Measuring Maternal Morbidity in Routinely Collected Health Data

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Abstract
As maternal deaths become rare in many countries, severe maternal morbidity has been suggested as a better indicator of quality of care. To develop and validate an indicator for measuring major maternal morbidity in routinely collected population health datasets (PHDS). 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. 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). 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.