Pervasive Developmental Disorders

PDD-NOS Module

PDD-NOS Module

PDD-NOS Module

Data

Data Collection
It summarizes information about the data sources needed to monitor &  evaluate the program.
The plan should include information for each data source such as:
• The timing and frequency of collection
• The person/agency responsible for the collection
• The information needed for the indicators
• Any additional information that will be obtained from the source

Data Quality
Data quality is important to consider when determining the usefulness of various data sources; the data collected are most useful when they are of the highest quality.
It is important to use the highest quality data that are obtainable, but this often requires a trade off with what it is feasible to obtain. The highest quality data are usually obtained through the triangulation of data from several sources. It is also important to remember that behavioral and motivational factors on the part of the people collecting and analyzing the data can also affect its quality.

Some types of errors or biases common in data collection include:
• Sampling bias: occurs when the sample taken to represent population values is not a representative sample
• Non-sampling error: all other kinds of measurement, such as courtesy bias, incomplete records, or non-response rates
• Subjective measurement: occurs when the data are influenced by the measure

Here are some data quality issues to consider:
• Coverage: Will the data cover all of the elements of interest?
• Completeness: Is there a complete set of data for each element of interest?
• Accuracy: Have the instruments been tested to ensure validity and reliability of the data?
• Frequency: Are the data collected as frequently as needed?
• Reporting Schedule: Do the available data reflect the time periods of interest?
• Accessibility: Are the data needed collectable/retrievable?
• Power: Is the sample size big enough to provide a stable estimate or detect change?

Data Use
The term data refers to raw, unprocessed information while information, or strategic information, usually refers to processed data or data presented in some sort of context.

Collecting data is only meaningful and worthwhile if it is subsequently used for evidence-based decision-making. To be useful, information must be based on quality data, and it also must be communicated effectively to policy makers and other interested stakeholders.
M&E data need to be manageable and timely, reliable, specific to the activities in question, and the results need to be well understood.

The key to effective data use involves linking the data to the decisions that need to be made and to those making these decisions.
The decision-maker needs to be aware of relevant information in order to make informed decisions.
When decision-makers understand the kinds of information that can be used to inform decisions and improve results, they are more likely to seek out and use this information.