The Open Data Kit (ODK) tool is created a revolution in data collection from mobile devices. It is brilliant for its ease of creation of complex questionnaires with dependencies with on any topic or indicators. The creators really deserve the gun powder prize for their enormous contribution.

The underlying XForms and XLSForms in ODK based on JavaRosa/OpenRosa are very difficult for integration of complex calculations such as those for WHO z-scores. But now an ODK questionnaire form with integrated validation of WHO Flags is available to everyone for free.

WHZ WHO flags

Open Data Kit created a revolution in paperless data collection after its launch in 2010. For environmental and cost saving reasons alone, the paperless data collection provides huge benefits. For improved data quality, these types of tools are unequalled.

To integrate the WHO flags into the form, the corresponding age and measures were calculated by sex of child and/or length/height for the flags for each indicator of child nutritional status:

  • weight for height (+/-5 standard deviations)
  • height for age (+/- 6 standard deviations)
  • weight for age (+5/-6 standard deviations)
  • MUAC for age (+/-6 standard deviations).

Then the curves for all the z-score limits were calculated and incorporated into the ODK questionnaire. Following statistical theory, there is a one in 17,000,000 chance that the anthropometric measures of a child can fall outside of the +/- 5 standard deviation range. This is equivalent to an event that occurs once in the time since recorded history began (~5000 years ago). These statistically improbable cases can be easily caused by entering height in the weight category, mistaking the child’s age by one year or simply guessing at the relative weight and height of a child. Unfortunately, some surveys can have up to 24% of flagged data.

The WHO flags questionnaire follows best practices and does not assume that the data collector has made an error when an indicator is detected outside the WHO flags. The data collection flow goes as follows:

  • Data are entered on age, height, measure by length/height, weight, MUAC and bilateral edema
  • The measures are assessed to determine if any indicators are flagged. If yes, a request for re-measure is made
  • If there are no flags, a random request for re-measure is made for 5% of the children measured, thus it is never evident to the data collector if the re-measure was triggered by a flag or random request
  • The once() function in ODK is used to protect the data from tinkering by constraining the form to make only one test of flags and one random measure on the first data entry.
  • The re-measure is made and data are entered into the form as the second measure of the child.

As the data are send via the 3G or Edge network, they are available immediately for analysis.  With the WHO flags and the request for the random re-measure, the survey coordination team can identify keying errors, gross errors and data manipulation during data collection and respond quickly to prevent these errors from invalidating the survey results.

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