1. White, Jessiya BS
  2. Morris, Hannah BA
  3. Cortright, Lindsay MA
  4. Buckman, Cierra MHS
  5. Tumin, Dmitry PhD
  6. Jamison, Shaundreal MD


Objective: We used public data from 2 national surveys to determine how survey mode and questionnaire wording potentially impact estimated prevalence and predictors of children's unmet health care needs.


Methods: Data from 2016-2017 were obtained for the National Health Interview Survey (NHIS), where interviewers ask caregivers about each type of unmet health care need in person, and the National Survey of Children's Health (NSCH), a self-administered questionnaire asking a general question about any unmet health care needs, with subparts about specific types of unmet needs. Weighted proportions and multivariable logistic regression were used to analyze each data set.


Results: The weighted proportion of any unmet health care needs was significantly higher in the NHIS (7.5%; 95% confidence interval [CI], 7.0-8.1; N = 17 723) than in the NSCH (3.3%; 95% CI, 2.9-3.7; N = 65 766). When analyzing specific unmet needs, unmet need for dental care was significantly higher according to the NHIS (4.2% vs 1.9% in the NSCH), as was unmet need for vision care (1.7% vs 0.8%). Conversely, estimates of unmet need for medical care were comparable between the surveys (1.4% and 1.0%). On multivariable analysis, predictors of unmet health care needs, such as being uninsured, had effect sizes of similar magnitude in both surveys.


Conclusion: The NHIS design, asking about each type of unmet need in person, may have been more conducive to identifying the full range of unmet health care needs among children. However, our results did not indicate that this was a source of bias in multivariable regression analysis.