Discussion

Overview

This study used mixed methods to identify the extent to which London stroke services were providing 24/7 care and, if they were, how it was being achieved. The research presented a range of organisational factors that influence 24/7 provision of stroke care, such as staffing rotas and availability of scans, assessing the extent to which temporal patterns of provision are reflected in patient outcomes, including mortality, LOS and functional independence. Our five research objectives were to investigate:

1. the extent to which evidence-based care received by stroke patients differs between in-hours and out-of-hours services in London HASUs
2. the extent to which clinical outcomes differ between in-hours and out-of-hours services in London HASUs
3. how in-hours and out-of-hours services are organised and provided in London HASUs
4. how these services are perceived by stakeholders (including stroke clinicians, patients and carers)
5. the costs of acute stroke care in London HASUs on different days and at different times of admission.

In this chapter, we present a summary of our principal findings, linked to our research objectives. We then discuss the implications of these findings, as well as the strengths and limitations of our study, and propose a future research agenda.

Summary of main findings

Our analysis of the extent to which evidence-based care (objective 1), clinical outcomes (objective 2) and costs (objective 5) differ between in-hours and out-of-hours services in London HASUs found the following:

• London HASUs do not operate a 24/7 service in all aspects of acute stroke care. However, nor are they designed to.
• There was no variation in 3-day mortality and mRS score at hospital discharge by day of admission.
• In accordance with national and local stroke standards, London HASUs do not vary temporally in quality of care by day and time of admission across the week in terms of timely access to:
  • brain scanning
  • stroke nursing care
  • thrombolysis.
• Other time-dependent quality-of-care measures did significantly vary across the week in London HASUs.
• Three patterns of variation were detected: (1) by time of day, but not by day of the week; (2) by day of the week, but not by time of day; and (3) by time of day and by day of the week.
• We found that there was little variation in the cost of care processes, including receipt of thrombolysis across the week, although LOS on the HASU and total LOS were longer for patients admitted during the weekend.
• When incorporating total LOS, the additional mean cost per patient was £445–668, depending on when the patient was admitted during the weekend.
• Those who were admitted 20.00–07.59 on a weekday had similar costs to those who were admitted 08.00–19.59 on a weekday.

Our analysis of temporal variation in nurse staffing and the effect on quality-of-care measures (objectives 1–3) found the following:

• Many HASUs timetable nurses at higher bands (e.g. band 7) to take on senior nursing tasks, such as the nurse-in-charge role, during the day on weekdays.
• Quality of care was better if the nurse in charge was a higher band and/or there were more nurses on duty.
• The more senior the nurse in charge, the less likely it was for a patient to see a stroke physician within the first 12 or 24 hours.
• Nurse staffing had a direct effect on quality-of-care measures soon after arrival at the hospital (brain scan within 1 hour, dysphagia screen within 4 hours, admission to a stroke unit within 4 hours).
• Wards are organised and made efficient by senior nurse care.
• In both the acute admission area and the ward area of hyperacute stroke units there are some specific tasks that require the attendance of a senior nurse.
• Senior nurse care was demonstrated to make a difference to some outcomes, but this may be compromised if the senior nurse has to manage two areas.
• Junior nurses in some HASUs are trained to perform certain tasks so that they can ‘act up’ to senior roles; however, this does not enable them to juggle the many demands of the senior role that are so different from junior tasks.

Our analysis of how in-hours and out-of-hours services are organised and provided in London HASUs (objective 3) and how this was perceived by stakeholders (including stroke clinicians, patients and carers) (objective 4) found the following:

• 24/7 services were built out of ‘old-fashioned’ models of team practice.
• This was minimally disruptive to previous practices: ward rounds and therapy rota models stayed the same.
• Consistency was achieved by:
  • adapting and extending roles
  • creating continuities between different times of day
  • building relationships and trust
  • prioritisation of ‘front-door’ interventions.
• There are unintended consequences of adaptations, however, such as delays in repatriation, higher levels of pressure for staff and increased admissions to the HASU at night.
• Variation persists due to inconsistencies in:
  • medical, managerial and allied health professional staffing by time of day
  • delivery of therapist assessments
  • barriers in repatriation processes.

Our study has revealed a new way of thinking about temporal consistency, characterised by the following:

• The SSNAP and London stroke service standards dominate the timing of clinical events in the ‘front-door’ part of the patient pathway through setting of micro time limits that are evidence linked to clinical outcomes (1 hour, 4 hours, etc.).
• The SSNAP metrics later in the patient pathway have longer time limits (24 hours, 72 hours) that are not indicative of clinical benefit but reflect cultural norms about rotas and activities, such as ward rounds, which have financial implications.
• Assessing temporal variation for events that occur > 1 hour after arrival in terms of ‘in-hours’ and ‘out-of-hours’ arrival periods was meaningless, as the punctuation of temporal structures, such as therapy rotas and ward rounds, is what determines clinical contacts.
• Repatriation from the HASU was temporally structured by the cultural norms and working patterns of other departments and organisations.
• Measuring temporal concepts, such as clustering, pressure and bottlenecks, is as important as consistency.

Implications of these findings

Part of the value of this study has been the chance to evaluate the study of temporal consistency as a whole. As such, we have developed new ways of analysing routine data (see Chapter 3) and have demonstrated the benefits of gathering other forms of data (e.g. nursing rotas, see Chapter 5) and qualitative data (e.g. interviews and observations to understand variation from a patient and professional perspective, see Chapters 4–6). This enabled us to move from an ‘in-hours’ and ‘out-of-hours’ comparison to granular analysis of processes and outcomes over time (see Table 6).

This also builds on previous studies40 of the London HASU structural reorganisations by showing, for example, the downstream effect of strong designated leadership on HASU culture and ethos.

Implications for whether or not acute stroke services can be temporally consistent (24/7)

London HASUs were designed to be 24/7 services, but were built out of ‘old-fashioned’ models of team practice in a way that was minimally disruptive to previous practices. This can be likened to ‘sedimentation’, whereby elements of the new culture merely sediment over the values and structures of the old culture.94 This has been recognised as a limitation to aspirations for ‘transformational’ change in health care.95

Hyperacute stroke units have been able to produce temporal consistency in provision of some crucial interventions and clinical outcomes; however, we found deep-rooted patterns of variation on HASUs in a number of key areas:

• Medical and nursing staff were reduced in number and seniority at night, and junior staff had to ‘act up’ to fulfil senior responsibilities.
• Therapy provision was a contentious issue, with some HASUs attempting 7-day provision and others not (see Chapter 4, Variations in delivering therapist assessments).
• Those that did attempt 7-day provision found that their staff were stretched thin and only basic assessments were completed over the weekend.
• Many patterns of working on the HASU still have observable variation in the way that rotas are constructed in different professional groups. For example, the rotas of all key staffing groups (doctors, nurses and therapists) remain based around conventional working-week models.
• This is seen most strongly with the therapy teams, who work only conventional working hours 5 days per week, and least seen with the nursing teams, in which staffing is more often timetabled to meet peaks in activity.
• Many hospital departments had no access to testing at night or only with consultant-to-consultant request, in a stark contrast to the facilitated pathways during the week.
• Repatriation to social services and rehabilitation centres is bottlenecked by entrenched 5-day working patterns.

For stroke and other services to achieve greater gains in temporal consistency, they will need to overcome cultural acceptance of ‘difference’ at weekends and at night. Otherwise quality improvement will continue to be hampered and lead to frustration among patients who cannot progress to repatriation or make therapeutic advances.

We gathered data in each London HASU at different times of day, both during the week and at weekends, providing a rich picture of the realities of organising and providing a high-performing acute care system. Our study has provided detailed information about the organisation and management of the HASU, particularly in terms of nursing (see Chapter 5). Our study suggests the following:

• Senior nursing management is crucial to a well-managed ward and high-quality patient care.
• Both HASUs and EDs are dynamic and, if the clinician responsible for organising an interaction between the CT scanner and these two environments is in charge of both the patient in the ED and the preparation of the potential bed-space in HASU after brain scanning, this task may well be performed more efficiently.
• In addition to the urgent patient assessments, our observations identify that those patients presenting to the ED who do not need an immediate input could be deprioritised, either by junior nurses in the tPA role or by the team in the radiology department.
• Senior stroke nurses working in the ED (and controlling the HASU bed space) may be more aware of the potential for this deprioritisation to result in poorer and slower care, and so manage both the urgent and the non-urgent pathways more effectively than junior nurses with less awareness.
• Unsurprisingly, a nurse who is acting as both ward manager and tPA nurse is able to manage transitions well, but they neglect the management of essential interventions, such as dysphagia screening.
• Patients who are not eligible for thrombolysis could be perceived as less urgent, either by junior nurses in a tPA role or by, for example, radiology: we showed that a senior nurse manages this process better for non-thrombolysis patients.

Our finding that managerial nursing seniority varies between weekdays and weekends and between day and night is novel, and has broad implications. We did not find that nurse-in-charge seniority had an effect on 3-day and discharge mortality in consort with studies looking at medical specialist intensity,31 which could be interpreted as consistent quality. A contrasting interpretation of these findings, however, is that staff are able to ‘step up’ in junior roles or ‘rescue’ patients in particularly serious situations. However, some authors, such as Dixon-Woods,96 have cautioned that normalisation of these workarounds as a way of adapting to staff shortages and bed pressures can be an inadequate defence against patient safety threat when staff are inexperienced or undermanaged. Regular use of stretched junior staff may also lead to unforeseen consequences, such as that being constantly under strain is normal and valuable, rather than a sign of mismanagement.96 Therefore, stroke services should not interpret our results as evidence that wards can be equally well managed by junior nurses, but that infrequent use of junior staff as subtitutes can be safe, but should not be normalised.

An example of this is to look at processes rather than outcomes. Indeed, we did find that senior nurses in charge of the ward were more likely to ensure dysphagia screen assessment unless also working as thrombolysis nurses (see Table 16) than junior colleagues. Other studies have also shown the important relationship between well-trained nursing staff, dysphagia and mortality.87 Without long-term mortality data, our ability to perceive an impact on patient outcomes is limited. However, other studies have found that missed dysphagia screening predicts higher odds of pneumonia, severe disability, discharge to long-term care and 1-year mortality.97 Furthermore, considered in conjunction with our findings about reduced therapist provision over the weekend, the risk of pneumonia and, therefore, long-term poor outcomes, may be further increased: a study of stroke patients found that delays in dysphagia screening and speech and language therapy dysphagia assessment were associated with a higher risk of pneumonia, with an absolute increase in the incidence of pneumonia of 1% per day of delay.89

Our novel findings about this inpatient setting may have generalisable implications for 7-day working and bed management more widely. For example, the observed extension of nursing roles to create continuity could have widespread implications for NHS recruitment and training in the transition to 7-day services. Strategies that we found to be important included creating ward capacity, staff acting up to other roles and achieving a degree of self-sufficiency in making thrombolysis decisions. The flexible use of adjacent ward space to create free beds, and the staff prioritisation of new patients and those ready for discharge, is consistent with existing literature, suggesting that emergency room staff anchor working practice around admission and discharge possibilities.98

The second implication is that we found evidence of no time-of-admission effect across the week on early outcomes in acute stroke patients admitted to a London HASU. We also found no evidence of an effect in terms of rapid access to brain scanning, stroke nursing care and thrombolysis in London HASUs. Other quality-of-care measures did significantly vary across the week in London HASUs. Therefore, in terms of the outcomes considered here, and for ‘front-door’ quality-of-care measures, the centralised model in London would seem to be more effective at providing 24/7 care. Several issues are worth bearing in mind. First, our study focuses on patients admitted to London HASUs only, not other hospitals in London; our data suggest that 6% of acute stroke patients in London are not treated in a HASU. Our focus on London HASUs was deliberate, as the aim of our study was to evaluate if they operate 24/7 care, but it means that our findings for London HASUs should not be generalised to all stroke patients in London. Indeed, there is evidence that quality of care is lower for the 6% of acute stroke patients in London not treated in a HASU than for those who are treated in a HASU.41,99 Hence, better adherence to HASU referral protocols in these patients is likely to mean that the quality of care that they receive will increase. Another issue is that the centralisation of acute stroke services in London was not without cost; the additional cost required as a result of the higher cost per bed-day in a HASU was estimated at £20M. With this additional level of funding, it might be expected that there should be little or no variation in quality of care and outcomes across the week in London. There is some evidence that the reorganisation in London was cost-effective, but further analyses accounting for the size of the up-front investment, the relatively high costs per day of hyperacute stroke care, the impact on mortality and functional outcome, and the lifetime costs incurred by the NHS, social services and families caring for stroke survivors at different levels of functional outcome would be helpful.

Implications for the study of temporal variation in acute stroke services

There is a large literature examining weekend effects in health care across a range of clinical areas (see Chapter 1). In agreement with more recent studies22 we found that (1) there is no significant temporal variation in HASU care in London in all but a few clinical variables; (2) mortality is not affected by time and day of admission when controlling for baseline patient characteristics and case mix; and (3) temporal variation in a wider range of variables should be measured.22 The study of temporal variation is restricted by reliance on routinely collected data sets, such as the SSNAP, that themselves enshrine some of the cultural norms of daytime, 5-day working in the metrics relating to consultant and therapist contact. In the case of stroke, the SSNAP data set provides a more accurate record of stroke patients’ clinical interventions and outcomes than other hospital data, but has not shown more severe variations in outcome than other hospital data sets.100 We suggest that:

• other indexes of quality should be derived from patient-centred principles, and assessed for temporal variation
• staff in a successful system work to fulfil the commitments of their audited service standards, and this has driven temporal consistency in London’s HASUs in the metrics relating to ‘front-door’ provision
• temporal variation remains further along the patient pathway and may influence long-term patient outcomes
• assessment of temporal variation for improvement is limited when success or quality are being assessed by what happened, rather than assessing whether or not potential risks were taken, or whether or not the service was optimal.

This has been highlighted in cases of grave misconduct, such as the Morecambe Bay investigation, where the reliance on ‘high-level data may not reveal underlying risks’ (Reproduced with permission from Morecambe Bay Investigation copyright 2015. The Report of the Morecambe Bay Investigation101). Another way to characterise this is the over-reliance on ‘hard metrics’, such as incidents, and not enough attention to ‘soft metrics’, such as cultural impediments and social practices, as identified by senior leaders of health systems.102 We hope that the results of this report contribute to soft intelligence in striving to meet the goals for 7-day working.

Strengths and weaknesses

We gathered data in each London HASU at different times of day, both during the week and at weekends, providing a rich picture of the realities of organising and providing a high-performing acute care system. In terms of our analyses of how temporal consistency was and was not achieved, our main strength was observing and comparing how eight sites organised themselves in different ways to meet the same standards. Furthermore, we collected in-depth qualitative data collected at all times of the day and week, to analyse a large centralised acute stroke system that has been demonstrated to deliver better care and outcomes. This affords generalisability to our results.

In our analyses of whether or not London HASUs generate temporal consistency in terms of clinical outcomes and processes, our main strength is the large number of data used, which contains detailed audit data, including patient characteristics, clinical processes and outcomes, as well as a unique nursing rota data set.

Unlike previous studies (see our literature review in Chapter 1, The ‘weekend effect’ and 7-day working policies), we have taken a critical approach to temporal variation and its measurement, developing our own variables, such as whether or not the roles of nurse in charge and thrombolysis nurse were fulfilled by the same person. Our outcomes were stroke mortality and disability, whereas previous studies have focused on mortality. The rich set of patient characteristics in the data set meant that we could control for patient factors likely to affect quality of care and outcomes that vary by day and time of admission across the week.

There were several limitations to the study. First, we were unable to measure long-term outcomes, as our request for these was not granted. Mortality data in the SSNAP are currently available only for patients who are in hospital and, therefore, to reduce the risk of bias, we measured mortality at 3 days after admission, when most patients will still be in hospital. Three-day mortality has been used in previous studies to evaluate the centralisation of acute stroke services in London. Similarly, long-term functional outcome data are not available in the SSNAP, and so the long-term functional outcome was measured by mRS score at the end of the inpatient spell. This will be improved with the recent addition of a Commissioning for Quality and Innovation payment requiring completion of 6-month reviews. This is measured at different points in time for different patients, so to control for this we included an indicator for number of days after admission at which this outcome was measured.

We did not gather any (qualitative) data in hyperacute stroke services operating within a different service model (whether centralised or non-centralised). The lack of a comparator (e.g. a centralised model of care) limited our confidence that our findings explain 24/7 care per se with respect to our quantitative analysis.

Second, we did not interview all relevant professions within the studied organisations (e.g. pharmacy, emergency medical practitioners). Therefore, our perspective on important working relationships beyond the HASU was based on HASU staff perceptions, although they were supported by our own observations, particularly of the ED co-ordination. Although we had an interdisciplinary research team, we could have gained from training a patient researcher to conduct some of our interviews and observations. Finally, these services develop constantly, and some aspects of provision, such as staffing levels, are likely to have changed.

Furthermore, there are specific limitations relating to the SSNAP data set. Although case ascertainment (the selection of patients for the data set) in the SSNAP was 90% during the time period of our study, these data might not be representative of all stroke patients. Although analyses of hospital administrative data to investigate weekend effects in stroke have been undermined by evidence of variations in inaccurate coding across the week, SSNAP data were collected on a voluntary basis by hospitals and we cannot exclude the possibility of inaccurate or selective reporting. Particularly problematic for our study would be if this bias was more likely to vary by time of admission.

Although the richness of our data set means that we have been able to control for confounding factors, we cannot exclude the possibility of confounding due to unobserved patient characteristics. Although the sample size of our study is large, when evaluating quality of care and outcomes across the week the number of observations in each of the 42 time periods was relatively small. We cannot exclude the possibility that this resulted in wide CIs around the adjusted predicted probabilities in each time period, making the analysis less likely to show significant variation.

Recommendations for research

The London HASUs were an attempt to build a 24/7 service, and we have shown that these were built onto 9-to-5, 5-day models of delivery, creating a hybrid that is demonstrated in the temporal consistencies and inconsistencies of its processes and outcomes. There is now an opportunity to refine this model to achieve greater levels of consistency. Research is needed to discover the best patterns for therapeutic coverage, rota lengths, ward rounds, etc. The Stroke Sentinel National Audit Programme suggests that the organisational factors we have identified as being important in achieving temporally consistent outcomes, such as daily consultant ward rounds and differentiated junior and senior nursing roles, are not replicated elsewhere in the UK.103 Therefore, further research would help to further inform how 24/7 acute stroke services ought to be designed in the future to maximise patient outcomes in a cost-effective manner. Researchers also need to examine other efforts to deliver clinical interventions 24/7 in stroke and other clinical settings. In-depth analysis of the interdependencies that influence 24/7 delivery of care, both within and beyond the host hospital, would be of value.

Future research into temporal variation will continue to be based, at least in part, on clinical audit data such as SSNAP data. Although we have outlined the limitations of this resource, its accuracy and coverage make it a unique and invaluable source of data. Researchers using these data should consider absolute time intervals rather than binary fulfilment of the SSNAP criteria, as well as patterns of timing (e.g. clustering and limit-stretching periods of higher clinical risk), to accurately visualise temporal variation by times of admission. In addition, researchers should collect variables in accordance with their own values and patient-centred indicators of quality, such as sedentary periods for patients, management of fluid balance, impaired swallow function and avoidable delays in repatriation, and assess those for temporal variation. Outcomes other than mortality and mRS score that have meaning to patients should be linked and incorporated.

We suggest that new types of temporal variation questions should be asked of stroke care, based on patients’ needs, taking a wider approach to quality. The key targets for clinical improvement lie in looking at cultural norms and practices in the hospital outside the HASU as well as stroke units, rehabilitation centres and other repatriation routes for patients. More research into optimal time frames for therapies and other interventions rely on the availability of longer-term morbidity data and the capturing of information about what type of intervention is being made by therapists at each contact with patients. Discussions about staff rotas should be had on an interprofessional basis, so that ideas about when peaks and troughs of activity will fall will be shared.

The methods we have employed could be usefully used to understand performance in more focused analyses of different service models in different locations. Further research would be beneficial to evaluate the impact of stroke admission at different times of the week on longer-term mortality and disability outcomes, and to investigate the relationship between quality of care and outcomes and if this relationship varies by time of admission. Further research would also be useful to investigate the reasons why for some standards, care in London HASUs was constant across the week, irrespective of day and time of admission, but for others it was not. In addition, accounting for the organisational factors at the stroke unit level could explain an important part of the variation in quality of acute stroke care and outcomes by day and the time of admission in London HASUs. This research would help to further inform how acute stroke services ought to be designed in the future to maximise patient outcomes in a cost-effective manner.

Conclusions

Movement towards temporal consistency in health care is part of UK policy and the research basis for organising this movement is developing. Part of creating temporal consistency will be in the design of services, including staffing, targets and patient pathway design. Our study has shown that NHS staff are adept in learning how to meet targets and can achieve new standards that save lives. The attention to tight, ambitious targets is what enables meaningful change. Enshrining cultural values that are discordant with temporal consistency within targets are not and have financial implications (improving therapy services at weekends will take a financial investment and not just changes to rotas). Mixed-methods studies such as this show that temporal consistency is possible and how it can be achieved. The measurement of temporal consistency should acknowledge how services are organised and not just rely on routinely collected or audit data, as this is focused on outcomes.