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Vital records for quality improvement.

CPQCC Publication
TitleVital records for quality improvement.
Publication TypeJournal Article
Year of Publication1999
AuthorsGould JB
JournalPediatrics
Volume103
Issue1 Suppl E
Pagination278-90
Date Published1999 Jan
ISSN1098-4275
KeywordsBirth Certificates, Death Certificates, Fetal Death, Hospital Mortality, Hospitals, Humans, Infant, Infant Mortality, Infant, Newborn, Perinatal Care, Quality Indicators, Health Care, Risk Adjustment, Total Quality Management, United States
Abstract

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.

Alternate JournalPediatrics
PubMed ID9917471