Sample Data Collection Checklist to Be Used in Chart Review
A Checklist For Designing Data Collection Regimes
by Stacey Barr |
Information collection is a process, non an event. Thinking well-nigh it as a process makes it easier to appreciate all the steps that are involved, who is involved in each footstep and what resources will be needed to brand these steps work well. Employ the following checklist every bit a starting point for thinking through the design of your data collection processes.
When you're designing a new information collection process, or revamping an existing one, here are the six steps and 36 checkpoints that will ensure you get the correct data, in the right way, and at the correct level of reliability:
Footstep 1: Make the purpose clear.
- Identify the functioning measures, business questions or decisions that you require the data for.
- List the data items yous need to collect (eg these may come from your Performance Measure Definitions, if y'all have them, or assay of the information requirements for your business questions or decisions).
- Make sure your data items are useful, NOT simply interesting. If they are but interesting, and so consider the unintended consequences of collecting them (such every bit toll, abrasive respondents or data collectors, compromising integrity, etc.).
- Develop a purpose statement for the data collection procedure, then that anybody understands why it exists.
Footstep ii: Ascertain the scope of your data collection.
- List the characteristics that ascertain who or what yous will be collecting data most (eg historic period groups, roles, activities involved in, education level).
- List the characteristics that ascertain where this data will be nerveless (eg specific departments or divisions, geographical locations, specific offices or places of piece of work).
- Listing the characteristics that define when this data will exist collected (eg during November, all the fourth dimension, for the side by side 3 years, until an comeback is achieved).
- Use these lists to define the telescopic of your data collection: your 'target population'.
- Bank check and refine your telescopic definition past testing information technology with examples of people, things, places or times that are out of scope.
Step iii: Blueprint your sample.
- Define how reliable you lot want the data to be (eg how small a modify in your measures do you desire to be able to reliably discover?). This may already exist recorded in your Performance Measure Definitions.
- Nominate any demographic or nomenclature (or drilling) variables that y'all want to utilise in assay of your data (eg do you want to have averages or percentages by geographic location or age group or section or gender?). This may already be recorded in your Operation Measure Definitions.
- Discuss what kind of results you are expecting, in terms of the range of data values you think you are probable to get (eg are customers probable to rate their satisfaction mostly at iii or 4 on your 5 point satisfaction scale, or are they likely to be more spread out on the scale?).
- Explore logistical constraints of collecting information from your target population e.thousand. accessibility, cost and data integrity.
- Utilize the above four decisions (and a survey statistician or other help) to decide whether or not a sample volition exist more cost constructive than a census.
And if you have chosen to go with a sample, go professional person help then yous don't inadvertently make it completely useless:
- Place a survey statistician or other aid in survey sampling. It's a science, not an art.
- Make up one's mind whether or not information technology volition be stratified (ie your total sample is really a drove of smaller samples based on your demographic or classification variable, which may be geographic location, historic period group, section or gender). Stratifying a sample tin can sometimes be a style to reduce the overall sample size or improve the overall reliability of the results.
- Select a sample size (or sample sizes, if stratifying) that will deliver the reliability y'all require.
- Select your sample using a random method – not a convenient method like quotas or volunteers – or else you lot run the risk of bias, where the information yous get is not representative of your target population.
Stride 4: Develop your data collection instrument.
- Decide the basic method of data collection you desire (or tin can afford), such as self-completion, phone interview, face to face interview, focus group, or automated (if possible).
- Formulate questions or constructs around the set of data items you listed at Step 1. Give consideration to the type of construct that will give you the data you need, such equally open-concluded questions, yep/no questions, multiple pick, rating scales, selection lists, etc.
- Sequence the questions or constructs in a logical gild.
- Cheque the language and wording of your questions or constructs to remove ambiguity and "fluff". Requite consideration to providing concise instructions for how to answer to each construct.
- Pattern a layout for arranging your questions in a readable and usable way. Give consideration to the medium y'all will apply (such as web folio, reckoner data entry screen, newspaper, etc.), how you lot align things on the "folio", how you utilize white space to end it looking like a huge blob of text, how you use contrast to brand questions stand autonomously from instructions and the response expanse (eg the selection list, the rating scale, etc.).
- Test your questionnaire or form on a handful of people ideally those who volition collect the data or provide the information. The obvious problems won't be obvious to yous. Blot their feedback for ideas on making the questionnaire more than relevant, understandable and usable.
Step 5: Flowchart the procedure of collecting the information.
- Identify the trigger that volition let people know that data has to be collected. It might be a customer call, a specific consequence occurring or finishing, an activity starting.
- Identify how the data will be captured, such as which database volition it be entered into.
- List the steps that yous think will be involved in the information collection procedure, from the trigger to the capture of the data. Notation downwardly who will have a role in which step.
- Draw a flowchart (or cross-functional process map) that shows the menstruum of the steps through time, against who performs them. Requite consideration to the expected time frames within which each step should exist performed.
- For each step, identify the resources required to perform it successfully.
Footstep 6: Pilot test the whole thing.
- Choose a part of your information scope, based on location and time, in which yous volition carry your pilot test.
- List the outcomes that ascertain success for this data drove process. Explore what success might await like from each stakeholder's point of view (eg people collecting the data, providing the information, capturing the data, using the data, etc.). These might include touch on people's time, data integrity, data usability, costs and timeliness.
- Develop a Airplane pilot Examination plan for testing the information drove process, and a way to notice "evidence of success".
- Implement the Pilot Test plan.
- Reflect on the "evidence of success" and summarise what yous learned. List changes or improvements that you need to make to the data collection process and/or resources.
- Make the improvements to your information collection design.
- Deploy the data collection process. Go along to monitor it over time to ensure the "success outcomes" are tracking well.
At that place you have it. At present information technology's time to get busy! Merely don't think for a second that it's as well much effort to design robust information collection regimes. You lot just have to consider how much fourth dimension and try and functioning improvement opportunity is wasted through having irrelevant information, at the wrong time, and with depression reliability.
Have ACTION:
How does your approach to collecting information for your operation measures compare with this checklist? Do you take some potential to meliorate information technology, and thereby collect more of the data y'all need, in a more than timely and reliable way?
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Source: https://www.staceybarr.com/measure-up/a-checklist-for-designing-data-collection-regimes/
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