Abstract
Introduction
Obstetric hemorrhage is one of the leading causes of maternal death and also one of the most preventable. In 2017, a New York statewide initiative led by the New York State Perinatal Quality Collaborative asked birthing hospitals to implement an ACOG District II Safe Motherhood Initiative evidence‐based bundle on recognition and management of hemorrhage, and to assist and offer extensive education, assistance, and feedback. This report describes the process and results.
Methods
The bundle was available to all birthing hospitals. Hospitals were asked to implement 21 measures, with a goal of each measure being implemented by at least 85% of hospitals. Webinars and teaching sessions were attended by participating hospital teams to foster collaborative learning, share best practices, provide technical assistance and education, and serve as a forum for discussion of successes and barriers. Hospitals used standardized data collection forms to report measure implementation, aggregate patient data, and for major hemorrhages (requiring massive transfusion, hysterectomy, transfer to a higher level of care, or death), deidentified patient‐level data. Data were analyzed using chi‐square, repeated measures ANOVA, linear regression, and Cochrane's Q tests.
Results
Eighty‐six hospitals initially engaged (78 ultimately completed), with teams attending 35 webinars and 3 learning sessions. At the initiative's start, 6 of the 21 measures already were in place at 85% of hospitals; by the initiative's end, this increased to 19 of 21 with significant increases (p < 0.05) for all but two. The percent of patients defined as having obstetric hemorrhages increased during the initiative as use of quantitative blood loss (QBL) increased from 9.8% to 14.5% (p < 0.001); among patients with major hemorrhages, exclusive QBL use increased blood loss volume by 287 mL (p = 0.004). Among patients with major hemorrhages, the need for transfer to higher levels of care decreased during the initiative (p = 0.02), although rates of hysterectomy or use of massive transfusion were unchanged.
Conclusion
A comprehensive statewide initiative encouraging hospitals to adopt an evidence‐based bundle on obstetric hemorrhage was successful in that 19 of 21 measures were implemented by ≥85% of hospitals. Focused statewide initiatives can improve hospitals’ ability to provide evidence‐based obstetrical care.
Keywords: bundle, hemorrhage, implementation, initiative, outcomes, quality improvement
1. INTRODUCTION
Maternal mortality has been increasing in the United States where it is more common than in most other Westernized countries [1]. There is debate as to whether this is a reflection of medical care, racism, socioeconomic inequality, different means of ascertainment, or a combination thereof [2], but a consistent finding is that obstetric hemorrhage is one of the leading causes of maternal death [3] and also one of the most preventable [4]. Evidence‐based bundles on hemorrhage prevention and management have been developed to standardize “the 4 Rs”—Readiness, Recognition (and Prevention), Response, and Reporting—and to familiarize obstetrical units with current standard of care requirements. California has successfully used such bundles to lower overall hemorrhage‐related obstetrical morbidity, as well as reduce racial disparities in hemorrhage outcomes [5, 6]. Smaller studies within hospitals or hospital systems have generally—although not always—reported favorable results [7, 8, 9].
New York State (NYS) birthing facilities worked on instituting a bundle on obstetric hemorrhage, initially through the American College of Obstetricians and Gynecologists’ (ACOG) Safe Motherhood Initiative (SMI) in 2013 and later through a collaborative effort with the New York State Department of Health (NYSDOH) New York State Perinatal Quality Collaborative (NYSPQC) [10, 11, 12]. Our objective in this report is to describe the process and progress across participating NYS birthing hospitals in adopting elements of the bundle, and the impact on hemorrhage‐related outcomes. The hypothesis was that increasing numbers of hospitals would implement the majority of elements within the hemorrhage bundle, and that hemorrhage‐related maternal morbidity and mortality then would decrease.
2. MATERIALS AND METHODS
The NYSPQC convened the NYS Obstetric Hemorrhage Project, beginning with an in‐person learning session in November 2017, and data reporting from March 2018 to March 2021. The NYSPQC led this project along with ACOG District II, the Healthcare Association of NYS, and the Greater New York Hospital Association, with support from the National Institute for Children's Health Quality (NICHQ). The project aligned with the Alliance for Innovation on Maternal Health (AIM) program, led by ACOG National. The project was reviewed by the NYSDOH Institutional Review Board and approved as exempt.
The project consisted of the following:
Implemented a learning collaborative among hospital teams to share strategies, best practices, and barriers to bundle implementation;
Hospital teams implemented evidence‐based strategies for the assessment and management of obstetric hemorrhage;
Clinical experts provided clinical and quality improvement education and technical assistance;
Monthly data collection, analysis, and feedback to hospital teams; and
Monthly coaching call webinars for progress review, input, questions, discussion of obstacles encountered by hospitals, sharing of experiences, data reporting, and educational presentations.
Benefits to participating hospitals were projected to be:
Support from national and state faculty, including trained quality improvement (QI) and obstetric experts;
Coaching and technical assistance, including in‐person and virtual learning sessions, regular coaching call webinars, support to implement and test improvements, data collection, data analysis and real‐time feedback on data, including monthly run‐charts for hospital teams to track improvements;
Access to the project website, a virtual learning community sharing resources and engaging participants in discussions;
Opportunities to connect with other hospital teams to share strategies, lessons learned, overcome barriers, and expedite implementation of project goals; and
Opportunities to build QI knowledge and capacity applicable beyond the project.
As the basis for recommendations, the project utilized hemorrhage bundles formulated by ACOG District II's SMI [13] (most recent revision), the California Maternal Quality Care Collaborative (CMQCC) [14], and AIM [15], focusing on the “4 Rs” (Figure 1). All birthing hospitals in NYS were contacted and encouraged to participate in the project. Each hospital was asked to form a core working multidisciplinary group that included departmental leadership, OBGYN “champions,” nursing representatives from labor and delivery and postpartum, and QI staff. At least two representatives were asked to commit to attending monthly learning and coaching call in‐person meetings or webinars. A preliminary survey assessed the degree to which each hospital already had implemented key bundle concepts.
FIGURE 1.
Key driver diagram.
During the project, NYSDOH conducted monthly educational meetings and webinars as described above. All participating hospital teams were encouraged to identify their system gaps and undertake QI activities to address them, particularly in Plan‐Do‐Study‐Act (PDSA) format [16], and then invited to present their institutional progress (or obstacles thereto) during monthly webinars. The sessions supported teams in their onsite work to implement and test improvements and continued through the duration of the Collaborative. During these webinars, data and progress to date were reviewed and time was provided for teams to share experiences and lessons learned.
Learning sessions were the major integrative events of the project where multidisciplinary teams from each facility came together virtually or in‐person for focused content and quality improvement learning. Attendees had the opportunity to learn from faculty and colleagues, receive individual coaching from faculty, gain new knowledge on the subject matter and process improvement, share experiences and collaborate on improvement plans, and develop strategies to overcome improvement barriers.
An important component of the project was tracking and feedback of hemorrhage‐related data to assess and improve the quality of the hospital‐based practice systems in place for the management of obstetric hemorrhage. For these purposes, three audit tools were developed for the collection of hemorrhage‐related data (see Appendix in the Supporting Information): aggregate data collection, deidentified data on patients with major obstetric hemorrhages (defined below), and as of the first quarter of 2019, process and structure measure data (hereby referred to as structure measures). Inclusion criteria varied by data collection tool. For aggregate data, it consisted of all pregnant patients delivering liveborns or stillbirths at ≥20 weeks’ gestation. For aggregate data on documented OB risk assessment, hospitals with fewer than 20 deliveries per month were to report all such admissions. For hospitals with ≥20 deliveries per month, at least 20 were reported, by either random or systematic sampling (e.g., every N th patient). For patient‐specific data, inclusion criteria included pregnant patients delivering at ≥20 weeks’ gestation and one or more of the following:
Massive transfusion (≥4 units of red blood cells);
Hemorrhage with admission to a higher level of care (intensive care unit [ICU] or transfer to a higher level hospital);
Hemorrhage with hysterectomy; and
Death from hemorrhage.
Patient‐specific data also included hemorrhage etiology.
Hospitals submitted data from March 2018 to March 2021. Each center was instructed to collect data upon discharge of those giving birth monthly and to report on hospital policies and procedures quarterly. When the quarterly structure measure data collection tool was added, hospitals submitted quarterly data from Quarter 1 of 2019 to Quarter 1 of 2021. All data were submitted electronically to the NYSDOH on a secure website.
Hospital‐specific structure measure reports were sent to each hospital on a quarterly basis to demonstrate their progress on measures. Reports included aggregated data from other participating hospitals, allowing comparisons to identify areas for possible improvement and to drive change. Project‐wide data for all tools were presented on monthly coaching call webinars to share progress on measures. The goal of the project was that, for each structure measure, at least 85% of hospitals have systems (policies, procedures, protocols, etc.) in place to operationalize each measure.
2.1. Methods of analysis and reporting
Analysis was performed using SPSS v24. Analysis was performed on the final quarter of structure data to determine the percentage of measures implemented by hospitals at the close of the project (Figure 2). Run charts were developed using aggregate and patient‐level data for the monthly project measures. The run charts were made available to hospitals through the NYSDOH website, and updated nightly so that teams were able to see their data in almost real time. Representative examples used during the project are shown in Figures 3, 4, 5, 6. Structure measure reports were sent to hospital teams quarterly to share their progress. The reports provided a comparison to other participants and were used by sites to identify areas for improvement and to drive change. Project‐wide data for all tools were shared on monthly coaching call webinars to present progress on measures. Time was divided into four quarters per year for purposes of statistical analysis (note: because the project began in March of 2018, that first “quarter” consisted of only 1 month). Analysis of patient data used chi‐square and linear regression (counts converted to percentages by quarter for regression), and for aggregate data used repeated‐measures ANOVA and linear regression (13 quarters each). Cochrane‐Q testing was used for structure data, which consisted of nine quarters because this section was added after the start of the project.
FIGURE 2.
Percent of Structure Measures in Place in Final Quarter.
FIGURE 3.
Hemorrhage risk assessment.
FIGURE 4.
Methods of determining blood loss.
FIGURE 5.
Hemorrhage after vaginal delivery.
FIGURE 6.
Hemorrhage after cesarean delivery.
3. RESULTS
Over the course of the project, the NYSPQC engaged with 86 of 120 NYS birthing hospitals (71.7%). Due to lack of resources/staff, competing priorities, and other barriers, not all hospitals were able to submit data for the duration of the project. At the end of the project, 78 facilities submitted data and are included in this analysis. Hospitals included 17 Regional Perinatal Centers (RPCs), 20 Level III hospitals, 18 Level II hospitals, and 23 Level I hospitals. Over the duration of the project, there were 35 coaching call webinars and 3 in‐person learning sessions. Seventy hospitals submitted complete data; monthly data were incomplete in 8, with a mean of 4 missing months out of the 37 total.
Data on 21 structure measures were submitted beginning in January 2019. In the first quarter of 2019, the rates of structure measures in place varied from a low of 39.7% of hospitals (Hemorrhage Stage‐Based Checklist) to a high of 97.4% (Emergency Blood Product Release Protocol). The goal for each structure measure was that ≥85% hospitals would have adopted each given measure by the final quarter; that goal already had been met in the first quarter for 6 of the 21 measures. By the final quarter, the goal had been met for 19 of the 21 measures (Table 1). The only two measures not meeting goal by the final quarter were policies for support for patients and policies for support for families during a hemorrhage, at 83.1% and 76.6%, respectively. For 19 of 21 measures, the improvement over the duration of the project was statistically significant at p < 0.05. The two for which the improvements were not statistically significant were Unit Hemorrhage Policy (p = 0.15) and Emergency Blood Release Protocol (p = 0.25); both started with rates of 96.2% and 97.4%, respectively, thus already were nearly 100%. Percent improvement from baseline over the duration of the project ranged from 3% (Unit Hemorrhage Policy) to 143% (Hemorrhage Stage‐Based Checklist).
TABLE 1.
Percent of hospitals with structure measures in place, by quarter.
| Quarter | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Structure measure | 2019 Q1 | 2019 Q2 | 2019 Q3 | 2019 Q4 | 2020 Q1 | 2020 Q2 | 2020 Q3 | 2020 Q4 | 2021 Q1 | Percent change from first quarter | Cochrane's Q p‐value |
| Unit Hemorrhage Policy | 96.1% | 98.7% | 97.4% | 98.7% | 98.7% | 98.7% | 98.7% | 98.7% | 98.7% | 2.7% | 0.151 |
| Hemorrhage Risk Assessment | 71.4% | 72.7% | 72.7% | 80.5% | 89.6% | 90.9% | 93.5% | 97.4% | 100% | 40.1% | 0.000 |
| Exclusive Quantitative Blood Loss | 40.3% | 54.5% | 64.9% | 70.1% | 76.6% | 81.8% | 81.8% | 83.1% | 89.6% | 122% | 0.000 |
| Massive Transfusion Policy | 94.8% | 96.1% | 96.1% | 97.4% | 97.4% | 98.7% | 98.7% | 98.7% | 98.7% | 4.1% | 0.048 |
| Emergency Blood Release Policy | 97.4% | 98.7% | 98.7% | 98.7% | 98.7% | 100% | 100% | 100% | 100% | 2.7% | 0.246 |
| Policy for Refusing Blood Products | 70.1% | 74.0% | 75.3% | 81.8% | 83.1% | 84.4% | 87.0% | 89.6% | 89.6% | 27.8% | 0.000 |
| Hemorrhage Cart | 94.8% | 97.4% | 97.4% | 100% | 100% | 100% | 100% | 100% | 100% | 5.5% | 0.005 |
| STAT Medications | 94.8% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 100% | 5.5% | 0.000 |
| Hemorrhage Response Team | 75.3% | 79.2% | 79.2% | 84.4% | 87.0% | 90.9% | 92.2% | 94.8% | 94.8% | 25.9% | 0.000 |
| Hemorrhage Drills | 77.9% | 81.8% | 81.8% | 85.7% | 87.0% | 90.9% | 89.6% | 89.6% | 89.6% | 15.0% | 0.000 |
| Hemorrhage Checklists | 70.1% | 80.5% | 83.1% | 89.6% | 93.5% | 93.5% | 93.5% | 93.5% | 97.4% | 38.9% | 0.000 |
| Policy for Support of Patients | 51.9% | 58.4% | 66.2% | 70.1% | 72.7% | 74.0% | 77.9% | 77.9% | 83.1% | 60.1% | 0.000 |
| Policy for Support of Family | 42.9% | 49.4% | 57.1% | 61.0% | 66.2% | 67.5% | 70.1% | 71.4% | 76.6% | 78.6% | 0.000 |
| Policy for Support of Staff | 54.5% | 61.0% | 66.2% | 71.4% | 76.6% | 79.2% | 81.8% | 84.4% | 88.3% | 62.0% | 0.000 |
| Post‐Hemorrhage Debriefs | 79.2% | 83.1% | 87.0% | 88.3% | 92.2% | 92.2% | 90.9% | 92.2% | 93.5% | 18.1% | 0.000 |
| Hemorrhage Case Reviews | 85.7% | 87.0% | 88.3% | 90.9% | 94.8% | 96.1% | 93.5% | 94.8% | 94.8% | 10.6% | 0.000 |
| Hemorrhage Stage Checklist | 39.0% | 51.9% | 67.5% | 83.1% | 87.0% | 92.2% | 92.2% | 92.2% | 94.8% | 143% | 0.000 |
| Instrument Checklist | 46.8% | 58.4% | 71.4% | 88.3% | 90.9% | 92.2% | 93.5% | 93.5% | 94.8% | 102% | 0.000 |
| Hemorrhage Risk Assessment Tables | 75.3% | 88.3% | 90.9% | 96.1% | 97.4% | 97.4% | 97.4% | 96.1% | 97.4% | 29.3% | 0.000 |
| Massive Transfusion Protocol | 79.2% | 87.0% | 94.8% | 97.4% | 97.4% | 98.7% | 98.7% | 98.7% | 98.7% | 24.6% | 0.000 |
| Post‐Hemorrhage Debrief Form | 44.2% | 61.0% | 74.0% | 85.7% | 87.0% | 87.0% | 90.9% | 93.5% | 94.8% | 114% | 0.000 |
Figure 2 shows the breakdown of the percentage of hospitals with structure measures in place in the project's final quarter. One hundred percent of hospitals had four measures in place (Risk Assessment, Emergency Blood Release, Hemorrhage Cart, and STAT Medications), 95%–99% of hospitals had an additional five measures in place (i.e., 9 total measures in place), 90%–94% of hospitals had an additional six measures in place (i.e., 15 total), and 85%–89% of hospitals had an additional four measures in place, and two measures did not meet the goal of ≥85%, with 83% and 76% of hospitals having the measure in place.
Although hemorrhage drills were one of the structure measures and by the project's close 89.6% of hospitals reported that they had adopted that structure measure, only 78.2% of hospitals reported on aggregate data that at least one drill was completed in the last 12 months of the project.
From the aggregate data, hemorrhage risk assessment on admission improved by 25%, from 75.5% in March of 2018 to 94.7% in March of 2021 (Table 2 and Figure 3). Postpartum hemorrhage risk assessment improved by 104%, from 41.3% to 84.4% over the duration of the project, more than doubling although still not quite meeting the goal of ≥85%.
TABLE 2.
Aggregate data by quarter.
| Quarter | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Outcome | 2018 Mar | 2018 Q2 | 2018 Q3 | 2018 Q4 | 2019 Q1 | 2019 Q2 | 2019 Q3 | 2019 Q4 | 2020 Q1 | 2020 Q2 | 2020 Q3 | 2020 Q4 | 2021 Q1 | Percent change | p‐value (repeated measures ANOVA) a |
| Blood loss 500–1499 mL after vaginal delivery | 6.6% | 6.8% | 6.9% | 7.5% | 8.0% | 8.1% | 9.2% | 9.4% | 9.5% | 10.7% | 11.0% | 11.3% | 10.9% | 64.9% | 0.000 |
| Blood loss ≥ 1500 mL after vaginal delivery | 0.5% | 0.6% | 0.6% | 0.6% | 0.7% | 0.7% | 0.7% | 0.8% | 0.8% | 0.8% | 0.9% | 0.9% | 1.0% | 108% | 0.005 |
| Blood loss 1000–1499 mL after cesarean delivery | 12.6% | 13.1% | 13.3% | 13.8% | 13.4% | 14.5% | 14.6% | 13.4% | 13.9% | 13.8% | 14.1% | 15.4% | 15.1% | 20.6% | 0.106 |
| Blood loss ≥ 1500 mL after cesarean delivery | 2.6% | 2.6% | 2.8% | 3.0% | 3.1% | 3.4% | 3.7% | 3.5% | 3.4% | 3.8% | 4.0% | 4.3% | 4.3% | 62.1% | 0.005 |
| Massive transfusion | 0.32% | 0.34% | 0.29% | 0.36% | 0.32% | 0.33% | 0.28% | 0.26% | 0.29% | 0.25% | 0.29% | 0.29% | 0.28% | −11.6% | 0.121 |
| Transfer to higher level of care after hemorrhage | 2.4% | 2.2% | 2.1% | 1.9% | 1.7% | 1.7% | 1.7% | 1.4% | 1.6% | 1.1% | 1.3% | 1.1% | 0.8% | −65.8% | 0.150 |
| Hysterectomy after hemorrhage | 1.4% | 1.4% | 1.4% | 1.7% | 1.5% | 1.1% | 1.1% | 1.2% | 1.3% | 1.3% | 1.1% | 0.9% | 1.0% | −31.0% | 0.130 |
| Death from hemorrhage | 0.00% | 0.06% | 0.03% | 0.03% | 0.00% | 0.00% | 0.06% | 0.05% | 0.02% | 0.05% | 0.00% | 0.00% | 0.00% | 0% | 0.351 |
| Hemorrhage risk assessment on admission | 75.5% | 79.4% | 82.9% | 87.7% | 91.1% | 92.5% | 91.4% | 91.6% | 92.8% | 93.9% | 94.0% | 93.1% | 94.5% | 25.2% | 0.000 |
| Hemorrhage risk assessment postpartum | 41.3% | 48.6% | 51.6% | 55.4% | 62.0% | 60.6% | 64.5% | 66.7% | 74.1% | 75.1% | 80.3% | 79.3% | 82.3% | 99.0% | 0.000 |
Although not all repeated measure ANOVAs were significant, there were positive linear progressions to all outcomes but deaths.
Quantitative blood loss (QBL) was being done by 41.0% of institutions as of the first quarter of data submission, increasing to 89.6% by the final quarter 2 years later (Figure 4). By the final quarter, only one hospital had yet to adopt QBL, either exclusively or mixed with estimated blood loss (EBL). With the switch from estimated to QBL, the percent of patients with any degree of hemorrhage (≥500 mL after vaginal or ≥1000 mL after cesarean delivery) increased from 9.8% to 14.5% (p < 0.001). The percent of patients with blood loss between 500 mL and 1499 mL after vaginal deliveries increased over the study period, from 6.1% in the first month to 9.8% in the final month (p < 0.001). The percent of patients with blood loss ≥1500 mL after vaginal delivery increased by a smaller absolute margin, from 0.48% to 0.98% (p = 0.005; Figure 5). For cesarean deliveries, there was not a significant increase for blood loss for 1000–1499 mL (p = 0.11), but there was an increase for blood loss ≥1500 mL (2.6%–4.5%, p = 0.005; Figure 6). Despite the reported increases, the rates of massive transfusion (≥4 units of red blood cells), peripartum hysterectomy, and transfer to a higher level of care declined, although none significantly (Table 2). There was no change in the number of hemorrhage‐related deaths (12 total deaths over 13 quarters; 6 quarters had no deaths).
3.1. Patient data
In 1839 reported patients with hemorrhages over this time period, the proportion in whom exclusive QBL was used increased from 21.4% to 50.8%, and the use of EBL alone as a method declined from 40.5% to 7.9%. There were significant differences in the proportion of patients assessed with QBL versus EBL over time (p‐value < 0.0001). Mixed methods made up the remainder, with stable rates (Table 3).
TABLE 3.
Patient‐level data by quarter.
| Quarter | |||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Outcome | 2018 Q1 | 2018 Q2 | 2018 Q3 | 2018 Q4 | 2019 Q1 | 2019 Q2 | 2019 Q3 | 2019 Q4 | 2020 Q1 | 2020 Q2 | 2020 Q3 | 2020 Q4 | 2021 Q1 | Percent change | Chi‐square p‐value |
| Massive transfusion | 76.2% | 86.6% | 82.0% | 88.1% | 82.7% | 85.1% | 80.5% | 76.2% | 79.5% | 79.4% | 83.2% | 76.9% | 76.7% | 0.7% | 0.123 |
| Transfer to higher care | 57.1% | 49.7% | 53.4% | 51.8% | 43.3% | 45.2% | 52.4% | 40.1% | 47.7% | 38.2% | 42.6% | 40.1% | 36.4% | −36.3% | 0.019 |
| Hysterectomy | 31.0% | 30.9% | 36.8% | 35.7% | 34.0% | 27.4% | 32.3% | 32.0% | 38.4% | 39.7% | 33.5% | 31.3% | 33.3% | 7.4% | 0.703 |
| Death | 0.0% | 1.3% | 0.8% | 0.6% | 0.0% | 0.0% | 1.8% | 1.4% | 0.7% | 1.5% | 0.0% | 0.0% | 0.0% | NA | 0.417 |
| Post‐hemorrhage debrief | 73.8% | 67.8% | 78.9% | 75.6% | 75.3% | 73.2% | 76.8% | 73.5% | 71.5% | 80.9% | 77.4% | 77.6% | 77.5% | 5.0% | 0.532 |
| Cesarean section | 76.2% | 75.2% | 74.4% | 82.1% | 75.3% | 71.4% | 73.2% | 75.5% | 75.5% | 75.0% | 71.6% | 75.5% | 76.0% | −0.3% | 0.925 |
| Hemorrhage risk assessment on admission | 0.0% | 2.0% | 1.5% | 15.5% | 86.0% | 83.3% | 89.0% | 91.2% | 91.4% | 90.4% | 92.3% | 92.5% | 90.7% | 485% | 0.000 |
| Hemorrhage risk assessment postpartum | 0.0% | 0.7% | 0.8% | 4.2% | 57.3% | 56.5% | 61.6% | 57.8% | 58.9% | 74.3% | 79.4% | 68.0% | 72.1% | 1616% | 0.000 |
| Exclusive QBL | 21.4% | 21.5% | 24.1% | 26.2% | 30.0% | 24.4% | 32.3% | 41.5% | 37.7% | 54.4% | 54.8% | 49.0% | 50.8% | 137% | 0.000 |
Among these patients with major hemorrhages, mean blood loss ± SD after vaginal delivery over the course of the project was 2673 ± 1646 mL and after cesarean was 3101 ± 2092 mL, and mean total blood loss did not change significantly from the first full quarter to the final quarter (2892 ± 1845 mL to 3073 ± 2040 mL, p = 0.46). In linear regressions on blood loss by quarter, exclusive use of QBL, and cesarean delivery, QBL was associated with an increase in reported blood loss of 287 mL (p = 0.004) and cesarean with an increase of 432 mL (p < 0.001). Comparing the first to final quarter in this group of hemorrhage patients, rates were unchanged for massive transfusion (76.2%–76.7%), hysterectomy (31.0%–33.3%), and death (0%–0%, all p > 0.05), while the rate of transfer to a higher level of care declined from 57.1% to 36.4% (p = 0.02). There was no pattern regarding type of care transfer over the duration of the initiative. Over the course of the initiative, 95.3% went to the ICU at the delivery hospital (min/max by quarter 86.7%–100%), with 4.7% requiring transfer to a higher level hospital (min/max 0%–13.3%). Seventy‐five percent of severe hemorrhages followed cesarean delivery, although in patients with severe hemorrhages, the likelihood of transfer was not related to route of delivery (45.8% following cesarean and 45.0% following vaginal delivery, p = 0.77). There were no significant changes in the reasons for hemorrhage by quarter (data not shown).
Because of increased rates of placenta accreta spectrum (PAS) in recent years following the rise in cesarean section rates in the early 2000s, and with the frequency of hysterectomy in the setting of PAS [17], a subanalysis was performed, stratifying hysterectomy by presence or absence of PAS. The rate of PAS did not change over the course of the project but accounted for 21.5% of major hemorrhages. Of 618 peripartum hysterectomies, 334 (54.1%) were in patients with PAS. In 396 cases of hemorrhage related to PAS, 396 (84.3%) underwent hysterectomy. In contrast, of 1443 cases of hemorrhage without PAS, 284 (19.7%) underwent hysterectomy (p < 0.001). It is unclear how many of these PAS cases were known in advance, and if so, how many may have been scheduled cesarean hysterectomies. In addition, there was a trend in the percent of peripartum hysterectomies in which PAS was not a diagnosis declining from 58.7% in the second quarter of 2018 to 37.2% in the first quarter of 2021 (p = 0.30). Among patients with major hemorrhages, the frequency of a diagnosis of PAS did not change over the course of the project (21.4%–25.6%, p = 0.87).
4. DISCUSSION
We report that, with a structured statewide initiative to improve the recognition and management of postpartum hemorrhage, there are high levels of acceptance of the tenets of the hemorrhage bundle. Of 21 structure measures, 19 were implemented by at least 85% of participating hospitals by the conclusion of the initiative. Two measures did not reach the implementation goal of 85%, but all improved over time. These implementation rates are equal to or better than reported in several previous studies [18, 19].
Of the various structure measures adopted, QBL met the most initial resistance but also showed one of the greatest eventual degrees of improvement, with the rate of use more than doubling over the 27 months of study. While QBL is more accurate than EBL, it is also more labor‐intensive and has not conclusively been shown to improve outcomes [20, 21, 22, 23, 24]. For these reasons, and as reported previously [19], some providers were slow to embrace it, and staff training took time. With multiple informational and explanatory presentations during coaching and educational webinars, however, including how various hospitals had effected and sustained their transition to QBL, statewide rates improved.
Another reason there was initial resistance to QBL was a concern that, because EBL underestimates blood loss, early adopters of QBL might appear to have higher‐than‐expected rates of postpartum hemorrhage that, until 2017, was defined by EBL ≥500 mL after a vaginal delivery and ≥1000 mL after cesarean [25, 26]. Rates increased for both thresholds after vaginal delivery, although only for ≥1500 mL for cesarean section. These increases likely represent increased accuracy of assessment rather than actual increases in blood loss, however, because hysterectomy and massive transfusion rates were unchanged. By the project's final quarter, only one hospital had yet to adopt some degree of QBL, minimizing differences between hospitals.
While the California initiative clearly improved hemorrhage‐related morbidity, hemorrhage bundles have not been shown to decrease mortality. Our project was highly successful in terms of hospitals adopting the tenets of preparedness and management of hemorrhage, although subsequent improvement in patient outcome was less clear. Fewer patients required transfer to higher levels of care, although the rates of massive transfusion, hysterectomy, and hemorrhage‐related mortality did not change significantly. The proportion of hysterectomies in patients without PAS did decline. Long‐term monitoring will determine whether rates improve significantly. Another possible explanation may be that hospitals may report adopting certain measures but not consistently implement them. This was the case for drills and exclusive use of QBL.
In terms of maternal outcomes, our results were similar to those of Wolfe et al., who reported a decline in transfer to higher levels of care after QBL had been implemented [27], and to those of Sullivan et al. [28], who also reported higher rates of postpartum hemorrhage after implementation of the CMQCC bundle. Our results differed from Sullivan's in that, in contrast to us, they found no decrease in transfer to intensive care. That study was done at a single referral hospital, thus did not include transfer to higher level hospitals, whereas our study encompassed all hospital levels.
There are several strengths and several limitations to our study. It was an organized statewide initiative in which participation rates were high and hospitals actively contributed their experiences and lessons‐learned during monthly coaching webinars. Data were collected using standardized tools, analyzed, run charts generated, and regularly shared with hospitals. All of these factors were important contributors to the initiative's success. There are also limitations. One is that NYSPQC's data collection started 5 years after the ACOG SMI had been released. Because of this, hospitals had a “head start” on many of the structure measures on which data were being collected, thus minimizing the apparent degree of improvement over the 37 months of the current study. A second limitation is that most data were collected in tabular form rather than raw data on individual patients. This limited our ability to perform analyses on subsets of diagnoses and outcomes. In addition, because the bundle addressed a range of care categories, outcome data can be difficult to interpret because it may be explained in different ways. As an example, if thresholds for transfusions previously were too high, a finding of more—or no decline in—transfusions over the project's span could be interpreted as a negative trend but might actually reflect greater awareness of need, a positive finding. Hospitals were asked for data only on massive transfusion; thus, we lack information on lesser degrees of hemorrhage and transfusion. A third limitation is that adoption of structure measures were self‐reported, but this may not always match what actually is done, and that aggregate data did not necessarily include all patients in high‐volume hospitals, thus are a sample rather than complete data from those facilities. Hospitals did not all join at the same time, meaning denominators changed slightly over the duration of the study. Because this meant some hospitals had less time to make progress, it is possible that this resulted in lower apparent levels of implementation in for some structure measures. Another limitation was that, because participation in the initiative was not mandatory and hospitals often have limited resources, we had to cap the amount of data requested to avoid exceeding hospitals’ collection and submission capabilities and lowering participation rates. This meant fewer subanalyses could be performed.
5. CONCLUSION
We describe how an evidence‐based bundle for obstetric hemorrhage was implemented. While it is not yet possible to determine whether this resulted in improvement in hemorrhage‐related maternal mortality, it was associated with improvement trends in several measures of maternal morbidity.
CONFLICT OF INTEREST STATEMENT
D Goffman: Organon (JADA) Research support to institution, Scientific Advisory Board, Speaker; KOKO Medical Research support to institution. The other authors declare no conflicts of interest.
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ACKNOWLEDGMENTS
This work was supported by Health Resources & Services Administration (HRSA) Maternal and Child Health Block Grant (MCHBG), and the Centers for Disease Control and Prevention’s State‐based Perinatal Quality Collaboratives grant #5NU38DP005363.
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