Estimating the obstetric co-morbidity burden using administrative data: The impact of the pregnancy-related assessment window.

BACKGROUND

Despite increased research using large administrative databases to identify determinants of maternal morbidity and mortality, the extent to which these databases capture obstetric co-morbidities is unknown.

OBJECTIVE

To evaluate the impact that the time window used to assess obstetric co-morbidities has on the completeness of ascertainment of those co-morbidities.

METHODS

We conducted a five-year analysis of inpatient hospitalisations of pregnant women from 2010-2014 using the Nationwide Readmissions Database. For each woman, using discharge diagnoses, we identified 24 conditions used to create the Obstetric Comorbidity Index. Using various assessment windows for capturing obstetric co-morbidities, including the delivery hospitalisation only and all weekly windows from 7 to 280 days, we calculated the frequency and rate of each co-morbidity and the degree of underascertainment of the co-morbidity. Under each scenario, and for each co-morbidity, we also calculated the all-cause, 30-day readmission rate.

RESULTS

There were over 3 million delivery hospitalisations from 2010 to 2014 included in this analysis. Compared with a full 280-day window, assessment of obstetric co-morbidities using only diagnoses made during the delivery hospitalisation would result in failing to identify over 35% of cases of chronic renal disease, 28.5% cases in which alcohol abuse was documented during pregnancy, and 23.1% of women with pulmonary hypertension. For seven other co-morbidities, at least 1 in 20 women with that condition would have been missed with exclusive reliance on the delivery hospitalisation for co-morbidity diagnoses. Not only would reliance on delivery hospitalisations have resulted in missed cases of co-morbidities, but for many conditions, estimates of readmission rates for women with obstetric co-morbidities would have been underestimated.

CONCLUSIONS

An increasing proportion of maternal and child health research is based on large administrative databases. This study provides data that facilitate the assessment of the degree to which important obstetric co-morbidities may be underascertained when using these databases.