Hospital Variations in Unexpected Complications Among Term Newborns

Discussion

We found a 14-fold variation in Florida hospital rates of total unexpected newborn complications in 2004 to 2013. Based on the high proportion of variation explained by hospital factors, there are potential opportunities for quality improvement (QI). Before this study, the CMQCC reported large variation in complication rates among 220 California hospitals (95th percentiles for total complication rates ranged from 10 to 80 per 1000). The measure had high intrahospital consistency over three 6-month periods (mean reliability: 0.92) and tracked closely to hospitals in the US East Coast in a comparison trial by gestational age. The CMQCC report did not focus on exploring risk factors and reasons for hospital variation in complication rates.^9,15 We quantified the contribution of individual and hospital factors to hospital variation and discuss implications for improvement.

First, although severe and moderate complications were classified based on the level of hospital morbidity, the 2 measures that made up total unexpected complications do not appear to reflect a continuum of hospital quality. A hospital’s rate for 1 type of complication did not predict its rate for the other. Among hospitals with high rates of total complications, some had high severe complication rates and others had high moderate complication rates; few had both. Furthermore, significant hospital factors differed by type of complication, suggesting that high hospital rates of severe or moderate complications imply different QI issues.

Second, hospital differences in unexpected complications seem to be driven more by identified hospital factors than individual factors. Substantial reductions in observed hospital variation in complication rates were achieved only by adjusting for hospital geographic location, level of care or birth volume, and percentage of Medicaid births. Specific diagnosis categories explained the hospital factors that contributed to variation in severe and moderate complications. For instance, differences by hospital geographic location were driven predominantly by infection rates (higher in southern Florida hospitals), and differences by level of care were influenced largely by neonatal transfer rates (higher in level I hospitals). Differences by percentage of Medicaid births were influenced by hospital transfer and infection rates (higher in high-Medicaid hospitals and possibly reflecting hospital level of care). These data imply that hospital differences in complication rates may be related to differences in quality of care and coding practice. In a previous investigation of Florida late preterm births, our group identified differences in coding accuracy for labor and delivery characteristics (eg, induction) between hospitals with high versus low rates of primary late preterm cesarean delivery.¹¹ It is possible that hospital differences in coding of newborn complications contribute to some of the variation in complication rates. However, based on the large variation, it is unlikely that differences in coding practice alone account for all the differences. Only published US studies assessing coding accuracy of hospital discharge or birth certificate for mortality and congenital anomalies, and not other newborn complications, were identified.¹⁶ The first step in QI efforts by individual hospitals or systems should be directed at validating the clinical findings.

Third, hospital performance comparisons that used the unexpected complications measure may be most appropriately done by level of care. We reported that delivering in level I hospitals was a significant factor for severe complications, whereas delivering in level III hospitals increased the odds of moderate complications. Although neonatal transfers explained the high rates of severe complications in level I hospitals, transfer rates varied widely by hospital at that level. This finding suggests that transferring neonates to another hospital is not just a capacity issue with basic-level hospitals. Level III hospitals, on the other hand, had high rates and high variation in moderate respiratory problems and unspecified long neonatal LOS, suggesting that high complication rates in this group are not simply an issue of referrals to higher-level hospitals. Functional capabilities may be fundamentally different for hospitals with basic care level versus high-level NICU hospitals,¹⁷ but there seem to be quality issues to be addressed at each level.

Finally, additional opportunities for prevention may involve targeting potentially modifiable factors at the individual level, related to early-term gestation and medical indications for delivery, lack of prenatal care, nulliparity, obesity, and smoking. These factors are consistent with previous studies reporting risk factors for adverse neonatal outcomes such as respiratory difficulties, NICU admissions, preterm birth, and low birth weight.^6,18–23 Of note, our findings for early-term NMI inductions, a moderate factor for both severe and moderate complications, differ from those of a recent Florida study of singleton term and postterm deliveries. Using data from 2005 to 2009, Salemi et al²² found that NMI inductions at 37 to 38 weeks did not increase the odds of neonatal respiratory morbidity or NICU admission relative to deliveries at ≥39 weeks. Two methodological differences might explain the different findings. First, the Salemi et al study population excluded mothers with chronic medical indications for early delivery, such as diabetes. Medical indications for early delivery included only acute conditions detected at the time of labor and delivery, such as vasa previa.²² This population differed from our study population, which included mothers with both chronic and acute medical indications. Second, inductions at 37 to 38 weeks with medical indications identified at delivery were retrospectively excluded from the NMI early-term induction group but not from the ≥39 weeks reference group. For example, as reported in that study, deliveries with vasa previa were excluded from NMI deliveries at 37 to 38 weeks but not from the ≥39 weeks reference group.²² In contrast, the ≥39 weeks reference group in our study excluded medical indications. The inclusion of medical indications in the reference group may have contributed to the null estimate of association in the Salemi et al study.

Our study was limited by the inability to assess the level of care of receiving hospitals for transfers. We received anecdotal reports from regional centers suggesting that almost all neonatal transfers during the first 4 days of life in Florida are to a higher-level hospital. It is unlikely that transfers in the study included a large number of back transfers among level III hospitals because 95% of transfers occurred within 4 days of birth, and transfers from level III hospitals were extremely rare. Another potential limitation is the use of birth certificate and maternal hospital discharge records to identify unexpected complications. An intrinsic problem with these data is the underreporting or poor accuracy of some care processes, such as use of oxytocin and trial of labor.¹¹ The extent to which differences in these care processes contribute to hospital variation in neonatal complications is not well known.²⁴ Nonetheless, this currently may be the most appropriate available data for this type of investigation.²⁵ An additional limitation is the inability to adjust for mothers with >1 delivery over the study period. This limitation is not likely to have affected our estimates of association because complication rates were higher in first-time mothers.