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Measuring Maternal Morbidity in Routinely Collected Health Data: Development and Validation of a Maternal Morbidity Outcome Indicator

Roberts, Christine L. MBBS, DipObsRANZCOG, DrPH*†; Cameron, Carolyn A. MPH*; Bell, Jane C. BDS, DipEd, MPH, MAppEpid*†; Algert, Charles S. BS, MPH*†; Morris, Jonathan M. MB ChB, FRANZCOG, PhD†‡

doi: 10.1097/MLR.0b013e318178eae4
Original Article

Background: As maternal deaths become rare in many countries, severe maternal morbidity has been suggested as a better indicator of quality of care.

Objective: To develop and validate an indicator for measuring major maternal morbidity in routinely collected population health datasets (PHDS).

Methods: First, diagnoses and procedures that might indicate major maternal morbidity were compiled and used to sample possible cases in PHDS; second, a validation study of indicated cases was undertaken by review of birth admission medical records using a nested case-control study approach with 400 possible cases and 800 controls; finally “true” morbidity from the validation study was used to define a maternal morbidity outcome indicator (MMOI) with a high positive predictive value (PPV). Sensitivity, specificity, PPV, negative predictive value (NPV), and exact 95% confidence intervals (95% CI) were weighted by the sampling probabilities.

Results: There were 1184 records available for review. Of 393 possible cases only 188 were confirmed as suffering major morbidity (weighted PPV 47.3%, sensitivity 72.9%) and of the 791 initial noncases, 787 were confirmed as noncases (weighted NPV 99.5%, specificity 98.5%). Revision of the initial indicator with exclusion of noncontributing International Classification of Disease (ICD) codes provided a MMOI with population-weighted rate of 1.5%, PPV 94.6% (95% CI: 72.3–99.9), sensitivity 78.4% (95% CI: 55.2–93.1), specificity 99.9% (95% CI: 99.5–99.9), and 99.5% agreement with “true” morbidity (kappa 0.86).

Conclusions: PHDS can be used reliably to identify women who suffer a major adverse outcome during the birth admission and have potential for monitoring the quality of obstetric care in a uniform and cost-effective way.

From the *Clinical and Population Perinatal Health Research, The Kolling Institute of Medical Research, University of Sydney, NSW, Australia; †Department of Obstetrics and Gynaecology, Royal North Shore Hospital, St Leonards, NSW, Australia; and ‡Northern Clinical School, University of Sydney, NSW, Australia.

Supported by a NHMRC Project Grant (#402498).

Christine Roberts is a National Health and Medical Research Council (NHMRC) Senior Research Fellow.

Reprints: Dr Christine Roberts, Department of Obstetrics and Gynaecology Level 4, Wallace Freeborn Building (26), Royal North Shore Hospital, St Leonards 2065, Australia. E-mail:

© 2008 Lippincott Williams & Wilkins, Inc.