Correlates and effect of non-response in a postpartum survey of obstetrical care quality

J Clin Epidemiol. 1997 Oct;50(10):1117-22. doi: 10.1016/s0895-4356(97)00096-6.


This study investigated the differences between unprompted respondents, prompted respondents, and non-respondents to a postpartum postal survey, and determined the likely impact of non-response on the accuracy of calculations of patient assessments of obstetrical care quality. Birth certificate and hospital discharge data were obtained for 1664 live births at three hospitals in Washington State between 8/91-10/91 and linked with 1268 completed postpartum maternal postal surveys. Non-white race, public insurance payer, unmarried status, and smoking in pregnancy were independent risk factors for non-participation. Among participants, non-white race, unmarried status, and having an infant who was low birthweight, preterm, or discharged late were independent risk factors for prompted response. The inclusion of prompted respondents did not substantially alter the calculated proportion of women rating obstetrical care quality as low, and these figures were similar to proportions estimated for the entire intended cohort using a modification of Drane's method. A one-time mailing of an obstetrical care quality survey can provide information similar to that obtained with more extensive follow-up even though substantial differences may exist between unprompted and prompted respondents, and with adjustment for factors related to non-participation and timing of response, it may be possible to obtain accurate estimation of outcome prevalences for the entire intended cohort.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Adult
  • Cohort Studies
  • Continental Population Groups
  • Female
  • Health Care Surveys* / methods
  • Humans
  • Logistic Models
  • Marital Status
  • Outcome Assessment, Health Care / methods*
  • Outcome Assessment, Health Care / statistics & numerical data
  • Patient Participation
  • Postal Service
  • Postpartum Period
  • Pregnancy
  • Prenatal Care / statistics & numerical data*
  • Quality of Health Care / statistics & numerical data*
  • Risk Factors
  • Selection Bias*