DATA COLLECTION PLAN

Data Collection Plan

Data Collection Plan

Definition/Purpose

Use of this tool helps to remind you of why you're collecting data, reinforces standard methods for data collection, and shares the plan among team members and with project sponsors. Definitions used for data collection are included below. Used in Measure phase.

Definitions for Data Collection Plan Worksheet & Template

•Continuous (variable) Data: Often obtained by use of a measuring system or devise. When you measure, you get an actual number or value. There is a scale. Example: Length of stay, temperature, lab value, blood pressure value. These are the preferred type of data.

•Discrete (attribute) Data: Includes percentage or proportion (i.e. percent of employees absent), count occurrences (i.e. hash mark data, Yes/No data), observational (i.e. type of patient, type of equipment used, location of activity, day of week), and ranking (i.e. customer satisfaction ranking).

•Operational Definition: Defines exactly how you will go about collecting and recording the data. Provide precise description for the characteristic for which you trying to measure so that everyone involved has the same understanding of what is to be measured and how it will be measured. Must be clarified before data collection (i.e. define 'late'. If doing cycle time, must use the same clock.)

•Outcome Measure: Objectively measures the outcome of your project. Example: Customer satisfaction score on Press Ganey survey for overall wait time is >3.5 by 6/30/05.

•Process Measure: Objectively measures a process or key step in your process that leads to your ultimate outcome. Example: Patient check in time reduced by 25% by 5/31/05.

•Sampling: Must be representative (not biased). The higher sample number, the more accurate the data.

To use as a template, please save a copy by clicking on the save icon. Complete the form, taking note of definitions page. Use additional pages if needed. Recheck your data collection plan after 1 week of use:

•Are data being collected still reasonable?

•Do you need to collect all the data you originally thought you needed?



Pre-Data Collection Steps

1. Clearly define the goals and objectives of the data collection

2. Reach understanding and agreement on operational definitions and methodology for the data collection plan

3. Ensure data collection (and measurement) repeatability, reproducibility, accuracy, and stability

During Collection Steps

4. Follow through with the data collection process

Post-Data Collection Steps

5. Follow through with the results

Step 1: Define Goals And Objectives

A good data collection plan should include:

* A brief description of the project

* The specific data that is needed

* The rationale for collecting the data

* What insight the data might provide (to a process being studied) and how it will help the improvement team

* What will be done with the data once it has been collected

Being clear on these elements will facilitate the accurate and efficient collection of data.

Step 2: Define Operational Definitions and Methodology

The improvement team should clearly define what data is to be collected and how. It should decide what is to be evaluated and determine how a numerical value will be assigned, so as to facilitate ...