2000115-Strengthening-Communities-with-Neighborhood-Data

176 Strengthening Communities with Neighborhood Data
• GPRA 4. Number and percentage of students at or above grade level
according to state mathematics and English language arts assessments
in at least grades 3rd through 8th and once in high school
• GPRA 10. Number and percentage of students who feel safe at
school and traveling to and from school
In order to report the GPRA measures, Promise grantees must regularly
collect neighborhood-level data from national and local data files
and special surveys on school climate and various neighborhood conditions.
However, a more formidable challenge is for them to maintain
data on individual children in a case management system. The data on
services are collected for each child in the program and typically cover
demographics, the type and dates of services provided, level of service
(e.g., number of hours in counseling), and indicators of achievement
(e.g., grade in a course that has been completed). 30
Although case management data are required for only two of the
GPRA measures, Promise grantees are nonetheless encouraged to develop
a case management system because of the importance of such systems
to effective program management and outcomes. It is very difficult, for
example, for case managers to offer sensible advice about next steps in
supporting individual children and families in the program without considerable
knowledge about their circumstances and their prior service
histories.
Much of the challenge for systems development, however, arises from
the requirement that Promise Neighborhoods coordinate and track a
number of services delivered by separate local providers. 31 This implies
the need to integrate records that are maintained by separate providers
on individual children and their families. It might involve, for example,
integrating data about a student from school records (e.g., proficiency
scores, absenteeism, school mobility) with data on the same child from
child welfare agencies, health care providers, and afterschool programs.
Credible summary information on what this type of program achieves
requires summarizing data on what happens to individuals, but the task
of data integration is obviously difficult, especially if attempted on a
small scale. This task has certainly been a formidable challenge for the
LISC’s TTM effort in Chicago. Perhaps more important than the technical
difficulties are the steps that must be taken to maintain high standards
regarding confidentiality. This work inevitably presses the boundaries set
under the HIPAA and FERPA legislation noted in chapter 2. Even so, as