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Health Survey Nonresponse Code

Separate explicitly supplied refusal and missing response codes without imputing survey answers.

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Description

Distinguish missing and refused survey response codes.

Public-health data distinguishes assigned case definitions, invitation responses, missing codes, repeat attendances and population denominators. A display-suppression rule changes visible text without necessarily preventing re-identification. Administrative labels and local summaries require verified study, privacy and clinical context before they can support population-health decisions.

Distinguish missing and refused survey response codes.

When to use this tool

Use Health Survey Nonresponse Code when you already have recordedCode, missingCodes, refusedCodes and need to distinguish missing and refused survey response codes.

How to use the tool and how it works

  1. Enter recordedCode, missingCodes, refusedCodes. Follow any array-alignment requirements below. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read status. Use the output convention below.

Require missingCodes and refusedCodes disjoint; classify recordedCode by membership, otherwise other.1

Input fieldMeaning and unitsAccepted input
recordedCodeRecorded CodeRequired. Text; maximum UTF-16 length 8192.
missingCodesMissing CodesRequired. Array of text; maximum UTF-16 length 8192; maximum items 256.
refusedCodesRefused CodesRequired. Array of text; maximum UTF-16 length 8192; maximum items 256.
Output fieldInterpretationReturned shape
statusStatusRequired. Text; maximum UTF-16 length 8192.
json
{
  "input": {
    "recordedCode": "R",
    "missingCodes": [
      "M"
    ],
    "refusedCodes": [
      "R"
    ]
  },
  "output": {
    "status": "refused"
  }
}

Limitations and assumptions

  • Code lists may repeat; the tool does not infer the reason for a missing response or compute survey weights.
  • Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.

Alternative or Complementary methods

Review the surveillance definition, survey codebook and population frame for actual counts and classifications. Assess disclosure controls across the full released dataset, including linked totals and repeated queries, rather than relying on one small-cell display rule.

References

  1. Calculation and input contract: public-health/health-survey-nonresponse-code — tool.io

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