Association of Maternal Comorbidity With Severe Maternal Morbidity: A Cohort Study of California Mothers Delivering Between 1997 and 2014

The U.S. maternal mortality rate is the highest among all high-resource countries (1). Although rates are decreasing in other countries, those in the United States continue to climb (1–3). Major complications related to childbirth are also a concern and have been characterized by the Centers for Disease Control and Prevention (CDC) through definition and measurement of severe maternal morbidity (SMM) using hospital discharge data (4, 5). This composite measure uses 21 categories of diagnoses and procedures, which can each be life-threatening and have potential long-term effects on health. Severe maternal morbidity occurs nearly 100 times more than maternal death and is also on the rise (6). Because SMM is much more common, it may provide further insights into both potential causation and improvement opportunities (7).

In this report, we explore the roles of both obstetric and medical comorbid conditions in association with the increases in SMM using a well-described, linked data set from California that includes vital records and hospital discharge records from multiple years (8). We relate this analysis to the maternal comorbidity index first derived by Bateman and colleagues (9) using multistate Medicaid data. This approach parallels the analyses done by the CDC Pregnancy Mortality Surveillance System examining the underlying causes of U.S. maternal deaths. Reports from 3 periods illustrate a progressive increase in underlying medical conditions, which caused 19.6% of maternal deaths in 1987 to 1990, 43.5% in 1998 to 2005, and 47.6% in 2011 to 2013 (10–12). The findings in this report should further enhance our understanding of maternal comorbid conditions and their association with severe morbidity, which could, in turn, help reduce both maternal morbidity and mortality through efforts to improve maternal medical and obstetric care.

Methods

We analyzed the frequency of SMM using linked discharge data from delivery hospitalizations, fetal death certificates, and live birth certificates from 9 179 472 deliveries in California during 1997 to 2014. The data had been linked previously by the California Office of Statewide Health Planning and Development (1997 to 2011) and the California Maternal Quality Care Collaborative (2012 to 2014), with successful linkage in more than 98% of cases (13). Figure 1 illustrates the selection of study samples for analysis. During 1997 to 2011, when sibling linkage information was available, there were 6 902 025 births to 5 057 098 women; this degree of clustering was previously found to not affect results (14).

• Download figure
• Download PowerPoint

Severe maternal morbidity events were identified in delivery hospitalization discharge records using the International Classification of Diseases, Ninth Revision, Clinical Modification list of 21 groupings of diagnosis and procedure codes developed by the CDC and shown in Table 1 (15). The SMM composite measure was subsequently validated in a large case review study in California (16); SMM includes indicators of specific, well-defined severe events, such as blood transfusion, disseminated intravascular coagulation, and hysterectomy. Blood transfusion is the only qualifying indicator for approximately half of SMM cases, and studies using a national hospital sample have noted that much of the increase in SMM is due to increasing rates of blood transfusion (6, 17). We therefore studied a second outcome that excluded transfusion-only cases, which we hereafter call “nontransfusion SMM.”

Table 1. SMM Indicators and Corresponding ICD-9-CM Codes as Defined by the Centers for Disease Control and Prevention (14)

Maternal comorbid conditions were assessed using the maternal comorbidity index developed by Bateman and colleagues (9) in 2013 to predict risk for maternal end-organ injury or death. A logistic regression model was followed by a stepwise selection algorithm that included candidate comorbid conditions and maternal age. The latest revision of the index (2019) includes 24 individual conditions that receive scores from 0 to 5 (“weights”) (18). Each of the conditions included in the final model is assigned a weight based on its β-coefficient. Scores are summed to determine a woman's total comorbidity score. This index performed statistically significantly better than other comorbidity indices used in general medicine (Charlson Comorbidity Index, Elixhauser comorbidity classification system, and their adaptations) (9).

Statistical Analysis

We identified comorbid conditions using both hospitalization discharge and vital record data to increase accuracy (19). Both data sources tend to underestimate medical and obstetric complication rates, and the union of the 2 sources provides the most complete and accurate diagnosis set (19). In addition, we examined the frequency of comorbidity scores, grouped as 0, 1 to 2, 3 to 4, and 5 or higher. Finally, we assessed the time trends of comorbid conditions, grouped as medical comorbid conditions, obstetric comorbid conditions, previous cesarean birth, advanced maternal age (≥35 years), and elevated body mass index (BMI) before pregnancy (≥40 kg/m²).

We calculated and plotted the prevalence of SMM, including and excluding transfusion-only cases, in each year of data (1997 to 2014), as well as the change in prevalence over the study period. We then examined the associations between maternal comorbid conditions and SMM. We used data from deliveries in 2007 to 2014 because California began recording prepregnancy and delivery BMI in vital records in 2007. We then used multivariable logistic regression models to assess the associations of each comorbid condition included in the 2019 revision of the maternal comorbidity index with SMM and nontransfusion SMM. We selected confounding variables for model adjustment a priori on the basis of causal graphs and available data to obtain independent risk assessments for each comorbid condition. Each was further adjusted for maternal age, BMI, race/ethnicity, education, insurance status, and all other medical comorbid conditions listed in Table 2 combined as a score. This was important given the frequent interactions identified among the comorbid conditions. Odds ratios derived from the models closely approximated relative risks (RRs) because the outcome was rare (<2%). We hereafter use the term RR to aid in interpretability of the results.

Table 2. Associations Between Medical Comorbid Conditions Using 2019 Maternal Comorbidity Index (9, 18) and SMM (n = 3 647 427)*

We did additional analyses to examine changes in comorbid conditions, SMM, and their association over time. We calculated and plotted the prevalence of each comorbidity group in each study year, as well as the change in prevalence over time. We then selected 3 years across the study period (1997, 2007, and 2014), and within each year we calculated the prevalence of each comorbidity group and the population-attributable risk percentage for SMM and nontransfusion SMM. We selected 2007 because California adopted the revised U.S. Standard Certificate of Live Birth that year, which added collection of BMI information. We used multivariable logistic regression models to calculate population-attributable risk, which estimates what percentage of SMM cases in California during that year could be attributed to the comorbidity group. We bootstrapped the calculations of population-attributable risk 500 times to obtain 95% CIs.

All analyses were done in R, version 3.4.2 (R Foundation for Statistical Computing), and SAS, version 9.4 (SAS Institute). Human studies approvals for this research were obtained from the State of California Committee for the Protection of Human Subjects and the Stanford University Research Compliance Office.

Role of the Funding Source

Funding was provided in part by the National Institutes of Health, the Office of Research on Women's Health, and Stanford Maternal and Child Health Research Institute. The funding organizations had no role in the design of the study; the collection, analysis, or interpretation of the data; or the decision to approve publication of the finished manuscript.

Results

Severe maternal morbidity increased dramatically between 1997 and 2014 in California, from 67 to 174 cases per 10 000 births (160% increase) (Figure 2). Between 2007 and 2014, the rate of nontransfusion SMM increased by 53%, to 69 cases per 10 000 births. We then sought to determine the relationship of the medical and obstetric comorbid conditions described in the maternal comorbidity index with total SMM and nontransfusion SMM. In analyzing associations between comorbid conditions and SMM, we included pregnancies during 2007 to 2014 (n = 4 094 444) that had linked maternal discharge and vital record data (n = 4 005 423 [97.8%]) and plausible, recorded values for maternal age (212 missing values [0.005%]), BMI at delivery (213 906 missing values [5.3%]), race/ethnicity (280 333 missing values [7.0%]), education level (353 065 missing values [8.8%]), and insurance status (357 996 missing values [8.9%]). The population for analysis with all factors available was 3 647 427 deliveries, or 91.1% of the initial population.

• Download figure
• Download PowerPoint

Given the inability to identify and separate sibling births in this data set, as noted in the Methods section, the actual unit of analysis used in this investigation is unique deliveries, not unique women. However, describing “deliveries that had SMM” is awkward, so “women having SMM” is used, recognizing that they are not unique. Table 2 presents the published maternal comorbidity index weight and the frequency of each medical comorbid condition among all delivering women. Relative risks for the associations between each comorbid condition and total SMM and nontransfusion SMM are presented. Of women who did have SMM, 22.6% had a medical comorbid condition. As shown in Table 2, the adjusted RR for SMM in women with any medical comorbid condition was 3.1 (95% CI, 3.0 to 3.1) compared with those without such a condition. Overall, 32.4% of women who had nontransfusion SMM had a medical comorbid condition. The adjusted RR for nontransfusion SMM in women with any medical comorbid condition was 4.9 (CI, 4.8 to 5.1) compared with those without such a condition. All conditions but 2 had adjusted RRs greater than 2.0 for SMM. Cardiovascular conditions, chronic renal disease, and hematologic disorders had high adjusted RRs (range, 3.2 to 14.3) for SMM. These conditions also had high adjusted RRs (range, 4.6 to 32.4) for nontransfusion SMM.

Table 3 presents data for comorbid conditions related to current and prior pregnancies as well as for advanced maternal age and elevated prepregnancy BMI. Again, these comorbid conditions were evaluated for total SMM and nontransfusion SMM. Severe preeclampsia, placental complications, and fetal death stand out with high RRs for SMM of more than 5.0. In contrast to medical comorbid conditions, obstetric comorbid conditions had little change in RR for nontransfusion SMM compared with total SMM.

Table 3. Associations Between Current and Prior Pregnancy and Demographic Comorbid Conditions Using 2019 Maternal Comorbidity Index (9, 18) and SMM (n = 3 647 427)*

Creating an independent risk assessment for each comorbid condition then allowed us to sum the individual comorbidity weights for a given mother. The performance of adding comorbidity index–weighted scores was tested; 3.3% of the population had a summed maternal comorbidity index score of 5 or greater, and their RR for SMM was 12.4 (CI, 12.1 to 12.7) compared with mothers with a score of 0. This same population with a score of 5 or greater had an RR for nontransfusion SMM that was even higher at 17.1 (CI, 16.5 to 17.7), indicating a population at high risk for the most severe complications. The absolute rates of total SMM and nontransfusion SMM in this high-comorbidity group were 9.2% and 4.9%, respectively, compared with 0.8% and 0.3% in women without a comorbid condition.

Figure 3 illustrates time trends for key comorbid conditions. Between 1997 and 2014, the proportion of mothers with maternal age older than 35 years (RR for SMM, 1.7) increased by 39%, prior cesarean delivery (RR for SMM, 1.5) by 40%, current obstetric comorbid conditions (RR for SMM, 4.8) by 33%, medical comorbid conditions (RR for SMM, 3.1) by 111%, and prepregnancy BMI of at least 40 kg/m² (RR for SMM, 1.4) by 30% (between 2007 and 2014 because of limited years of data collection).

• Download figure
• Download PowerPoint

Table 4 provides further analysis of the relationship and relative effect of comorbid conditions and SMM over time. The prevalence of medical comorbid conditions increased from 4.7% to 10.0%, whereas the population-attributable risk for SMM increased from 10.4% to 14.2% and that for nontransfusion SMM more than doubled from 12.1% to 26.8%. The population-attributable risk for obstetric comorbid conditions, maternal age, and BMI did not substantially change between 1997 and 2014.

Table 4. Comorbid Condition Prevalence and Estimated Contributions to SMM and Nontransfusion SMM, by Year of Birth*

Discussion

The maternal mortality rate in the United States is higher than that in other high-resource countries, and the rate of SMM has also risen substantially. This investigation highlights the importance of medical and obstetric comorbid conditions for both outcomes. In particular, medical comorbid conditions now account for half of maternal deaths and are associated with an increasing fraction of SMM.

These analyses of SMM provide several high-level lessons. The 160% increase in SMM in California over the past 20 years is similar to that reported in a nationwide sample and provides strong confirmatory evidence that the increase in maternal mortality represents a real trend and not an artifact in data collection (17). Explorations of comorbid conditions show the emergence of cardiovascular disease as an important contributor to both maternal death and illness. Maternal deaths are relatively rare and provide informative trends only in very large populations. Because SMM is 100 times more frequent than maternal death and is collected using administrative data, trends in SMM can be observed in much shorter time frames and with smaller units than is possible for maternal mortality. Therefore, analysis of SMM cases assumes a greater importance by defining areas of focus for efforts toward quality and safety improvement for hospitals, health systems, and states.

Both the United States and the United Kingdom have noted an increase in obstetric hemorrhage (20), and blood transfusion alone now accounts for more than half of SMM. Blood transfusion of 1 to 2 units without other complications may not be as severe a morbidity as actual organ injury, so we propose that the submeasure of nontransfusion SMM provides important additional information and should be broadly used.

Patient characteristics and comorbid conditions are often combined as a weighted index to estimate risk for death or critical illness. Although the Charlson and Elixhauser comorbidity indices are the most used tools outside pregnancy, the maternal comorbidity index is the only tool that has been derived and validated using pregnant and postpartum women with risk factors that are germane to pregnancy (21). An external validation has been done in a single hospital sample (22). The maternal comorbidity index was recently updated to include newly available variables (18). In our study, it performed adequately to identify SMM, but with several notable exceptions. Preexisting hypertension, chronic renal disease, and cardiovascular disease seem to be underweighted (that is, the weight is much lower than the RR in this analysis), whereas advanced maternal age and elevated prepregnancy BMI seem to be overweighted. In the analysis of nontransfusion SMM, RRs were much higher than maternal comorbidity index weights for most medical comorbid conditions. Further investigation into the relative weights and potential roles of geography, socioeconomic status, and race is recommended. Measures of social determinants are not currently included in this data set and should be considered in future research.

The U.K. program for mortality and morbidity surveillance (Mothers and Babies: Reducing Risk through Audits and Confidential Enquiries across the UK, or MBRRACE-UK, the successor to the long-standing Confidential Enquiries into Maternal Deaths) provides detailed information on causes of maternal death that allows for comparisons (23). Underlying medical causes now account for 56% of U.K. maternal deaths, similar to the U.S. rate of 48%. However, the actual U.K. rate of medical causes of maternal death is lower, at 5.52 deaths per 100 000 deliveries, than the U.S. rate of 8.1 deaths per 100 000 deliveries. Cardiac conditions account for nearly half of medical causes of death in the United Kingdom, also similar to the rate in California and the United States (24, 25). Unfortunately, comparable U.K. data for the contribution of comorbid conditions to SMM are not available.

Medical comorbid conditions increased considerably (111%) during the study period. Obstetric and demographic comorbid conditions also increased but at a lower rate, between 30% and 40%. The 40% increase in repeated cesarean deliveries observed in this study is particularly noteworthy. The CDC has noted that women with a prior cesarean delivery, no matter how they give birth in their next pregnancy, have much higher rates of major complications (26). Although its RR in this study was relatively modest (1.6), previous cesarean birth was the single most common comorbid condition and had the second greatest increase over the past 15 years.

Limitations of the study include the reliance on administrative data for the assessment of both comorbid conditions and SMM. Rare maternal conditions can be substantially underreported in hospital discharge data. However, combining data from both birth certificates and hospital discharge files can produce a statistically significant improvement in accuracy (19). Furthermore, the period was chosen so as not to bridge major administrative changes in the data set. Our SMM analysis was limited to California, a highly diverse state with 12% of U.S. births. Furthermore, the California data set includes linkage between discharge diagnosis files and birth certificate files that contain meaningful data on demographics and social determinants that are not available in any other large data set. Comparison of state perinatal demographics is available (27), but generalizability to other settings is unstudied. Although we controlled for confounding among comorbid conditions at the patient level, we did not examine for clustering of comorbid conditions at the provider or hospital level. Further research for such clustering is warranted.

This study has important implications for practice. The importance of underlying medical conditions for both maternal mortality and SMM should be recognized. Many of the comorbid conditions can be present early in pregnancy, providing ample opportunities for comanagement with appropriate medical specialists. Women with high maternal comorbidity index scores may benefit from consultation with maternal–fetal medicine specialists for a management plan, including a discussion of the most appropriate location for delivery. Those at highest risk for SMM may be better served in facilities with capabilities and personnel suited to their needs. In addition, it is important to recognize that those at highest risk for complications may be concentrated in hospitals with level III and IV maternal care, making it ill-advised to use SMM for comparing facilities without adjusting for case mix.

National efforts to reduce maternal morbidity and mortality are led by state perinatal quality collaboratives supported by the CDC (28) and the Alliance for Innovation in Maternal Health (29). Severe maternal morbidity is proving to be an important measure for large-scale quality improvement efforts. Successes have been documented in projects to reduce maternal illness from hemorrhage (30) and preeclampsia. A focus of these initiatives has been to identify comorbid conditions, such as multiple gestations, prior cesarean birth, and underlying medical comorbid conditions, and plan and treat accordingly.

Further utilization and refinement of SMM measures and the related comorbidity score can inform risk-appropriate maternal care. An expanded obstetric comorbidity index was recently developed and validated using both California and U.S. data sets; it shows improved accuracy and precision (31). This should further the ability to compare rates of SMM and nontransfusion SMM across hospitals and other patient populations that vary in comorbidity case mix. Measurement and examination of SMM and associated comorbid conditions can also assist in national efforts to establish levels of maternal care, which focus on ensuring that all maternity facilities have the resources available to care for unforeseen emergencies and the ability to stabilize and transfer the highest-risk mothers to facilities with necessary capabilities and personnel (32).