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Headline
The performance of maternity services is seen as a touchstone of whether or not we are delivering high-quality NHS care. This study looked at the relationship between organisational factors, staffing, skill mix, cost, safety and quality of care in maternity services, and developed new healthy mother and healthy baby indicators. Mother and baby outcomes are largely determined by women’s level of clinical risk, parity and age. Staffing levels in maternity services have limited effects on some outcomes and deployment for most beneficial impact is important. Generally, doctors have a positive impact on higher-risk women and midwives have a positive impact on lower-risk women. Managers may wish to exercise caution in increasing the number of support workers caring for higher-risk women. There also appear to be limited opportunities for role substitution.
Abstract
Background:
The performance of maternity services is seen as a touchstone of whether or not we are delivering high-quality NHS care. Staffing has been identified in numerous reports as being a critical component of safe, effective, user-centred care. There is little evidence regarding the impact of maternity workforce staffing and skill mix on the safety, quality and cost of maternity care in the UK.
Objectives:
To understand the relationship between organisational factors, maternity workforce staffing and skill mix, cost and indicators of safe and high-quality care.
Design and methods:
Data included Hospital Episode Statistics (HES) from 143 NHS trusts in England in 2010–11 (656,969 delivery records), NHS Workforce Statistics, England, 2010–11, Care Quality Commission Maternity Survey of women’s experiences 2010 and NHS reference costs 2010/11. Ten indicators were derived from HES data. They included healthy mother and healthy baby outcomes and mode of birth. Adjustments were made for background characteristics and clinical risk. Data were analysed to examine the influence of organisational factors, staffing and costs using multilevel logistic regression models. A production function analysis examined the relationship between staffing, skill mix and output.
Results:
Outcomes were largely determined by women’s level of clinical risk [based on National Institute for Health and Care Excellence (NICE) guidance], parity and age. The effects of trust size and trust university status were small. Larger trust size reduced the chance of a healthy mother outcome and also reduced the likelihood of a healthy mother/healthy baby dyad outcome, and increased the chances of other childbirth interventions. Increased investment in staff did not necessarily have an effect on the outcome and experience measures chosen, although there was a higher rate of intact perineum and also of delivery with bodily integrity in trusts with greater levels of midwifery staffing. An analysis of the multiplicative effects of parity and clinical risk with the staffing variables was more revealing. Increasing the number of doctors had the greatest impact on outcomes in higher-risk women and increasing the number of midwives had the greatest impact on outcomes in lower-risk women. Although increased numbers of support workers impacted on reducing childbirth interventions in lower-risk women, they also had a negative impact on the healthy mother/healthy baby dyad outcomes in all women. In terms of maximising the capacity of a trust to deliver babies, midwives and support workers were found to be substitutes for each other, as were consultants and other doctors. However, any substitution between staff groups could impact on the quality of care given. Economically speaking, midwives are best used in combination with consultants and other doctors.
Conclusions:
Staffing levels have positive and negative effects on some outcomes, and deployment of doctors and midwives where they have most beneficial impact is important. Managers may wish to exercise caution in increasing the number of support workers who care for higher-risk women. There also appear to be limited opportunities for role substitution.
Future work:
Wide variations in outcomes remain after adjustment for sociodemographic and clinical risk, and organisational factors. Further research is required on what may be influencing unexplained variation such as organisational climate and culture, use of NICE guidelines in practice, variation of models of care within trusts and women’s choices.
Funding:
The National Institute for Health Research Health Services and Delivery Research programme.
Contents
- Plain English summary
- Scientific summary
- Chapter 1. Background and research objectives
- Chapter 2. Design and methods
- Research questions
- Study design
- Patient and public involvement
- Data sources
- Data storage, governance and ethics
- Data cleaning and quality
- Study size and bias
- Derivation of process and outcome indicators
- Indicators used in analysis
- Independent variables
- Statistical methods
- Costing analysis
- Methodology to explore midwifery staffing levels, outcomes and the cost of providing maternity services for NHS trusts
- Exclusion of data for quality and bias
- Economic modelling methodology
- Chapter 3. Findings
- Chapter 4. Discussion
- How do organisational factors affect variability in maternal interventions and maternal and perinatal outcomes?
- What is the relationship between maternity staffing, skill mix and maternal and perinatal outcomes?
- What is the relationship between maternity staffing, cost and outcomes?
- Economic modelling
- Limitations
- Public and patient involvement
- Chapter 5. Conclusions
- Acknowledgements
- References
- Appendix 1 Advisory group membership
- Appendix 2 Data sources, cleaning and derivation of indicators
- Appendix 3 Funnel plots for the 10 indicators used in analysis
- Appendix 4 Multilevel models
- Appendix 5 Multilevel model sensitivity analyses
- Appendix 6 Parity and clinical risk: tests of interaction with staffing variables
- Appendix 7 Completeness of data by trust
- Glossary
- List of abbreviations
Article history
The research reported in this issue of the journal was funded by the HS&DR programme or one of its proceeding programmes as project number 10/1011/94. The contractual start date was in March 2012. The final report began editorial review in October 2013 and was accepted for publication in March 2014. The authors have been wholly responsible for all data collection, analysis and interpretation, and for writing up their work. The HS&DR editors and production house have tried to ensure the accuracy of the authors’ report and would like to thank the reviewers for their constructive comments on the final report document. However, they do not accept liability for damages or losses arising from material published in this report.
Declared competing interests of authors
none
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