Midwife continuity of care models versus other models of care for childbearing women

BACKGROUND

Midwives are primary providers of care for childbearing women globally and there is a need to establish whether there are differences in effectiveness between midwife continuity of care models and other models of care. This is an update of a review published in 2016.

OBJECTIVES

To compare the effects of midwife continuity of care models with other models of care for childbearing women and their infants.

SEARCH METHODS

We searched the Cochrane Pregnancy and Childbirth Trials Register, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform (ICTRP) (17 August 2022), as well as the reference lists of retrieved studies.

SELECTION CRITERIA

All published and unpublished trials in which pregnant women are randomly allocated to midwife continuity of care models or other models of care during pregnancy and birth.

DATA COLLECTION AND ANALYSIS

Two authors independently assessed studies for inclusion criteria, scientific integrity, and risk of bias, and carried out data extraction and entry. Primary outcomes were spontaneous vaginal birth, caesarean section, regional anaesthesia, intact perineum, fetal loss after 24 weeks gestation, preterm birth, and neonatal death. We used GRADE to rate the certainty of evidence.

MAIN RESULTS

We included 17 studies involving 18,533 randomised women. We assessed all studies as being at low risk of scientific integrity/trustworthiness concerns. Studies were conducted in Australia, Canada, China, Ireland, and the United Kingdom. The majority of the included studies did not include women at high risk of complications. There are three ongoing studies targeting disadvantaged women. Primary outcomes Based on control group risks observed in the studies, midwife continuity of care models, as compared to other models of care, likely increase spontaneous vaginal birth from 66% to 70% (risk ratio (RR) 1.05, 95% confidence interval (CI) 1.03 to 1.07; 15 studies, 17,864 participants; moderate-certainty evidence), likelyreduce caesarean sections from 16% to 15% (RR 0.91, 95% CI 0.84 to 0.99; 16 studies, 18,037 participants; moderate-certainty evidence), and likely result in little to no difference in intact perineum (29% in other care models and 31% in midwife continuity of care models, average RR 1.05, 95% CI 0.98 to 1.12; 12 studies, 14,268 participants; moderate-certainty evidence). There may belittle or no difference in preterm birth (< 37 weeks) (6% under both care models, average RR 0.95, 95% CI 0.78 to 1.16; 10 studies, 13,850 participants; low-certainty evidence). We arevery uncertain about the effect of midwife continuity of care models on regional analgesia (average RR 0.85, 95% CI 0.79 to 0.92; 15 studies, 17,754 participants, very low-certainty evidence), fetal loss at or after 24 weeks gestation (average RR 1.24, 95% CI 0.73 to 2.13; 12 studies, 16,122 participants; very low-certainty evidence), and neonatal death (average RR 0.85, 95% CI 0.43 to 1.71; 10 studies, 14,718 participants; very low-certainty evidence). Secondary outcomes When compared to other models of care, midwife continuity of care models likely reduce instrumental vaginal birth (forceps/vacuum) from 14% to 13% (average RR 0.89, 95% CI 0.83 to 0.96; 14 studies, 17,769 participants; moderate-certainty evidence), and may reduceepisiotomy 23% to 19% (average RR 0.83, 95% CI 0.77 to 0.91; 15 studies, 17,839 participants; low-certainty evidence). When compared to other models of care, midwife continuity of care models likelyresult in little to no difference inpostpartum haemorrhage (average RR 0.92, 95% CI 0.82 to 1.03; 11 studies, 14,407 participants; moderate-certainty evidence) and admission to special care nursery/neonatal intensive care unit (average RR 0.89, 95% CI 0.77 to 1.03; 13 studies, 16,260 participants; moderate-certainty evidence). There may be little or no difference in induction of labour (average RR 0.92, 95% CI 0.85 to 1.00; 14 studies, 17,666 participants; low-certainty evidence), breastfeeding initiation (average RR 1.06, 95% CI 1.00 to 1.12; 8 studies, 8575 participants; low-certainty evidence), and birth weight less than 2500 g (average RR 0.92, 95% CI 0.79 to 1.08; 9 studies, 12,420 participants; low-certainty evidence). We are very uncertain about the effect of midwife continuity of care models compared to other models of care onthird or fourth-degree tear (average RR 1.10, 95% CI 0.81 to 1.49; 7 studies, 9437 participants; very low-certainty evidence), maternal readmission within 28 days (average RR 1.52, 95% CI 0.78 to 2.96; 1 study, 1195 participants; very low-certainty evidence), attendance at birth by a known midwife (average RR 9.13, 95% CI 5.87 to 14.21; 11 studies, 9273 participants; very low-certainty evidence), Apgar score less than or equal to seven at five minutes (average RR 0.95, 95% CI 0.72 to 1.24; 13 studies, 12,806 participants; very low-certainty evidence) andfetal loss before 24 weeks gestation (average RR 0.82, 95% CI 0.67 to 1.01; 12 studies, 15,913 participants; very low-certainty evidence). No maternal deaths were reported across three studies. Although the observed risk of adverse events was similar between midwifery continuity of care models and other models, our confidence in the findings was limited. Our confidence in the findings was lowered by possible risks of bias, inconsistency, and imprecision of some estimates. There were no available data for the outcomes: maternal health status, neonatal readmission within 28 days, infant health status, and birth weight of 4000 g or more. Maternal experiences and cost implications are described narratively. Women receiving care from midwife continuity of care models, as opposed to other care models, generally reported more positive experiences during pregnancy, labour, and postpartum. Cost savings were noted in the antenatal and intrapartum periods in midwife continuity of care models.

AUTHORS' CONCLUSIONS

Women receiving midwife continuity of care models were less likely to experience a caesarean section and instrumental birth, and may be less likely to experience episiotomy. They were more likely to experience spontaneous vaginal birth and report a positive experience. The certainty of some findings varies due to possible risks of bias, inconsistencies, and imprecision of some estimates. Future research should focus on the impact on women with social risk factors, and those at higher risk of complications, and implementation and scaling up of midwife continuity of care models, with emphasis on low- and middle-income countries.

Pathway Design for Acute Stroke Care in the Era of Endovascular Thrombectomy: A Critical Overview of Optimization Efforts

The efficacy of intravenous thrombolysis and endovascular thrombectomy (EVT) for acute ischemic stroke is highly time dependent. Optimal organization of acute stroke care is therefore important to reduce treatment delays but has become more complex after the introduction of EVT as regular treatment for large vessel occlusions. There is no singular optimal organizational model that can be generalized to different geographic regions worldwide. Current dominant organizational models for EVT include the drip-and-ship- and mothership model. Guidelines recommend routing of suspected patients with stroke to the nearest intravenous thrombolysis capable facility; however, the choice of routing to a certain model should depend on regional stroke service organization and individual patient characteristics. In general, design approaches for organizing stroke care are required, in which 2 key strategies could be considered. The first entails the identification of interventions within existing organizational models for optimizing timely delivery of intravenous thrombolysis and/or EVT. This includes adaptive patient routing toward a comprehensive stroke center, which focuses particularly on prehospital triage tools; bringing intravenous thrombolysis or EVT to the location of the patient; and expediting services and processes along the stroke pathway. The second strategy is to develop analytical or simulation model-based approaches enabling the design and evaluation of organizational models before their implementation. Organizational models for acute stroke care need to take regional and patient characteristics into account and can most efficiently be assessed and optimized through the application of model-based approaches.

Improving medical practice: a conceptual framework

PURPOSE

The purpose of this article is to produce a relatively simple conceptual framework for guiding and studying practice improvement.

METHODS

I summarize the lessons from my experience with a variety of quality improvement research studies during the last 30 years, supplemented with relevant literature from both medicine and other industries about the issues associated with successful quality improvement.

RESULTS

My experience suggests that organizational leadership with an urgent vision for change, ability to manage the change process, and selection of systematic changes capable of fulfilling the vision are each critical for successful quality improvement. Published literature from other industries emphasizes the importance of a goal-directed change process managed by leaders who recognize the need to engage their employees and other leaders in a disciplined but flexible way that accommodates external and internal factors and uses teams and group learning. It also suggests the importance of organizational context and the level of external and internal barriers and facilitators for change. The resulting model proposes that priority, change process, and care process content are necessary for measurable improvements in quality of care and patient outcomes, although internal and external barriers must also be attended to and addressed.

CONCLUSION

This framework may provide a guide to those in the front lines of care who would like to make the care transformations that are needed to greatly improve care. It may also be helpful to those who are developing or testing interventions and recruiting medical practices for such change efforts.

Care quality and implementation of the chronic care model: a quantitative study

PURPOSE

We wanted to test whether improvements in care quality were correlated with changes in the Chronic Care Model (CCM) in a large medical group that attempted to implement the CCM.

METHODS

The leaders of 17 primary care clinics in this medical group completed the Assessing Chronic Illness Care (ACIC) survey measure of CCM implementation before and after care system changes were made. We used administrative data to measure care quality changes for yearly samples of patients with diabetes, coronary heart disease, or depression.

RESULTS

The total ACIC score for the CCM increased by an overall average of 1.4 points (from 5.8 to 7.2 on a scale of 1 to 11, P = .02) and significant increases occurred for 3 of the 6 components of the CCM. During this time, patients experienced a significant increase in the proportion meeting a composite outcome measure for low-density lipoprotein (LDL) and glycated hemoglobin levels (from 15.7% to 25.5%, P = .001). Heart disease patients meeting a composite measure for LDL values increased from 46.8% to 57.8%, and the percentage of patients with 1 or more cardiac events dropped from 17.2% to 11.4% (P = .001 for each). Persistent use of new antidepressants did not change, but more of these patients had follow-up visits (P = .02). Only the diabetes measure was significantly correlated with 2 CCM elements-clinical information systems and decision support.

CONCLUSION

Despite implementation of the CCM and improvements in quality measures for 3 chronic diseases, there were few significant correlations between these changes. Showing such a relationship may require larger changes, a larger number of clinics, changes in other CCM elements, or a more-sensitive measurement tool.