Introduction

1. What are family support services?


2. What is evaluation?

3. How can we evaluate family support services?

4. Where does measuring outcomes fit?

5. Why do we want to measure outcomes in family support?

6. How, “in theory” can we measure outcomes in family support?

7. What are some of the paradoxes and dilemmas in practice? How do we respond?

8. What is realistic? Who can do what?

9. What tools are available on this site for family support services? How can they be used?

Endnote 1: Data collation and analysis

Endnote 2: Feedback and ongoing development

Endnote 3: Connections and Links

Endnote 4: Developing this guide

  Measuring Outcomes in Family Support : Practitioners' Guide Version 1.0  

Endnote 1: Data Collation and Analysis

Service realities

Family support services in NSW are typically focused on direct service delivery. Staff skills, demands of work and work time frames are all client focused.

Data collation and analysis require a different set of tools, skills and work demands.

The following are some issues and tips for family support services to consider.

Levels of collation and analysis

Client data can be used at different levels, for example:

The individual client
Eg. comparing the clients situation at the beginning of service with the client’s situation on completion; c
omparing the client and workers views of the client's situation.

A group of clients in a local service
Eg. describing a group of clients in a service;
comparing the changes in clients situations for all clients in the service in a 12 month period

Clients in a region or across NSW
Eg. comparing the changes in clients situations for a random sample of family support clients across NSW in a 12 month period.

When working with data for an individual client the analysis can be straightforward and may not require sophisticated data bases or statistical analysis.

When collating data for larger groups of clients, either within a local service or across the state, more sophisticated data bases and statistical software will be required.

Types of questions and analysis

There are many types of analysis, from simple and straightforward to complex. For example data analysis could attempt to answer the following questions:

1. What are the changes in the clients answers to individual questions in the client questionnaire given at the beginning and the end of service?

2. How, on average do the clients in our service change from the beginning of service to the end of service?

3. What is the relationship between their responses to the survey questions and other data such as the language they speak, their level of income, size of family and so on?

4. What are the best predictors of clients who are making progress and clients who are not making progress?

Questions 1 can be answered in a straightforward way without sophisticated data analysis. Question 2 may require s spreadsheet. Questions 3 and 4 will require statistical analysis probably using statistical software.

Critical issues

If services wish to collate and analyse data they need to address the following critical issue:

1. Do we have the systems and databases in place to collate the data collected from clients and workers?

2. Do we have the skills to undertake the analyses we require?

3. Do we have the staff with appropriate work demands to be able to do the analysis? (ie, not continually interrupted with queries from clients)?

4. Do we have the right tools to collate the data (eg a computer database system)?

5. Do we have the right tools to analyse the data (eg statistical software)?

Resources on research and statistical analysis

A starting point for resources on research and statistical analysis is elsewhere on this site.