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Category: FCDA Web Tool Recipe

In May 2011, Chapin Hall researchers released a study that used FCDA data to produce an epidemiological and developmental snapshot of infants in foster care. The research showed that infants are a growing proportion of first-time admissions to foster care. It also showed that infants experience foster care differently from children who enter care at older ages. For example, children who enter care as infants spend a longer amount of time in foster care; are more likely to exit to adoption; and are particularly vulnerable to developmental risk factors such as physical neglect, poor health, caregiver substance abuse, and others. Meeting the needs of infants in foster care requires developmentally appropriate interventions delivered in the right dose. This Recipe is the first in a 4-part series that uses the web tool to explore infants’ experience in care and how to target opportunities for improving their outcomes. Here, in Part 1,… Read more >

The web tool has two main platforms: the Multistate site and the state-specific site. In this post, I explain the differences between them and give examples of when you might want to use each. Whereas all Data Center member states have access to the Multistate site, individual states must elect to create a state-specific site. You’ll know whether or not your state has a state-specific site after you log in to the system. If your state has a state-specific site, after logging in you’ll be asked to choose whether you want to proceed to the Multistate or state-specific site. If your state does not have a state-specific site, you’ll be taken directly to the Multistate site.   The Multistate site: When a state joins the Data Center, our staff create a longitudinal file based on children’s records pulled directly from the state’s SACWIS or other electronic data collection system. That… Read more >

This Recipe will show you how to work with “nicknames,” a new feature of the All Spells component of the web tool designed to help you clarify and organize your analyses. This Recipe will take you about 5 minutes to complete. What do nicknames do? Nicknames offer you the option to customize the labels of the comparison groups in your analysis, instead of using the default labels generated by the system. Because they can be tailored to each query, nicknames will help you keep track of your analyses, giving you a quick reference for remembering which of your analyses deal with which groups of children—something that will come in especially handy when you print out the PDF results from multiple queries to share with colleagues. Where does the nickname option appear on the site? You’ll find the Population nickname option in the Define output section of the All Spells page;… Read more >

Length or stay is a key indicator of permanency for children in foster care. For the sake of child well-being, we strive to minimize length of stay—to get children out of foster care and into permanent homes as quickly as possible. But length of stay also as a fiscal implication. Foster care is expensive to provide. Many states are exploring ways to reduce foster care expenditures and reinvest savings into preventive and in-home services that decrease the need for out-of-home care. In the previous Recipe, I used the web tool’s Baseline Care Days and Exits Summary to answer the question of whether interventions designed to improve permanency outcomes have their intended effects. In this Recipe, I’ll show you how to use the information produced by that template to set baselines and targets for expenditures as well as outcomes. This Recipe takes about 10 minutes to complete. In addition to the web tool,… Read more >

Child welfare systems are constantly implementing new policies and practices as they endeavor to improve outcomes for the children and families they serve. But how do you know if your policy and practice interventions have the effects that you intend? To get to the answer, you must start by establishing your system’s baseline performance on the outcomes that you expect your intervention will improve. In establishing baseline outcomes, you answer to the question, “Based on historical performance, how should I expect my system perform on this outcome if we do not intervene, if business proceeds as usual?” Put differently, baseline outcomes are your “before” outcomes. They provide a reference point on which you expect to improve. In this Recipe I’ll use the web tool’s Baseline Exits and Care Day Summary report to show you how to generate baseline performance on two permanency indicators: (1) proportion of children exiting to permanency… Read more >

In the previous Recipe, you learned how to calculate the number of children entering care each year who are at risk of aging out within five years. This Recipe will show you how to calculate the proportion of children in this group that actually do age out. This Recipe will take you about 20 minutes to complete. In addition to the web tool, you will need a spreadsheet program such as Microsoft Excel.   Question: Of children who are at risk of aging out of foster care within 5 years of entry, how many actually do age out? [Note: This Recipe presumes that children will age out of foster care upon turning 18. The steps can be altered for jurisdictions that extend foster care benefits to children through age 19, 20, or 21.] On the All spells page, scroll down to the Spell overview section. Under Spell started age, enter… Read more >

Among other changes, the Fostering Connections law introduced new requirements for casework with older foster youth. It also established new reporting requirements regarding youth aging out of care. In light of these changes, monitoring the number of children who are at risk of aging out and providing them with the services they need are pressing issues for foster care systems today. In this Recipe I explain how to use the web tool to determine the number of youth entering care in your jurisdiction who are at risk of aging out within five years. This Recipe will take you about 10 minutes to complete. In addition to the web tool, it requires a spreadsheet program such as Microsoft Excel.   Question: In recent years, how many children entering care in my jurisdiction were at risk of aging out within five years of entry? Has that figure changed over time? [Note: This… Read more >

In the previous Recipe, we found that children entering foster care for the first time stayed in care longer than children who re-entered care after a previous spell. Why might that be? This Recipe shows you how to explore demographic and case-related differences between the comparison groups in your length of stay analysis to help you get closer to the answer.   Question: In my length of stay analysis, I found that first-time entrants stayed in care longer than re-entrants. Are there differences between these two groups that might account for that? Follow the steps for the length of stay analysis in the previous Recipe. In the upper right hand corner of the output page, click the button labeled Go to Demographic Comparison. On the next screen you’ll see a summary of your comparison groups. Under Report Options, select the variables that you’re interested in. To get a sense of… Read more >

As you know, different populations of children don’t always experience foster care in the same way. That’s why it’s so important to stratify your population—to take a measure of the whole group, and then break the results down by those child- and case-related characteristics that might make a difference in the outcome. One of those characteristics is admission type—whether the spell in question is the child’s first spell in foster care, or whether that spell is a re-entry after a prior discharge. Springboarding off my earlier post on length of stay, this Recipe will show you how to break length of stay results down by admission type in order to see whether children entering care for the first time have similar lengths of stay as children returning to care.   Question: Do children entering foster care for the first time stay in care as long as children re-entering care? On… Read more >

One important thing to bear in mind about entry cohort analyses is that when we follow a cohort of children forward, it takes time for each member’s outcomes to unfold. For example, say we want to know the length of stay of children who entered foster care in 2011. We can calculate that figure for the 2011 entrants who have already exited care, but there will be other 2011 entrants for whom we can’t calculate that figure because as of the censor date–the date as of which the archive was most recently updated–they were still in foster care. These children could have exited the day after the censor date or they may not exit for another two years; we just don’t know yet. When outcomes for children cannot be determined because they were still in care as of the censor date, we say that their spells (and thus, their data)… Read more >