to talk a little bit about what's going on in the District of Columbia, specifically as we look at identifying risk factors for developmental delay and disability in children. I'd like to acknowledge my colleagues who weren't able to be in not-so-sunny Miami . Kerda Dehan, Dr. Gabriel Suskadani, Sherry Billings, John Pitts, and James Poe, who are back at the office diligently collecting data for our system.

What we've talked about so far are some sort of existing data systems, and this would just be an opportunity for me to talk a little bit about the one that we've established in the District of Columbia .

Just as background, just to build on what's already been said, disability in children, of course, is of particular importance, since 14% of children, ages zero to seven have a special need. And that 10% of children born each year in the District of Columbia are estimated to have a disabling condition of some type. And, of course, we've heard a whole list of risk factors related to babies born with low birth weight or premature age and their increased likelihood of having a disabling condition.

So let me talk a little bit about the DC linkage and tracking system and show you some pictures of what it looks like and how we use it to help identify children at risk for developmental delay and disability. First developed in 1986 to track children from birth to age three, this system currently tracks children now from birth to age eight years old. And with the recent upgrades that I described with you, has a capacity to allow for children, following children up until age 22, and, potentially, for those who have been officially diagnosed with MR or DD, actually following through their enrollment or their being clients of the mental retardation and developmental disability administration as adults. So this really is a potential system to follow people from the cradle to the grave.

We begin by abstracting records from four major hospitals, or birthing centers in the District of Columbia . And we identified children with at least 20 risk factors, and we're looking right now to add additional ones.

The objectives of the system are to ensure that early identification enrollment of children at risk for developmental delays and disabilities. So the earlier you identify them, the earlier you can get them in for intervention. In addition, we also want to develop a data system to track the health outcomes of children who are at risk. So, for example, we've had this data going on for some time, but haven't necessarily been able to have the linkages to follow them through school systems or into other administrative data sets, because those linkages haven't existed. So, hopefully, with the advances that we're starting to see now, with the examples that we see in Florida and other jurisdictions, we can begin to make those kinds of linkages happen. We also want to create a centralized data repository for the capability of integrating future databases.

So currently the system that we have originated on a Fox Pro platform and has most recently been migrated to an Oracle Web DV platform in 2002. It's using program languages like Java, JSP, J-script, HTML. And users have access to the system through local--our Department of Health, wide area network. So Web browsers like Microsoft Internet Explorer can be used for both internal customers and potentially external customers to access data, of course, with the appropriate securities built-in.

So this is sort of what our system looks like to begin with. And sort of the welcome screen and you'll notice on the menu on the side that you can actually go through and find a client. So components of the system include the identification, one, to ensure that there's no duplication in the system, case management, and then, also service report modules for service providers who would be interested in seeing information about their particular consumers, but would also be interested in adding information too so that we really do have a true tracking system going on to see what services they're being provided.

After the login, the unique centrally assigned login is provided through our office, then we're able to go in and access the system and do that client search using sort of the Sound X and several ways to look up children who are identified through these hospitals. So hospitals currently provide us with a list of children who are born with developmental delays. And we're specifically looking for people who have District addresses. One of the challenges in the District is that people move in and out of the jurisdiction quite a bit. So, keeping people in our system and making sure we know where they are is a challenge. But with this ability to do client searches, it assists us with that process.

So some of the information that we see in addition to the race, we see the birth, death information if that applies. So there are a whole host of variables related to the demographic sides of things. And then for the case management side, we actually have nurses that go out to do assessments to see if children are at risk, so that, you know, for example, if you have any one of those birth risk factors, you may or may not actually be at risk once you go out and have a developmental assessment done. But this is the case management portion where that information would be entered. And once we've identified them, then we refer them out to services. We don't maintain the case management in our side of the Bureau of Epidemiology, but just do the surveillance and tracking portion.

In addition, I talked earlier about the service information that could be added. So service providers of various types can come in and place information, whether it's for speech and language or physical therapy, a whole range of services can be entered here. And we primarily get our children enrolled in the system based on identification at birth, but they can also be enrolled at a later point. So if, for example, an agency saw the need to have a child who they identified through another means added to the system, we could add them in at any point, and they could add the service data in there. And then, we could go back and look at birth records, if they were born in the District.

So this is an example of some of the agency codes. There are hospitals. There would be other social service agencies. There would be specific hospital departments. And then, also, special community-based organizations would be potentially having access to the system if they provide services that are applicable.

Now, the risk factors that we look at are varied, and today I've just selected a few. But you'll see here listed, anything from substance abuse exposure, APAR scores, prenatal care, etcetera.

So the study questions that we looked at are what are some of the characteristics of the DC LTS population? And we realize this isn't completely representative of what's going on the District. But for those who have been identified through our system. And, also, it lets us know some of the risk factors that are being observed in the population that we see. So we looked at data from 1996 to 2000, and we see that there were approximately 9,000 children identified. We looked at demographic, geographic factors, as well as risk factors to give an example of the proportion of children who meet specific characteristics.

So, specifically, we start looking at maternal age. You can see in this graph, looking at us over time, that we see an increase in that bottom-line. It's very slight and hard to see, but there is a slight increase in the number of women over 45 and, in particular, you probably can see with that red line that's sort of near the bottom, but that there's an increase over time in the number of women 40 to 44 years of age. So that presents a particular set of challenges. But then we also see the success of some of our programs and interventions that we've had in place because we see a decrease in the number of teen pregnancies, when you look at that 10 to 14 and, also, the 15 to 19 age groups. So one of the advantages of the system is it allows us to track these birth risk factors over time.

When you look at race and ethnicity, very overwhelmingly certainly the number of clients in the population proportionately are African American, but what is of particular interest to us is that we see an increase in the number of, or proportion of Hispanics in this city. And so over time, we realize the importance of having more and more services directed towards those in the Latino community.

The District of Columbia , though not a state yet, is divided into eight very distinct political jurisdictions, and so the numbers there indicate the wards, the ward of residence. And there's a very, very distinct different look demographically, economically, etcetera. So those wards that are six, seven, and eight are what we call east of the river. And those that are more affluent are Ward Three--Ward One also has a very growing Latino population. So when you look at that pink line in Ward One, you see we have an increase in that. So that's the increase in the Latino population. You also see proportionately that in Wards Six, Seven, and Eight, and particularly in eight, it's most dramatic that you see a relative decrease in the number of women that we're seeing there. So hopefully, some of our interventions in that area are working. Ward Three is one of the more affluent populations and, actually, many of them are probably not enrolled. And so we have relatively few numbers in that particular ward in our program.

Risk factors at delivery, including maternal conditions, maternal smoking, maternal substance abuse, and low birth weight, are some of the risk factors that we look at. And we see that for example maternal smoking has gone down over the years, but that maternal conditions which include conditions such as premature rupture of membranes, infection, HIV infection, STD, etcetera, are on the rise proportionately. So we realize that while some of our interventions may be in smoking cessation and tobacco use and substance abuse, interventions are working. We have to look at and see what's going on in those maternal conditions.

So in conclusion, we see that there's a lot of potential for linking our data with various data sets. As you see listed here, like the vital records data, etcetera, as well as Healthy Start and other program data. And we see--specifically from the tables that we looked at today--that there's an increased proportion of older women at risk, increased proportion of Hispanic women, and selected geographic areas should be targeted for services. Maternal conditions are the current most frequent risk factor. And so therefore, would be in need of policy and program changes.

For public health implications, we see that service providers can utilize data to target programs, to children at risk for developmental delay and disability. And DC LTS can be utilized to follow children into adulthood to evaluate outcomes. Policymakers can in turn establish initiatives to target prevention of specific prenatal risks, and reduce the effects of adverse outcomes. Thank you.