Scenario:
This is likely the most frequent scenario with which administrators are presented. In times of budget pressures, or at other times when asked to justify services, administrators are asked to show why specific services are necessary. This could include justifying why service slots are necessary at a specific intensity or restrictiveness of care. They could include justification of length of stay, or explanations of why linkages take as long as they do. Underlying these is the question, "Are these services working for children and youth?" We'll talk about how billing data can provide answers to some of these questions and let us know when we need to collect additional information to answer our questions.

How do I use this?
Billing data provide a convenient source of data about all clients receiving fee-for-service services. This allows administrators to understand how many persons are entering and using services, for how long, and at what intensity of care. These data also allow administrators to see what happens to clients after they experience a service: whether they re-enter the system, how quickly, and at what intensity of service use.

Steps in the process:
The first step in the process is to understand the content and limitations of your billing data. Begin by asking a couple of basic questions. Ask which populations are included in your database. Find out whether there are special programs or services which have payment procedures that are not captured in a way that alows them to be integrated and analyzed wth the rest of your billing data. Once you know the limitations associated with the data, you can find other ways to ascertain what is needed, or simply note the limitations of the data.
Then you'll want to construct a series of analyses that let you understand client flow. Client flow consists of the rate at which people enter, use and exit services. Understanding flow allows you to state how many people currently use services, at what intensity of care, for how long, and the rate at which they transition from one level of service use to another. These data also give you one proxy for service effectiveness: the rate at which persons exit from a lower level of care and quickly enter a higher level of care. The lack of data on actual client functioning keeps us from being sure about why a client moved from one level of care to another. In the absence of direct functioning data, it is a reasonable inference to make that most clients who move up to a higher level of care from a lower level of care do so because the care at the lower level was ineffective.

The links (below) to the Sustainability Institute and the MIT System Dynamics Group provide a theoretical and cross- discipline perspective on understanding system flow data. The PowerPoint presentation walks through an application of fee-for-service billing data in San Francisco's children's mental health system.

What do I still not know?
As alluded to above, billing data cannot tell us why a service was provided. Billing data cannot tell you whether any pattern of service use was clinically appropriate. For that you must have clinical data. Billing data is also limited to the data that you have at hand; services which are not fee-for-service may provide particular difficulty for integration. Missing data, such as these, keep us from being able to fully describe client movement through the service system.




Link to Sustainability Institute resources: http://www.sustainer.org/tools_resources/index.html


Link to MIT System Dynamics Group: http://sdg.scripts.mit.edu/