Variation in quality of acute stroke care by day and time of admission: prospective cohort study of weekday and weekend centralised hyperacute stroke unit care

What is known about this topic?

• There is conflicting evidence whether patients admitted at weekends have higher or lower quality of acute stroke care and better or worse outcomes than those admitted at other times of the week.
• Recent analyses have shown that analyses of weekend compared with weekday effects or in-hours effects compared with out-of-hours effects may be flawed, as they do not account for variations by day of the week and time of day.
• The centralisation of acute stroke services in London was associated, on average, with higher likelihood of providing evidence-based care and greater reductions in mortality.

What this analysis adds

• London HASUs operate a uniform service across the week, with respect to rapid access to stroke nurse review, brain scans and administration of thrombolysis to eligible patients.
• Three-day mortality and disability at hospital discharge do not vary by day and time of admission in London HASUs.
• Other aspects of care are not constant across the week in London HASUs.
• Costs of acute stroke care in London HASUs are higher for patients admitted at the weekend than for those admitted during the week.

Introduction

There is conflicting evidence whether or not patients presenting with acute stroke symptoms receive lower quality of care and have worse outcomes if admitted to hospital outside normal weekday working hours or at weekends (the so-called ‘weekend effect’). Some studies have shown that acute stroke patients admitted at weekends have lower quality of care and higher mortality,56 whereas others have shown the opposite,10,12,13,57 although there is little evidence in the context of acute stroke care. Evaluation of these studies is further complicated by recent evidence that stroke incidence reporting at the weekend may be unreliable in older studies,58 although this is based on data on patients admitted to a single hospital trust. Recent work based on data from the SSNAP data set further found that care quality and outcomes in acute stroke vary across the week, and concluded that binary comparisons of weekend and weekday, or of in-hours and out-of-hours, processes and effects oversimplify more likely variations by day of week and time of day.22 Furthermore, no studies have investigated the impact of time of admission on disability following a stroke.

If there is lower quality of care and there are worse outcomes at the weekend, then these could be linked to reduced staffing levels.59 Nurse staffing levels at weekends have been shown to be a significant predictor of mortality from acute stroke,60 whereas evidence from the USA suggests that specialised stroke units, with round-the-clock availability of specialist stroke teams and rapid access to imaging and thrombolysis, reduce variation in quality of care and outcomes across the week.61–63 Following these findings, the aim of this study was to investigate variations in the quality of acute stroke care and outcomes by day and time of admission in London HASUs (objectives 1 and 2). We used national audit data for all patients in London HASUs who had a stroke during a 12-month period recorded by the SSNAP.64 We hypothesised where there would be non-significant variation across the week in care quality measures in London HASUs and that this would also translate into non-significant variation in outcomes.

Methods

This section is based on a paper by Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. The text below includes minor additions and formatting changes to the original text.

Data and measures

As outlined in Chapter 2, Quantitative data collection, we used anonymised patient-level data from the SSNAP for all patients in London HASUs with a primary diagnosis of stroke between 1 January and 31 December 2014.

Statistical analysis

We ran patient-level logistic regressions by regressing each measure against the time period of admission. For LOS, we used parametric survival models (modelled as time to event of discharge), assuming a log-normal survival distribution. In every model we controlled for baseline patient and case mix characteristics, month of admission (12 categories) and hospital trust. When analysing mRS scores 0–2 compared with 3–5 at the end of the inpatient spell, we additionally controlled for the number of days after admission the mRS score was measured. We were unable to do this for the analysis of mRS score 0–2 compared with 3–6, as date of death was not available. We tested for statistically significant variations across the week using Wald tests and reported the results as joint p-values under the null hypothesis that the regression coefficients for every time period relative to the omitted time period were zero. We calculated the average predicted probability of each outcome (predicted median LOS in the case of the LOS variables) in each time period controlling for the covariates. Patients admitted with a diagnosis of acute stroke in London who were not treated in a HASU were excluded (6% of all London patients in our data set were not treated in a HASU). p-values < 0.05 were considered to be statistically significant. Data on National Institutes of Health Stroke Scale (NIHSS) score, a validated measure of stroke severity on a scale from 0 (no stroke symptoms) to 42 (severe stroke), were available for 93% of patients in London HASUs. Owing to the extent of missing NIHSS data, in our main analysis we controlled for stroke severity using level of consciousness on arrival at the hospital (one component of NIHSS, which was available for all patients in London HASUs). We then re-ran all analyses controlling for NIHSS on arrival at the hospital on the smaller sample, instead of level of consciousness on arrival. The findings using NIHSS score on arrival were qualitatively the same and are presented in the Report Supplementary Material 2, Figures S1–6.

Cost analysis

To investigate the costs of acute stroke care in London HASUs on different days and at different times of admission, we explored whether or not mean costs per patient in the HASU varied by time period of admission. Our cost perspective was the HASU. We examined costs associated with variations in LOS in the HASU. In a secondary analysis, we also included total LOS in the hospital. We re-ran the LOS models, described above, using ordinary least squares and computed adjusted mean HASU and total LOS by time period of admission (although mean costs are affected by skewness and median costs are not, it is the arithmetic mean costs that are most informative for health-care policy decision).66 We also examined costs associated with variations in the non-time-dependent quality-of-care measures described in Chapter 2 (see Box 1) for patients in London HASUs (whether or not the patient had brain imaging; was admitted to a stroke unit; had dysphagia screening; was assessed by a nurse trained in stroke management, or a stroke specialist consultant physician, physiotherapist, occupational therapist or a SLT). Note that the reason for focusing on the non-time-limited measures was that costs are driven by whether or not the patient received these processes, rather than whether or not they received them within a given time period. We also included receipt of thrombolysis (administration of intravenous thrombolysis to eligible patients). As it was simpler to identify trends, we focused on variations between the four broad time periods across the week (Monday to Friday, 08.00 to 19.59; Monday to Friday, 20.00 to 07.59; Saturday and Sunday, 08.00 to 19.59; and Saturday and Sunday, 20.00 to 07.59). Measures for which there were variations by time period of admission were included in the cost analysis. In this case, we multiplied the incremental volume of resource use associated with each measure for the three other time periods compared with Monday to Friday 08.00 to 19.59 by its unit cost, taken from two published economic evaluations of acute stroke care in London HASUs67,68 and inflated to 2017/18 prices.69 We assumed that unit costs of the non-time-dependent measures did not vary by the time period of admission, because these are typically provided during normal working hours (see Chapter 6, What this analysis adds).

Results

This section is based on a paper by Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. The text below includes minor additions and formatting changes to the original text.

The study cohort comprised 7094 patients from eight London HASUs. The number of admissions varied across the week: admissions peaked during the day then fell at night; there were more admissions during the day through the week than during the day at the weekend; there were similar numbers of admissions during the night each day; and the highest number of admissions was during the day on Monday (Figure 3).

FIGURE 3 Number of admissions in London HASUs across the 42 time periods in the week. This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

The mean number of admissions per HASU per week in each of the 42 4-hour time periods ranged from 1.03 to 1.44. There was slightly higher proportion of men than women, the mean age was 72 years and 38% of patients were non-white (Table 5). London HASUs case mix was characterised by a large proportion of people with congestive heart failure, hypertension and diabetes. Twenty-two per cent of patients had at least moderate disability according to their mRS score before stroke and 84% of patients arrived at the hospital in an ambulance. Thirty-nine per cent of patients were admitted to the hospital within 3 hours from onset of stroke symptoms, but for 29% of patients the time of symptom onset was unknown.

There was no significant variation in care quality across the 42 time periods in any of the measures relating to brain scanning, stroke nursing care and thrombolysis in London HASUs (all p-values > 0.05) (Figure 4).

FIGURE 4 Quality of care across the 42 time periods in the week: measures linked to performance standards for London HASUs. (a) Brain scan within 1 hour (p = 0.1372); (b) brain scan within 12 hours (p = 0.1757); (c) dysphagia screen within 4 hours (p = 0.2217); (d) nurse assessment within 24 hours (p = 0.3318); (e) administration of intravenous thrombolysis to eligible patients (p = 0.9233); and (f) door-to-needle time < 1 hour (p = 0.5400). This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

For all the other quality-of care-measures, there was significant variation by time period of admission across the week (all p-values < 0.01). There were three patterns of variation. First, variation by time of day but not day of the week was observed for assessment by a stroke specialist consultant physician within 12 hours and within 24 hours in London HASUs, and admission to a stroke unit within 4 hours (Figure 5).

FIGURE 5 Quality of care across the 42 time periods in the week in London HASUs: variation by time of day but not day of the week. (a) Assessment by a stroke consultant (stroke physician < 12 hours, p < 0.0001; stroke physician < 24 hours, p = 0.01); and (b) admission to a stroke unit within 4 hours (stroke unit admission < 4 hours, p < 0.0001). This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

With this pattern, similar variations during the day were found each day of the week. Second, variation by day of the week but not time of day was observed for assessments by a physiotherapist, occupational therapist and SLT within 72 hours in London HASUs (Figure 6).

FIGURE 6 Quality of care across the 42 time periods in the week in London HASUs: variation by day of the week but not time of day. (a) Physiotherapist assessment within 72 hours (p < 0.0001); (b) occupational therapist assessment within 72 hours (p < 0.0001); (c) swallow assessment by a SLT within 72 hours (p < 0.0001); and (d) communication assessment by a SLT within 72 hours (p < 0.0001). This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

With this pattern, care quality was worse for patients admitted on a Friday. Third, variation by time of day and day of the week was observed for therapist assessments within 24 hours (Figure 7). With this pattern, there was variation during the day on Monday to Friday and care quality was worse at weekends.

FIGURE 7 Quality of care across the 42 time periods in the week in London HASUs: variation by time of day and day of the week. (a) Physiotherapist assessment within 24 hours (p < 0.0001); (b) occupational therapist assessment within 24 hours (p < 0.0001); and (c) communication assessment by a SLT within 24 hours (p < 0.0001). This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

There was no significant variation in outcomes across the 42 time periods in London HASUs (all p > 0.05) (Figure 8).

FIGURE 8 Outcomes across the 42 time periods in the week in London HASUs. (a) Mortality at 3 days (p = 0.9230); (b) mRS score 3–6 (p = 0.1777); and (c) mRS score 3–5 (p = 0.2015). This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

There was significant variation in LOS across the 42 time periods, in terms of both HASU LOS and total inpatient LOS (p < 0.001 for HASU LOS and p = 0.005 for total LOS in hospital) (Figure 9). Median HASU LOS varied between 2.6 and 3.6 days across the 42 time periods. It was difficult to detect a trend by day and time of admission in HASU LOS and inpatient LOS.

FIGURE 9 Length of stay across the 42 time periods in the week in London HASUs. (a) LOS in HASU (p < 0.0001); and (b) LOS in hospital (p < 0.0001). This figure is adapted from Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. This figure includes minor additions and formatting changes to the original figure. (Figure not reproduced here; see the original article.)

Results using the four time period specifications (Table 6) were broadly similar to those with the 42 time periods, but pooling time periods meant that the extent of variation during the week for some of the quality-of-care measures was reduced (see Report Supplementary Material 2, Tables S1 and S2, for unadjusted figures and p-values, respectively). In these analyses, there was no significant variation in London HASUs in quality-of-care measures linked to specialist stroke nurse assessments, rapid access to brain scans and administration of thrombolysis to eligible patients for London HASUs, nor was there in the outcome measures. LOS varied significantly for London HASUs: pooling time periods more clearly indicates longer LOS among patients admitted at the weekend.

Cost analysis

Results were similar when controlling for NIHSS score on arrival at hospital, instead of level of consciousness, on the smaller sample of patients with non-missing NIHSS data: results with p-values < 0.05 and trends across the week were unchanged (see Report Supplementary Material 2, Figures S1–S6 and Table S3).

Variations in the non-time-dependent quality-of-care measures by the four time periods are shown in Figure 10).

FIGURE 10 Non-time-dependent quality-of-care measures across four periods in the week in London HASUs. Figures are average predicted probabilities of each measure in each time period controlling for the covariates. We tested for statistically significant variations across the four time periods using Wald tests and reported the results as joint p-values under the null hypothesis that the regression coefficients for every time period relative to the omitted time period were zero (p-values in parentheses). All patients received a brain scan in every time period. n/a, not applicable. (Figure not reproduced here; see the original article.)

In contrast to the findings for the time-dependent versions of these measures in Table 6, Figure 10 shows that > 90% of patients receive every measure and that there is little variation across the four time periods. We also note from Table 6 that there is no variation in administration of intravenous thrombolysis across the four time periods. We conclude from these data that the costs of acute care in London HASUs, with respect to these measures, is unlikely to vary on different days and at different times of admission. Table 6 shows significant variation in median LOS for London HASUs, with longer HASU and total LOS among patients admitted at the weekend. Table 7 shows a similar trend for mean LOS (note that the mean values in Table 7 are higher than the corresponding median values in Table 6, indicating skewed data).

In Table 8 we compute the cost implications of the difference in LOS. Focusing on differences in mean LOS, patients who were admitted between 08.00 and 19.59 at the weekend were, on average, £166 more costly to treat in the HASU (£668 when including total LOS) than those admitted between 08.00 and 19.59 on a weekday. Those who were admitted between 20.00 and 07.59 at the weekend were on average no more costly than those admitted between 08.00 and 19.59 on Monday to Friday (£445 more costly when including total LOS). For those admitted between 20.00 and 07.59 on a weekday, the cost difference per patient was small compared with those admitted between 08.00 and 19.59 on a weekday.

Discussion

This section is based on a paper by Melnychuk et al.65 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/. The text below includes minor additions and formatting changes to the original text.

Principal findings

In our study, we found no evidence for an admission effect across the week on early outcomes in acute stroke patients admitted to a London HASU: 3-day mortality and mRS score at hospital discharge did not vary by day and time of admission in London HASUs. This is consistent with a recent study based on administrative data in the UK.34 The study34 found a steady reduction in in-hospital mortality difference between weekday and weekend stroke admissions in 2008–14 across England, and that this difference is no longer statistically significant in 2014.

There was also no variation by day and time of admission across the week 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 and three patterns of variation were detected: (1) by time of day, but not day of the week; (2) by day of the week, but not time of day; and (3) by time of day and day of the week. LOS was longer among patients admitted to London HASUs at the weekend. We hypothesised that there would be non-significant variation across the week in care quality measures in London HASUs and that this would translate into non-significant variations in outcomes. The lower variation in care quality measures across the week in London HASUs was confirmed, but only with respect to ‘front-door’ measures of acute stroke care. With respect to the health outcomes, there was no variation in mortality at 3 days and disability at hospital discharge by day and time of admission across the week in London HASUs. This is consistent with previous studies showing that timely access to thrombolysis is associated with good stroke outcomes.70

We found that patients who were admitted at the weekend were on average more costly than those who were admitted during the week because of their longer LOS. When incorporating total LOS, the additional mean cost per patient was £445–668, depending on when the patient was admitted at the weekend. Those who were admitted between 20.00 and 07.59 on a weekday had similar costs to those who were admitted between 08.00 and 19.59 on a weekday.

Strengths and weaknesses

The main strength of our study is the rich data set we have used, containing detailed information on quality of care, outcomes and patient characteristics. We have examined whether or not time of admission was related to quality of care using a comprehensive set of indicators from across the acute stroke care pathway. Most of the measures were from a pre-existing set of national acute stroke care indicators, and those that were added had more stringent time constraints to reflect the time-critical nature of acute stroke care. Our outcomes were stroke mortality and disability, whereas previous studies have focused on mortality.6,25,34,71–73 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 are several weaknesses. First, although case ascertainment in the SSNAP was 90% during the time period of our study, these data might not be representative of all stroke patients. Second, although analyses of hospital administrative data to investigate weekend effects in stroke may have been undermined by evidence of variations in inaccurate coding across the week,58 in the SSNAP data are inputted voluntarily 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. Third, we were unable to measure long-term outcomes, as these were not available in the SSNAP. 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,35 but the focus in our study on in-hospital mortality only is a further limitation. Similarly, long-term disability data are not reliably collected in the SSNAP, and so disability was measured by the mRS at the end of the inpatient spell. Fourth, 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 or staffing levels. Fifth, although the sample size of our study is relatively large (n = 7094), when evaluating quality of care and outcomes across the week the number of observations in each of the 42 time periods was considerably smaller (mean of 169). We cannot exclude the possibility that this number of patients resulted in wide confidence intervals (CIs) around the adjusted predicted probabilities in each time period, making it less likely to show significant variation in the measures evaluated. It is difficult to provide sample size calculations for statistical analyses between 42 groups (time periods). However, when we re-ran our analyses of quality of care and outcomes across the four pooled time periods in the week in London HASUs, the results were broadly similar, and this provides some reassurance about the statistical power of our analyses. Sixth, we acknowledge that previous studies have identified that improvements in outcomes following acute stroke in England have been shown to be statistically unrelated to the centralisation of stroke services in London, but are consistent with an overall national focus on improving stroke services.34 Further research examining whether or not the findings seen in the present study for London HASUs were also achieved in the rest of England would be beneficial.

Comparison with other studies

There is a large literature examining weekend effects in health care across a range of clinical areas.74 In acute stroke, there is conflicting evidence on whether patients admitted at weekends have higher or lower quality of care and better or worse outcomes.6,9,40,71,72,75 However, recent analyses have shown that care quality and outcomes in acute stroke vary across the week, and that comparing weekend with weekday or in-hours effects with out-of-hours effects is flawed, as it does not take into account variations by day of the week and time of day.22 This study,22 using the same data set as ours, but from an earlier time period and analysing the whole of England and Wales, found that quality of care varied across the entire week, not only between weekends and weekdays, with a number quality-of-care measures showing different patterns of variation over the week. What our study adds is analyses of variation in quality of care and outcomes in London HASUs by separately following the centralisation of acute stroke services in London in 2010, which has been shown to increase the quality of care and outcomes overall.35,38,41

Implications

There are several implications of our study. The first is that London HASUs appear to operate a uniform service across the week with respect to some, but not all, aspects of acute stroke care. Performance standards originally set by Healthcare for London stipulated that London HASUs should operate a 24/7 service with respect to first assessment by a stroke nurse, rapid access to brain scans and administration of thrombolysis to eligible patients; our findings show that London HASUs do operate a 24/7 service with respect to these measures. However, for other less time-critical measures, such as senior stroke physician assessment within 24 hours and therapist assessments within 72 hours, we found significant variation by day and time of admission in London HASUs. This suggests that some performance standards, such as ‘front-door’ interventions, may be emphasised more than others. The second implication is that our study focuses only on patients admitted to London HASUs and not other hospitals in London; our data suggest that 6% of acute stroke patients in London are not treated in a HASU. However, some of these patients will not have been eligible for HASU care because of greatly delayed presentation or identification of stroke, and others will have had a stroke after surgical procedures or in another context which precluded their admission to a HASU. Our focus on London HASUs was deliberate, as the aim of our study was to evaluate the HASU model. However, it means that our findings for London HASUs should not be generalised to all patients in London. Indeed, there is evidence that quality of care is lower for acute stroke patients in London not treated in a HASU than for those who are.38 Second, the London model may not apply to services operating in other areas, in particular rural settings, where the greater travel times make centralisation of this kind challenging.76 This means that potential benefits of the London model, in terms of 24/7 care, are unlikely to be achieved nationwide. Third, the centralisation of acute stroke services in London was estimated to occur at an additional cost of £20M, allocated to cover the increased cost per bed-day in a HASU.77 With this additional level of funding it might be expected that the quality of care in London should improve, although whether or not it should produce less variation in quality of care and outcomes across the week in London is unclear. There is some evidence that the reorganisation in London was cost-effective,67,68 but further analyses accounting for the size of the upfront investment, the relatively high costs per day of hyperacute stroke care, the impact on mortality and disability, and the lifetime costs incurred by the NHS, social services and families caring for stroke survivors at different levels of disability, would be helpful.

We evaluated the costs of acute stroke care in London HASUs on different days and at different times of admission. We found that patients who were admitted at the weekend were on average more costly than those who were admitted during the week, due to their longer LOS. Those who were admitted between 20.00 and 07.59 on a weekday had similar costs to those who were admitted between 08.00 and 19.59 on a weekday.