PubMed · 6595806
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J B Gregg, W F Stanage, W Johnson. 1984. Birth certificate data: how reliable?. https://pubmed.ncbi.nlm.nih.gov/6595806/
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The birth certificate and death certificate are important sources of population-based data for assessing the extent of risk and the quality of perinatal outcome. The birth certificate contains the hospital of birth and many items, such as birth weight and race, that can serve as important risk adjusters for neonatal mortality. To assess mortality a second vital record, the death certificate, must be linked to the birth certificate. If the analysis is to be stratified by level of neonatal care or other hospital characteristics, a third file providing these details must also be utilized. The exact vital record formats, recording protocols, and quality control efforts are determined by and differ across each state. Even with these differences, the quality and completeness of vital records and their linkage are reasonable for population-based analyses. Although the most important vital outcome from a neonatologist's perspective is neonatal mortality, vital records can also be used to assess fetal, perinatal, postneonatal, and infant mortality. The analytic paradigm that is used in quality analysis performed on data derived from the vital record states that observed outcome is a function of risk, chance, and care. Risk is a characteristic or condition such as low birth weight or low 1-minute Apgar score that elevates the probability of an adverse outcome but is beyond the control of the agent responsible for the outcome. Using risk matrices or regression analysis one determines the expected mortality for a specific institution's case-mix. This expectation is usually based on the statewide analysis of infants with a similar risk profile. A standardized mortality ratio is calculated by dividing observed by expected mortality. A hospital with a high observed mortality (12 deaths per 1000) and an even higher expected mortality based on the risk characteristics of its neonates (24 per 1000) would have a standardized mortality ratio of 0.5. Once the effects of chance have been accounted for by statistical testing this finding could indicate that mortality in this hospital is 50% lower then expected. Although initially intended for legal and broad-based public health purposes, vital records represent an important source of data to inform perinatal quality improvement activities. The optimal usefulness of information derived from vital records requires that clinicians take an active role in assuring that data entry is complete and accurately reflects risk status, clinical factors, and outcomes. However, even a superb database will be of limited usefulness unless it is linked to an initiative that actively involves clinicians committed to quality improvement.
Previous studies of birth certificates have not fully evaluated how accurately they identify delivery methods that have a historical component, such as repeat cesarean and vaginal birth after previous cesarean (VBAC). The authors used linked Georgia birth certificates for first and second deliveries to examine the accuracy of four reported delivery methods in the second pregnancy: vaginal (without previous cesarean), VBAC, primary cesarean, and repeat cesarean, as well as an indicator of a previous cesarean. From the immediate birth certificates, the delivery method for each of the two births was classified as vaginal (V) or cesarean section (CS), which produced possible sequences of V-V, CS-V, V-CS, and CS-CS. The delivery method for the second births to 106,049 women from 1989 through 1992 was reviewed, taking into account the historical information from the linked certificates regarding the first births. Only 42.0% of women with a CS-V sequence were correctly designated on the second birth certificate as a VBAC; 79.3% of women with a V- CS sequence were correctly designated as primary cesarean. From 1980 through 1988, birth certificates contained a check box indicating a previous cesarean (but no VBAC box). During this period, only 75.5% of 25,491 women with a previous cesarean were so designated on the birth certificate. These findings suggest that cross-sectional vital records data substantially underestimate VBAC and primary cesarean rates.
Log-linear models for capture-recapture type data are widely used for estimating sizes of populations. Log-linear methods model conditional interactions between the sources. Often, however, the marginal associations are more appropriate and easier for the practitioner to conceptualize. Analyses here of previously published data on cases of spina bifida in upstate New York are used to show how the assumption that sources are conditionally independent can give biased estimates if in fact the sources are marginally independent. A plausible model for the structural sources of interactions between the sources of information about spina bifida cases is developed which implies marginal independence of two of the sources rather than conditional independence. Estimates of the population total based on marginal independence are derived and give larger estimates of the population total than those derived based upon conditional dependence. When investigators can in fact model the likely underlying relationships of the sources in the population, we suggest considering modelling the potential interdependencies of the sources, which we term 'structural source modeling'.