Hospital Mortality Monitoring of... · 2020-06-09 · NEQOS Hospital Mortality Monitoring report 30: April 2015 to March 2016 October 2016 (FINAL) Page 6 1.8 It is expected that NHS

Hospital Mortality Monitoring

Report 30: April 2015 to March 2016

October 2016

undertaken by

North East Quality

Observatory Service (NEQOS)

on behalf of

NEQOS subscribers

NEQOS is jointly operated by Northumberland, Tyne and Wear

and South Tees Hospitals NHS Foundation Trusts

Ridley House, Henry Street, Newcastle upon Tyne, NE3 1DQ

0191 245 6708

www.neqos.nhs.uk

[email protected]

http://www.neqos.nhs.uk/

mailto:[email protected]

NEQOS Hospital Mortality Monitoring report 30: April 2015 to March 2016 October 2016 (FINAL)

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Confidential Contains commercially sensitive information © 2016, NTW and South Tees NHS Foundation Trusts on behalf of North East Quality Observatory Service (NEQOS)


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Contents

Contents ................................................................................................................................................................. 3

Executive Summary ................................................................................................................................................ 4

1. Context and background .......................................................................................................................... 5

2. Methods and measures ............................................................................................................................ 6

3. Trust-level Comparisons of SHMI and HSMR ............................................................................................ 7

Figure 1: SHMI funnel plot using 95% Control Limits and adjustment for over-dispersion for April 2015

to March 2016 .......................................................................................................................................... 7

Table 1: SHMI, total discharges, observed and expected deaths, % aged 75+ and banding for April

2015 to March 2016 ................................................................................................................................. 7

Figure 2: HSMR by acute trust for July 2015 to June 2016 ....................................................................... 8

4. Hospital mortality through time for Trusts in the North East .................................................................. 9

Table 2: SHMI, observed and expected deaths, for 2014/15 and 2015/16 .............................................. 9

Figure 3: SHMI and crude mortality for NCNTW trusts .......................................................................... 10

Figure 4: HSMR and palliative care for NCNTW trusts ............................................................................ 11

Figure 5: Mortality indices for DDT trusts............................................................................................... 12

Figure 6: Average SHMI and HSMR by Acute Trust, April 2013 to March 2016 ..................................... 13

Figure 7: Trend in palliative coding, SHMI contextual indicator, June 2013 to March 2016 .................. 13

5. Seven day services .................................................................................................................................. 14

Table 3: Weekday and weekend mortality (HSMR), July 2015 to June 2016 ......................................... 14

6. SHMI by CCS bundle ............................................................................................................................... 15

Table 4: SHMI CCS bundles summary by Acute Trust, April 2015 to March 2016 .................................. 15

7. SHMI for selected CCS groups ................................................................................................................ 15

Figure 10: SHMI for selected CCS groups (code) .................................................................................... 16

8. Comparison of SHMI by Clinical Commissioning Group ......................................................................... 17

Table 4: SHMI by CCG for January to December 2015............................................................................ 17

Figure 11: Place of death by CCG, April to March 2016 .......................................................................... 17

9. Comorbidity coding ................................................................................................................................ 18

Figure 12: Number of co-morbidities per spell, April 2013 to March 2016 ............................................ 18

10. Conclusions ............................................................................................................................................. 18

11. Abbreviations and glossary ..................................................................................................................... 19

12. Appendix ................................................................................................................................................. 20


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Executive Summary

Overview of report

This report presents analysis showing the SHMI and HSMR mortality indices: at a high level for trusts identifying variation from the norm (outliers); then showing trends through time; and then using more granular analysis to describe contributing factors.

Section 1 provides information on the latest publications on mortality. Sections 2 is concerned with methodological details. Sections 3 to 9 present analysis which gives a comprehensive view of mortality across the region:

3. Trust-level SHMI and HSMR outliers 4. Hospital mortality through time for Trusts 5. Seven day services 6. SHMI by broad clinical area 7. SHMI for selected clinical conditions: in this report these are pneumonia, acute bronchitis,

septicaemia and urinary tract infection 8. Comparison of SHMI by Clinical Commissioning Group 9. Comorbidity coding

The monitoring of hospital mortality as a means of providing assurance about the quality care provided by NHS Trusts, and as a potential means of informing quality and safety improvement work, remains controversial. As was confirmed in the Single Oversight Framework, (published in September 2016) NHS Improvement, the Care Quality Commission and other NHS organisations will continue to use mortality indicators as part of a broader assessment of quality of care. Conclusions

In the period April 2015 to March 2016 two trusts have ‘higher than expected’ Summary Hospital-

level Mortality Indicator (SHMI) mortality. North Tees and South Tyneside have SHMIs of 113 and

118 respectively. The Hartlepool and Stockton-on-Tees and South Tees CCGs show as SHMI outliers

for this period.

North Tees and South Tyneside are persistent outliers for SHMI. North Tees are not outlying on

HSMR: whilst the SHMI has fallen, for the Trust to be “as expected” observed mortality will have to

reduce further.

HSMRs are high for two trusts, South Tyneside and Sunderland. In South Tyneside the hospice is

affecting both SHMI and HSMR.

The increased HSMR in patients admitted at weekends compared to weekdays largely results from the reduction in the discharges being much greater than the fall in the deaths.


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1. Context and background

1.1 This is the thirtieth report for NHS organisations in the North East (NE) reviewing hospital mortality. The objective is to give providers and commissioners hospital mortality monitoring data and benchmarking to assist with assurance. The report is provided to organisations subscribing to the North East Quality Observatory Service (NEQOS) and covers the Academic Health Science Network: North East and North Cumbria (AHSN-NENC) area.

1.2 NHS Digital (previously called the Health and Social Care Information Centre) is consulting on a new digital tool and guide to support release of SHMI data and NEQOS have contributed to this consultation on behalf of the region. This is expected to be published in early 20171.

1.3 NHS Improvement (NHS I) published their Single Oversight Framework (SOF) in September 20162. The five themes of the SOF are: Quality of care (safe, effective, caring, responsive); Finance and use of resources; Operational performance; Strategic change; and Leadership and improvement capability (well-led).

1.4 Regulation of providers by NHS I will be based on an assessment that places each in one of four segments: Providers with maximum autonomy; Providers offered targeted support Providers receiving mandated support for significant concerns; Special measures.

1.5 The SOF includes an appendix listing the Quality of care (safe, effective, caring, responsive) monitoring metrics that NHS I will use and this includes mortality indicators. It is not currently known when the first publication of the metrics or the trust segmentation will be available.

1.6 Public Health England (PHE)3 and The Lancet4 have published a report on 30-day mortality after systemic anticancer treatment for breast and lung cancer in England.

1.7 PHE publishes a weekly Emergency Departments bulletin5 which gives up to date epidemiological information for a range of conditions (eg pneumonia). Mortality indicators reflect incidence of disease as well as quality of care and so this data is helpful in understanding the current pattern of mortality.

1 http://content.digital.nhs.uk/SHMI 2 https://improvement.nhs.uk/resources/single-oversight-framework/ 3 https://www.gov.uk/government/publications/chemotherapy-for-breast-and-lung-cancer-30-day-mortality 4 http://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(16)30383-7/abstract 5 https://www.gov.uk/government/publications/emergency-department-bulletin

http://content.digital.nhs.uk/SHMI

https://improvement.nhs.uk/resources/single-oversight-framework/

http://www.thelancet.com/journals/lanonc/article/PIIS1470-2045(16)30383-7/abstract

https://www.gov.uk/government/publications/emergency-department-bulletin


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1.8 It is expected that NHS Digital will publish new weekend mortality indicators as part of 7 day

services work in October 2017. The next report will consider this further.

1.9 The 2017-18 and 2018-19 CQUIN Guidance6 for sepsis was published in September 2016. The

scheme covers screening and use of antibiotics in patients with sepsis, in line with the NICE

Guidance for Sepsis (NG51)7 which was published in July 2016.

2. Methods and measures

2.1 SHMI is the hospital-level indicator which reports all deaths in hospital and all deaths that occur within 30 days of discharge from hospital across the NHS in England8. It compares the observed number of deaths with the number expected calculated from a statistical model that takes account of age, sex, method of admission to hospital, diagnosis and comorbidities.

2.2 The primary diagnosis and comorbidities are taken from the first consultant episode within the provider spell. Primary diagnosis is the main condition treated or investigated during the episode and where there is no definitive diagnosis, is the main symptom, abnormal findings or problem (represented by an R-Code).

2.3 Details of how SHMI is calculated when the primary diagnosis is an R-code (i.e. from within the ICD-10 Signs and Symptoms chapter) are given in the SHMI guidance. This methodology applies to the derivation of the Dr Foster HSMR as well as to the HSCIC’s SHMI.

2.4 SHMI was designed for non-specialist acute trusts and so trusts including community hospital services may be disadvantaged because the period of the spell is increased to include the community hospital stay. This means that deaths are more likely to occur for these trusts within 30 days of discharge due to the increase in the length of spell.

2.5 The latest tranche of data, published 22nd September 2016 covers April 2015 to March 2016. Patient level SHMI data is released allowing the calculation of VLADs by diagnosis group.

2.6 The SHMI and HSMR are extracted from the Healthcare Evaluation Data (HED) system supplied by University Hospitals Birmingham NHS Foundation Trust (UHB). HED reproduce the mortality indicators to a high degree of accuracy and NEQOS use these within this report.

2.7 This report presents the latest data using funnel plots for the cross sectional analysis of trusts. The SHMI is the ratio of observed over expected deaths, where 100 indicates that both the observed and expected deaths are the same, and is the average across England.

2.8 The funnel plot displays the SHMI on the vertical axis against the number of expected deaths (the denominator) along the horizontal axis. Trusts are identified as outliers if their SHMI value places them outside the control limits on the funnel plots. The 95% Control Limits with adjustment for over-dispersion are used for banding Trusts as ‘low’, ‘as expected’, or ‘high’.

2.9 Trends through time are presented for each trust for SHMI and the unadjusted mortality rate (Figures 3 and 5). The trends have not been statistically tested for significance (a method for doing so has yet to be agreed nationally) and so caution must be exercised in interpretation.

6 https://www.england.nhs.uk/wp-content/uploads/2015/12/ann-a-cquin.pdf 7 https://www.nice.org.uk/guidance/ng51 8 http://content.digital.nhs.uk/SHMI

https://www.england.nhs.uk/wp-content/uploads/2015/12/ann-a-cquin.pdf

https://www.nice.org.uk/guidance/ng51

http://content.digital.nhs.uk/SHMI


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3. Trust-level SHMI and HSMR outliers

3.1 Figure 1 shows the SHMI for all Trusts in England for April 2015 to March 2016, using the funnel plot adjusted for over-dispersion. Table 1 shows the SHMI, total discharges, banding and proportion of deaths that occurred in patients aged 75 or older for the relevant acute trusts in the latest tranche of data released by the HSCIC.

Figure 1: SHMI funnel plot using 95% Control Limits and adjustment for over-dispersion for April 2015 to March 2016

Table 1: SHMI, total discharges, observed and expected deaths, % aged 75+ and banding for April 2015 to March 2016

3.2 North Tees and Hartlepool is a persistent high outlier with a SHMI of 113; this is a fall from the previous figure of 117. South Tyneside are also now persistent high outliers.

3.3 North Tees is no longer an outlier for HSMR and the trust SHMI has fallen from the high of 121; however a further reduction in the observed mortality will be needed for the Trust to cease to be a SHMI outlier.

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Source: Summary Hospital-level Mortality Indicator (SHMI). Data released by the NHS Digital, Sep 2016

Provider Discharges Observed % aged 75+ Expected SHMI Category

County Durham and Darlington NHS FT 82112 3010 68.9 2916 103.2 as expected

North Tees and Hartlepool NHS FT 54080 2005 67.0 1771 113.2 Higher than expected

South Tees Hospitals NHS FT 86581 2741 64.3 2536 108.1 as expected

Gateshead Health NHS FT 36618 1449 67.4 1487 97.5 as expected

South Tyneside NHS FT 23833 1169 65.4 992 117.8 Higher than expected

City Hospitals Sunderland NHS FT 57204 2024 66.7 2060 98.3 as expected

The Newcastle Upon Tyne Hospitals NHS FT 107376 2712 56.5 2779 97.6 as expected

Northumbria Healthcare NHS FT 64828 2966 67.7 2862 103.6 as expected

North Cumbria University Hospitals NHS Trust 46481 1761 66.2 1744 101.0 as expected


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3.4 Key facts for April to March 2016 (against the same period a year ago):

16 trusts had a 'higher than expected' SHMI value compared to 16 trusts previously.

16 trusts had a 'lower than expected' SHMI value compared to 13 trusts previously.

104 trusts had an 'as expected' SHMI value, compared to 107 trusts previously.

Observed mortality for current period is 283,000, which is lower than 287,000 (same period a year ago).

3.5 Figure 2 shows the HSMR for July 2015 to June 2016, using the narrow control limits without adjustment for over-dispersion preferred by Dr Foster. South Tyneside and Sunderland are high outliers. South Tyneside’s figure continues to reflect the inclusion of St Benedict’s hospice, the trust was an HSMR outlier in the last report.

HSMR for July 2015 to June 2016

(with 99.9% and 95% control limits without adjustment for over-dispersion)

Figure 2: HSMR by acute trust for July 2015 to June 2016


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4. Hospital mortality through time for Trusts

4.1 Table 2 shows the monthly SHMI for 2014/15 compared to 2015/16. All of the trusts show a decrease in the observed deaths, despite this the SHMI shows a small increase in three trusts. This increase is explained by the expected deaths decreasing by more than the observed.

4.2 North Tees and South Tyneside are both persistent high outliers for SHMI. For North Tees the SHMI has fallen whilst there is little change shown across the 2 years for South Tyneside. For South Tyneside the presence of St Benedict’s hospice affects Trust mortality.

Table 2: SHMI, observed and expected deaths, for 2014/15 and 2015/16

4.3 In figures 3, 4 and 5 the mortality indices are shown quarterly over the last three years. There is no national agreement on the best method for testing for statistically significant trends.

4.4 The SHMI for all trusts in the North East mirrors unadjusted mortality. Unadjusted mortality varies between trusts from approximately 2% to 6%. This rate includes all deaths in hospital plus deaths within 30 days of discharge.

4.5 The quarterly charts provide a more detailed breakdown of the movement in the SHMI with individual trusts following the unadjusted mortality. Most trusts show an increase in quarter 4 of 2014/15.

4.6 The pattern for HSMR is broadly inversely related to the specialist palliative care coding rate (HSMR is sensitive to this coding whilst SHMI ignores it) and does not follow the unadjusted mortality rate.

4.7 The pattern of palliative care (PC) coding continues to show variation across the region, with Gateshead the lowest, Northumbria the highest and the coding at South Tyneside is below England (see figure 7). The South Tyneside CCG has the highest proportion of deaths in hospital (see figure 11).

2014/15 2015/16

Observed Expected SHMI Observed Expected SHMI

County Durham and Darlington NHS FT 3030 2976 102 3010 2916 103 1.4 -0.7%

North Tees and Hartlepool NHS FT 2034 1674 122 2005 1771 113 -8.3 -1.4%

South Tees Hospitals NHS FT 2803 2681 105 2741 2536 108 3.5 -2.2%

Gateshead Health NHS FT 1478 1470 101 1449 1487 97 -3.1 -2.0%

South Tyneside NHS FT 1178 997 118 1169 992 118 -0.3 -0.8%

City Hospitals Sunderland NHS FT 2064 1997 103 2024 2060 98 -5.1 -1.9%

The Newcastle Upon Tyne Hospitals NHS FT 2739 2755 99 2712 2779 98 -1.8 -1.0%

Northumbria Healthcare NHS FT 3274 3115 105 2966 2862 104 -1.5 -9.4%

North Cumbria University Hospitals NHS Trust 1828 1825 100 1761 1744 101 0.8 -3.7%

ProviderSHMI

Change

Observed

Difference


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4.8 Figure 3 shows the SHMI and unadjusted mortality rate for the trusts in the North Cumbria, Northumbria, Tyne & Wear area (NCNTW) by quarter from April 2013 to March 2016.

Figure 3: SHMI and crude mortality for NCNTW trusts

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Source: NEQOS Hospital Mortality Monitoring: Report 30

Data extracted from HED September 2016


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4.9 Figure 4 shows the HSMR and palliative care discharge rate for each trust in the NCNTW area by quarter from April 2013 to June 2016.

Figure 4: HSMR and palliative care for NCNTW trusts

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4.10 Figure 5 shows the SHMI and HSMR for the trusts in the Durham, Darlington and Tees area by quarter from April 2013 to March 2016.

Figure 5: Mortality indices for DDT trusts

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4.11 Figure 6 presents the SHMI and HSMR from April 2013 to March 2016. The methodologies for constructing the two indices are different however you would expect them to produce similar signals and for two trusts (North Tees and Newcastle) this is the case. The trust with the highest difference shows variation of 9 points. The variation between indices can be attributable to their construction, natural variation and clinical coding.

Figure 6: Average SHMI and HSMR by Acute Trust, April 2013 to March 2016

4.12 HSMR, unlike SHMI, is adjusted for discharges with a specialist palliative care code (Z515 diagnosis code or 315 specialty code). This coding provides a very limited view of palliative care in hospitals, with variation in practice across the NHS.

4.13 Figure 7 shows the rolling 12 month proportion of deaths with specialist palliative care coding per the SHMI contextual indicator. It shows the increasing level of coding in England with only Northumbria and North Tees above England. South Tyneside has fallen below England. The level of coding for North Tees has shown a marked rise over the last 18 months.

Figure 7: Trend in palliative coding, SHMI contextual indicator, June 2013 to March 2016

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Proportion of deaths with palliative care coding (rolling year)

ENGLAND South Tees

North Tees CDD

South Tyneside Sunderland

North Cumbria Gateshead

Newcastle Northumbria

Source: NEQOS Hospital Mortality Monitoring: Report 30Data from NHS D contextual indicators, September 2016


Page 14

5. Seven day services

5.1 This analysis repeats the work presented in report 25, however interpretation of mortality in patients admitted during weekends continues to be controversial.

5.2 To help in understanding this issue table 3 illustrates how the number of discharges, deaths and HSMR vary between weekdays and weekends.

Table 3: Weekday and weekend mortality (HSMR), July 2015 to June 2016

5.3 Table 3 shows that in the region the average number of discharges per weekday is 1127 compared to 471 for weekend day which is substantially lower. The average number of deaths is also lower, with 30 deaths in patients admitted at weekends compared to 35 on weekdays. Despite the lower number of deaths, the HSMR increases from 104 to 110. This pattern is slightly different for the DDT trusts with a ratio of HSMRs (weekend/weekday) close to 1.

5.4 The last three columns in table 3 present the ratios and show that weekend discharges are less than half of weekday, whilst deaths are only around 14% lower. The pattern is relatively consistent across the trusts. The increased HSMR largely results from the reduction in the denominator (discharges) being much greater than the fall in the number of deaths. The weekend effect is ubiquitous but unexplained. Health systems need to understand the differences in patient pathways to address this issue.

5.5 It is expected that NHS Digital will publish new weekend mortality indicators in October 2016, based on a new method. These indicators will supplement information about the NHS England 7 day services clinical standards9. This will be considered in the next mortality report.

9 https://www.england.nhs.uk/ourwork/qual-clin-lead/seven-day-hospital-services/

HSMR

Trust Name

Number of

discharges

per day

Number of

deaths per

day

HSMR

Number of

discharges

per day

Number of

deaths per

day

HSMR

Discharges

(weekday -

weekend)

Deaths

(weekday -

weekend)

HSMR

(weekday -

weekend)

Discharges

(weekend/w

eekday)

Deaths

(weekend/

weekday)

HSMR

(weekend/

weekday)

CDD 140 5.3 107 71 4.2 103 69 1.1 4 0.51 0.79 0.96

North Tees 118 3.6 104 45 3.0 107 73 0.6 -3 0.38 0.84 1.03

South Tees 164 4.8 102 71 3.9 103 93 0.9 -1 0.44 0.81 1.01

Gateshead 87 2.4 98 36 2.3 107 51 0.2 -9 0.41 0.94 1.10

South Tyneside 49 1.8 112 22 1.6 116 27 0.2 -4 0.44 0.91 1.04

Sunderland 115 3.9 107 57 3.5 117 59 0.4 -10 0.49 0.90 1.09

Newcastle 222 4.5 101 73 3.8 116 149 0.7 -15 0.33 0.85 1.15

Northumbria 138 5.6 104 60 5.1 115 79 0.5 -10 0.43 0.91 1.10

North Cumbria 94 3.3 99 37 2.9 114 57 0.3 -15 0.39 0.90 1.15

Total 1127 35 104 471 30 110 656 5 -7 0.42 0.86 1.07

Weekday average Weekend average Difference Ratio

https://www.england.nhs.uk/ourwork/qual-clin-lead/seven-day-hospital-services/


Page 15

6. SHMI by broad clinical area (CCS bundle)

6.1 The HED system holds information about the primary diagnosis in the form of the Clinical Classification System (CCS) code. There are 255 CCS codes covering the range of diagnosis codes within ICD-10 and these are grouped into 140 diagnosis groups in the calculation of SHMI. NEQOS have grouped these diagnosis groups into 7 larger bundles to make the overall pattern of mortality discernible at a lower level by trust. The data for South Tyneside has been adjusted to exclude cancer activity relating to St Benedict’s hospice site. The Appendix details the CCS groups included in each bundle.

6.2 There is no nationally agreed method for identifying outlying values below Trust level (ie including all 140 diagnosis groups), although using funnel plots is consistent with the method used for Trust level SHMIs. Three standard deviation funnel plots are calculated (ie funnel plots using 99.8% Poisson control limits) for each of the 7 CCS bundles and this output is summarised in table 4.

6.3 The table highlights areas that have higher than expected mortality. Trusts will want to examine their own data (including coding) and review case notes where appropriate to investigate the causes of variation. Note: some of the CCS bundles will contain relatively low numbers of deaths (e.g. injury) and hence will show wider variation for the smaller trusts.

Table 4: SHMI CCS bundles summary by Acute Trust, April 2015 to March 2016

7. SHMI for selected clinical conditions (CCS groups)

7.1 In this report information will be provided on the CCS groups which make a substantial contribution to overall mortality and provide a useful clinical focus. Data is shown for 2013/14, 2014/15 and 2015/16 to show the variation between years.

7.2 The CCS bundles shown previously can be broken-down into the 140 constituent diagnostic groups used in the SHMI statistical model. In this report data is presented for Pneumonia, Septicemia, Acute Bronchitis and UTIs. Analysing by CCS group reduces systematic variation at the expense of increasing random variation, since the sample is more consistent, but smaller.

7.3 At this scale using funnel plots to identify outliers may fail to detect important patterns. Analysis within trusts is more important than comparison between trusts and therefore a funnel plot method is less helpful to trusts than understanding their VLADs.

7.4 The selected conditions are all in the top 20 for mortality and will relate to patients requiring acute hospital care and the SHMIs may give an indication of the quality of hospital care. This will also reflect the management of chronic respiratory patients (e.g. COPD) in the community and to a lesser extent patients at the end of life (e.g. with terminal cancer).

7.5 For Pneumonia the variation between years is relatively small with no striking rises or falls from 2014/15 to 2015/16. The trusts tend to be above 100 with the exception of South Tees and Gateshead.

CCS Groups County Durham North Tees South Tees Gateshead South Tyneside Sunderland Newcastle Northumbria North Cumbria

Cancer as expected as expected as expected as expected as expected Low Low High as expected

Cardiac as expected as expected as expected as expected as expected as expected Low as expected as expected

Gut as expected as expected as expected as expected as expected as expected as expected as expected as expected

Injury as expected as expected as expected as expected as expected as expected High as expected as expected

Other causes as expected as expected as expected as expected as expected as expected as expected as expected as expected

Other Medical as expected High as expected as expected as expected as expected as expected as expected as expected

Respiratory High as expected as expected as expected as expected as expected as expected as expected as expected


Page 16

7.6 For Acute Bronchitis the number of deaths is smaller and consequently there is more variation apparent by trust with a notable rise for South Tees and a large fall seen at Sunderland. The SHMI data for 2015/16 shows five trusts at around or below 100 with South Tees at the higher end. There will be some crossover with Pneumonia since where the notes state “? Pneumonia” this cannot be coded to Pneumonia and is likely to be coded to Acute Bronchitis.

7.7 Septicemia shows some variation between 2014/15 and 2015/16 with a notable decrease for South Tyneside. The SHMI data for 2015/16 shows six trusts around or below 100.

7.8 For UTIs there is considerable variation by trust between years with South Tees showing a clear rise from 2014/15 to 2015/16 and Sunderland a clear fall. Four of the trusts show considerable change over the period. The SHMI data for 2015/16 shows six of the trusts around or below 100.

Figure 10: SHMI for selected CCS groups (code)

0

25

50

75

100

125

150

SH

MI

SHMI for Pneumonia (73)

2013/14 2014/15 2015/16

0

25

50

75

100

125

150

SH

MI

SHMI for Acute Bronchitis (74)

2013/14 2014/15 2015/16

0

25

50

75

100

125

150

SH

MI

SHMI for Septicemia (2)

2013/14 2014/15 2015/16

0

25

50

75

100

125

150

SH

MI

SHMI for Urinary Tract Infection (101)

2013/14 2014/15 2015/16




Page 17

8. Comparison of SHMI by Clinical Commissioning Group

8.1 The Clinical Commissioning Groups (CCGs) formally came into being on the 1st April 2013 and in line with the NHS Mandate a breakdown of SHMI by CCG is provided.

8.2 The SHMI for Hartlepool and Stockton-on-Tees (HAST) CCG is 113 for the latest period which falls above the expected range for the period as does South Tees with a SHMI of 116.

Table 4: SHMI by CCG for January to December 2015

8.3 Figure 11 shows the place of death by CCG with most CCGs showing a similar picture to England, the exception is South Tyneside which shows more deaths in home and at hospital. The range of deaths in hospital across England is from 35% to 67%.

Figure 11: Place of death by CCG, April to March 2016

8.4 This is the fourth time that the End of Life Care (EoLC) Intelligence Network has provided a rolling 12 months of place of death data that corresponds to the latest SHMI data10. NHS England have updated their toolkit11 for commissioning person centred EoLC, this provides information and resources to help identify demand, local service provision and gaps.

10 http://www.endoflifecare-intelligence.org.uk/data_sources/place_of_death 11 https://www.england.nhs.uk/wp-content/uploads/2016/04/nhsiq-comms-eolc-tlkit-.pdf

CCG Observed Expected SHMI Category

Cumbria 2855 2833 101 as expected

Darlington 650 601 108 as expected

DDES 1905 1841 104 as expected

Gateshead 1341 1424 94 as expected

HAST 1821 1613 113 Higher than expected

Newcastle NE 712 679 105 as expected

Newcastle W 804 754 107 as expected

North Durham 1367 1348 101 as expected

North Tyneside 1485 1449 103 as expected

Northumberland 2137 2118 101 as expected

South Tees 1799 1548 116 Higher than expected

South Tyneside 1088 1106 98 as expected

Sunderland 1846 1830 101 as expected

52% 51% 50% 50% 49% 48% 47% 46% 44% 44% 43%47%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Pro

po

rtio

n o

f d

eat

hs

Place of death by CCG, April 2015 to March 2016

Other (%) Hospice (%) Care home (%) Home (%) Hospital (%)Source: NEQOS Hospital Mortality Monitoring: Report 30Data from EoL care network, Sep 2016

http://www.endoflifecare-intelligence.org.uk/data_sources/place_of_death


Page 18

9. Comorbidity coding

9.1 Figure 12 shows the number of comorbidities included in the Charlson Index12 recorded per hospital spell. The general trend is upwards, although there is variation in the increase for each trust with most trusts showing higher comorbidities than England. There has been a small change in the calculation of the comorbidity score within HED which has changed the absolute values but not the overall pattern.

9.2 As noted in the Executive summary, because the data for the most recent months are provisional, the values for Q1 2016/17 will change and so this quarter is not included.

9.3 The comorbidity count matters because of its impact on the risk adjustment used in modelling mortality. Combined with palliative care coding, coding depth has a substantial impact on the mortality indicators. North Tees show a clear fall over the last year.

Figure 12: Number of co-morbidities per spell, April 2013 to March 2016

10. Conclusions

10.1 In the period April 2015 to March 2016 two trusts have ‘higher than expected’ SHMI mortality. North Tees and South Tyneside have SHMIs of 113 and 118 respectively. The Hartlepool and Stockton-on-Tees and South Tees CCGs show as SHMI outliers for this period.

10.2 North Tees and South Tyneside are persistent outliers for SHMI. North Tees are not outlying on HSMR: whilst the SHMI has fallen, for the Trust to be “as expected” observed mortality will have to reduce further.

10.3 HSMRs are high for two trusts, South Tyneside and Sunderland. In South Tyneside the hospice is affecting both SHMI and HSMR.

10.4 The increased HSMR in patients admitted at weekends compared to weekdays largely results from the reduction in the discharges being much greater than the fall in the deaths.

12 SHMI Indicator Specification http://www.hscic.gov.uk/media/16110/Indicator-Specification-Summary-Hospital-level-Mortality-Indicator-methodology-updated/pdf/SHMI_specification.pdf

0

1

2

3

4

5

6

7

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

2013/14 2013/14 2013/14 2013/14 2014/15 2014/15 2014/15 2014/15 2015/16 2015/16 2015/16 2015/16

Co

mo

rbid

ity

sco

re p

er

spe

ll

Comorbidity score per FCE by Trust, April 2013 to March 2016

CDD

Gateshead

Newcastle

North Tees

Northumbria

North Cumbria

South Tees

South Tyneside

Sunderland

ENGLANDSource: NEQOS Hospital Mortality Monitoring: Report 30Data extracted from HED, October 2016

http://www.hscic.gov.uk/media/16110/Indicator-Specification-Summary-Hospital-level-Mortality-Indicator-methodology-updated/pdf/SHMI_specification.pdf

http://www.hscic.gov.uk/media/16110/Indicator-Specification-Summary-Hospital-level-Mortality-Indicator-methodology-updated/pdf/SHMI_specification.pdf


Page 19

11. Abbreviations and glossary

AHSN-NENC Academic Health Science Network: North East and North Cumbria

CCS Clinical Classification System

CCG Clinical Commissioning Group

CQC Care Quality Commission

CuSum Cumulative Sum control chart

DDT Durham, Darlington and Tees

FCE Finished Consultant Episode

HED Healthcare Evaluation Data. Tool to access mortality data.

HSMR Hospital Standardised Mortality Ratio

HSCIC The Health and Social Care Information Centre

ICD-10 International Classification of Disease (version 10)

NCEPOD National Confidential Enquiry into Patient Outcome and Death

NCNTW North Cumbria, Northumbria, Tyne and Wear

NEQOS The North East Quality Observatory Service

NHS D NHS Digital (formerly HSCIC)

NHS I NHS Improvement

NRCRR National Retrospective Case Record Review

ONS Office for National Statistics

PHE Public Health England

QSG Quality Surveillance Group

RCRR Retrospective Case Record Review

SHMI Summary Hospital-level Mortality Indicator

SSNAP The Sentinel Stroke National Audit Programme

Unadjusted mortality rate

The count of deaths divided by the number of hospital spells. No adjustments for the age, sex or comorbidities of patients.

UHB University Hospitals Birmingham NHS Foundation Trust

VLADs Variable Life Adjusted Displays


Page 20

12. Appendix

CCS bundles Description of bundles

SHMI diagnosis groups (140)

CCS groups (255)

Cancer All cancers 7 - 33 11 - 47; 167

Cardiac All cardio-vascular disease

54 – 71 96 - 117

Gut Diseases of the digestive system

83 – 98; 138 135, 138 - 155; 251

Injury Trauma and poisoning

120 - 133 225 - 244

Other Medical

Infections, Endocrine, Renal and Urological conditions

2; 34 - 38; 99 - 103

2; 48 - 53 , 55 , 58; 156 - 163; 249

Respiratory All lung disease 1; 73-82 1; 56; 122 - 134

Other causes All other CCS groups

All other CCS groups

All other CCS groups


Page 21

DOCUMENT GOVERNANCE

Document name Hospital Mortality Monitoring

Report 30: April 2015 to March 2016

Document type Report

Version DRAFT

Date October 2016

Document Classification This report is confidential to the NHS organisations in the North East. Other NHS organisations can know that this kind of report into mortality has been done and is within the capabilities of the NEQOS team.

Prepared on behalf of The subscribing Acute Trusts, CCGs, NECS and NHS England Area Teams in NHS North East

Created by Tony Roberts and Michael Walkley

Approved by Epidemiologist Prototype report discussed by group of epidemiologists

Approved by Project Director Tony Roberts

Peer Reviewed by (if appropriate) Andrea Brown

Originating organisation North East Quality Observatory System (NEQOS)

Website of originating organisation www.neqos.nhs.uk - Please contact the NEQOS advisory service through this web link for further information or to enquire about NEQOS undertaking similar work.

Contact email address [email protected]

Public file location

Internal file location

http://www.neqos.nhs.uk/

mailto:[email protected]


Page 22

VERSION CONTROL

Version Document Type Date Amendments By

1 Draft Report 04/10/2016 First draft Michael Walkley

2 Draft Report 06/10/2016 Second draft Michael Walkley Tony Roberts

3 Draft Report 10/10/2016 Third draft Tony Roberts Michael Walkley

4 Draft Report 17/10/2016 Fourth draft incorporating comments from reviewers

Andrea Brown Alastair Beattie

5 Final Report 17/10/2016 Final Report Tony Roberts Michael Walkley

PLEASE SEND FINAL REPORT TO NEQOS OFFICE FOR DISTRIBUTION

CONFIDENTIALITY CHECKLIST – FOR COMPLETION PRIOR TO ANY DRAFTS SENT TO CLIENTS

Does the report include any small numbers?

If yes, can we produce a meaningful suppressed version?

If not, the Epidemiologist AND Director must justify why not here, highlight, and agree the need for an NDA

Have HES at IC approved use of NDA in order to disclose small numbers?

Has the recipient of the report signed the NDA?

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