Hospital guide methodology

The Dr Foster Hospital Guide provides information on NHS acute hospitals with more than 300 beds, some smaller NHS acute hospitals that provide key services to a geographical area and selected specialist hospitals.

Acute and Specialist hospitals are run by NHS Trusts in England and Wales, Health and Social Services Trusts in Northern Ireland, and by NHS Boards in Scotland. A trust or board may run one or more hospitals depending on its location. The information in this guide can be at trust/board level or hospital level, depending on how it has been collected.

About the indicators

There are a number of different clinical indicators in the hospital guide presented for a range of clinical procedures. This section provides more detailed information on how the various indicators are calculated, where the data comes from and what time periods are covered.

Hospital homepages

General hospital information

Metric

Information about the facilities available at individual hospitals has been drawn from the Hospital Estates and Facilities Statistics data-set. The fields used include:

  • number of beds
  • percentage of single rooms
  • total parking spaces available for patients/visitors
  • average parking fee per hour

More information can be found on the Hospital Estates and Facilities Statistics website.

Data Source
The Information Centre - Hospital Estates and Facilities Statistics
Time frame
April 2010 - March 2011
Basis
Hospital Level

Procedural Scorecard Indicators

Length of Stay

Metric
Average number of days spent in an acute trust for planned treatment.
Numerator

The total number of days in elective inpatient spells, at an acute trust for a given main procedure.

The difference between the date of discharge and date of admission is used to determine the interval of stay within the trust (days after possible transfers from the trust are not included). Day cases are omitted from the calculation (a day case is an inpatient spell where the patient is not intended and does remain overnight).

Denominator

A count of the number of elective spells occurring at a trust (NHS) or a site (IS) during the current extract period. A count of the number of elective spells occurring at a provider during the extract period.

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used
The indicator is a statistical mean (average) of the raw days spent in hospital: the total number of days accruing from finished spells, divided by the number of spells. It is not standardised.
National median
A national median length of stay for each relevant procedure is calculated by arranging the length of stay for all relevant spells (elective spells in NHS acute hospitals in England) in ascending order to identify the middle value; where there are an even number of values, an average of the two central values is taken.

Relative risk of Readmission

Metric
A ratio of the observed number of emergency readmissions at a given trust to the expected number of 28-day readmissions for a particular procedure.
Numerator
The total number of emergency readmissions resulting from inpatient spells at an acute trust for a given procedure. The emergency readmission must occur within a 28-day period - 0-28 days inclusive - from the discharge date of the originating spell.
Denominator

The expected number of emergency readmissions resulting from every finished inpatient spell at an acute trust for a given procedure where the procedure is the main procedure in the spell.

The expected number of readmissions is obtained by modelling the risk of readmission.

Each inpatient spell has a risk of readmission associated with it based upon deprivation, sex, age, co-morbidity, the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. The risks are summed to obtain the overall expected number of readmissions.

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used

Logistic regression models of readmissions are built from all years of HES data from 1996/7 onwards based upon the available case-mix factors. The factors adjusted for are: age, sex and method of admission (non-elective or elective), year of admission, deprivation quintile, the Charlson index of comorbidity (see for example, Sundararajan et al, Journal of Clinical Epidemiology 2004; 57: 1288-1294, available via ScienceDirect), the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. Based upon these parameters a logistic regression model is developed which predicts the risk of readmission for an inpatient spell.

A 97.5% confidence interval is calculated for the indicator using Byar's approximation. The confidence interval enables a banding of the indicator for comparison purposes.

Banding

Relative risk is not a quantitative benchmarking measure. It is not intended to give exact readmission rates for a procedure, it is designed to highlight and show where a trust's readmission is not in line with outcomes nationwide.

There are three reported bands:

  1. if the lower limit of the confidence interval is greater then 100 than the assigned band is red, "more than expected"
  2. if the upper limit of the confidence interval is less then 100 than the assigned band is green, "less than expected"
  3. otherwise, the assigned band is blue, "as expected"

1 Year Hospital Standardised Mortality Ratio

Metric
The ratio of the observed number of in-hospital deaths during admissions with a Hospital Standardised Mortality Ratio (HSMR) diagnosis to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4,5)
Denominator

Superspells containing a spell with a primary dominant diagnosis of any of the 56 CCS groups that comprise the HSMR basket

See appendix M: HSMR basket

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

The HSMR basket of CCS groups accounts for approximately 83% of all in-hospital deaths in England.

See 'HSMR Toolkit' for full methodological detail

Superspell: a group of spells linked by transfer

3 Year Hospital Standardised Mortality Ratio

Metric
The ratio of the observed number of in-hospital deaths during admissions with a Hospital Standardised Mortality Ratio (HSMR) diagnosis to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4,5)
Denominator

Superspells containing a spell with a primary dominant diagnosis of any of the 56 CCS groups that comprise the HSMR basket

See appendix M: HSMR basket

Data Source
SUS - CDS
Time frame
Financial years 2008/09, 2009/10, 2010/11
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

The HSMR basket of CCS groups accounts for approximately 83% of all in-hospital deaths in England.

See 'HSMR Toolkit' for full methodological detail

Superspell: a group of spells linked by transfer

One-year revision rates for primary hip and knee replacements

Metric

The proportion of joint replacements with a revision procedure within 365 days of the initial (index) procedure, over the total number of joint replacements carried out at the trust over a three year period.

Three years of index procedures are combined to provide sufficient numbers at trust level. A further year of data is needed to allow a year's follow-up for every index procedure. Index operations in 2004/5 to 2006/7 give rise, potentially, to revisions between 2004/5 and 2007/8.

Note that only one revision within 365 days per patient is counted (some people can have several), and revisions are matched to side of index procedure (right or left).

Construction

Index procedure codes for primary total hip replacement (THR)

Codes: oper1 in ('W371','W381','W391') or (oper1='W581' and (oper2='Z843' or oper3='Z843' or oper4='Z843'))

Description: These cover primary total replacement including resurfacing procedures. For the latter, the Z code is required in any secondary op field (oper2-oper12 - only 2 to 4 shown above for brevity) to specify hip.

Revision procedure codes for THR

Codes: oper1 in ('W373','W383','W393', 'W372','W374', 'W382','W384','W392','W394') or (oper1='W582' and (oper2='Z843' or oper3='Z843' or oper4='Z843')) or oper2 in ('W580', 'W370', 'W380', 'W390') or oper3 in ('W580', 'W370', 'W380', 'W390') or oper4 in ('W580', 'W370', 'W380', 'W390');

Description: These cover revisions (primary op field), conversions (in any secondary op field) and "attention to joint" (primary op field).

Index procedure codes for primary total knee replacement (TKR)

Codes: oper1 in ('W401','W411','W421') or (oper1='W581' and (oper2='Z846' or oper3='Z846' or oper4='Z846'))

Description: These cover primary total replacement including resurfacing procedures. For the latter, the Z code is required in any secondary op field to specify knee.

Revision procedure codes for TKR

Codes: oper1 in ('W403','W413','W423', 'W402','W404', 'W412','W414', 'W422','W424') or (oper1 in ('W580','W582') and (oper2='Z846' or oper3='Z846' or oper4='Z846')) or oper2 in ('W400', 'W410', 'W420') or oper3 in ('W400', 'W410', 'W420') or oper4 in ('W400', 'W410', 'W420')

Description: These cover revisions (primary op field), conversions (in any secondary op field) and "attention to joint" (primary op field).

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2006 - March 2010
Basis
Acute Trust where index procedure took place.
Statistical methods used
Crude rate
Banding

Upper and lower control limits are calculated at 97.5% level of significance and these are used to band the crude rate.

There are three reported bands:

  1. if the crude rate of revisions is greater than the upper control limit then the assigned band is red, "more than expected"
  2. if the crude rate of revisions is less than the lower control limit then the assigned band is green, "less than expected"
  3. otherwise, the assigned band is blue, "as expected"

Waiting time - Inpatient

Metric
By procedure, for elective care, the median wait time (elapsed number of days) between the decision to admit and the day of admission
Numerator
Not applicable.
Denominator
Not applicable.
Data Source
Commissioning Data Sets (CDS)
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used
The median is a statistical term that identifies the middle observation of a data set ordered in increasing value; where there is an even number of values, an average of the two central values is taken.
National median
An identical calculation the basis of which is national data (all English NHS Acute Trusts).

Waiting time - Outpatient

Metric

By specialty, the median wait time (elapsed number of days) for the first outpatient attendance following a GP referral.

In order to determine what specialty to show in relation to a procedure, we identify, nationally, all the discharge specialties that a procedure has been assigned to. We then identify the discharge specialty with the greatest number of spells assigned to it.

Numerator
Not applicable.
Denominator
Not applicable.
Data Source
Commissioning Data Sets (CDS)
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used
The median is a statistical term that identifies the middle observation of a data set ordered in increasing value; where there is an even number of values, an average of the two central values is taken.
National median
An identical calculation the basis of which is national data (all English NHS Acute Trusts).

Relative risk of inpatient admission

Metric
By procedure, a ratio of the observed number of inpatient admissions to the total number of all elective admissions (inpatient and day cases).
Numerator
By procedure, the total number of observed inpatient admissions.
Denominator

The expected number of inpatient admissions.

The expected number of admissions is obtained by modelling the risk of admission.

Each inpatient spell has a risk of admission associated with it based upon deprivation, sex, age, co-morbidity, the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. The risks are summed to obtain the overall expected number of inpatient admissions.

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used

Logistic regression models of inpatient admissions are built from all years of HES data from 1996/7 onwards based upon the available case-mix factors. The factors adjusted for are: age, sex and method of admission (non-elective or elective), year of admission, deprivation quintile, the Charlson index of comorbidity (see for example, Sundararajan et al, Journal of Clinical Epidemiology 2004; 57: 1288-1294, available via ScienceDirect), the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. Based upon these parameters a logistic regression model is developed which predicts the risk of admission for an inpatient spell.

A 97.5% confidence interval is calculated for the indicator using Byar's approximation. The confidence interval enables a banding of the indicator for comparison purposes.

Banding

Relative risk is not a quantitative benchmarking measure. It is not intended to give exact admission rates for a procedure, it is designed to highlight where a trust's inpatient admissions are not in line with outcomes nationwide.

There are three reported bands:

  1. if the lower limit of the confidence interval is greater than 100 then the assigned band is red, "more than expected"
  2. if the upper limit of the confidence interval is less than 100 then the assigned band is green, "less than expected"
  3. otherwise, the assigned band is blue, "as expected"

Mortality rate: Hip replacement

Metric
Relative risk of mortality within 30 days of a procedure, that is, the ratio of the observed number of deaths at a given trust to the expected number of 30-day mortalities for a particular procedure (this ratio is multiplied by 100).
Numerator

The total number of observed mortalities (in-hospital 30 days, 0-30 days inclusive) resulting from every finished inpatient spell at an acute trust for an elective Hip replacement procedure (the numerator is multiplied by 100).

The mortality must occur within 30 days of the date of the main procedure in the spell.

Denominator

The expected number of mortalities resulting from every finished inpatient spell at an acute trust for an elective Hip replacement.

The expected number of mortalities is obtained by modelling the risk of mortality using a logistic regression model. Each inpatient spell has a risk of mortality associated with it based upon deprivation, sex, age, co-morbidity. The risks are summed to obtain the overall expected number of mortalities.

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2007 - March 2010
Basis
Acute Trust
Statistical methods used
Logistic regression models of the risk of post-operative mortality are built from all years of HES data from 1996/7 onwards based upon the available case-mix factors. The major factors adjusted for are: age, sex and method of admission (non-elective or elective), year of admission and deprivation quintile. Three further variables are included in the models: the Charlson index of comorbidity, the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. Based upon these parameters a logistic regression model is developed which predicts the risk of mortality for an inpatient spell. Since the admission events to a provider are (assumed) independent these risks are summed at the provider level for NHS Trusts, to yield the expected number of port operative (30 day) deaths. 99.8% (Poisson) control limits is calculated for the indicator. The control limits enable a banding of the indicator for comparison purposes.
Banding

Any relative risk of mortality is not a quantitative benchmarking measure. It is not intended to give exact mortality rates for a procedure, it is designed to highlight and show where a trust's mortality rate is not in line with outcomes nationwide.

There are four bands:

  • Where the relative risk of mortality is higher than the upper control limit the assigned band is red, "More than expected"
  • Where the relative risk of mortality is below the lower control limit the assigned band is green, "Less than expected"
  • Where the relative risk of mortality falls between the upper and lower control limits the assigned band is blue, "As expected"
  • If the expected figure is less than 1, it is likely that the sample size is too small to allow any meaningful comparison and the assigned band is black, "Sample too small"

Note: Where the expected figure lies between 1 and 5, the banding is restricted to red, "More than expected", and blue, "As expected".

Mortality rate: Knee replacement

Metric
Relative risk of mortality within 30 days of a procedure, that is, the ratio of the observed number of deaths at a given trust to the expected number of 30-day mortalities for a particular procedure (this ratio is multiplied by 100).
Numerator

The total number of observed mortalities (in-hospital 30 days, 0-30 days inclusive) resulting from every finished inpatient spell at an acute trust for an elective Knee replacement procedure (the numerator is multiplied by 100).

The mortality must occur within 30 days of the date of the main procedure in the spell.

Denominator

The expected number of mortalities resulting from every finished inpatient spell at an acute trust for an elective knee replacement.

The expected number of mortalities is obtained by modelling the risk of mortality using a logistic regression model. Each inpatient spell has a risk of mortality associated with it based upon deprivation, sex, age, co-morbidity. The risks are summed to obtain the overall expected number of mortalities.

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2007 - March 2010
Basis
Acute Trust
Statistical methods used
Logistic regression models of the risk of post-operative mortality are built from all years of HES data from 1996/7 onwards based upon the available case-mix factors. The major factors adjusted for are: age, sex and method of admission (non-elective or elective), year of admission and deprivation quintile. Three further variables are included in the models: the Charlson index of comorbidity, the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. Based upon these parameters a logistic regression model is developed which predicts the risk of mortality for an inpatient spell. Since the admission events to a provider are (assumed) independent these risks are summed at the provider level for NHS Trusts, to yield the expected number of port operative (30 day) deaths. 99.8% (Poisson) control limits is calculated for the indicator. The control limits enable a banding of the indicator for comparison purposes.
Banding

Any relative risk of mortality is not a quantitative benchmarking measure. It is not intended to give exact mortality rates for a procedure, it is designed to highlight and show where a trust's mortality rate is not in line with outcomes nationwide.

There are four bands:

  • Where the relative risk of mortality is higher than the upper control limit the assigned band is red, "More than expected"
  • Where the relative risk of mortality is below the lower control limit the assigned band is green, "Less than expected"
  • Where the relative risk of mortality falls between the upper and lower control limits the assigned band is blue, "As expected"
  • If the expected figure is less than 1, it is likely that the sample size is too small to allow any meaningful comparison and the assigned band is black, "Sample too small"

Note: Where the expected figure lies between 1 and 5, the banding is restricted to red, "More than expected", and blue, "As expected".

Mortality rate: Abdominal Aortic Aneurysm (AAA) repair

Metric
Relative risk of mortality within 30 days of a procedure, that is, the ratio of the observed number of deaths at a given trust to the expected number of 30-day mortalities for a particular procedure (this ratio is multiplied by 100).
Numerator

The total number of observed mortalities (in-hospital 30 days, 0-30 days inclusive) resulting from every finished inpatient spell at an acute trust for an elective Abdominal Aortic Aneurysm (AAA) repair (the numerator is multiplied by 100).

The mortality must occur within 30 days of the date of the main procedure in the spell.

Denominator

The expected number of mortalities resulting from every finished inpatient spell at an acute trust for an elective Abdominal Aortic Aneurysm (AAA) repair.

The expected number of mortalities is obtained by modelling the risk of mortality using a logistic regression model. Each inpatient spell has a risk of mortality associated with it based upon deprivation, sex, age, co-morbidity. The risks are summed to obtain the overall expected number of mortalities.

Data Source
Commissioning Data Sets (CDS)
Time frame
April 2007 - March 2010
Basis
Acute Trust
Statistical methods used
Logistic regression models of the risk of post-operative mortality are built from all years of HES data from 1996/7 onwards based upon the available case-mix factors. The major factors adjusted for are: age, sex and method of admission (non-elective or elective), year of admission and deprivation quintile. Three further variables are included in the models: the Charlson index of comorbidity, the number of emergency admissions a patient has had in the previous 12 months and the presence of a palliative care episode. Based upon these parameters a logistic regression model is developed which predicts the risk of mortality for an inpatient spell. Since the admission events to a provider are (assumed) independent these risks are summed at the provider level for NHS Trusts, to yield the expected number of port operative (30 day) deaths. 99.8% (Poisson) control limits is calculated for the indicator. The control limits enable a banding of the indicator for comparison purposes.
Banding

Any relative risk of mortality is not a quantitative benchmarking measure. It is not intended to give exact mortality rates for a procedure, it is designed to highlight and show where a trust's mortality rate is not in line with outcomes nationwide.

There are four bands:

  • Where the relative risk of mortality is higher than the upper control limit the assigned band is red, "More than expected"
  • Where the relative risk of mortality is below the lower control limit the assigned band is green, "Less than expected"
  • Where the relative risk of mortality falls between the upper and lower control limits the assigned band is blue, "As expected"
  • If the expected figure is less than 1, it is likely that the sample size is too small to allow any meaningful comparison and the assigned band is black, "Sample too small"

Note: Where the expected figure lies between 1 and 5, the banding is restricted to red, "More than expected", and blue, "As expected".

If the expected figure lies between 1 and 5, the banding is restricted to Bands 1 and 2. When the expected figure is greater than five, Bands 1, 2 and 3 pertain.

MRSA rates

Metric

This indicator shows the rate of blood infections caused by MRSA for all patients. This includes those who are admitted as an emergency and those who are elective patients i.e. they have planned their treatment in advance. The data is presented as the number of cases per 10,000 bed days. A bed day is defined as one person in hospital for one night.

You can find out more information by visiting the Health Protection Agency website.

Data Source
The Health Protection Agency
Time frame
Financial year 2009/2010
Basis
Trust level information

Clostridium difficile infection rates

Metric

This indicator shows the rate per 10,000 bed-days for specimens taken from patients aged 2 years and over (Trust apportioned cases. A bed day is defined as one person in hospital for one night.

You can find out more information by visiting the Health Protection Agency website.

Data Source
The Health Protection Agency
Time frame
Financial year 2009/2010
Basis
Trust level information

Accident and Emergency Scorecard Indicators

Thrombolytic treatment within 30 minutes of arrival at hospital

Metric

This indicator shows the percentage of eligible heart attack patients who received thrombolytic treatment within 30 minutes of arriving at the hospital.

The National Service Framework (NSF) for coronary heart disease (CHD) sets a standard that 75% of eligible heart attack patients in England should receive thrombolytic drugs within 30 minutes of arriving at hospital.

You can find out more information about the Myocardial Ischaemia National Audit Project by visiting the Royal College of Physicians website

Data Source
Myocardial Ischaemia National Audit Project 2009
Time frame
April 2010 - March 2011
Basis
Hospital Level

Thrombolytic treatment within 60 minutes of calling for professional help

Metric

This indicator shows the percentage of patients eligible heart attack patients who received thrombolytic treatment within 60 minutes of calling for professional help.

The call for professional help will usually be direct to the ambulance service but may be to a GP or NHS Direct.

The Department of Health has set NHS organisations in England the target of 68% of patients receiving thrombolytic treatment within 60 minutes of calling for professional help.

You can find out more information about the Myocardial Ischaemia National Audit Project by visiting the Royal College of Physicians website.

Data Source
Myocardial Ischaemia National Audit Project 2009
Time frame
April 2010 - March 2011
Basis
Hospital Level

Primary angioplasty within 90 minutes of arrival at interventional centre door

Metric

This indicator shows the percentage of patients that received primary angioplasty within 90 minutes of arrival at the interventional centre.

An interim good practice standard of 90 minutes from arrival at an interventional hospital to the time when the blocked artery is reopened (door to balloon time) has been agreed for provision of primary angioplasty, based on international guidelines.

You can find out more information about the Myocardial Ischaemia National Audit Project by visiting the Royal College of Physicians website.

Data Source
Myocardial Ischaemia National Audit Project 2009
Time frame
April 2010 - March 2011
Basis
Hospital Level

Patients discharged from hospital on secondary prevention medication

Metric

Recent national guidelines recommend that all patients who have had an acute heart attack should be offered treatment with a combination of the following drugs provided each drug is tolerated by the patient, and that the patient has no medical reason to avoid the drug:

  • ACE inhibitors/or angiotensin receptor blockers
  • aspirin
  • beta blockers
  • clopidogrel
  • statins

You can find out more information about the Myocardial Ischaemia National Audit Project by visiting the Royal College of Physicians website.

Data Source
Myocardial Ischaemia National Audit Project 2009
Time frame
April 2010 - March 2011
Basis
Hospital Level

NHS Trust homepage Indicators

Mortality

1 Year Hospital Standardised Mortality Ratio

Metric
The ratio of the observed number of in-hospital deaths during admissions with a Hospital Standardised Mortality Ratio (HSMR) diagnosis to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4,5)
Denominator

Superspells containing a spell with a primary dominant diagnosis of any of the 56 CCS groups that comprise the HSMR basket

See appendix M: HSMR basket

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

The HSMR basket of CCS groups accounts for approximately 83% of all in-hospital deaths in England.

See 'HSMR Toolkit' for full methodological detail

Superspell: a group of spells linked by transfer

3 Year Hospital Standardised Mortality Ratio

Metric
The ratio of the observed number of in-hospital deaths during admissions with a Hospital Standardised Mortality Ratio (HSMR) diagnosis to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4,5)
Denominator

Superspells containing a spell with a primary dominant diagnosis of any of the 56 CCS groups that comprise the HSMR basket

See appendix M: HSMR basket

Data Source
SUS - CDS
Time frame
Financial years 2008/09, 2009/10, 2010/11
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

The HSMR basket of CCS groups accounts for approximately 83% of all in-hospital deaths in England.

See 'HSMR Toolkit' for full methodological detail

Superspell: a group of spells linked by transfer

Overall mortality ratio for patients admitted as an emergency

Metric
The ratio of the observed number of in-hospital deaths during emergency admissions with a Hospital Standardised Mortality Ratio (HSMR) diagnosis to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4,5)
Denominator

Superspells containing an emergency spell with a primary dominant diagnosis of any of the 56 CCS groups that comprise the HSMR basket.

Emergency admission method codes:

  • 21: Emergency - via A&E
  • 22: Emergency - via GP
  • 23: Emergency - via Bed Bureau
  • 24: Emergency - via Out-patient clinic
  • 28: Emergency - via other means

See appendix M: HSMR basket

Data Source
SUS - CDS
Time frame
Financial years 2008/09, 2009/10, 2010/11
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

The HSMR basket of CCS groups accounts for approximately 83% of all in-hospital deaths in England.

See 'HSMR Toolkit' for full methodological detail

Superspell: a group of spells linked by transfer

Deaths After Surgery

Metric
Deaths following surgery per 100 surgical procedures associated with a secondary diagnosis for potential complications of care
Observed
Denominator spells with method of discharge as death (DISMETH = 4)
Denominator

Elective surgical spells, defined by a surgical HRG and an OPCS code for an operating room procedure, for which a code indicating potential complications of care is present in any secondary field; and emergency surgical spells, defined by a surgical HRG and an OPCS code for an operating room procedure where the principal operating room procedure took place within 2 days of admission, for which a code indicating potential complications of care is present in any secondary field.

Inclusion:

  • Elective admission (admission method 11, 12 or 13)
    or
  • Emergency admission (admission method 21, 22, 23, 24 or 28) where the principal operating room procedure took place in <= 2 days of admission
  • Discharge age between 18 and 90

Exclusion:

  • External transfers or unknown transfers (DISDEST = 49-53 but no subsequent spell found)

See Appendix A: Surgical HRGs

See Appendix C: Derived Operating Room Procedures

See Appendix D: Potential Complications of Care Diagnoses

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

For emergency admissions, the principal operating room procedure date was searched for within the first two episodes of the spell, to check that the procedure took place within two days of the admission date and not just the start of the episode.

Based on AHRQ PSI indicators. Translated by Peter Griffiths and Simon Jones from King's College London and Alex Bottle from the Dr Foster Unit at Imperial College.

Deaths in low-risk conditions

Metric
Deaths per 100 spells for conditions normally associated with a very low rate of mortality
Observed
Denominator spells with method of discharge as death (DISMETH = 4)
Denominator

Spells with a dominant primary diagnosis associated with a low mortality diagnosis group (mortality rate has been shown to be consistently below 0.5%)

Exclusion:

  • Any diagnosis codes for trauma, immunocompromised state, or cancer
  • Admission age under 19

See appendix E: Immunocompromised state

See appendix F: Cancer codes

See appendix G: Trauma codes

See appendix H: Low mortality CCS groups

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Crude Rate

Expected values are based on the national average rate

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Deaths in high-risk conditions

Metric
The ratio of the observed number of in-hospital deaths to the expected number of deaths, multiplied by 100 for a basket of five specific diagnosis groups.
Numerator

All spells with method of discharge as death (DISMETH=4 or 5), defined by specific diagnosis codes for the primary diagnosis of the spell.

5 specific diagnosis groups:

CCS Group Diagnosis name ICD-10 Codes
100 Acute myocardial infarction I21,I22
109 Acute cerebrovascular disease G46,I60-I64,I66
122 Pneumonia A202, A212, A221, A310, A420, A430, A481, A78, B012, B052, B250, B583, B59, B671, J12-J16, J170-J173, J178, J18, J850, J851
108 Congestive heart failure, nonhypertensive I50
226 Fracture of neck of femur (hip) S720-S722
Denominator

Expected number of in-hospitals deaths derived from logistic regression, adjusting for factors to indirectly standardise for difference in case-mix for the 5 diagnosis groups.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Primary diagnosis (based on the Clinical Classification System - CCS group)
  • Co-morbidities (Dr Foster methodology)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Ethnicity
  • Source of admission
Data Source
SUS - CD
Time frame
April 2010- March 2011
Basis
Acute Trust
Statistical methods used

Logistic regression

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an HSMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An HSMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Broken Hip Repair

Deaths following a hip fracture

Metric
The ratio of the observed number of in-hospital deaths during non-elective fracture of neck of femur admissions to the expected number of deaths, multiplied by 100.
Observed
Denominator superspells with method of discharge as death (DISMETH=4)
Denominator

Superspells containing a non-elective spell with a primary diagnosis of fracture of neck of femur

Fracture of neck of femur (hip) ICD10 codes: S720-S722

Non-Elective admissions do not have admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
  • 99: Unknown
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Superspell: a group of spells linked by transfer

Hip fracture - Operation within 2 days

Metric
The percentage of fracture of neck of femur (FNOF) admissions that do not have a related procedure within 2 days of admission
Observed

Denominator superspells where the operation date for FNOF occurs more than 2 days after the diagnosis start date

The diagnosis start date is defined as the date of admission for the spell with the dominant primary diagnosis of FNOF. The operation date is the earliest date within the superspell of a dominant procedure related to fracture of neck of femur.

Denominator

Superspells containing a non-elective spell with a dominant primary diagnosis of fracture of neck of femur and a dominant procedure related to fracture of neck of femur

Fracture of neck of femur (hip) ICD10 codes: S720-S722

Exclusions

  • Superspells without an operation date (missing)
  • Admission method codes:
    • 11: Elective - from waiting list
    • 12: Elective - booked
    • 13: Elective - planned
    • 99: Unknown

See appendix I: Fracture of Neck of Femur Related Procedure Codes

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Crude Rate

Expected values are based on the national average rate

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% binomial control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% binomial control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Superspell: a group of spells linked by transfer

Hip fracture - length of stay

Metric
The ratio of the observed number of long length of stay fracture neck of femur spells to the expected number, multiplied by 100
Observed

Denominator spells where the length of stay is greater than the length of stay of the 75th percentile non-elective fracture neck of femur patient in England

Length of stay: discharge date - admission date

Denominator

Non-elective spells with a primary dominant diagnosis of fracture of neck of femur

Fracture of neck of femur (hip) ICD10 codes: S720-S722

Non-Elective admissions do not have admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
  • 99: Unknown
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic Regression

Expected value is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The risk is calculated by dividing the actual number of events by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an RR of 100, that means that the number of events is exactly as it would be expected taking into account the standardisation factors. An RR above 100 means there were more events than would be expected; one below 100 means that fewer than expected events occurred.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Long LOS percentile cut-off is defined for each procedure/diagnosis group, spell year and admission method (elective/non-elective), and excludes day cases.

Hip fracture - readmitted patients

Metric
The ratio of the observed number of non-elective fracture of neck of femur admissions with an emergency readmission within 28 days of discharge to the expected number, multiplied by 100
Observed

Denominator superspells with an emergency readmission within 28 days of discharge

Inclusion

  • Readmitting episode - Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date minus discharge date < 28 days
Denominator

Superspells containing a non-elective spell with a primary dominant diagnosis of fracture of neck of femur

Fracture of neck of femur (hip) ICD10 codes: S720-S722

Non-Elective admissions do not have admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
  • 99: Unknown
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of readmissions by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has a SRR of 100, that means that the number of patients who were readmitted is exactly as would be expected taking into account the standardisation factors. A SRR above 100 means more patients were readmitted than would be expected; one below 100 means that fewer than expected were readmitted.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Superspell: a group of spells linked by transfer

Stroke and vascular

Deaths following a stroke

Metric
The ratio of the observed number of in-hospital deaths during admissions for stroke to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4)
Denominator

Superspells containing a spell with a primary dominant diagnosis of acute cerebrovascular disease.

Acute cerebrovascular disease ICD10 codes: G46,I60-I64,I66

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Superspell: a group of spells linked by transfer

Pneumonia following swallowing problems

Metric
The ratio of the observed number of stroke patients developing hospital-acquired pneumonitis due to swallowing difficulty to the expected number, multiplied by 100
Observed

Denominator superspells containing a diagnosis code for pneumonitis in any position where the start of the episode is after the first stroke admission episode or where the code is immediately followed by a nosocomial code.

Pneumonitis ICD10 codes:

  • J690: Pneumonitis due to food and vomit
  • J698: Pneumonitis due to other solids or liquids

Nosocomial ICD10 codes:

  • Y95: Nosocomial condition
Denominator

Superspells containing a spell with a primary dominant diagnosis of stroke

Stroke ICD10 codes: I60-I64

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Based on Laudicella and Street, University of York cited in S. Leatherman, K. Sutherland, M. Airoldi (2008) Bridging the quality gap: Stroke. Quest for Quality and Improved Performance. Adapted by the Dr Foster Unit at Imperial College.

Superspell: a group of spells linked by transfer

Stroke - readmitted patients

Metric
The ratio of the observed number of stroke admissions with an emergency readmissions within 28 days of discharge to the expected number, multiplied by 100
Observed

Denominator superspells with an emergency readmission within 28 days of discharge

Inclusion:

  • Readmitting episode - Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date minus discharge date < 28 days
Denominator

Superspells containing a spell with primary dominant diagnosis of acute cerebrovascular disease

Acute cerebrovascular disease ICD10 codes: G46,I60-I64,I66

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Superspell: a group of spells linked by transfer

Discharge to usual place of residence

Metric
The ratio of the observed number of stroke patients not returning to their usual place of residence within 56 days of hospital admission to the expected number, multiplied by 100
Observed

Denominator superspells where the patient stayed 56 days or longer or did not return to their usual place of residence

Length of stay: discharge date - admission date

Usual place of residence:

DISDEST=19
Or
ADMISORC = 29,30,48,50,54,84,85,86,88 And DISDEST=ADMISORC
Or
ADMISORC = 37,38,39 And DISDEST = 37,38,39
Or
ADMISORC = 65,66,69 And DISDEST = 65,66,69
Or
ADMISORC= 89 And DISDEST = 85,86,88,89
Or
ADMISORC = 85,86,88 And DISDEST=89

Denominator

Superspells containing a spell with a primary dominant diagnosis of stroke and where the patient was discharged alive

Stroke ICD10 codes: I60-I64

Exclusion:

  • Admissions which end in death (DISMETH=4-5)
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Based on National Centre for Health Outcome Development. Returning to usual place of residence following hospital treatment: Stroke. Adapted by the Dr Foster Unit at Imperial College.

Superspell: a group of spells linked by transfer

Stroke - length of stay

Metric
The ratio of the observed number of long length of stay stroke spells to the expected number, multiplied by 100
Observed

Denominator spells where the length of stay is greater than the length of stay of the 75th percentile stroke patient in England

Length of stay: discharge date - admission date

Denominator

Spells with a primary dominant diagnosis of acute cerebrovascular disease

Acute cerebrovascular disease ICD10 codes: G46,I60-I64,I66

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Long LOS percentile cut-off is defined for each procedure/diagnosis group, spell year and admission method (elective/non-elective), and excludes day cases.

Deaths following repair of abdominal aortic aneurysms

Metric
The ratio of the observed number of in-hospital deaths within 30 days of a repair of abdominal aortic aneurysm (AAA) to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4) and where the discharge date of the final spell in the superspell minus the AAA operation date is less than 30 days
Denominator

Superspells containing a spell with a dominant procedure of repair of abdominal aortic aneurysm

AAA OPCS 4 codes: L183-6,L193-6,L203-6,L213-6,L271-2,L275-6,L281-2,L285-6

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust

Orthopaedics

Hip replacement - length of stay

Metric
The ratio of the observed number of long length of stay elective hip replacement spells to the expected number, multiplied by 100
Observed

Denominator spells where the length of stay is greater than the length of stay of the 75th percentile elective hip replacement patient in England

Length of stay: discharge date - admission date

Denominator

Elective spells with a dominant procedure of hip replacement

Hip replacement OPCS 4 codes: W37-W39,W93-W95

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Long LOS percentile cut-off is defined for each procedure/diagnosis group, spell year and admission method (elective/non-elective), and excludes day cases.

Knee replacement - length of stay

Metric
The ratio of the observed number of long length of stay elective knee replacement spells to the expected number, multiplied by 100
Observed

Denominator spells where the length of stay is greater than the length of stay of the 75th percentile elective knee replacement patient in England

Length of stay: discharge date - admission date

Denominator

Elective spells with a dominant procedure of knee replacement

Knee replacement OPCS 4 codes: O18,W40-W42,W5[234][1389] (+Z844-6),W580-2 (+Z846)

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Long LOS percentile cut-off is defined for each procedure/diagnosis group, spell year and admission method (elective/non-elective), and excludes day cases.

Hip revisions and manipulations within 1 year

Metric
The number of elective hip replacements with a revision procedure within 365 days of the initial (index) procedure, over the total number of elective hip replacements carried out at the trust over a three year period
Observed

Denominator superspells with a revision procedure on the same side within 365 days of the index procedure

Revision of hip replacement OPCS 4 codes: W370, W372, W373, W374, W380, W382, W383, W384, W390, W392, W393, W394, W395, W396, W55-W57(+W3[789]0|W9[345]0), W580(+Z843), W582(+Z843), W930, W932, W933, W940, W942, W943, W950, W952, W953, W954

Denominator

Superspells containing an elective spell with a dominant procedure of hip replacement and a valid side of index procedure.

Primary total hip replacement OPCS 4 codes: W371, W381, W391, W581(+Z843), W931, W941, W951

Side of index procedure OPCS 4 codes: Z941, (Z942 + Z943), Z942, Z943, Z944

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
Index procedure: April 2007 - March 2010. Revisions: April 2008 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Crude Rate

Expected values are based on the national average rate.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% binomial control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% binomial control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Three years of index procedures are combined to provide sufficient numbers at trust level. A further year of data is needed to allow a year's follow-up for every index procedure. Index operations in 2007/8 to 2009/10 give rise, potentially, to revisions between 2008/9 and 2010/11.

Only one revision within 365 days per patient is counted (some people can have several), and revisions are matched to side of index procedure (right or left).

An observed revision is attributed to the denominator superspell containing the index procedure.

Superspell: a group of spells linked by transfer

Knee revisions and manipulations within 1 year

Metric
The number of elective knee replacements with a revision procedure within 365 days of the initial (index) procedure, over the total number of elective knee replacements carried out at the trust over a three year period
Observed

Denominator superspells with a revision procedure on the same side within 365 days of the index procedure

Revision of knee replacement OPCS 4 codes: O182, O183, O184, W400, W402, W403, W404, W410, W412, W413, W414, W420, W422, W423, W424, W425, W5[234]3(+Z84[456]), W55-W57(+W4[012]0), W58[02](+Z846)

Denominator

Superspells containing an elective spell with a dominant procedure of knee replacement and a valid side of index procedure

Primary total knee replacement OPCS 4 codes: O181, W401, W411, W421, W5[234]1(+Z84[456]), W581(+Z846)

Side of index procedure OPCS 4 codes: Z941, (Z942 + Z943), Z942, Z943, Z944

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
Index procedure: April 2007 - March 2010. Revisions: April 2008 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Crude Rate

Expected values are based on the national average rate.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% binomial control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% binomial control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Three years of index procedures are combined to provide sufficient numbers at trust level. A further year of data is needed to allow a year's follow-up for every index procedure. Index operations in 2007/8 to 2009/10 give rise, potentially, to revisions between 2008/9 and 2010/11.

Only one revision within 365 days per patient is counted (some people can have several), and revisions are matched to side of index procedure (right or left).

An observed revision is attributed to the denominator superspell containing the index procedure.

Superspell: a group of spells linked by transfer

Planned hip replacement - readmitted patients

Metric
The ratio of the observed number of elective hip replacement admissions with an emergency readmission within 28 days of discharge to the expected number, multiplied by 100
Observed

Denominator superspells with an emergency readmission within 28 days of discharge

Inclusion:

  • Readmitting episode- Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date minus discharge date < 28 days
Denominator

Superspells containing an elective spell with a dominant procedure of hip replacement

Hip replacement OPCS 4 codes: W37-W39,W93-W95

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Superspell: a group of spells linked by transfer

Planned knee replacement - readmitted patients

Metric
The ratio of the observed number of elective knee replacement admissions with an emergency readmission within 28 days of discharge to the expected number, multiplied by 100
Observed

Denominator superspells with an emergency readmission within 28 days of discharge

Inclusion:

  • Readmitting episode - Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date minus discharge date < 28 days
Denominator

Superspells containing an elective spell with a dominant procedure of knee replacement

Knee replacement OPCS 4 codes: O18,W40-W42,W5[234][1389] (+Z844-6),W580-2 (+Z846)

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Superspell: a group of spells linked by transfer

Urology

Redo rates for prostate resection

Metric
The rate (expressed as a percentage) of TURP procedures where a second operation was performed within three years.
Numerator (Redos)

All spells where another TURP procedure was performed within 3 years of the last TURP procedure (the index procedure).

Procedure Group - Endoscopic resection of outlet of male bladder: OPCS code - M65

Denominator (Index procedure)

Procedure Group- Endoscopic resection of outlet of male bladder: OPCS code- M65

The episode with the dominant procedure was used in the analysis.

Data Source
SUS - CDS
Time frame
Discharge for the index TURP procedure must have occurred between April 2005 and March 2008.
Basis
Acute Trust
Statistical methods

Crude rate expressed as a percentage.

Control limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% control limit are said to be 'higher than expected', data points falling below the lower 99.8% control limit are said to be 'lower than expected', otherwise 'within expected range'.

Dominant procedure episode Spell-based. The following rules were applied to all of the OPER codes in a spell in the order of preference:

Situation CHOSEN_OP
Spell has none of the OPER codes listed below First OPER code that isn't "&"
AAA code in spell First AAA
Both PTCA and Contrast codes somewhere in spell, but no CABG code First PTCA
Both CABG plus PTCA in spell If the OPDAT for the PTCA is the same or one day after the OPDAT for the CABG, pick the PTCA, otherwise pick the CABG. (If OPDATs are missing, pick the CABG.)
Both CABG plus Carotid in spell First CABG
Otherwise... Pick the first op which has a code in the table below.

OPER codes fall into the above groups based on the following (the codes must begin with one of the appropriate values):

Type Definition
CABG K40, K41, K42, K43, K44, K45, K46
PTCA K49, K50
Contrast K63, K65
Carotid L29
AAA L183, L193, L203, L213, L184, L185, L186, L194, L195, L196, L204, L205, L206, L214, L215, L216
Listed A01, A02, A08, A12, A38, A40, A41, A52, A65, A83, A84, B27, B28, C12, C31, C32, C33, C34, C35, C60, C71, C72, C73, C74, C75, C77, C82, D03, D15, E03, E04, E25, E29, E36, E49, E51, E53, E54, F09, F10, F22, F34, G01, G02, G03, G14, G15, G16, G17, G18, G19, G27, G28, G35, G43, G44, G45, G52, G53, G58, G69, G70, G71, G78, H01, H02, H04, H05, H06, H07, H08, H09, H10, H11, H13, H15, H20, H21, H22, H23, H24, H25, H26, H27, H28, H33, H44, H48, H50, H51, H52, H54, H56, J01, J02, J13, J14, J18, J38, J39, J40, J41, J43, J56, J69, K01, K02, K04, K05, K06, K07, K09, K10, K11, K12, K14, K18, K19, K20, K25, K26, K27, K28, K29, K30, K31, K34, K37, K40, K41, K42, K43, K44, K45, K46, K49, K50, K53, K60, K63, K65, K66, L01, L05, L06, L09, L10, L12, L18, L19, L20, L21, L29, L33, L35, L48, L49, L50, L51, L52, L53, L56, L57, L58, L59, L60, L62, L63, L85, L87, L95, M01, M02, M14, M26, M27, M28, M29, M34, M42, M45, M65, N08, N09, N17, N30, P23, P31, Q01, Q02, Q03, Q07, Q08, Q10, Q11, Q14, Q17, Q18, Q35, Q36, Q38, Q39, Q41, Q49, Q50, R17, R18, R19, R20, R21, R22, R23, R24, R25, S05, S06, T19, T20, T21, T24, T42, T43, T46, T52, T54, T59, T60, T67, V09, V22, V25, V26, V29, V33, V34, V38, V39, V43, V47, V48, V49, W15, W19, W20, W21, W22, W23, W24, W25, W26, W28, W34, W37, W38, W39, W40, W41, W42, W46, W47, W48, W59, W79, W82, W83, W84, W85, W86, W87, W88, W90, X09, X29, X33, X35, X41

The "first" OPER code is decided on an EPISODE then the number of the OPER variable - for instance, OPER2 is considered "before" OPER5 in the same episode. They are not ordered by date. OPDATn is a HES field and reflects the date associated with OPERn.

Prostate resection - readmitted patients

Metric
The ratio of the observed number of readmissions to the expected number of readmissions, multiplied by 100.
Numerator

All spells with an emergency readmission within 28 days of discharge.

  • Readmitting episode- Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date within 28 days of discharging spell

Procedure Group - Endoscopic resection of outlet of male bladder: OPCS code- M65

Denominator

Expected number of readmission derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Primary procedure
  • Co-morbidities (Dr Foster methodology)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Ethnicity
  • Source of admission
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Logistic regression

The ratio is calculated by dividing the actual number of readmissions by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has a SRR of 100, that means that the number of patients who were readmitted is exactly as would be expected taking into account the standardisation factors. A SRR above 100 means more patients were readmitted than would be expected; one below 100 means that fewer than expected were readmitted.

Control limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Bladder removal - length of stay

Metric
Adjusted average length of stay for patients that have a Cystectomy.
Observed

Average length of stay - average of (Date of discharge - Date of admission)

  • Inpatients only
  • Cystectomy - Total excision of bladder: OPCS code - M34
Expected
Expected length of stay is adjusted to indirectly standardise for differences in case-mix.
Data Source
SUS - CDS
Time frame
April 2008 - March 2011
Basis
Acute Trust
Statistical methods used

Indirect standardisation, adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Co-morbidities (Dr Foster methodology - Charlson score, see below)
  • Year of discharge (financial year)

Charlson score

Condition No. Condition Name Weight
1 Acute myocardial infarction 5
2 Cerebral vascular accident 11
3 Congestive heart failure 13
4 Connective tissue disorder 4
5 Dementia 14
6 Diabetes 3
7 Liver disease 8
8 Peptic ulcer 9
9 Peripheral vascular disease 6
10 Pulmonary disease 4
11 Cancer 8
12 Diabetes complications -1
13 Paraplegia 1
14 Renal disease 10
15 Metastatic cancer 14
16 Severe liver disease 18
17 HIV 2

Bladder removal - readmitted patients

Metric
The ratio of the observed number of readmissions to the expected number of readmissions, multiplied by 100.
Numerator

All spells with an emergency readmission within 28 days of discharge.

  • Readmitting episode - Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date within 28 days of discharging spell

Procedure Group - Total excision of bladder - OPCS code: M34

Denominator

Expected number of readmission derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Primary procedure
  • Co-morbidities (Dr Foster methodology)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Ethnicity
  • Source of admission
Data Source
SUS - CDS
Time frame
April 2008 - March 2011
Basis
Acute Trust
Statistical methods used

Logistic regression

The ratio is calculated by dividing the actual number of readmissions by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has a SRR of 100, that means that the number of patients who were readmitted is exactly as would be expected taking into account the standardisation factors. A SRR above 100 means more patients were readmitted than would be expected; one below 100 means that fewer than expected were readmitted.

Prostate removal - open vs closed

Metric
The proportion of Prostatectomies carried out laparoscopically (closed) to those carried out open.
Numerator
Laparoscopic Prostatectomy - OPCS codes - M61 (+ Y75)
Denominator

Open Prostatectomy - OPCS codes - M61.

The episode with the dominant procedure was used in the analysis.

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used

Crude ratio

Dominant procedure episode

Spell-based. The following rules were applied to all of the OPER codes in a spell in the order of preference:

Situation CHOSEN_OP
Spell has none the OPER codes listed below First OPER code that isn't "&"
AAA code in spell First AAA
Both PTCA and Contrast codes somewhere in spell, but no CABG code First PTCA
Both CABG plus PTCA in spell If the OPDAT for the PTCA is the same or one day after the OPDAT for the CABG, pick the PTCA, otherwise pick the CABG. (If OPDATs are missing, pick the CABG.)
Both CABG plus Carotid in spell First CABG
Otherwise... Pick the first op which has a code in the table below.

OPER codes fall into the above groups based on the following (the codes must begin with one of the appropriate values):

Type Definition
CABG K40, K41, K42, K43, K44, K45, K46
PTCA K49, K50
Contrast K63, K65
Carotid L29
AAA L183, L193, L203, L213, L184, L185, L186, L194, L195, L196, L204, L205, L206, L214, L215, L216
Listed A01, A02, A08, A12, A38, A40, A41, A52, A65, A83, A84, B27, B28, C12, C31, C32, C33, C34, C35, C60, C71, C72, C73, C74, C75, C77, C82, D03, D15, E03, E04, E25, E29, E36, E49, E51, E53, E54, F09, F10, F22, F34, G01, G02, G03, G14, G15, G16, G17, G18, G19, G27, G28, G35, G43, G44, G45, G52, G53, G58, G69, G70, G71, G78, H01, H02, H04, H05, H06, H07, H08, H09, H10, H11, H13, H15, H20, H21, H22, H23, H24, H25, H26, H27, H28, H33, H44, H48, H50, H51, H52, H54, H56, J01, J02, J13, J14, J18, J38, J39, J40, J41, J43, J56, J69, K01, K02, K04, K05, K06, K07, K09, K10, K11, K12, K14, K18, K19, K20, K25, K26, K27, K28, K29, K30, K31, K34, K37, K40, K41, K42, K43, K44, K45, K46, K49, K50, K53, K60, K63, K65, K66, L01, L05, L06, L09, L10, L12, L18, L19, L20, L21, L29, L33, L35, L48, L49, L50, L51, L52, L53, L56, L57, L58, L59, L60, L62, L63, L85, L87, L95, M01, M02, M14, M26, M27, M28, M29, M34, M42, M45, M65, N08, N09, N17, N30, P23, P31, Q01, Q02, Q03, Q07, Q08, Q10, Q11, Q14, Q17, Q18, Q35, Q36, Q38, Q39, Q41, Q49, Q50, R17, R18, R19, R20, R21, R22, R23, R24, R25, S05, S06, T19, T20, T21, T24, T42, T43, T46, T52, T54, T59, T60, T67, V09, V22, V25, V26, V29, V33, V34, V38, V39, V43, V47, V48, V49, W15, W19, W20, W21, W22, W23, W24, W25, W26, W28, W34, W37, W38, W39, W40, W41, W42, W46, W47, W48, W59, W79, W82, W83, W84, W85, W86, W87, W88, W90, X09, X29, X33, X35, X41

The "first" OPER code is decided on an EPISODE then the number of the OPER variable - for instance, OPER2 is considered "before" OPER5 in the same episode. They are not ordered by date.

OPDATn is a HES field and reflects the date associated with OPERn.

Kidney removal - readmitted patients

Metric
The ratio of the observed number of readmissions to the expected number of readmissions, multiplied by 100.
Numerator

All spells with an emergency readmission within 28 days of discharge.

Readmitting episode - Emergency admissions:

  • 21, Emergency - via A&E
  • 22, Emergency - via GP
  • 23, Emergency - via Bed Bureau
  • 24, Emergency - via Out-patient clinic
  • 28, Emergency - via other means

Readmission date within 28 days of discharging spell

Procedure Group - Total excision of kidney - OPCS code: M02

Denominator

Expected number of readmission derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Primary procedure
  • Co-morbidities (Dr Foster methodology)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Ethnicity
  • Source of admission
Data Source
SUS - CDS
Time frame
April 2008 - March 2011
Basis
Acute Trust
Statistical methods used

Logistic regression

The ratio is calculated by dividing the actual number of readmissions by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has a SRR of 100, that means that the number of patients who were readmitted is exactly as would be expected taking into account the standardisation factors. A SRR above 100 means more patients were readmitted than would be expected; one below 100 means that fewer than expected were readmitted.

Cardiac

Deaths following a heart attack

Metric
The ratio of the observed number of in-hospital deaths during admissions for acute myocardial infarction to the expected number of deaths, multiplied by 100
Observed
Denominator superspells with method of discharge as death (DISMETH=4)
Denominator

Superspells containing a spell with a primary dominant diagnosis of acute myocardial infarction

Acute myocardial infarction ICD10 codes: I21,I22

Data Source
SUS - CDS
Time frame
Financial year 2006/07 - 2010/11
Basis
Acute Trust
Statistical methods

Expected number of in-hospitals deaths is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Superspell: a group of spells linked by transfer

Heart disease - readmitted patients

Metric
The cost of readmissions within 30 days of discharge after having a CABG for a specific group of diagnoses.
Definition

The sum of the PbR tariffs of the emergency readmissions within 30 days of discharge of the original episode.

Original episode -

Isolated first CABG -

OPCS code:

  • K40-K46

Excluding spells with any of the following codes:

  • K2[5-9]|K3[0-5]
  • K1[01]|K22|K23[^2]|K5[256]|K6[01]

Readmitting episode - Emergency admissions:

  • 21, Emergency - via A&E
  • 22, Emergency - via GP
  • 23, Emergency - via Bed Bureau
  • 24, Emergency - via Out-patient clinic
  • 28, Emergency - via other means

Readmission date within 30 days of discharging spell

Specific diagnosis groups:

Diagnosis group ICD10 codes
Acute myocardial infarction I21, I22
Coronary atherosclerosis and other heart disease I20, I24, I251, I252, I255-I259
Nonspecific chest pain R071-R074
Conduction disorders I44, I45
Cardiac dysrhythmias I47, I48, I491-I499, R00
Cardiac arrest and ventricular fibrillation I46, I490
Congestive heart failure, nonhypertensive I50
Phlebitis, thrombophlebitis and thromboembolism I80-I82
Pneumonia A202, A212, A221, A310, A420, A430, A481, A78, B012, B052, B250, B583, B59, B671, J12-J16, J170-J173, J178, J18, J850, J851
Pleurisy, pneumothorax, pulmonary collapse J86, J90-J94, J981-J983, R091
Gastrointestinal haemorrhage I850, K250, K252, K254, K256, K260, K262, K264, K266, K270, K272, K274, K276, K280, K282, K284, K286, K625, K920-K922
Acute and unspecified renal failure N17, N19
Complication of device, implant or graft T82-T87
Complications of surgical procedures or medical care G97, H59, H95, I97, J95, K91, M020, M022, M803, M813, M96, N98, N99, O29, O89, T80, T81, T88, T983
Data Source
SUS - CDS
Time frame
Financial year 2006/07 - 2010/11
Basis
Acute Trust
Statistical methods
Crude rate

Other quality indicators

Outpatient waits

Metric
Median outpatient waiting time (days)
Calculation
Median waiting time ('Waiting' gives the period in days between the date of the appointment date and either the referral request received date (reqdate) or the DNA (did not attend) date, if given.) for each Trust.
Criteria
  • Acute specialties only (see appendix)
  • Patients referred by a General Medical Practitioner, Dentist or Dental service
  • Patients with a null or zero waiting time are excluded
  • First attendances
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used
Z score
Appendix
Group id Diagnosis group
100 General Surgery
10 Urology
10 Transplantation Surgery
10 Breast Surgery
10 Colorectal Surgery
10 Hepatobiliary & Pancreatic Surgery
10 Upper Gastrointestinal Surgery
10 Vascular Surgery
110 Trauma & Orthopaedics
120 ENT
130 Ophthalmology
140 Oral Surgery
14 Restorative Dentistry
14 Orthodontics
14 Maxillo-Facial Surgery
14 Oral & Maxillo Facial Surgery
14 Endodontics
14 Periodontics
14 Prosthodontics
14 Surgical Dentistry
150 Neurosurgery
160 Plastic Surgery
16 Burns Care
170 Cardiothoracic Surgery
17 Cardiac Surgery
17 Thoracic Surgery
17 Cardiothoracic Transplantation
180 Accident & Emergency
190 Anaesthetics
19 Pain Management
19 Critical Care Medicine
14 Paediatric Dentistry
17 Paediatric Surgery
300 General Medicine
30 Gastroenterology
30 Endocrinology
30 Clinical Haematology
30 Clinical Physiology
30 Clinical Pharmacology
30 Hepatology
30 Diabetic Medicine
30 Blood And Marrow Transplantation
30 Haemophilia
310 Audiological Medicine
31 Clinical Genetics
31 Clinical Cytogenetics And Molecular Genetics
31 Clinical Immunology And Allergy
31 Rehabilitation
31 Palliative Medicine
31 Clinical Immunology
31 Allergy
31 Intermediate Care
31 Respite Care
320 Cardiology
32 Clinical Microbiology
330 Dermatology
340 Respiratory Medicine
34 Respiratory Physiology
350 Infectious Diseases
35 Tropical Medicine
360 Genito-Urinary Medicine
36 Nephrology
370 Medical Oncology
37 Nuclear Medicine
400 Neurology
40 Clinical Neuro-Physiology
410 Rheumatology
450 Dental Medicine Specialties
460 Medical Ophthalmology
32 Paediatric Cardiology
420 Paediatrics
42 Paediatric Neurology
620 GP Non-maternity
800 Clinical Oncology (previously Radiotherapy)
810 Radiology
81 Interventional Radiology
820 General Pathology
82 Blood Transfusion
82 Chemical Pathology
82 Haematology
82 Histopathology
830 Immunopathology
83 Medical Microbiology
83 Neuropathology
900 Community Medicine
90 Occupational Medicine

Day case overstays

Metric
Number of daycase overstays
Numerator
Spells where management intent =2 (day case) and length of stay is greater than zero.
Denominator
All spells where management intent =2 (day case)
Exclude cases

Elective only - admission method:

  • 11
  • 12
  • 13
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods used
Crude rate

% deaths at each trust which are coded as palliative care

Metric
The percent of all deaths with a Hospital Standardised Mortality Ratio (HSMR) diagnosis coded as palliative care
Numerator

Denominator superspells containing any episode with specialty of Palliative (315) or a diagnosis code at any position of Palliative care

Palliative care ICD10 codes: Z515

Denominator

Superspells containing a spell with a primary dominant diagnosis of any of the 56 CCS groups that comprise the HSMR basket and where the method of discharge is death (DISMETH=4,5)

See appendix M: HSMR basket

Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Notes

The HSMR basket of CCS groups accounts for approximately 80% of all in-hospital deaths in England.

Superspell: a group of spells linked by transfer

Ratio of Doctors per 100 beds

Metric
Dr Foster Research has calculated the ratio of doctors to 100 beds at each NHS Trust or board. This ratio has been shown to have a strong link to mortality figures: hospitals with high doctors per bed tend to have better than expected mortality ratios, and vice versa.
Data Source

England The submitted figures for the column All Staff (FTE) in Table 3.1 : Hospital and Community Health Services (HCHS) : Medical and dental staff within each Strategic Health Authority area by organisation and grade as at 30th September 2010 from the Medical and Dental Staff Detailed Results Tables.

The number of beds at each hospital is published in the General and Acute (available) column of 'Average daily number of available and occupied beds open overnight by sector - KH03' return and is for January to March 2011.

Time frame
England: April 2010- March 2011
Basis
Trust level

Ratio of Nurses per 100 beds

Metric
Dr Foster Research has calculated the ratio of nurses per 100 beds at each NHS Trust or board.
Data Source

England The submitted figures for the column Qualified nursing, midwifery & health visiting staff (full time equivalent) in Table 7a. NHS Hospital and Community Health Services: Staff by main staff groups in England as at 30th September 2010 from the Non Medical Workforce Census.

The number of beds at each hospital is published in the General and Acute (available) column of 'Average daily number of available and occupied beds open overnight by sector - KH03' return and is for January to March 2011.

Time frame
England: April 2010- March 2011
Basis
Trust level

Obstetric Trauma - Vaginal Delivery Without Instrument

Metric
Cases of obstetric trauma (3rd or 4th degree lacerations) per 100 vaginal deliveries without instrument assistance
Observed

Denominator spells with ICD codes for 3rd and 4th degree obstetric trauma in any diagnosis field or OPCS 4 codes for repair of obstetric trauma in any procedure field

ICD codes:

O702 Third degree perineal laceration during delivery
O703 Fourth degree perineal laceration during delivery
O713 Obstetric laceration of cervix
O714 Obstetric high laceration alone
O715 Other obstetric injury to pelvic organs

OPCS 4 codes:

R321 Immediate repair of obstetric laceration of uterus or cervix uteri
R328 + Z421 (Z421 relates to the bladder)
R322 Immediate repair of obstetric laceration of perineum and sphincter of anus
Denominator

Spells with normal delivery or delivery without instrument codes in any procedure field

OPCS 4 codes:

R23 Cephalic vaginal delivery with abn presentation of head without instrument
R24 Normal delivery
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust
Statistical methods

Crude rate

Expected values are based on the national average rate

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% binomial control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% binomial control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Based on AHRQ PSI indicators. Translated by the Dr Foster Unit at Imperial College in collaboration with the Care Quality Commission (formerly the Healthcare Commission).

Private Hospital Indicators

Orthopaedics

Elective Hip Replacement Standardised Rate of Long Length of Stay

Metric
The ratio of the observed number of long length of stay elective hip replacement spells to the expected number, multiplied by 100
Observed

Denominator spells where the length of stay is greater than the length of stay of the 75th percentile elective hip replacement patient in England

Length of stay: discharge date - admission date

Denominator

Elective spells with a dominant procedure of hip replacement

Hip replacement OPCS 4 codes: W37-W39,W93-W95

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Long LOS percentile cut-off is defined for each procedure/diagnosis group, spell year and admission method (elective/non-elective), and excludes day cases.

Elective Hip Replacement Standardised 28 day Emergency Readmission Rate

Metric
The ratio of the observed number of elective hip replacement admissions with an emergency readmission within 28 days of discharge to the expected number, multiplied by 100
Observed

Denominator superspells with an emergency readmission within 28 days of discharge

Inclusion:

  • Readmitting episode- Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date minus discharge date < 28 days
Denominator

Superspells containing an elective spell with a dominant procedure of hip replacement

Hip replacement OPCS 4 codes: W37-W39,W93-W95

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Superspell: a group of spells linked by transfer

Elective Hip Replacement Rate of Revision or Manipulation

Metric
The number of elective hip replacements with a revision procedure within 365 days of the initial (index) procedure, over the total number of elective hip replacements carried out at the trust over a three year period
Observed

Denominator superspells with a revision procedure on the same side within 365 days of the index procedure

Revision of hip replacement OPCS 4 codes: W370, W372, W373, W374, W380, W382, W383, W384, W390, W392, W393, W394, W395, W396, W55-W57(+W3[789]0|W9[345]0), W580(+Z843), W582(+Z843), W930, W932, W933, W940, W942, W943, W950, W952, W953, W954

Denominator

Superspells containing an elective spell with a dominant procedure of hip replacement and a valid side of index procedure.

Primary total hip replacement OPCS 4 codes: W371, W381, W391, W581(+Z843), W931, W941, W951

Side of index procedure OPCS 4 codes: Z941, (Z942 + Z943), Z942, Z943, Z944

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
Index procedure: April 2007 - March 2010. Revisions: April 2008 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Crude Rate

Expected values are based on the national average rate.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% binomial control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% binomial control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Three years of index procedures are combined to provide sufficient numbers at trust level. A further year of data is needed to allow a year's follow-up for every index procedure. Index operations in 2007/8 to 2009/10 give rise, potentially, to revisions between 2008/9 and 2010/11.

Only one revision within 365 days per patient is counted (some people can have several), and revisions are matched to side of index procedure (right or left).

An observed revision is attributed to the denominator superspell containing the index procedure.

Superspell: a group of spells linked by transfer

Elective Knee Replacement Standardised Rate of Long Length of Stay

Metric
The ratio of the observed number of long length of stay elective knee replacement spells to the expected number, multiplied by 100
Observed

Denominator spells where the length of stay is greater than the length of stay of the 75th percentile elective knee replacement patient in England

Length of stay: discharge date - admission date

Denominator

Elective spells with a dominant procedure of knee replacement

Knee replacement OPCS 4 codes: O18,W40-W42,W5[234][1389] (+Z844-6),W580-2 (+Z846)

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes
Long LOS percentile cut-off is defined for each procedure/diagnosis group, spell year and admission method (elective/non-elective), and excludes day cases.

Elective Knee Replacement Standardised 28 day Emergency Readmission Rate

Metric
The ratio of the observed number of elective knee replacement admissions with an emergency readmission within 28 days of discharge to the expected number, multiplied by 100
Observed

Denominator superspells with an emergency readmission within 28 days of discharge

Inclusion:

  • Readmitting episode - Emergency admissions:
    • 21, Emergency - via A&E
    • 22, Emergency - via GP
    • 23, Emergency - via Bed Bureau
    • 24, Emergency - via Out-patient clinic
    • 28, Emergency - via other means
  • Readmission date minus discharge date < 28 days
Denominator

Superspells containing an elective spell with a dominant procedure of knee replacement

Knee replacement OPCS 4 codes: O18,W40-W42,W5[234][1389] (+Z844-6),W580-2 (+Z846)

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
April 2010 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Logistic regression

Expected number of readmissions is derived from logistic regression, adjusting for factors to indirectly standardise for differences in case-mix.

Adjustments are made for:

  • Sex
  • Age on admission (in five year bands up to 90+)
  • Interactions between age on admission (in five year bands up to 90+) and Charlson co-morbidity score**
  • Admission method (non-elective or elective)
  • Socio-economic deprivation quintile of the area of residence of the patient (based on the Carstairs Index)
  • Diagnosis/procedure subgroup
  • Co-morbidities (based on Charlson score)
  • Number of previous emergency admissions
  • Year of discharge (financial year)
  • Palliative care (if any episode in the spell has the treatment function code 315 or contains ICD10 code Z515 in any of the diagnoses fields)
  • Month of admission
  • Source of admission

**new to logistic regression model in 2011

Relative Risk

The ratio is calculated by dividing the actual number of deaths by the expected number and multiplying the figure by 100. It is expressed as a relative risk, where a risk rating of 100 represents the national average. If the trust has an SMR of 100, that means that the number of patients who died is exactly as it would be expected taking into account the standardisation factors. An SMR above 100 means more patients died than would be expected; one below 100 means that fewer than expected died.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% poisson control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% poisson control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Superspell: a group of spells linked by transfer

Elective Knee Replacement Rate of Revision or Manipulation

Metric
The number of elective knee replacements with a revision procedure within 365 days of the initial (index) procedure, over the total number of elective knee replacements carried out at the trust over a three year period
Observed

Denominator superspells with a revision procedure on the same side within 365 days of the index procedure

Revision of knee replacement OPCS 4 codes: O182, O183, O184, W400, W402, W403, W404, W410, W412, W413, W414, W420, W422, W423, W424, W425, W5[234]3(+Z84[456]), W55-W57(+W4[012]0), W58[02](+Z846)

Denominator

Superspells containing an elective spell with a dominant procedure of knee replacement and a valid side of index procedure

Primary total knee replacement OPCS 4 codes: O181, W401, W411, W421, W5[234]1(+Z84[456]), W581(+Z846)

Side of index procedure OPCS 4 codes: Z941, (Z942 + Z943), Z942, Z943, Z944

Elective admission method codes:

  • 11: Elective - from waiting list
  • 12: Elective - booked
  • 13: Elective - planned
Data Source
SUS - CDS
Time frame
Index procedure: April 2007 - March 2010. Revisions: April 2008 - March 2011
Basis
Acute Trust, Orthopaedic Specialist Trust, Independent Sector Provider treating NHS patients
Statistical methods

Crude Rate

Expected values are based on the national average rate.

Control Limits

Control limits tell us the range of values which are consistent with random or chance variation. Data points falling within the control limits are consistent with random or chance variation and are said to display 'common-cause variation'; for data points falling outside the control limits, chance is an unlikely explanation and hence they are said to display 'special-cause variation' - that is, where the trust's rate diverges significantly from the national rate.

Data points falling above the upper 99.8% binomial control limit are said to be significantly 'higher than expected', data points falling below the lower 99.8% binomial control limit are said to be significantly 'lower than expected', otherwise 'within expected range'.

Notes

Three years of index procedures are combined to provide sufficient numbers at trust level. A further year of data is needed to allow a year's follow-up for every index procedure. Index operations in 2007/8 to 2009/10 give rise, potentially, to revisions between 2008/9 and 2010/11.

Only one revision within 365 days per patient is counted (some people can have several), and revisions are matched to side of index procedure (right or left).

An observed revision is attributed to the denominator superspell containing the index procedure.

Superspell: a group of spells linked by transfer

Appendix

Appendix documents referenced in the above can be downloaded from the following links

Appendix A: Surgical HRGs

Appendix B: Medical HRGS

Appendix C: Derived Operating Room Procedures

Appendix D: Potential Complications of Care Diagnoses

Appendix E: Immunocompromised states

Appendix F: Cancer codes

Appendix G: Trauma codes

Appendix H: Low mortality CCS groups

Appendix I: Francture of Neck of Femur Related Procedure Codes

Appendix L: Infection ICD10 codes

Appendix M: HSMR Basket

HSMR Toolkit Version 6