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An Enhanced Method for Identifying Obstetric Deliveries: Implications for Estimating Maternal Morbidity

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Objectives The accuracy of maternal morbidity estimates from hospital discharge data may be influenced by incomplete identification of deliveries. In maternal/infant health studies, obstetric deliveries are often identified only by the maternal outcome of delivery code (International Classification of Diseases code = V27). We developed an enhanced delivery identification method based on additional delivery-related codes and compared the performance of the enhanced method with the V27 method in identifying estimates of deliveries as well as estimates of maternal morbidity. Methods The enhanced and standard V27 methods for identifying deliveries were applied to data from the 1998–2004 Healthcare Cost and Utilization Project Nationwide Inpatient Sample, an annual nationwide representative survey of U.S. hospitalizations. Odds ratios (ORs) and 95% confidence intervals (CIs) from logistic regression were used to examine predictors of deliveries not identified using the V27 method. Results The enhanced method identified 958,868 (3.4%) more deliveries than the 27,128,539 identified using the V27 code alone. Severe complications including major puerperal infections (OR = 3.1, 95% CI 2.8–3.4), hysterectomy (OR = 6.0, 95% CI 5.3–6.8), sepsis (OR = 11.9, 95% CI 10.3–13.6) and respiratory distress syndrome (OR = 16.6, 95% CI 14.4–19.2) were strongly associated with deliveries not identified by the V27 method. Nationwide prevalence rates of severe maternal complications were underestimated with the V27 method compared to the enhanced method, ranging from 9% underestimation for major puerperal infections to 40% underestimation for respiratory distress syndrome. Conclusion Deliveries with severe obstetric complications may be more likely to be missed using the V27 code. Researchers should be aware that selecting deliveries from hospital stay records by V27 codes alone may affect the accuracy of their findings.

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The authors wish to thank Pooja Bansil and Andrew Mossa for programming assistance. The authors also thank the following organizations from across the United States for their contribution to the HCUP data collection: Arizona Department of Health Services, California Office of Statewide Health Planning & Development, Colorado Health & Hospital Association, Connecticut Integrated Health Information (Chime, Inc.), Florida Agency for Health Care Administration, Georgia GHA: An Association of Hospitals & Health Systems, Hawaii Health Information Corporation, Illinois Health Care Cost Containment Council and Department of Public Health, Indiana Hospital & Health Association, Iowa Hospital Association, Kansas Hospital Association, Kentucky Department for Public Health, Maine Health Data Organization, Maryland Health Services Cost Review Commission, Massachusetts Division of Health Care Finance and Policy, Michigan Health & Hospital Association, Minnesota Hospital Association, Missouri Hospital Industry Data Institute, Nebraska Hospital Association, Nevada Division of Health Care Financing and Policy, Department of Human Resources, New Hampshire Department of Health & Human Services, New Jersey Department of Health & Senior Services, New York State Department of Health, North Carolina Department of Health and Human Services, Ohio Hospital Association, Oregon Office for Oregon Health Policy and Research and Oregon Association of Hospitals and Health Systems, Pennsylvania Health Care Cost Containment Council, Rhode Island Department of Health, South Carolina State Budget & Control Board, South Dakota Association of Healthcare Organizations, Tennessee Hospital Association, Texas Department of State Health Services, Utah Department of Health Vermont Association of Hospitals and Health Systems, Virginia Health Information, Washington State Department of Health, West Virginia Health Care Authority, Wisconsin Department of Health & Family Services.

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Correspondence to Elena V. Kuklina.

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Presentations: The results were presented as a poster at the Second American Congress of Epidemiology, Seattle, WA, June 21–24, 2006.

Disclaimer: The findings and conclusions in this report are those of the authors and do not necessarily represent the view of the Centers for Disease Control and Prevention or the National Institutes of Health.




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Kuklina, E.V., Whiteman, M.K., Hillis, S.D. et al. An Enhanced Method for Identifying Obstetric Deliveries: Implications for Estimating Maternal Morbidity. Matern Child Health J 12, 469–477 (2008).

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