Assessing women with symptoms of threatened preterm labour: a service proposal

This article describes a proposed change to the assessment of women who attend local maternity services with symptoms of threatened preterm labour. Preterm births account for approximately 8% of UK births nationally (NHS Digital, 2019), affecting approximately 60 000 (Office for National Statistics, 2017) families who have babies born with higher risks of neonatal mortality, and significant disability. Morbidity is directly correlated to gestational age, with the most significant adverse outcomes occurring in births less than 32+0 weeks gestation (UK Preterm Clinical Network, 2019). Preterm births cost health services in England and Wales approximately £3.4bn per year (National Institute for Health and Care Excellence (NICE), 2015), and over the last 10 years, there has been no decline in the preterm birth rate (NICE, 2019).

The national maternity safety ambition is to halve the rates of stillbirths, neonatal and maternal deaths and brain injuries that occur during or soon after birth by 2030 (Department of Health, 2016). It has been recognised that there must be a reduction in preterm births to achieve this. The Department of Health (2016) have set an ambition to reduce preterm births from 8% to 6%, by 2025. In line with this, the author's trust's quality accounts report supports the recommendations from the Ockenden (2020) report, which highlight the saving babies lives care bundle as a priority in local maternity services (County Durham and Darlington NHS Foundation Trust (CDDFT), 2021).

The CDDFT rates of preterm births are in line with national levels (Figure 1). The trust has enrolled in a regional rollout to embed the British Association of Perinatal Medicine (BAPM) toolkit as part of the maternity and neonatal safety improvement programme (NHS Improvement, 2020). Use of the QUiPP app is integral to this improvement programme. Therefore, the aim of this proposal was to plan the implementation of this tool into the assessment and management of women with symptoms of preterm labour. The secondary aim was to perform a service evaluation post-implementation that will focus on the impact the app has on reducing hospital stays and patient experience.

The BAPM (2020) quality improvement toolkit (Figure 2) is designed to optimise antenatal management of preterm infants less than 34 weeks. This pathway is based on recommendations and drivers endorsed by the UK Preterm Clinical Network (2019) and saving babies lives care bundle version 2 (NHS England, 2020).

The key aims of the toolkit are appropriate timely recognition of women at risk of preterm birth, to ensure correct timing of corticosteroids and neuroprotection drugs to improve neonatal outcomes and to ensure optimal place of birth to provide appropriate levels of neonatal intensive care to reduce morbidities.

Preterm birth and threatened preterm labour

Optimal delivery of interventions relies on accurate prediction of preterm birth, which can be done through qualitative fetal fibronectin measurement. The first opportunity to identify women at risk of preterm birth is often when they present with symptoms of threatened preterm labour. This occurs in 9% of pregnancies but only 3–5% of women will give birth within 7 days (Peaceman et al, 1997; Honest et al, 2002; Abbott et al, 2013). The BAPM recommends adopting the QUiPP app, a decision support tool that combines clinical assessment and fetal fibronectin to give an individualised score that predicts preterm birth risk.

Optimal outcomes for preterm infants rely on appropriately timed medications (Norberg et al, 2017; Räikkönen et al, 2020). Several studies suggest that the use of qualitative fetal fibronectin measurement and the QUiPP app in decision making prevents unnecessary interventions, admissions and in-utero transfers (Giles et al, 2000; Foxman and Petr, 2004; Abenhaim et al, 2005; Watson et al, 2017; Dawes et al, 2020; Kuhrt et al, 2020). A holistic approach to care should be adopted, appreciating the psychological effects of anxiety of preterm birth (Parry, 2006). Carlisle et al (2020) conducted a qualitative study that found that use of the QUiPP app can reduce patient anxiety. However, it is important to note that this study only had a participant group, and no control group, so further research is warranted.

Threatened preterm labour is the most common reason for attending hospital before 37 weeks (Parisaei et al, 2016). Current guidelines (NICE, 2015) advise a treat-all policy for women presenting in threatened preterm labour before 30 weeks. The costs of length of stay, investigations and drugs exceed £1000 per admission (Parisaei et al, 2016). The National Tariff Payment System Healthcare Resource Group codes for false labour admission cost approximately £543–712 (NHS England, 2022). Staff have a duty to follow the NHS efficiency plan to reduce resources and costs associated with unnecessary admissions (NHS England, 2017). The QUiPP app is free and ensures accurate timing of interventions to improve outcomes for those at risk of preterm birth, as well as providing reassurance and protection from the side effects of unnecessary interventions for those not at risk. Training to use this app is simple and can be done in-house, with a minimal cost impact. Implementation of the tool is likely to provide cost savings for the author's trust with reduced hospital admissions and unnecessary in utero transfer (Giles et al, 2000; Watson et al, 2017).

Aims

Current local guidelines follow the NICE (2015) treat all approach, so there is a low threshold for interventions such as hospital admission, drug administration and in-utero transfer. The proposed new guideline will recommend qualitative fetal fibronectin measurement and use of the QUiPP app as a first-line diagnostic test. This will assist in clinical decision-making plans and help determine which interventions are needed, ensuring the right treatment is given to the right women at the right time (NHS, 2019).

With the assistance of an academic librarian, a literature search was performed to ensure effective research retrieval (Rethlefsen et al, 2015), which found several studies supporting use of this app. Hologic (2020), the company who provide fetal fibronectin equipment, showcase this evidence in support of the QUiPP app; however, potential marketing bias may exist. The NICE guidelines are viewed as the ‘gold standard’ evidence base, but their research was based on evidence from before 2015. The QUiPP app is supported by recent evidence, with the BAPM antenatal optimisation toolkit being developed in 2020. Watson et al (2017) directly compared the NICE treat-all approach and use of the QUiPP app, finding that 89% of admissions and unnecessary interventions could have been avoided.

This service proposal involves the addition of a small step in an established assessment process. It is for this reason that Lewin's (1951) change theory is used, which explains the process of organisational change in a 3-stage theory, referred to as ‘unfreeze, change and refreeze’ (Cameron and Green, 2004). Consideration was given to using Kotter's (1996) implementation model; however, it was too complex for a simple change. There are aspects of Kotter's (1996) strategy that coincide with Lewin's (1951) theory, such as creating a guiding coalition of influential people, but following review of Kotter's (1996) model, it was deemed more suitable to a full-service transformation. Consideration was also given to Carnall's (1990) managing transitions model, but as Cameron and Green (2004) suggest, this is focused on the role of the manager during the change project and not the actual change itself. Lewin's (1951) planned approach to change has been criticised for being too simple and goal driven for a continuously changing organisation (Wilson, 1992; Burns, 2004); ironically, these criticisms form the rationale for using this simplistic model.

Lewin's first stage: unfreeze

The first stage, unfreezing, involves assessment of the ‘status quo’, in this case, current processes for threatened preterm labour assessment. Admissions with threatened preterm labour are assessed in the pregnancy assessment unit or labour ward, which were the areas of focus.

Successful service improvements require several people to be involved in the planning and implementation process; these people are referred to as stakeholders (NHS Improving Quality, 2014a). A stakeholder analysis was performed to demonstrate who the key influential people will be in this project (Table 1). It is beneficial to identify who the powerful people are that need to support the project (NHS Institute for Innovation and Improvement, 2009).

When initiating a service improvement, it is valuable to identify senior staff that will be affected by the change, so they can act as internal drivers for the project (Gage, 2013). Two consultants will be champions for this project, as they lead on management of preterm births in the trust. Although they have high power, they are not at the forefront of threatened preterm labour assessment and therefore have little impact, so in addition, a team of ‘QUiPP champions’ will be recruited. This team will consist of stakeholders with high impact, namely the midwives and registrars who are based on the pregnancy assesment unit and labour ward and perform threatened preterm labour assessments. This group will be the ‘golden triangles’ of the change, positively driving objectives forward, yet empathising with the ‘waverers’ and ‘moaners’ (NHS Institute for Innovation and Improvement, 2009).

Stakeholders such as neonatal staff have little impact or power, but need to understand what the results imply to promote cohesive multidisciplinary care planning (BAPM, 2020). Teaching tools from the QUiPP quality improvement toolkit, will be shared with neonatal colleagues to demonstrate how this change impacts them.

Patient representation is invaluable when planning new services, as women want to be active partners in care planning (National Maternity Review, 2016). A meeting with the local maternity voices partnership representative has already occurred to discuss this change to the trust's approach to threatened preterm labour assessment. A presentation will be shared with service users, explaining what the QUiPP app is and how it may affect them.

Several psychological theories exist regarding human reactions to change. Schein's (1999) model of transformative change mirrors Lewin's (1951) model, focusing on the human element of change. Schein (1999) describes the first stage as creating motivation and psychological safety to overcome individual anxieties. This unfreeze stage is about supporting staff through their panic and discomfort zones (Reynolds, 2014). Schein (1999) describes eight ways to reduce anxiety in preparation to move on to stage two of the change process. These include creating positive role models, providing training and establishing groups to champion the change. Leaders need to be approachable and supportive towards vulnerable staff, as lack of support and not being listened to have been major contributory factors in negative cultures (Dixon-Woods et al, 2014).

Staff engagement is vital to success in any service improvement (Bowers, 2011). Effective communication plays a vital role in getting the desired support and involvement of the people in the change process (Barr and Dowding, 2008). A shared vision is key to any successful change project, and results in a team that is engaged, resilient and committed to working together to create a culture for change (BAPM, 2020).

When communicating this change, Rogers (2003) theory will be considered to identify innovators and early adopters. This will assist in recruitment of champions who will encourage the ‘laggards’ to accept new ways of working (Rogers, 2003). To become motivated and enthusiastic, staff need to have an understanding of the rationale for change. The QUiPP quality improvement toolkit provides resources to educate staff about the benefits of the app. Opportunities to share this information via various channels have been identified in an action planning tool (Table 2). When staff have an appreciation of the benefits of the app and its simplicity, engagement and enthusiasm should be secured.

This unfreeze stage would benefit from a transformational leadership style, where team creativity is enhanced through knowledge sharing (Dong et al, 2016). Goleman et al (2007) refers to ‘leading with passion’ and Clavelle and Prado-Inzerillio (2018) speak of ‘eliciting excitement’, which are both apt regarding the leadership style required for this unfreeze phase.

Lewin's second stage: change

Lewin's (1951) second stage is the project's implementation. The theory of change describes how and why a change is expected to happen, the long-term goals and the specific aims and objectives that are involved in the process of achieving the overall goal (Center for Theory of Change, 2017). A planning triangle has been used to build a theory of change to inform this proposal (Figure 3). This tool is a succinct way to focus on the smaller objectives required to fulfil long-term goals. The specific aims at the bottom of the triangle represent the changes in this service proposal. An alternative theory of change tool is the Lean model; however, its primary focus is to reduce waste, so would be more suited to a project to reduce waiting times (NHS Improving Quality, 2014b).

To assist in implementation, the objectives at the bottom of the planning triangle have been broken down into an action planning tool (Table 2). This tool provides direction, ensuring all teams members are clear about their roles, and demonstrates that tasks are completed by appropriate people in acceptable timeframes (Gage, 2013). This provides greater commitment to the innovation (Kline, 2019). West et al (2017) stated that leaders need to ensure direction and commitment to create a culture of improvement.

This stage involves acceptance of the new way of working, when the change is implemented and people become ‘unfrozen’. This stage can also be difficult for staff, as they may be fearful of the consequences of a change (Management Study Guide, 2020). Attributable to a servent leadership theory is the ability to sympathise with followers' anxieties, helping them become knowledgeable and autonomous (Nawaz and Khan, 2016).

Staff may feel vulnerable trusting a new tool to guide their management, so the aim will be to equip them with evidence to instill confidence, reduce vulnerability and increase psychological safety (Pfeifer and Vassey, 2019). Changes that happen suddenly can result in staff resistance, as they have not had time to accept and adapt to the new way of working (Management Study Guide, 2020). This suggests that stage two of Lewin's (1951) theory has been missed. During this planning period, continual communication with staff will allow opportunities for them to contribute ensuring they feel valued, to promote engagement (Barr and Dowding, 2008). A coaching style of leadership would be suited to this stage of the process, supporting staff to acquire new skills as part of this change project (Cameron and Green, 2004).

Lewin's third stage: refreezing

Lewin's (1951) refreezing stage is referred to as a state of equilibrium (Management Study Guide, 2020), where staff have passed through the panic and discomfort zones and reached their comfort zone where change is embedded (Reynolds, 2014). In healthcare, it has been suggested that approximately 33% of change innovations are not sustained (Maher et al, 2010). When weaknesses are exposed during the implementation process, adjustments can be initiated to strengthen the innovation (NHS Improvement, 2020).

Plan, do, study, act cycles examine the learning that can be achieved through reviewing the crux of the change (Reed and Card, 2016). These models will be used as they are a quick method of testing changes on a small scale, allowing stakeholders an insight into how an innovation can succeed (NHS Improving Quality, 2014a). Systematic reviews have assessed the effectiveness of plan, do, study, act cycles and suggested that they do not lead to service innovation (Knudsen et al, 2019). This is supported by Reed and Card (2016) who claim that its simplification carries the risk of losing information. Despite criticism, using these cycles will be valuable as the repetition of the cycle each time a weakness is identified will ensure that learning drives the change until a standarised process is achieved.

Continuation of a change in service provision, allowing it to become a ‘new norm’ illustrates sustainability (Maher et al, 2010). The NHS sustainability model (Maher et al, 2010) allows leaders to identify strengths and weaknesses in the implementation of a project that impact on its likelihood of achieving sustainability. This model appraises staff, process and organisational issues (Maher et al, 2010). The ‘process’ domain looks at the reliability of the innovation, staff's belief in its efficacy and its ability to improve outcomes. This information will be assessed through evaluation of the change. The ‘staff’ domain seeks to gain an awareness of the involvement and commitment of frontline staff in the innovation (Doyle et al, 2013). This will be reflected in the data collection of app use. The ‘organisation’ domain reviews if the innovation is aligned with the existing organisational culture, such as guidelines and staffing competence (Doyle et al, 2013) as planned. The aim to improve maternity standards is set out in the CDDFT (2020; 2021) Trust annual quality report, and the ‘improvement matters’ strategy is an internal driver for innovation that ensures safe quality care, that is right first time, every time, fulfilling the criteria in the organisational domain of the sustainability model.

Evaluation of this change proposal will take place following completion of all three of Lewin's (1951) stages. Evaluation is considered an essential part of any improvement project, assessing the impact of a project and reviewing whether the project aims have been achieved (NHS Institute for Innovation and Improvement, 2005). Evaluation enables leaders to identify what is and is not working, to highlight changes that are needed (NHS Improving Quality, 2014a). Quantitative and qualitative feedback are useful in service evaluation and are valuable when combined (Andrew and Halcomb, 2009).

Local figures for preterm birth and admissions with threatened preterm labour will form part of this evaluation. This will be done through use of the maternity data management system, allowing data collection that is cheap and quick (NHS Institute for Innovation and Improvement, 2005). It is imperative that women's experiences are evaluated, as the overall aim at the top of this project's planning triangle is to enhance women's experiences of care. Anonymised surveys and interviews will provide qualitative information to form the impact evaluation of this service improvement.

Ethical matters will be considered, as women may be caring for a poorly baby or possibly grieving following a poor outcome. If poor outcomes occur, it may not be possible to achieve a 100% evaluation rate. Emotional intelligence and compassionate leadership skills are needed to communicate with patients using empathy and compassion (West et al, 2017).

A formal evaluation of the service improvement will be shared with all stakeholders, through various means of communication (NHS Institute for Innovation and Improvement, 2005). The evaluation will be shared in a ‘reader-friendly’ format with service users through engagement with the maternity voices partnership and on the trust intranet, ensuring there is a focus on the needs of service users (Ham et al, 2016).

Trust data

Pre-change data were collected that were non-identifiable and included the number of women admitted with symptoms of threatened preterm labour, the number of days beds were used for women in threatened preterm labour and out of those admissions, how many women went on to have a preterm birth. To evaluate the success of this proposal, the same data need to be compared after the implementation. In compliance with the requirements of research governance, ethical agreement was obtained from the trust to use anonymised data, and ethical clearance was gained from Teesside University.

The trust information department was given the inclusion/exclusion criteria, which were all threatened preterm labour admissions for a 12-month period, which was considered to be a good sample size. Admissions from between April 2020 and 2021 were collected, to provide recent data in line with current practice. A new data management system was in use from May 2021, and so data from after this date were excluded.

The information officer used healthcare resource group codes for false labour to retrieve information, obtaining 96% of outcomes for the data collection set. Missing data were accessed manually by examining electronic patient records to find gestation at birth. These missing data were the result of geographical issues, for example women attending for assessment while visiting the area or following an admission, women who moved out of the area. It would be unrealistic to expect to gather 100% of the data in the absence of a national maternity data system.

In-patient days for women who went into preterm labour were assessed over the 12-month period, to examine how many days were necessary for optimised management. The costings of these admissions were reviewed, to assess if there were potential cost savings as a result of using the app.

A total of 89 of the 121 women admitted with threatened preterm labour gave birth over 35 weeks gestation who could have avoided admission with use of the QUiPP app (Figure 4). A total of 27 gave birth between 23 and 34+6 weeks where the QUiPP app could have been used in their management. Birth data were unable for five women. A total of 148 days of hospital admissions were associated with threatened preterm labour, of which 111 days could have been avoided by using the app (Figure 5). Figure 6 shows the costs of all threatened preterm labour admissions and those who gave birth between 23 and 34+6 weeks gestation who did warrant admission to optimise management. These costs are based on non-delivery admitted patient and outpatient procedure prices for maternity services (NHS England, 2022).

Figure 7 shows the minimal potential cost savings that could be achieved by using the QUiPP app. Unnecessary interventions, such as antenatal steroids and in-utero transfers, are also a cost saving consideration.

The subsequent evaluation of the change implemented in this service proposal will be quantitative and taken from a comparable 12-month period. A 2-month period after implementation will be given before commencing data collection, to ensure the app is embedded in practice. After implementation, qualitative data could be collected through interviews and surveys to analyse patient experience of the app and form a thematic analysis.

Conclusions

The rationale for this service proposal was to assess if a change in the assessment of women who present with symptoms of threatened preterm labour could improve early recognition of preterm birth, allowing time to implement interventions that improve outcomes (NHS England, 2019; BAPM, 2020). This work proposes use of the QUiPP app to assist in decision making for the management of threatened preterm labour. The evidence supporting use of this app is vast and recent, and thus may supersede the NICE (2015) preterm birth guideline, which currently adopts a treat-all management ethos.

This proposal involves a simple change to an assessment process. Pre-change data analysis over a 1-year period demonstrates it could potentially improve the care of 89 women in this trust. The data show potential reductions in unnecessary admissions and interventions. Evidence for using this app could be stronger if it were possible to assess how many interventions could be prevented, a limitation to the data collected. The previous maternity record system did not capture optimisation interventions. The new maternity data management system will capture this information, but unfortunately would not allow comparison between pre- and post-implementation data.

This proposed change would assist in achieving the Department of Health (2016) national maternity strategy's aim of reducing preterm birth from 8% to 6% by 2025 and optimising neonatal outcomes. These data highlight a potential cost saving in preterm birth care provision, which currently costs the NHS in England and Wales approximately £3.4bn per year (NICE, 2015).

Leadership skills

High-profile inquiries, including the Francis report (Mid Staffordshire NHS Foundation Trust Public Inquiry, 2013) and Ockenden (2020) report, have highlighted failings in healthcare and emphasised the importance of good leadership and compassion to the provision of safe, effective services (West et al, 2015). West et al (2014) describe inclusive leadership as motivating and empowering staff to seek opportunities to learn. This proposal provides a robust plan to educate staff about the benefits of this app. The author is confident that a shared vision will be created to facilitate a successful change. Change in a large organisation is not without its challenges, including human resistance to change. Inclusive leadership highlights the importance of establishing and maintaining consistent communication and building authentic relationships, to engage and empower staff to focus on innovation (Edwards et al, 2018).

The toxic cultures described by Francis (Mid Staffordshire NHS Foundation Trust Public Inquiry, 2013) and Ockenden (2020) place huge emphasis on the goals and targets of the organisation. While undergoing this change project, it is vital that staff feel psychologically safe to speak up about their concerns and fears. A compassionate leadership style is required to create a culture where staff feel safe and are supported to combat their anxieties around change. Following implementation of this change, staff will notice a positive improvement in the care, management and outcomes for women and preterm babies.

Key points

• This is a change proposal for the management and assessment of women who attend with symptoms of threatened preterm labour.
• Evidence has been viewed to assess why this change is needed to improve outcomes for preterm births.
• Appropriate change models have been used to plan the proposed change.
• Pre-change data collection has been conducted to assess current practice and potential benefits of the service proposal.
• The findings show potential reductions in unnecessary admissions and interventions, improving women's experiences and assisting in the national maternity strategy's aim to reduce preterm birth and optimise neonatal outcomes.