Objective
Using a population-based cohort, we examined hospital-level variation overall and by teaching status in 2 maternal outcomes, postpartum infections, and thrombosis.
Study Design
Linked birth certificate and hospital admission records for mother and infant were collected on all deliveries in Pennsylvania and California from 2004 through 2005. A risk adjustment model was created using maternal and fetal comorbidities identified by International Classification of Diseases -9 codes. Hospitals were classified as teaching (TH) or nonteaching hospitals (NTH) based on the presence of obstetrics and gynecology residents. Rates of infections and thrombosis were evaluated overall and by hospital teaching status.
Results
A total of 939,871 patients were evaluated from 402 hospitals (369 NTH and 33 TH). The unadjusted infection and venous thromboembolic events (VTE) rates were higher in TH vs NTH (infection: 2.04% vs 1.07%, P < .001; VTE: 1.04% vs 0.08%, P < .001). There was variation in the rates of these complications across hospitals, with the adjusted observed/expected ratio rates for infection and thrombosis for each hospital, ranging from 0–5.2 and 0–8.6, respectively.
Conclusion
There is substantial variation in infection and thrombosis rates among hospitals both overall and by teaching status, suggesting that these 2 outcomes may be useful measures of inpatient obstetric quality.
Despite maternity care being one of the most common reasons for inpatient hospital care, there is a scarcity of metrics to assess obstetric quality. The magnitude of the population affected by obstetric care makes it imperative to develop reliable and validated measures of obstetric quality to improve maternity care. Ideally, strong obstetric quality measures are easily measured, demonstrate variation across hospitals, and are modifiable through evidence-based interventions or processes.
Postdelivery infections and thrombosis are 2 such potential measures. Postdelivery infections including febrile morbidity, endometritis, and wound infections occur in up to 30% of women after cesarean delivery in the absence of prophylactic antibiotics. This rate is approximately 3% in women following a vaginal delivery. Postdelivery infections are largely preventable with the administration of appropriate prophylactic antibiotics, proper surgical site preparatory procedure, and surgical technique. However, the utilization and timing of these various prevention strategies is variable.
Another potentially preventable postdelivery complication is venous thromboembolic events (VTEs). VTEs are the leading cause of maternal mortality in the United States. They are estimated to occur in approximately 0.025-0.10% of pregnancies; approximately 75-80% of cases of pregnancy-associated venous thromboembolism are caused by deep venous thrombosis, and 20-25% of cases are caused by pulmonary embolus.
Pregnancy is an independent risk factor for thromboembolic disease, and cesarean delivery places women at even greater risk. Both mechanical and pharmacological prophylaxis has been demonstrated to prevent thrombosis formation, particularly in the postoperative patient. Expert opinion suggests that moderate- and high-risk women should receive prophylaxis. However, there is a large amount of variability in the use of either medication based or non–medication-based prophylaxis for deep venous thrombosis prevention in pregnancy.
As a result, both infections and thrombosis are plausible measures of obstetric quality. Although individual patient level risk factors are associated with postdelivery infection and VTE, appropriate prophylaxis has been known to significantly reduce this risk. This fact further improves the validity of these metrics as measures of quality because they are not solely influenced by patient level factors, thereby suggesting that prevention of postdelivery infection and thromboembolic disease require consistent, evidence-based, systematic processes of care.
In an effort to evaluate postdelivery infections and thromboses as potential metrics of obstetric quality, we first sought to examine the variation of these 2 outcomes across hospitals. Additionally, we sought to evaluate variation by hospital level characteristics. One hospital-level factor that plausibly may affect these processes of care and related outcomes is teaching status. Although previous work has demonstrated a lower failure to rescue rate (mortality after a major complication) in teaching hospitals, other studies have demonstrated higher complication rates in teaching hospitals. Therefore, we also sought to evaluate variation stratified by hospital teaching status as one potential explanatory hospital level characteristic.
Materials and Methods
Data source
We collected birth certificates from all deliveries occurring in California and Pennsylvania between Jan. 1, 2004, and June 30, 2005, and linked to death certificates by each state’s Department of Health using name and date of birth. These linked records were then matched to maternal and newborn hospital discharge records using previous methods. California data were linked by the state Department of Health using established algorithms, and Pennsylvania data were linked in a similar fashion internally at our center. More than 98% of all birth certificates in the 2 states were matched to maternal and newborn hospital records using these methods. The institutional review boards of The Children’s Hospital of Philadelphia and the departments of health in California and Pennsylvania approved this study.
Birth certificates containing a gestational age less than 23 weeks or greater than 44 weeks, a birthweight less than 400 g or greater than 8000 g were excluded. Furthermore, a birthweight that was more than 5 SD from the mean birthweight for the recorded gestational age in the cohort was excluded because of the concern that one or both may be incorrectly recorded. Hospitals with fewer than 50 deliveries were combined into 2 small hospital groups, one for California and one for Pennsylvania, because the small number of deliveries at each individual hospital resulted in less stable assessments of the outcomes at each individual hospital.
Hospitals were considered teaching if they specifically had an obstetrics and gynecology residency program. The number of annual residents was obtained through the Accreditation Council for Graduate Medical Education web site. Teaching status was further evaluated as small and large teaching hospitals (THs) based on the number of obstetrics and gynecology residents per year trained in the residency program. Programs with fewer than 6 residents per year were considered small teaching hospitals (STHs) and 6 or more residents per year were considered large teaching hospitals (LTHs).
Study outcomes
To evaluate the use of postdelivery infection and VTEs as possible metrics of obstetric quality, we first evaluated the overall variability of these outcomes across hospitals. If variability is not observed, these metrics would not make plausible quality metrics. Subsequently we evaluated variability stratified by the hospital-level characteristic of teaching status. Wound infection ( International Classification of Diseases , ninth revision, Clinical Modification [ICD-9CM] codes 674.1x, 674.2x, 674.3x, 64662, 67002, 67202) and thrombosis (ICD-9CM codes 671.2x, 671.3x, 671.4x, 671.5x, 673.22) were identified using International Classification of Diseases , ninth revision (ICD-9) codes.
Our risk adjustment model included covariate variables based on their association with 1 or more study outcomes, the likelihood that a patient with these covariates would develop an infection or thrombosis, biological plausibility, and previous work. These variables included maternal comorbid conditions and neonatal congenital anomalies grouped by affected organ system as well as sociodemographic factors. These maternal and neonatal comorbidities and other characteristics were also identified by ICD-9CM codes and birth certificate data and are shown in Table 1 .
| Comorbidities | Codes |
|---|---|
| Congenital anomalies | |
| Gastrointestinal | 560.2, 750.3, 750.4, 750.5, 750.7, 750.8, 750.9, 751.0, 751.1, 751.2, 751.3, 751.4, 751.5, 751.60, 751.61, 751.69, 751.7, 751.8, 751.9, 756.70, 756.79, 777.1, and birth certificate |
| Genitourinary | 753.0, 753.10, 753.12, 753.14, 753.15, 753.19, 753.2x, 753.3, 753.4, 753.6, 753.7, 753.8, 753.9, 756.71, and birth certificate |
| Central nervous system | 741.0x, 741.9x, 742.0, 742.1, 742.2, 742.3, 742.4, 742.59, 742.8, 742.9, and birth certificate |
| Pulmonary | 519.4, 553.3, 748.3, 748.4, 748.6x, 748.8, 748.9, 750.6, 756.6, and birth certificate |
| Cardio | 424.0, 424.1, 425.1, 425.3, 745.10, 745.11, 745.12, 745.19, 745.2, 745.3, 745.0, 745.60, 745.61, 745.69, 746.01, 746.09, 746.1, 746.2, 746.3, 746.4, 746.5, 746.6, 746.7, 746.81, 746.82, 746.83, 746.84, 746.85, 746.87, 746.89, 746.9, 747.1x, 747.21, 747.22, 747.29, 747.4x, and birth certificate |
| Skeletal | 756.50, 756.51, 756.55, 756.56, 756.59, and birth certificate |
| Chromosomes | 758.3, 758.5, 758.89, 758.9, 759.4, 759.7, 759.89, 759.9, and birth certificate |
| Maternal comorbidities | |
| Disorders of placentation | 641.0x, 641.1x, and 641.2x |
| Chronic hypertension | 642.0x, 642.1x, and 642.2x |
| Cord abnormality | 663.0x, 663.1x, and 663.5x |
| Preterm labor | 644.0x and 644.2x |
| PROM | 658.1x and 658.2x |
| Chorioamnionitis | 658.4x, 659.2x, and 659.3x |
| GU tract infection | 646.6x |
| PIH | 642.4x, 642.5x, and 642.7x |
| Oligohydramnios | 658.0x |
| Amniocentesis | 75.1 and birth certificate |
| Cord prolapse | 663.0x, 762.4, and birth certificate |
| Blood transfusion | 99.0, 99.00, 99.02, 99.03, and 99.04 |
| Lupus | 710.0 |
| Other collagen vascular | 710.1, 710.2, 710.3, 710.4, 710.5, 710.8, and 710.9 |
| Rheumatoid arthritis | 714.x |
| Cardiac | 648.5x and 648.6x |
| Irritable bowel | 564.1 |
| Stillbirth | v27.1 |
| Preterm birth | Birth certificate |
| Socioeconomic status | |
| Birthweight category | 400-1000, 1000-1500, 1500-2000, 2000-2500, 2500-3000, 3000-3500, 3500-4000, 4000-4500 (referent), and 4500-8000 |
| Insurance | FFS (referent), HMO, federal, other, and missing |
| Prenatal care start | 0-3 months (referent), 4-6 months, 7-9 months, and missing |
| Race/ethnicity | White (referent), black, Hispanic, Asian, and other |
| Education | No high school diploma, high school graduate, college graduate, and missing |
| Maternal age, y | Younger than 18, 18-35 (referent), and older than 35 |
Data analysis
Unadjusted rates for both infection and thrombosis were calculated by hospital. Subsequently the variation in observed to expected events for each outcome were evaluated by hospital. The expected number of infections and thrombotic events were calculated in the following manner. Logistic regression was performed using all of the explanatory variables (comorbidities, complications, birthweight, year, etc). The model’s results were used to calculate the probability a given patient would have an infection or thrombosis, known as the expected value. The expected values for each patient in a given hospital were summed to derive the expected rate of infection or thrombosis at that hospital. We then compared the expected rate of each outcome with the observed rate of the outcome at each hospital by using the following formula:
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