data analysis for assuring the quality of your cosf data 1

Data Analysis for Assuring the Quality of your COSF Data

1

What are these numbers??

2

OSEP reporting requirements: the outcomes Percentage of children who

demonstrated improved:

1.Positive social emotional skills (including positive social relationships)

2.Acquisition and use of knowledge and skills (including early language/ communication [and early literacy])

3.Use of appropriate behaviors to meet their needs

3

OSEP reporting categories

Percentage of children who:

a.Did not improve functioning

b.Improved functioning, but not sufficient to move nearer to functioning comparable to same-aged peers

c. Improved functioning to a level nearer to same-aged peers but did not reach it

• Improved functioning to reach a level comparable to same-aged peers

e. Maintained functioning at a level comparable to same-aged peers

3 outcomes x 5 “measures” = 15 numbers 4

Getting to progress categories from the COSF ratings

5

Functioning

6

Entry

7

Entry Exit

8

Entry Exit

9

Key Point

• The OSEP categories describe types of progress children can make between entry and exit

• Two COSF ratings (entry and exit) are needed to calculate what OSEP category describes a child progress

10

How changes in ratings on the COSF correspond to reporting categories a - e

e. % of children e. % of children who who maintainmaintain functioning at functioning at a level a level comparable to comparable to same-aged same-aged peerspeers

• Rated 6 or 7 at Rated 6 or 7 at entry; ANDentry; AND

• Rated 6 or 7 at Rated 6 or 7 at exitexit

11

Entry Exit

12

Entry Exit

13

Entry Exit

14


d. % of children d. % of children who improve who improve functioning to functioning to reachreach a level a level comparable to comparable to same-aged same-aged peerspeers

• Rated 5 or Rated 5 or lower at lower at entry; ANDentry; AND

• Rated 6 or 7 Rated 6 or 7 at exitat exit

15

Entry Exit

16


c. % of children c. % of children who improved who improved functioning to functioning to a level a level nearernearer to same aged to same aged peers, but did peers, but did not reach itnot reach it

• Rated higher Rated higher at exit than at exit than entry; ANDentry; AND

• Rated 5 or Rated 5 or below at exitbelow at exit

17

Entry Exit

18

Entry Exit

19


b. % of children b. % of children who who improvedimproved functioning, but functioning, but not sufficient to not sufficient to move nearer to move nearer to same aged same aged peerspeers

• Rated 5 or lower Rated 5 or lower at entry; ANDat entry; AND

• Rated the same Rated the same or lower at exit; or lower at exit; ANDAND

• ““Yes” on the Yes” on the progress progress question (b)question (b)

20

Entry Exit

21

Entry Exit

22

Entry Exit

23

Entry Exit

24


a. % of children who a. % of children who did not improvedid not improve functioningfunctioning

• Rated lower at Rated lower at exit than entry; exit than entry; OROR

• Rated 1 at both Rated 1 at both entry and exit; entry and exit; ANDAND

• Scored “No” on Scored “No” on the progress the progress question (b)question (b)

25

Entry Exit

26

Entry Exit

27

The ECO Calculator can be used to translate COSF entry and exit ratings to the 5 progress categories for federal reporting

28

Promoting quality data through data analysis

29

Promoting quality data through data analysis

• Examine the data for inconsistencies

• If/when you find something strange, what might help explain it?

• Is the variation because of a program data? Or because of bad data?

(at this point in the implementation process, data quality issues are likely!)

30

The validity of your data is questionable if…

The overall pattern in the data looks ‘strange’– Compared to what you expect– Compared to other data– Compared to similar

states/regions/agencies

31

COSF Ratings – Outcome 1 Entry data (fake data)

Rating Statewide

1 30

2 42

3 51

4 60

5 10

6 10

7 032


Rating Statewide

1 30 (15%)

2 42 (20%)

3 51 (25%)

4 60 (30%)

5 10 (5%)

6 10 (5%)

7 0 (0%)33

Frequency on Outcome 1 – Statewide (fake data)

34


Rating Agency 1

Agency 2

Agency 3

Agency 4

1 3 1 1 2

2 4 1 2 2

3 5 2 3 3

4 6 3 2 4

5 1 4 5 4

6 1 5 5 4

7 0 4 2 1 35


Rating Group 1 Group 2 Group 3 Group 4

1 15% 5% 5% 10%

2 20% 5% 10% 10%

3 25% 10% 15% 15%

4 30% 15% 10% 20%

5 5% 20% 25% 20%

6 5% 25% 25% 20%

7 0% 20% 10% 5%36

Questions to ask when looking at data

• Do the data make sense?– Am I surprised? – Do I believe the data? Some of it? All of it?

• If the data are reasonable (or when they become reasonable), what might they tell us?

• When we believe the data, how can we use it for program improvement?

37

Using data for program improvement

38

39

Plan (vision) Program characteristics

Child and family outcomes

Implement

Check(Collect and analyze data)

ReflectAre we where we

want to be?

Continuous Program Improvement

Using data for program improvement = EIA

•Evidence•Inference

•Action

40

41

Evidence

• Evidence refers to the numbers, such as“45% of children in category b”

• The numbers are not debatable

42

Inference• How do you interpret the #s?• What can you conclude from the

#s?• Does evidence mean good news?

Bad news? News we can’t interpret?

• To reach an inference, sometimes we analyze data in other ways (ask for more evidence)

43

Inference• Inference is debatable -- even

reasonable people can reach different conclusions

• Stakeholders can help with putting meaning on the numbers

• Early on, the inference may be more a question of the quality of the data

Explaining variation• Who has good outcomes = • Do outcomes vary by

•Region of the state?•Amount of services received?•Type of services received?•Age at entry to service?•Level of functioning at entry?•Family outcomes?•Education level of parent?

44

45

Action

• Given the inference from the numbers, what should be done?

• Recommendations or action steps• Action can be debatable – and

often is• Another role for stakeholders• Again, early on the action might

have to do with improving the quality of the data

Working Assumptions

• There are some high quality services and programs being provided across the state

• There are some children who are not getting the highest quality services

• If we can find ways to improve those services/programs, these children will experience better outcomes

46

Questions to ask of your data

• Are ALL services high quality?

• Are ALL children and families receiving ALL the services they should in a timely manner?

• Are ALL families being supported in being involved in their child’s program?

• What are the barriers to high quality services?

47

Program improvement: Where and how

– At the state level – TA, policy

– At the agency level – supervision, guidance

– Child level -- modify intervention

48

Key points

• Evidence refers to the numbers and the numbers by themselves are meaningless

• Inference is attached by those who read (interpret) the numbers

• You have the opportunity and obligation to attach meaning

49

Plan (vision) Program characteristics

Child and family outcomes

Implement

Check(Collect and analyze data)

ReflectAre we where we

want to be?

Is there a problem?

Why is it happening?

What should be done?

Is it being done?

Is it working?

Tweaking the System

50

Continuous means…

•…….the cycle never ends..the cycle never ends.

51

data analysis for assuring the quality of your cosf data 1

Documents