Campaign Measures Definitions · To find out more visit Version 1.1 - 08/12/08 2 Measures Introduction This paper focuses on the measures that are being recommended for the Patient

Making the Safety of patients everyone’s highest priority

Campaign

Measures Definitions

To find out more visitwww.patientsafetyfirst.nhs.uk


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Measures

Introduction

This paper focuses on the measures that are being recommended for the Patient Safety First Campaign. It covers briefly the justification for including measurement as part of the Campaign infrastructure. It then discusses the two components: overall Campaign measures and intervention specific measures. It concludes with a summary and recommendations.

The aim of the Patient Safety First campaign is to have no avoidable death and no avoidable harm. The Campaign is promoting a number of interventions to achieve this aim and by the end of the Campaign period will need to demonstrate to what extent it has been achieved. We have selected two measures, referred to as overall measures, which will track the Campaign’s progress against the aim. We have also recommended a set of measures relating to each intervention.

This paper explains what these measures are and also which are required for reporting on a regular basis.

Types of measure

Within the Patient Safety First Campaign there are three different categories of measures which will help assess the overall impact of the work. These are:

Overall Campaign measures•Recommended measures related to individual interventions; •Additional measures by intervention.•

Each measure can also be described as being of one of two types: a process measure or an outcome measure.

Process Measures are sometimes referred to as ‘the voice of the workings of the sys-tem’ because they assess how well or how reliably the processes of care are being per-formed. Outcome Measures are sometimes referred to as ‘the voice of the customer or patient’ because they measure the end result for the patient.

To demonstrate improved outcomes for patients, we need outcome measures but to achieve improved outcomes, we need reliable care processes. And to demonstrate these, we need process measures. The measures chosen for each intervention are mostly a mixture of process and outcome measures.


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Measuring overall campaign progress

The measures we are recommending to track progress against the campaign aim are:

Hospital standardised mortality rate (HSMR) as a proxy for avoidable death;•Adverse incident rate calculated by the UK Global Trigger Tool as an estimate of •avoidable harm.

Hospital Standardised Mortality Ratio (HSMR)

We will use the HSMR to track progress on avoiding deaths. We have selected the HSMR for very practical reasons. It is relatively easily available and understood. HSMR measures all death not just those that are avoidable so it is only a proxy. But measur-ing avoidable death is difficult to do with our current information systems and this is why we are advocating a simpler if less accurate approach. If you want to experiment with more accurate measures as part of the Campaign involvement then we encourage you to do so.

The measure will be calculated each month by Imperial College for the whole of •England.

Imperial will produce a baseline HSMR from which the expected level of deaths in •England will be projected forward over the life of the Campaign. The actual month-ly HSMR will be compared to these projections and the number of lives saved

estimated as the difference between the two figures.•

The hospital adverse event rate

We will use the hospital adverse event rate to track progress on preventing episodes •of harm. The actual measure is the adverse event rate per 1,000 patient days.

This measure will be produced by each Trust using the Global Trigger Tool (GTT). •The Tool has been developed to estimate avoidable harm in previous campaigns and programmes. It has been used in American, Canadian and Welsh campaigns to date. There is also a viable and tested way of working – a set of 20 case notes selected at random per month provides a robust estimate of harm when viewed as a time series.

The data gathered should be reported on the IHI Extranet.•

Trusts are strongly recommended to retrospectively review case notes over a 6 •month period to set a baseline rate from which any subsequent improvement can be judged. These results should also be reported on the IHI Extranet.

Please note the Campaign will only be reporting these measures on an England only basis.


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Measuring progress on agreed interventions

There are 5 agreed interventions for use within the campaign and this section covers the recommended measures for each in turn. There are 4 other interventions (VTE, falls, surviving sepsis bundle, and peripheral lines) that are under development. We are not currently recommending any measures for these but intend to define these as each intervention is developed.

Any organisation signing up for the Campaign must expect to report the 2 overall measures plus those associated with the Leadership for Safety and other chosen interventions.

Leadership for safety

The recommended measure is:

The number of safety walkarounds per month•

A qualitative measure that we think a useful addition is the noting whether Safety is an item on the Board agenda. You may also like to consider recording the number of actions generated by safety walkarounds (and those that have been progressed each month) and results of your safety culture survey.

Critical care

The recommended measures are:

Ventilator bundle compliance•

Days between Ventilator associated pneumonias (VAP)•

Central Line bundle compliance•

Days between central line infections (CLI)•

Additional measures are:

VAP rate per 1,000 ventilator days•

CLI rate per 1,000 central line days•

Ventilator length of stay•

Length of stay in ICU•

These measures are in use with the 1000 Lives campaign in Wales and also used by the Safer Patients Initiative.


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Peri-operative care


• SSIrate30dayspostoperation

• SSIbundlecompliance

• %antibioticsadministeredontime

• %antibioticsdiscontinuedontime

• %surgerywithappropriatehairremoval

• %ofsurgicalpatientswithperioperativenormothermia

• %diabeticswithcontrolledglucose

• %patientswithappropriatehairremoval

• %compliancewithuseoftheWHOSurgicalSafetyChecklist

Some of hese measures are in use with the 1000 Lives campaign in Wales and also used by the Safer Patients Initiative.

Deterioration


The number of cardiac arrests per month•

The number of Rapid Response calls per month•

The percentage of Rapid Response team communications performed with your •chosen communication tool. We have created measures for SBAR and RSVP, simply select the one you are using. If you use another tool, you will need to create a custom measure. Please contact the campaign team for further guidance on how to do this.

If you want more information on where your process for dealing with deteriorating patients is working or not working, you might like to consider the following process measures:

• Thepercentageofpatientobservationscomplete

• Thepercentageofpatientswhotriggeredthathadanappropriatereaction

These can both be picked up while doing the GTT audit. We also strongly recommend performing a mortality case note review to get a handle on the issues surrounding unexpected death.


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High risk medicines

The campaign is focusing on 4 drugs or drug groups: Anticoagulants, Opiates, Insulin and anaesthetic sedatives. Ideally we would want to measure compliance with treatment protocol (a process measure) and adverse drug events related to these drugs (an outcome measure). However these are extremely labour intensive to collect and so we recommend a series of proxy outcome measures as follows because they are more straightforward to collect:

• %ofinpatientwarfarindosesadministeredaccordingtoprotocol*

• NumberofpatientsreceivingWarfarinwithINR>6

• NumberofpatientsreceivingWarfarinwithINR>5*

• NumberofpatientsreceivingWarfarinwithINR>8*

• %ofpatientsreceivinglowmolecularweightheparinoutsideprotocollimits*

• Numberofpatientsreceivingflumazeniltocounteracteffectsofmidazolam*

• %ofpatientswithnoINRrecordedoninpatientwarfarinprescription*

Additional measures

There are additional measures contained in the How To Guide that participants may want to use to assess compliance with protocols and measure real outcomes. They are:

The number of patients who received opiates who receive subsequent treatment •withnaloxone*

Numberofpatientswhoreceived25%/50%glucosetocorrectinsulininduced•hypoglycaemia

Reportedanticoagulantadverseeventrate*•

Adverse event rate associated with use of low molecular weight heparin and •unfractionated heparin

Injectablesedativeadverseeventrate*•

%ofpatientstreatedwithinopiateprotocol*•

Opiateadverseeventrate*•

Insulinadverseeventrate*•

*Thesemeasuresareinusewiththe1000LivescampaigninWales.


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Section A - Leadership for safety

Measure name: L01 Number of walkrounds completedMeasure type: ProcessRelated driver: Board leadership: Demonstrate leadershipDescription: The total number of safety walkrounds conducted by the

senior leaders since the start of the campaign.Rationale: Leadership walkrounds provide an opportunity for teams to

reflect on safety issues, for senior leaders to obtain an overview of the safety issues, and a means to provide guidance for improving the system.

Numerator: The cumulated number of walkroundsData Source: Local AuditDenominator: NoneData Source: NoneMethod of calculation: AddthetotalNumberofwalkroundsconductedthismonth

by the Trust senior leaders to those undertaken in previous months to arrive at a cumulated total.

Collection guidance: Count the number of walkrounds that occur every month and report the total number since the start of the campaign. This measure requires no sampling.


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Section B – Critical Care

Measure name: C01 % compliance with ventilator care bundleMeasure type: ProcessRelated driver: Reduce harm from mechanical ventilationDescription: The percentage of patients compliant with a ventilator care

bundle. The ventilator care bundle includes 4 elements.Where all 4 elements have been met this demonstrates compliance with the ventilator care bundle.

Rationale: Adopting the 4 components of the ventilator bundle should reduce mortality and harm from mechanical ventilation.

Numerator: The number of ventilated patients in the sample receiving all 4 components of the ventilator bundle during the month.

Data Source: Local auditDenominator: The total number of patients reviewed in the sample during

the month.Data Source: Local auditMethod of calculation: Calculate the percent compliance with the ventilator bundle

by dividing the numerator by the denominator and multiplying the result by 100.

Collection guidance: Select ALL ventilated patients in the unit(s) on a randomly selected day each week. Rotate days of the week and shifts

Use daily goal sheet or consultant order sheet as the primary data source or direct observation.

RememberthisisaYES/NOoutcome-onlypatientsreceivingall 4 components of the bundle are recorded as compliant.

Report data monthly - Report the 4 figures for the month as an aggregated numerator and denominator each month.


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Measure name: C02 Days between a ventilator associated pneumonia

Measure type: OutcomeRelated driver: Reduce harm from mechanical ventilationDescription: This measure is a cumulative count of the number of days

that have gone by with no ventilator associated pneumonia (VAP) being reported. Every time a VAP occurs the count is started over again.

Rationale: In this case, we are plotting successes between failures, that is days with no VAP occurring. The more days between events the better the outcome.

Numerator: The number of days between the current and previous VAP. Calculate the number of days by subtracting date of the previous infection from the date of current VAP.

Data Source: Local AuditDenominator: NotapplicableData Source: NotapplicableMethod of calculation: Calculate the number of days by subtracting date of the

previous infection from the date of current infection.Collection guidance: Whenever events occur that are relatively rare in nature or

when a ward or pilot area has sufficiently small numbers of events, the preferred way to go about analysing the data is to plot: (1) successes between failures, or (2) time between failures. Both of these techniques have been used in the SPI work.


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Measure name: C03 Ventilator acquired pneumonia rateMeasure type: OutcomeRelated driver: Reduce harm from mechanical ventilationDescription: The Ventilator associated pneumonia (VAP) rate is defined as

the number of patients diagnosed with ventilator associated pneumonia for every 1,000 days on mechanical ventilation.

Rationale: This measure sets out to estimate the overall level of Ventilator associated pneumonias present at any one time in unit. By tackling issues that arise and implementing the recommended interventions you should see the level drop over time.

Numerator: The total number of ventilator associated pneumonia cases during the month.

Data Source: Local dataDenominator: The total number of days that patients were on mechanical

ventilation during the month.Data Source: Local dataMethod of calculation: The VAP rate is calculated by dividing the total number of

VAPs occurring in the month (the numerator) by the total number of ventilator days in the month (the denominator) and then multiplying the result by 1000 to create a VAP rate per 1000 ventilator days.

Collection guidance: Report monthly data over the life of the campaign into the Extranet. Provide numerators and denominators when entering the data. The annotation section should be used to reflect any interventions that were made to reduce the VAP rate.There should be no sampling for this measure.


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Measure name: C04 % compliance with central line bundleMeasure type: ProcessRelated driver: Reduce central line infections (CLI)Description: The percentage of patients with compliance to the Central

line bundle. There are 5 elements included in the bundle. Where all 5 elements have been met this demonstrates compliance with the bundle.

Rationale: Adopting the central line bundle will reduce mortality and harm due to complications of using central venous catheters.

Numerator: The total number of patients who have all 5 elements of the bundle in place during the month.

Data Source: Local auditDenominator: The total number of inserted lines reviewed during the

month.Data Source: Local auditMethod of calculation: Calculate the percent compliance with the central line

bundle by dividing the numerator by the denominator and then multiplying the resulting proportion by 100.

Collection guidance: There should be no sampling for this measure. All patients with central lines inserted should be reviewed for compliance.


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Measure name: C05 Days between a central line infectionMeasure type: OutcomeRelated driver: Reduce central line infections (CLI)Description: This measure is a cumulative count of the number of days

that have gone by with no central line infection being reported. Every time an infection occurs the count is started over again.

Rationale: In this case, we are plotting successes between failures, that is days with no infection occurring. The more days between events the better the outcome.

Numerator: The number of days between the current and previous infection. Calculate the number of days by subtracting date of the previous infection from the date of current infection.

Data Source: Local AuditDenominator: NotapplicableData Source: NotapplicableMethod of calculation: Calculate the number of days by subtracting date of the

previous infection from the date of current infection.Collection guidance: Whenever events occur that are relatively rare in nature or

when a ward or pilot area has sufficiently small numbers of events, the preferred way to go about analysing the data is to plot: (1) successes between failures, or (2) time between failures. Both of these techniques have been used in the SPI work.


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Measure name: C06 Central line infection rateMeasure type: OutcomeRelated content area / driver: Reduce central line infections (CLI)Description: The number of central venous catheter-related

bloodstream infections (CLIs) per 1,000 catheter days during the month.

Rationale: This measure sets out to estimate the overall level of central line catheter-related bloodstream infections present at any one time in unit. By tackling issues that arise and implementing recommended interventions should see the level drop over time.

Numerator: The total number of central venous catheter-related infections during the month.

Data Source: Local dataDenominator: The total number of patient days that central venous

catheters (central lines) were in place during the month.

Data Source: Local dataMethod of calculation: The CLI rate is calculated by dividing the total

numerator by the denominator and multiplying the result by 1000 to get the CLI rate per 1000 catheter days

Collection guidance: For each patient, count the number of days that they had a line inserted for and then total these to get a grand total of days for all patients. This is your denominator.

There should be no sampling for this measure.

Report data monthly.

Provide numerator and denominator when entering the data.

The annotation section should be used to reflect any interventions that were made to reduce the infection rate.


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Measure name: C07 Average mechanical ventilation LOSMeasure type: BalancingRelated driver: Reducing harm in critical careDescription: The average length of stay (LOS) on mechanical ventilation.

This measure assesses average number of days patients require ventilation during a calendar month.

Rationale: Following implementation of the Ventilator care bundle the average of Length of stay on Mechanical Ventilator should reduce over time.

Numerator: The total number of days patients were on an ICU mechanical ventilator during the month.

Data Source: Local dataDenominator: The total number of patients on an ICU mechanical

ventilator during the month.Data Source: Local dataMethod of calculation: Calculate the ALOS on mechanical ventilator by dividing the

numerator (total number of vent days) by the denominator (total vent patients).

Collection guidance: This measure should not be based on a sample. Instead it should include all the ventilator days and patients in the ICU(s) being studied.


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Measure name: C08 ICU average LOSMeasure type: BalancingRelated driver: Reducing harm in critical careDescription: The average length of stay (LOS) of all patients

discharged from Intensive care units during the month.Rationale: Implementing the evidence-based interventions should

reduce this measure over time.Numerator: The total number of days stay for patients discharged

from ICU during the month.Data Source: Augmented care datasetDenominator: The total number of patients discharged from ICU in the

month.Data Source: Augmented care datasetMethod of calculation: To calculate the ICU ALOS all patients discharged in a

given month should have their length of stays summed up and divided by the number of patients. This is the average for the month.

Collection guidance: Collect and report this measure monthly for patients discharged from ICU.


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Section C – Deterioration

Measure name: D01 Number of Cardiac Arrest CallsMeasure type: OutcomeRelated driver: Respond to deteriorationDescription: The number of Cardiac Arrest Calls made per month.Rationale: Implementation of a Rapid Response System should lead to a

reduction in the number of Cardiac Arrest Calls over time.Numerator: The total number of cardiac arrest calls in the current month.Data Source: Rapid response co-ordinator or other local sourceDenominator: NotApplicableData Source: NotApplicableMethod of calculation: Count the number of actual cardiac arrest calls during the

month.Collection guidance: ThisisNOTthenumberofarrestsbutofcallstoasuspected

arrest.

This is not a sample but a total of all relevant calls dur-ing the month. The number of cardiac arrest calls can be obtained from the Rapid response co-ordinator or hospital switchboard.


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Measure name: D02 Number of rapid response callsMeasure type: OutcomeRelated driver: Respond to deteriorationDescription: The number calls for a rapid response to patients who have

been assessed as being of medium or high risk illness. Refer toNICEGuidance50fordefinitionsofMediumandHighriskillness.

Rationale: Implementation of a comprehensive rapid response system should lead to an increase in the number of calls in this measure.

Numerator: The total number of calls for a response to patients who have prompted (1) EWS triggers or (2) staff concerns though no triggers

Data Source: Rapid Response co-ordinatorDenominator: NotApplicableData Source: NotApplicableMethod of calculation: Count of rapid response calls in a monthCollection guidance: This is not a sample but a total of all relevant calls during the

month. Your Rapid Response co-ordinator should be able to provide this data.


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Measure name: D03 % rapid response communications using SBARMeasure type: ProcessRelated driver: Respond to deteriorationDescription: The percentage of rapid response staff actually using SBAR in

communicating patient conditions and status.Rationale: Increasing the number of clinical staff using SBAR should

improve clinical communication.Numerator: The total number of calls to the rapid response team that use

the SBAR methodologyData Source: Local AuditDenominator: The total number of calls to the rapid response teamData Source: Local AuditMethod of calculation: Calculate the percent actually using SBAR by dividing

the numerator by the denominator and then multiplying the resulting proportion by 100

Collection guidance: This measure is designed to answer a simple question: AreclinicalstaffusingSBAR-YesorNo?Foreachphonecall received, ask the rapid response team to note down whether the person making the call uses SBAR in relaying the information.


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Measure name: D04 % rapid response communications using RSVPMeasure type: ProcessRelated driver: Respond to deteriorationDescription: The percentage of rapid response staff actually using RSVP in

communicating patient conditions and status.Rationale: Increasing the number of clinical staff using RSVP should

improve clinical communication.Numerator: The total number of calls to the rapid response team that use

the RSVP methodologyData Source: Local AuditDenominator: The total number of calls to the rapid response teamData Source: Local AuditMethod of calcula-tion:

Calculate the percent actually using RSVP by dividing the numerator by the denominator and then multiplying the resulting proportion by 100

Collection guidance: This measure is designed to answer a simple question: AreclinicalstaffusingRSVP-YesorNo?Foreachphonecall received, ask the rapid response team to note down whether the person making the call uses RSVP in relaying the information.


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Measure name: D05 % patients with observations completeMeasure type: ProcessRelated driver: Identify deteriorationDescription: The percentage of patients in the sample where all the

relevant clinical observations were recorded in the notes.Rationale: Taking regular observations on a consistent basis is one of

the key building blocks on which a policy for identifying and responding to deteriorating patients is built. This measure helps you to assess how reliably this is being done.

Numerator: The number of patients in the sample with all observations complete

Data Source: Local AuditDenominator: The total number of patients reviewedData Source: Local AuditMethod of calculation: Calculate the percent of observations by dividing the

numerator by the denominator and then multiplying the resulting proportion by 100

Collection guidance: RememberthisisaYES/NOoutcome-onlypatientswithallobservations complete are recorded as a YES.

Can be done as part of random case note review using the UK Global Trigger Tool or another sampling technique could be used to obtain this data.

For example, some teams use spot checks three times per week, whereas other teams have chosen assessments of compliance at designated times. Regardless of the method, be sure to maintain the standard over time for accurate results.


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Measure name: D06 % trigger patients receiving an appropriate response

Measure type: ProcessRelated driver: Respond to deteriorationDescription: The percentage of patients in the sample where a response

was indicated by one or more triggers who received an appropriate response in accordance with the local escalation policy

Rationale: An effective escalation policy is not just a Word document but needs to be enacted in a timely manner. This measure shows how well the policy is being used. Effective use of the policy should reduce the number cardiac arrest calls over time.

Numerator: The number of patients in the sample who triggered and received an appropriate response.

Data Source: Local AuditDenominator: The total number of patients reviewedData Source: Local AuditMethod of calculation: Calculate the percentage of patients by dividing the

numerator by the denominator and then multiplying the resulting proportion by 100

Collection guidance: RememberthisisaYES/NOoutcome-onlypatientswhotriggered and received appropriate response are recorded as compliant

Can be done as part of random case note review using the UK Global Trigger Tool or another sampling technique could be used to obtain this data

For example, some teams use spot checks three times per week, whereas other teams have chosen assessments of compliance at designated times. Regardless of the method, be sure to maintain the standard over time for accurate results.


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Section D – Peri-operative care

Measure name: P01 % of surgical patients with SSIMeasure type: OutcomeRelated driver: Reduce surgical site infectionsDescription: The percentage of elective surgical patients developing a

SurgicalSiteInfection(SSI)30dayspostoperation.Rationale: This is a measure of one aspect of the quality of care for

patients undergoing surgery.Numerator: The total number of elective surgical patients in the sample

who developed an SSI.Data Source: Local AuditDenominator: The total number of surgical cases (patients) in the sample.Data Source: Local AuditMethod of calculation: Calculate the actual percent of patients developing a SSI

by dividing the numerator by the denominator and then multiplying the resulting proportion by 100.

Collection guidance: Even though one patient could experience more than one SSI during the same admission or surgical procedure, this measure is a percentage not a rate. The numerator, therefore, is based on a simple question: Did the patient develop a SSI (YesorNo)?Themeasureisnotconcernedwithhowmanyinfections the patient developed.


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Measure name: P02 % compliance with SSI bundleMeasure type: ProcessRelated driver: Reduce surgical site infectionsDescription: The percentage of patients compliant with a surgical site

infection bundle. The bundle includes 4 elements that are also measured separately. Where all 4 elements have been met this demonstrates compliance with the bundle.

Rationale: Adopting all 4 components of the bundle consistently should reduce surgical site infections over time.

Numerator: The number of elective surgical patients in the sample receiving all 4 components of the bundle during the month.

Data Source: Local auditDenominator: The total number of elective surgical patients reviewed in

the sample during the month.Data Source: Local auditMethod of calculation: Calculate the percent compliance with the bundle by

dividing the numerator by the denominator and multiplying the result by 100.

Collection guidance: In order to do this simply it is necessary to have easy access to documented evidence for all components.

Decide locally where to collect data eg form completed by post op care staff as each patient discharged or retrospectively from surgical ward.

RememberthisisaYES/NOoutcome-onlypatientsreceiving all 4 components are recorded as compliant.

Collect data weekly. Aggregate your 4 scores to get a monthly compliance rate.


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Measure name: P03 % antibiotics administered on timeMeasure type: ProcessRelated driver: Reduce surgical site infectionsDescription: The percentage of elective patients receiving on-time

prophylactic antibiotics administration.Rationale: This measure assesses whether units are complying with

evidence-based practise. The implication is high compliance should reduce risk of infection.

Numerator: The number of elective surgical patients with on-time prophylactic antibiotics in your pilot population.

Data Source: Local audit (Data collection tools or patients notes)Denominator: The total number of elective surgical patients in your pilot

population during the month who should have received antibiotic prophylaxis.

Data Source: Local audit (Data collection tools or patients notes)Method of calculation: Calculate the actual percent of eligible patients receiving

antibiotic prophylaxis by dividing the numerator by the denominator and then multiplying by 100 resulting in a proportion.

Collection guidance: Use a pilot population of adult, elective surgical patients and track100%ofpatients.

RememberthisisaYES/NOoutcome-onlypatientsreceiving, the antibiotics within the 60 mins prior to surgical incision and have these discontinued within 24 hours are ticked as compliant. Give credit where a reason for exclusion is documented.

Report data monthly - Report the 4 figures for the month as an aggregated numerator and denominator each month.If you start measuring this in a pilot population, you will have to create a new data series in the Extranet every time you add another area to your surgical population.


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Measure name: P04 % antibiotics discontinued on timeMeasure type: ProcessRelated content area / driver: Reduce surgical site infectionsDescription: Percentage of elective patients whose prophylactic

antibiotics were discontinued 24 hours (48 hours for CABG or other cardiac surgery) after the end of surgery.

Rationale: This measure assesses whether units are complying with evidence-based practise. The implication is high compliance should reduce risk of infection and reduce the risk of antibiotic resistance.

Numerator: The total number of elective surgical patients whose prophylactic antibiotics were discontinued within 24 hours of the end of surgery (48 hours for CABG or other cardiac surgery) in your pilot population.

Data Source: Local audit (Data collection tools or patients notes)Denominator: The total number of elective surgical patients with no

evidence of existing pre-operative infection in your pilot population during the month.

Data Source: Local audit (Data collection tools or patients notes)Method of calculation: Calculate the actual percent of patients whose

antibiotics were discontinued by dividing the numerator by the denominator and then multiplying the resulting proportion by 100.

Collection guidance:

ThisisaYes/Noquestion.Weretheantibioticsdiscontinued within 24 hours of the end of sur-gery?NBPatientsinwhomantibioticsiscontinuedas treatment should be excluded from this measure.

Create a system to track this measure prospectively in100%ofrelevantpilotpopulation.Summariseandreport every month on the Extranet. If you start measuring this in a pilot population, you will have to create a new data series in the

Extranet every time you add another area to your surgical population.


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Measure name: P05 % with perioperative normothermiaMeasure type: ProcessRelated driver: Reduce surgical site infectionsDescription: The percentage of appropriate elective surgical patients

whose first temperature in the post operative care unit was greaterthan36.0degreesCentigrade.

Rationale: This measure assesses whether units are complying with agreed guidance. The implication is that high compliance should reduce the risk of developing a Surgical Site Infection

Numerator: The number of eligible elective surgical patients whose first temperature in the post operative care unit was greater than 36.0degreesCentigrade.

Data Source: Local AuditDenominator: The total number of elective surgical patients not excluded

from normothermic maintenance in your pilot population.Data Source: Local AuditMethod of calculation: Calculate the actual percent of eligible surgical patients

with perioperative normothermia by dividing the numerator by the denominator and then multiplying the resulting proportion by 100

Collection guidance: Createasystemtotrackthismeasureprospectivelyin100%of the surgical patients in the pilot population.

Use anaesthetic chart or post op unit chart as the primary data source.

ThisisaYES/NOoutcome.Onlyeligiblepatientswithatemperature>36°Conarrivalinpostopcareunitarerecorded as compliant. Temperature readings should be record immediately upon leaving the operating theatre.

Normothermia=temperatureofgreaterthan36.0degree Centigrade. Exclusion criteria: Patients for whom hypothermia is deliberately sought for therapeutic reasons (e.g. hypothermic total circulatory arrest).

If you start measuring this in a pilot population, you will have to create a new data series in the Extranet every time you add another area to your surgical population.


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Measure name: P06 % known diabetics with controlled glucoseMeasure type: ProcessRelated driver: Reduce surgical site infectionsDescription: The percentage of known diabetic elective surgical patients

with controlled serum glucose (5.0-10.0 mmol/l) on the day of surgery.

Rationale: This measure assesses whether units are complying with a small evidence-base. The implication is high compliance should reduce risk of infection

Numerator: The number of elective diabetic surgical patients with controlled serum glucose (5.0-10.0 mmol/l) on the day of surgery.

Data Source: Local AuditDenominator: The total number of diabetic elective surgical patients in

your pilot population.Data Source: Local AuditMethod of calculation: Calculate the actual percent of diabetic surgical pa-

tients with perioperative glucose control by dividing the numerator by the denominator and then multiplying the resulting proportion by 100

Collection guidance: Createasystemtotrackthismeasureprospectivelyin100%of the surgical patients in the relevant pilot population.

ThisisaYES/NOoutcome.Onlyeligiblepatientswithcontrolled serum glucose on the day of surgery are recorded as compliant.



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Measure name: P07 % surgical patients with appropriate hair removal

Measure type: ProcessRelated content area / driver:

Reduce surgical site infections

Description: The percentage of inpatient elective surgical patients with hair removal by an approved method.

Rationale: This measure assesses whether units are complying with evidence based practise. The implication is that high compliance should reduce the risk of developing a surgical site infection.

Numerator: The total number of elective surgical patients with surgi-cal site hair removal by an approved method in your pilot population.

Data Source: Local auditDenominator: The total number of elective surgical patients in your pilot

population.Data Source: Local auditMethod of calculation: Calculate the actual percent elective surgical patients with

appropriate hair removal by dividing the numerator by the denominator and then multiplying the resulting proportion by 100.

Collection guidance: Consult the How To Guide for advice on what constitutes appropriate hair removal.

ThisisaYES/NOoutcome.Onlyeligiblepatientswithcontrolled serum glucose on the day of surgery are recorded as compliant.



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Measure name: P08 % compliance with WHO Surgical Safety Checklist

Measure type: ProcessRelated driver: Improve teamwork and communicationDescription: The percentage compliance with using the World Health

Organisation (WHO) Surgical Safety Checklist including the core team.

Rationale: The implication is that regular use of a formalised communication tool including the core team will reduce the number of errors over time.

Numerator: The total number of number of days in the month in which the checklist was used in your pilot population.

Data Source: Local AuditDenominator: The total number of operating days in the month in your

pilot population.Data Source: Local AuditMethod of calculation: Calculate the percent compliance with using the checklist

by dividing the numerators by the denominator and then multiplying the resulting proportion by 100.


Createasystemtotrackthismeasureprospectivelyin100%of relevant pilot population.

ThisisaYES/NOoutcome.Onlydayswherethechecklistwasused for all appropriate cases are recorded as compliant.



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Section E

Measure name: M01 % of inpatient Warfarin doses administered according to Protocol

Measure type: ProcessRelated driver: High Risk medications/ patient level changesDescription: ThepercentageofinpatientWarfarindoseswithINRinside

the safety limits set by the hospital’s Warfarin protocol during the period in which Warfarin was first administered.

Rationale: Hospitals should use this measure as a starting point to begin investigating and identifying breakdowns in their processes, so that they can develop better processes. The data collection necessary for this measure will give teams a sample of admissions in which something probably went wrong. Investigate these by reviewing the patient notes, starting with the most serious cases.

Numerator: The number of inpatient warfarin doses that were adminis-tered according to protocol

Data Source: Local AuditDenominator: NumberofdosesreviewedData Source: Pharmacy recordsMethod of calculation: Divide the numerator by the denominator and multiply by

100 to give a percentageCollection guidance: Use a targeted sample of adult patients, we recommend a

sample of 20 patients, and report monthly.

Use patient Warfarin prescription charts to collect data

RememberthisisaYES/NOoutcomeonly:Onlypatientswhose medicines were administered according to the protocol are ticked as a YES

If you are beginning this intervention within a pilot unit or units, limit your initial measurement to only those units. As you spread the implementation, expand your measurement accordingly.


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Measure name: M02 % of Warfarin patients with INR results above 6Measure type: OutcomeRelated driver: High Risk medications/ patient level changesDescription: The percentage of patients receiving Warfarin where the

InternationalNormalisedRatio(INR)wasover6duringWarfarin administration.

Rationale: AlthoughhighINRvaluesdonotalwaysleadtopatientharm,there is a high risk that it may do so. Therefore this measure is a proxy for a harmful outcome and is easier to collect than the more accurate adverse event rate which is why it is included.

Numerator: NumberofpatientsreceivingWarfarinwithINRresultsabove 6 during Warfarin administration

Data Source: Local laboratory resultsDenominator: NumberofpatientsreceivingWarfarinData Source: Pharmacy recordsMethod of calculation: Divide the numerator by the denominator and multiply by

100 to give a percentageCollection guidance: Patients receiving Warfarin may be identified through

pharmacy records. These patients—or a sample of them—representyourdenominator.PatientswithINRlevelsoutsideof protocol limits may be identified using lab records.

There might be easier ways of collecting this data, depending on the internal systems a hospital has in place. We recommend a sample of 20 patients per month.



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Numerator: NumberofpatientsreceivingWarfarinwithINRresultsabove5 during Warfarin administration




There might be easier ways of collecting this data, depend-ing on the internal systems a hospital has in place. We recommend a sample of 20 patients per month.



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Numerator: NumberofpatientsreceivingWarfarinwithINRresultsabove8 during Warfarin administration




There might be easier ways of collecting this data, depending on the internal systems a hospital has in place. We recommend a sample of 20 patients per month.



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Measure name: M05 % Heparin patients outside protocol limitsMeasure type: OutcomeRelated driver: High Risk Medicines/ patient level changesDescription: The percentage of patients receiving low molecular weight Heparin

with aPPT outside the safety limits set by the hospital’s heparin protocol during any period in which heparin was administered.

Rationale: Hospitals should use this measure as a starting point to identifying breakdowns in their processes, so that they can improve them. The data collection necessary for this measure will give teams a sample of admissions in which something probably went wrong. Investi-gate these by reviewing the patient notes, starting with the most serious cases.

Numerator: The number of patients receiving low molecular weight Heparin with aPPT outside the safety limits set by the hospital’s heparin protocol during any period in which heparin was administered.

Data Source: Local AuditDenominator: NumberofpatientsreviewedData Source: Local AuditMethod of calculation:

Divide the numerator by the denominator and multiply by 100 to give a percentage


This measure relies on the existence of a protocol that defines the safe limit of aPPT in patients receiving heparin. Hospitals will need to define this before they can begin their improvement work on anticoagulants, and before they can start using this measure. The Campaign does not have a prescriptive recommendation for this limit; it is appropriate for each hospital to choose this themselves - the important thing in this case is that the protocol is reliably followed.

Use a targeted sample of adult patients, we recommend a sample of 20 patients, and report monthly.Patients receiving heparin may be identified through pharmacy records. These patients—or a sample of them—represent your denominator. Patients with aPPT levels outside of protocol limits may be identified using lab records. These patients should be reconciled with those patients receiving heparin; matched patients—or a sample of them—represent your numerator. There might be easier ways of collecting this data, depending on the internal systems a hospital has in place.



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Measure name: M06 % patients treated with FlumazenilMeasure type: OutcomeRelated driver: High Risk medications/ patient level changesDescription: The percentage of patients receiving a sedative who receive

subsequenttreatmentwithFlumazenilthatisassociatedwith receiving the sedative.

Rationale: Administration of a reversal agent may an indicator that patients are being over-sedated due to improper doses or errors in administration. This measure may be useful to determine the effectiveness of dosing guideline and dose reduction programs. Use this measure by checking to see whether changes to your processes have a corresponding reduction in the percentage.

Numerator: ThenumberofpatientsreceivingFlumazeniltocounteracttheeffectsofMidazolam.

Data Source: Local AuditDenominator: NumberofpatientsreviewedData Source: Local AuditMethod of calculation: Divide the numerator by the denominator and multiply by

100 to give a percentageCollection guidance: Use the pharmacy database to get a sample of patients

receiving a sedative and the number within this population whoreceivedflumazenil.

We recommend a sample of 20 patients per month.


Insomeinstances,flumazenilmaybeadministeredtoapatientifitissuspectedthatthebenzodiazepinecontributedto the patient’s condition. In these cases, count the case in the numerator only if the reversal agent is effective.


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Measure name: M07 % patients treated with NaloxoneMeasure type: OutcomeRelated driver: High Risk medications/ patient level changesDescription: The percentage of patients receiving an opiate who receive

subsequenttreatmentwithNaloxone.Rationale: AdministrationofNaloxonemaybeanindicatorofinap-

propriate dosing or error in dosing. This measure, while not necessarily measuring harm itself, is intended to give a quick approximation of adverse drug events associated with narcotic use. Use this measure by checking to see whether changes to your processes have a corresponding reduction in the percentage.

Numerator: The number of patients receiving an opiate who receive subsequenttreatmentwithNaloxone.


100 to give a percentageCollection guidance: Patients receiving an opiate may be identified

through pharmacy records. These patients—or a sample of them—represent your denominator. Similarly, patients subsequentlyreceivingNaloxonemaybeidentifiedfrom pharmacy records, or may require case note re-view,especiallyifNaloxoneisautomaticallyprescribedwhenever a narcotic is administered as part of hospital nar-cotic protocol.

We recommend a sample of 20 patients per month.


PatientsreceivingNaloxonefortreatmentofsymptomsnotassociated with overdose, such as pruritis and apnea, or as part of protocolised procedure should be excluded from the numerator.


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Measure name: M08 % of Patients receiving 25%/ 50% glucoseMeasure type: OutcomeRelated driver: High Risk medications/ patient level changesDescription: Thepercentageofpatientsreceiving25%or50%glucoseto

correct insulin induced hypoglycaemia.Rationale: Hospitals should use this measure as a starting point to

identifying breakdowns in their processes, so that they can improve them. The data collection necessary for this measure will give teams a sample of admissions in which something probably went wrong. Investigate these by reviewing the patient notes, starting with the most serious cases.

Numerator: Thenumberofpatientsreceiving25%or50%glucosetocorrect insulin induced hypoglycaemia.


100 to give a percentageCollection guidance: Track100%ifpossible.Ifnotuseasampleofadultpatients

If sampling, identify patients who received glucose from the pharmacy system or nursing medication administration records

Report data monthly

The annotation section should be used to reflect any interventions that were made to reduce necessity for administrationof25%/50%glucose



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Measure name: M09 % patients with no INR recordedMeasure type: ProcessRelated driver: High Risk medicationsDescription: The percentage of patients receiving Warfarin where there is

noInternationalNormalisedRatio(INR)recordedonWarfarininpatient prescription

Rationale: This is an indication that patients on Warfarin are not being managedcorrectly.ThereisnoguaranteethattheINRhasnot been observed but the lack of any record makes it harder to know whether any further action is necessary.

Numerator: The number of patients receiving Warfarin during the month wherethereisnoInternationalNormalisedRatio(INR)recorded on Warfarin inpatient prescription.

Data Source: Local AuditDenominator: The total number of patients receiving warfarin during the

month.Data Source: Local AuditMethod of calculation: (numerator / denominator) x 100Collection guidance: Patients receiving Warfarin may be identified through

pharmacy records. These patients—or a sample of them—representyourdenominator.PatientswithINRlevelsoutside of protocol limits may be identified using lab records.


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Measure name: M10 Anticoagulant adverse event rateMeasure type: OutcomeRelated driver: High Risk medicationsDescription: The number of adverse drug events per 100 admissions with

anticoagulant administered.Rationale: Reduce adverse drug events related to anticoagulants.Numerator: Numberofadversedrugevents(ADEs)inthesamplerelated

to the use of an anticoagulant. Use only the Medication Module and Care Module triggers.

Data Source: Case note reviewDenominator: NumberofpatientsinthesampleData Source: Case note reviewMethod of calculation: Calculate the actual anticoagulant ADE rate by dividing

the numerator by the denominator and then multiplying the resulting number by 100 to obtain an ADE rate per 100 admissions.

Collection guidance: This measure uses chart review aided by the IHI Global Trigger Tool. Follow the guidance for using the tool including the selection of a random set of records to review.

The IHI Global Trigger Tool is designed to help identify all adverse events, not only adverse drug events. However, for the purposes of this measure, limit the triggers to those in the Medication Module and the Care Module, both of which contain triggers that are sensitive to adverse drug events. Do not spend time investigating triggers or adverse events that are clearly unrelated to the patient receiving an anticoagulant. Using this approach, the notes review can be done quickly.

Review a minimum of 20 case notes per month from the population of patients receiving an anticoagulant. You can conduct reviews over multiple sessions (for example, 10 records every 2 weeks) to spread out the need for resources.If you are beginning this intervention within a pilot unit or units, limit your initial measurement to only those units. As you spread the implementation, expand your measurement accordingly.


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Measure name: M11 Heparin adverse event rateMeasure type: OutcomeRelated driver: High Risk medicationsDescription: The number of adverse drug events per 100 admissions

associated with the use of low molecular weight heparin or unfractionated heparin.

Rationale: Reduce adverse drug events related to anticoagulants.Numerator: Numberofadversedrugevents(ADEs)inthesamplerelated

to the use of low molecular weight heparin or unfractionated heparin. Use only the Medication Module and Care Module triggers.

Data Source: Case note reviewDenominator: NumberofpatientsinthesampleData Source: Case note reviewMethod of calculation: Calculate the actual ADE rate by dividing the numerator by

the denominator and then multiplying the resulting number by 100 to obtain an ADE rate per 100 admissions.


The IHI Global Trigger Tool is designed to help identify all adverse events, not only adverse drug events. However, for the purposes of this measure, limit the triggers to those in the Medication Module and the Care Module, both of which contain triggers that are sensitive to adverse drug events. Do not spend time investigating triggers or adverse events that are clearly unrelated to the patient receiving heparin. Using this approach, the notes review can be done quickly.

Review a minimum of 20 case notes per month from the population of patients receiving an anticoagulant. You can conduct reviews over multiple sessions (for example, 10 records every 2 weeks) to spread out the need for resources.



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Measure name: M12 Injectable Sedative adverse event rateMeasure type: OutcomeRelated content area / driver:

High Risk medications

Description: The number of adverse drug events per 100 admissions associated with injectable sedative administered.

Rationale: Reduce adverse drugs events related to sedation.Numerator: Numberofadversedrugevents(ADEs)inthesamplere-

lated to the use of an injectable sedative. Use only the Medication Module and Care Module triggers.

Data Source: Local AuditDenominator: NumberofpatientsinthesampleData Source: Local AuditMethod of calculation: Calculate the actual ADE rate by dividing the numera-

tor by the denominator and then multiplying the re-sulting number by 100 to obtain an ADE rate per 100 admissions


The IHI Global Trigger Tool is designed to help identify all adverse events, not only adverse drug events. However, for the purposes of this measure, limit the triggers to those in the Medication Module and the Care Module, both of which contain triggers that are sensitive to adverse drug events. Do not spend time investigating triggers or adverse events that are clearly unrelated to the patient receiving heparin. Using this approach, the notes review can be done quickly.

Review a minimum of 20 case notes per month from the population of patients receiving an anticoagulant. You can conduct reviews over multiple sessions (for example, 10 records every 2 weeks) to spread out the need for resources.



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Measure name:

M13 % patients treated within opiate protocol

Measure type: ProcessRelated driver: High Risk medications.Description: The percent of patients receiving an opiate whose treatment was ordered,

received, and managed according to protocol or for whom protocol was not followed due to a documented contraindication.

Rationale: The purpose of this measure is to determine the reliability of the process in place. It is intended to be used in those situations where a hospital has already adopted a protocol for the management of a selected high-alert medication.We recommend that hospitals use measures like this one to track protocol compliance within medication categories (i.e.., narcotics, anticoagulants, insulin, and sedatives) separately, which will help target compliance issues more easily.

Numerator: Numberofpatientsreceivinganopiateinthesamplewhosetreatment was ordered, received, and managed according to protocol or for whom protocol was not followed due to a documented contraindication.

Data Source: Local AuditDenominator: NumberofpatientsinthesampleData Source: Local AuditMethod of calculation:

Calculate the actual percentage compliance by dividing the numerator by the denominator and then multiplying the resulting number by 100


Opiate treatment is the process of ordering, delivering, and managing aopiate.Notethatasingletreatmentmayincludemultipledoses,andincludes not only the initial ordering and delivery of the medication, but also extends through the entire management of the treatment until discontinuation.

Identify patients who received opiates from the pharmacy system or nursing medication administration records. Sources used to determine protocol compliance may include patient charts, lab results, and/or pharmacy records. If a single patient has more than one distinct opiate treatment during their admission, consider only the first in this measure. Exclude patients with length of stay less than 24 hours.

Each month, review a minimum of 20 patient records with at least one narcotic treatment. You can conduct reviews over multiple sessions (for example, 10 records every 2 weeks) to spread out the need for resources. If you have fewer than 20 records after making any appropriate exclusion, use as many records as fit the inclusion criteria.If you are beginning this intervention within a pilot unit or units, limit your initial measurement to only those units. As you spread the implementation, expand your measurement accordingly.


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Measure name: M14 Opiate adverse event rateMeasure type: OutcomeRelated content area / driver: High Risk medicationsDescription: The number of adverse drug events per 100

admissions associated with opiates administered.Rationale: Reduce adverse drugs events related to opiate use.Numerator: Numberofadversedrugevents(ADEs)inthe

sample related to the use of an opiate. Use only the Medication Module and Care Module triggers.

Data Source: Local AuditDenominator: NumberofpatientsinthesampleData Source: Local AuditMethod of calculation: Calculate the actual ADE rate by dividing the

numerator by the denominator and then multiplying the resulting number by 100 to obtain an ADE rate per 100 admissions


The IHI Global Trigger Tool is designed to help iden-tify all adverse events, not only adverse drug events. However, for the purposes of this measure, limit the triggers to those in the Medication Module and the Care Module, both of which contain triggers that are sensitive to adverse drug events. Do not spend time investigating triggers or adverse events that are clearly unrelated to the patient receiving an opiate. Using this approach, the notes review can be done quickly.

Review a minimum of 20 case notes per month from the population of patients receiving an opiate. You can conduct reviews over multiple sessions (for example, 10 records every 2 weeks) to spread out the need for resources.

If you are beginning this intervention within a pilot unit or units, limit your inisial measurement to only those units. As you spread the implementation, ex-pand your measurement accordingly.


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Measure name: M15 Insulin adverse event rateMeasure type: OutcomeRelated content area / driver:

High Risk medications

Description: The number of adverse drug events per 100 admissions associated with insulin administered.

Rationale: Reduce adverse drugs events related to insulin.Numerator: Numberofadversedrugevents(ADEs)inthesample

related to the use of insulin. Use only the Medication Module and Care Module triggers.

Data Source: Local AuditDenominator: NumberofpatientsinthesampleData Source: Local AuditMethod of calculation: Calculate the actual ADE rate by dividing the numerator

by the denominator and then multiplying the resulting number by 100 to obtain an ADE rate per 100 admissions


The IHI Global Trigger Tool is designed to help identify all adverse events, not only adverse drug events. However, for the purposes of this measure, limit the triggers to those in the Medication Module and the Care Module, both of which contain triggers that are sensitive to adverse drug events. Do not spend time investigating triggers or adverse events that are clearly unrelated to the patient receiving insulin. Using this approach, the notes review can be done quickly.

Review a minimum of 20 case notes per month from the population of patients receiving insulin. You can conduct reviews over multiple sessions (for example, 10 records every 2 weeks) to spread out the need for resources.If you are beginning this intervention within a pilot unit or units, limit your initial measurement to only those units. As you spread the implementation, expand your measurement accordingly.

Documents

Campaign Measures Definitions · To find out more visit Version 1.1 - 08/12/08 2 Measures Introduction This paper focuses on the measures that are being recommended for the Patient