Research and analysis

Quality and methodology information for surgical site infections surveillance in NHS hospitals in England: annual report 2023 to 2024

Updated 12 December 2024

Applies to England

About this report

This report explains the quality and methodology information (QMI) relevant to the Surveillance of surgical site infections in NHS hospitals in England: annual report statistics published by the UK Health Security Agency (UKHSA).

This QMI report helps users understand the strengths and limitations of these statistics, ensuring that UKHSA is compliant with the quality standards stated in the Code of Practice for Statistics. The report explains:

• the strengths and limitations of the data used to produce the statistics
• the methods used to produce the statistics
• the quality of the statistical outputs

About the statistics

Surgical site infections (SSIs) are hospital-acquired infections that may occur due to micro organisms entering the surgical wound as a result of a patient undergoing a surgical procedure. This SSI Annual Report presents data on mandatory (at least one orthopaedic surgical category for at least one quarter in a financial year) and voluntary (a choice of additional 13 surgical categories) parts of the surveillance. The report includes data from NHS hospitals and independent sector NHS treatment centres but excludes data reported by other independent sector hospitals.

The data in this report is provisional and subject to revision according to reporting timelines outlined in the protocol.

Geographical coverage: England

Publication frequency: Annual

Changelog

12 December 2024: QMI report first published

Contact

Lead analyst: Miroslava Mihalkova

Contact information: [email protected]

Suitable data sources

Statistics should be based on the most appropriate data to meet intended uses. This section describes the data used to produce the statistics.

Data sources

The annual report is based on data submitted to the Surgical Site Infection Surveillance Service (SSISS), which has been in operation since 1997. The data is collected prospectively on a quarterly basis and includes all eligible patients undergoing surgery in pre-selected surgical categories during each 3-month period (quarter). Patients are followed up to identify SSIs for 30 days after surgery for procedures which do not involve the insertion of a prosthetic implant, and for one year for procedures involving the insertion of a prosthetic implant. A set of demographic and surgery-related data is collected for each eligible procedure and submitted by trained staff to the UKHSA SSISS via a secure web-based application.

The UKHSA SSISS protocol defines SSIs according to standard clinical criteria for infections that affect the superficial tissues (skin and subcutaneous layer) of the incision and those that affect the deeper tissues (deep incisional or organ/space). These are based on the definitions established by the US Centers for Disease Control and Prevention (CDC) with minor modifications to 2 of the criteria, namely:

• the presence of pus cells for infections determined by positive microbiology without obvious clinical signs and symptoms to prevent mis-diagnosis of wound infections as a result of a positive microbiology due to colonisation
• at least 2 clinical signs and symptoms of infection to accompany a clinician’s diagnosis for superficial incisional infections to increase the likelihood of it being a true wound infection

The SSISS protocol further outlines a standard methodology, including case finding methods, which all participating hospitals must adhere to. Hospitals participating in UKHSA’s national SSI surveillance programme are strongly encouraged to have staff attend the UKHSA SSISS quarterly training before starting surveillance in order maintain the quality of surveillance data.

Active, prospective surveillance is undertaken by hospital surveillance staff to identify patients with SSIs during their initial inpatient stay. Hospitals are also required to have systems in place to identify patients with SSIs who are subsequently readmitted to hospital with an SSI. SSIs identified on re-admission are assigned to the hospital where the original operation took place. Inpatient and re-admission SSIs form the primary statistics used in the SSISS annual report, as well as the calculation of national benchmark data for each surgical category, as these case ascertainment methods are required of all participating hospitals, with other forms of post discharge surveillance (explained below) are optionally used by hospitals.

Other optional post-discharge surveillance (PDS) methods are recommended, particularly for procedures with a short duration of post-operative stay such as breast surgery where the majority of patients are discharged on the day of surgery. They comprise: a) systematic review of surgical wounds and documentation of patients attending outpatient clinics or seen at home by hospital clinical staff trained to apply the case definitions, and b) wound healing post-discharge questionnaires (PDQs) completed by the patient or their carer at 30 days after their operation.

SSIs detected through PDQs are recorded as ‘patient-reported only’ if they have not been identified by one of the other detection methods involving a hospital clinician. Data from these optional forms of PDS is not currently included in the national benchmarks, or used for outlier assessment as the methods are optional and so not used by all hospitals.

Hospital staff need to submit quarterly data within 60 days after the end of quarter (for example, January to March data needs to be submitted by June 30). The data is then reconciled and the surveillance period is closed. If any amendments need to be made to already reconciled data, approval by the UKHSA SSISS surveillance manager is required. The SSISS web app has automated error checking and SSISS administration staff commence validation of data after reconciliation. Records are checked for missing, incorrect and incompatible entries and queried with hospital staff.    

The Hospital Episode Statistics (HES) Admitted Patient Care (APC) data set was used to obtain data on patients’ ethnicity and relative deprivation as measured by the small-area index of multiple deprivation (IMD) score based on the patient’s area of residence at the time of surgery. The HES data set contains information about individual patients admitted to NHS hospitals including clinical (diagnoses and operations), patient (age group, sex, and ethnicity), administrative (dates and methods of admission and discharge) and geographical (place of treatment and residence) information.

Ethnic group classifications (as defined in the 2001 census) were regrouped due to small numbers of inpatient and readmission SSIs for ethnic groups into:

• white
• Asian
• black
• mixed
• other
• unknown

The IMD is an overall relative measure of deprivation formed by combining 7 domains of deprivation, each given a varying degree of relative weighting as a percentage (%):

• income deprivation (22.5%)
• employment deprivation (22.5%)
• education, skills and training deprivation (13.5%)
• health deprivation and disability (13.5%)
• crime (9.3%)
• barriers to housing and services (9.3%)
• living environment deprivation (9.3%)

These are counted according to their respective weights for lower-super output areas (LSOA). These are small areas of a similar population size of about 1,500 residents or 650 households. The number of LSOAs for 2019 indices was 32,844 (based on revision following 2011 census). The LSOA with a rank of 1 is the most deprived and the LSOA with a rank of 32,844 is least deprived. The report presents SSISS data by IMD deciles (the number of LSOAs divided into 10 equal groups according to their deprivation rank) rather than individual ranks with decile 1 representing the most deprived LSOAs and decile 10 the least deprived LSOAs.

The law on protecting personal information, known as the UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018, allows UKHSA to use the surgical wound infection information submitted by the hospitals participating the surveillance. Section 251 of the National Health Service Act 2006 and regulation 3(3) of the associated Health Service (Control of Patient Information) Regulations 2002 allows UKHSA SSISS use confidential patient information without asking directly for your consent for the purpose of diagnosing, recognising trends, controlling and preventing, and monitoring and managing risks to health such as surgical wound infections. More details about the legal basis are available in the UKHSA SSISS Privacy Notice.

Regulation 7 of the Health Service (Control of Patient Information) Regulations 2002 requires UKHSA to have in place a system of annual review of Regulation 3 purposes and data uses, including linkages to other databases such as HES. The linkage of HES data was justified based on Regulation 3: Communicable disease and other risks to health of The Health Service (Control of Patient Information) Regulation 2002.

UKHSA SSISS (CAP-2018-103) annually submits an application for this assessment to the UKHSA Caldicott Advisory Panel. Additionally, the UKHSA Privacy Notice, and the Data Protection Impact Assessment (DPIA) undergo regular reviews.

Data quality

The data that we use to produce statistics must be fit for purpose. The lack of data quality can lead to failures in identifying relevant groups most at risk, and even threats to patient safety, preventing effective public health action being taken.

We have assessed the quality of the source data against the data quality dimensions in the Government Data Quality Framework.

This assessment covers the quality of the data that was used to produce the statistics, not the quality of the final statistical outputs. The quality summary section below explains the quality of the final statistical outputs.

Strengths and limitations of the data

The strengths of the data include:

• the UKHSA SSISS provides the infrastructure for systematic surveillance and monitoring of SSIs, allowing hospitals in England to review clinical practice, and take action to reduce their SSI rates, leading to improved patient safety
• the UKHSA SSISS enables hospitals in England to meet the mandatory requirements for surveillance of SSIs in orthopaedic surgical categories, while also offering voluntary surveillance in 13 other surgical categories
• surveillance data is collected prospectively on a quarterly basis and includes all eligible patients undergoing surgery in pre-selected surgical categories (all eligible Operating Procedure Codes Supplement (OPCS) codes) during each 3-month period (quarter)
• automatic error checking at the time of data submission reduces data errors

After each completed quarter, data is subject to quality assurance processes by UKHSA SSISS to identify anomalies or missing data. The limitations of the data include:

• data collection is only mandated for one surveillance quarter per financial year per NHS trust in one of 4 orthopaedic categories – therefore the data set does not include all operations for a specific surgical category
• data quality and completeness issues not identified by the automated error checking, are identified by manual scrutiny of data after the quarterly submission deadline, and therefore the full data quality assurance is not instant but happens with some delay

Summary of strengths and limitations

SSISS offers the most consistent and reliable data source for reporting of SSIs in English NHS hospitals.  It was designed specifically for the purpose of surveillance of surgical site infections and quality improvements of patient care. The design of SSISS, which includes training of hospital surveillance staff, data validation and reconciliation, as well as monitoring of trends at hospital level against the national benchmark, helps to ensure that the data is accurate and valid.

Accuracy

Accuracy is about the degree to which the data reflects the real world. This can refer to correct names, addresses or represent factual and up-to-date data.

The submitted data is based on patient records and surveillance held at a hospital where the operation took place and is entered on the web application before the deadline for a respective surveillance quarter. Hospital staff are encouraged to fill in the surveillance data sheet for each eligible operation within the surveillance period and submit the data on the web application as soon as possible after the operation. Patients are monitored for signs and symptoms of infections prospectively and systematically to capture all inpatient and re-admission SSIs. The surveillance applies active, prospective case finding methodology, which can improve sensitivity. However, where this methodology is not applied consistently, it can lead to a failure of identifying cases.

To address some of these concerns, UKHSA SSISS conducts a quarterly outlier analysis, which compares hospital-specific SSI rates to the 5-year national benchmark data by surgical category. This methodology applies statistical methods to identify both high outliers (hospitals with high SSI rates in a specific surgical category) as well as low outliers (unusually low SSI rates). The outlier notifications are shared with hospitals and act as potential warnings for either high SSI rates, or potential under-detection of SSIs. The UKHSA SSISS team provides bespoke advice and support for hospitals to address the concerns related to outlier status and targeted public health action through further investigation and/or training. Hospital staff are also have access to the quarterly organised UKHSA SSISS training day, where they receive comprehensive training on the surveillance methodology. The training days are held quarterly.

Completeness

Completeness describes the degree to which records are present, and which data fields have been populated.

For a data set to be complete, all records are included, and the most important data is present in those records. This means that the data set contains all the records that it should and all essential values in a record are populated.

Completeness is not the same as accuracy as a full data set may still have incorrect values.

SSI surveillance contains a number of patient and surgery-related mandatory fields, such as date of admission and operation, ASA score, operation duration, date inpatient surveillance discontinued and wound class that must be completed in order to submit a record on the web application. Where the information is not available for risk factor fields such as ASA score or wound class, hospitals can record these as ‘unknown’ and still submit the record. The quarterly data validation by UKHSA SSISS team ensures the data completion to high standard, and the web application offers automated reports on data completeness and quality.

Data completeness of essential information is reported in the annual report (Table 9a and Table 9b).

Uniqueness

Uniqueness describes the degree to which there is no duplication in records. This means that the data contains only one record for each entity it represents, and each value is stored once.

Each operation should result in one web entry unless the patient had a bilateral operation, which can occur for hip and knee replacements, reduction of long bone fracture, reduction of neck of femur, limb amputation, and breast surgery, or when multiple surgeries (for example, small and large bowel surgery) are performed during the same operation. In these cases, the patient will have at least 2 web entries, all  with unique database identifiers.

Duplicate entries for single procedures can occur by accidental submission of data for the same patient and operation but are detected during data validation and cleaning processes.

Consistency

Consistency describes the degree to which values in a data set do not contradict other values representing the same entity. For example, a mother’s date of birth should be before her child’s.

Data is consistent if it doesn’t contradict data for the same person in the same or in another data set. For example, the date of birth recorded for the same person in the same or different data sets should be the same.

For the purposes of the SSISS Annual Report, where patient identifiers are recorded and valid, data can be matched to the Hospital Episode Statistics data set.

Administrative staff in the SSISS team routinely checks data for consistency to identify data entry errors and return queries to relevant hospital staff for resolution to ensure data consistency. In addition, the SSISS web application has in-built, automated checks to ensure data consistency at the point of data submission and reconciliation.

Timeliness

Timeliness describes the degree to which the data is an accurate reflection of the period that it represents, and that the data and its values are up to date.

Some data, such as date of birth, may stay the same whereas some, such as patient ASA score, may not.

Data is timely if the time lag between collection and availability is appropriate for the intended use.

The SSISS web application and database is managed by the SSISS team, therefore there is no delay between the data collection and availability. Hospitals have access to their quarterly automated reports after their quarterly data is reconciled, and reports activated.

The annual report is produced every year as soon as the January to March data submission for respective year is completed, all the records validated, and any discrepancies have been queried with hospital staff.

Validity

Validity describes the degree to which the data is in the range and format expected. For example, date of birth does not exceed the present day and is within a reasonable range.

Valid data is stored in a data set in the appropriate format for that type of data. For example, a date of birth is stored in a date format rather than in plain text.

Data entry users are prevented from entering invalid data by a series of error and warning messages on the system. These alert users to data that is invalid, inconsistent, missing or outside of expected range of values. Users need to amend data with error messages and comment on missing data and/or outside of expected range in the user comment box before they are able to submit a record. This ensures the data used for benchmarking and outlier analyses meet the requirements set out in the SSISS protocol.

Sound methods

Statistical outputs should be produced using appropriate methods and recognised standards.

This section describes how the statistics were produced and quality assured.

Data set production

The SSISS data used to produce the report is extracted from the SSISS database once the data has been validated by the UKHSA administration staff, ensuring that all inpatient and re-admission SSIs meet surveillance definitions. The data is then cleaned and analysed including linkage to HES data set to obtain patients’ ethnicity and IMD data.

Quality assurance

The annual report is produced using STATA and R. The production of figures and tables has been automated to a large degree. Some ad hoc changes occur based on feedback from senior colleagues during the review process. Automating figures and tables reduces the risk of human error. Quality assurance is performed after running the code.

The figures and tables are reviewed by members of the team during several rounds of draft report reviews. If any discrepancies are found, further checks are conducted to investigate any possible errors in the data.

Confidentiality and disclosure control

Personal and confidential data is collected, processed and used in accordance with the UKHSA SSISS Privacy Notice and any risks are monitored and mitigated through a continually updated Data Protection Impact Assessment (DPIA). All UKHSA staff with access to personal or confidential information must complete mandatory information governance training, which must be refreshed every year. Information is stored on computer systems that are kept up to date and regularly tested to make sure they are secure and protected from viruses and hacking. UKHSA staff do not store data on their own laptops or computers. Instead, data is stored centrally on UKHSA servers.

No personally identifiable information is included in the published data.

There are no specific disclosure control methods used in the body of the report, as aggregation of the published figures protects personal data.

Trust tables for the last 2 financial years are published alongside the annual report presenting participation and SSI risk in mandatory orthopaedic categories by NHS trust in England. Primary cell suppression is used where the number of operations per trust and surgical category is less than 5.

Geography

The statistics in the report and accompanying trust tables are published at 2 geographical levels: country (England) and NHS trust.

Other outputs (if applicable)

• trust tables – SSI risk by NHS trust and surgical category for mandatory orthopaedic categories for last 2 financial years
• Fingertips indicators – SSI risk for hip and knee replacement by financial year

Quality summary

Quality means that statistics fit their intended uses, are based on appropriate data and methods, and are not materially misleading.

Quality requires skilled professional judgement about collecting, preparing, analysing, and publishing statistics and data in ways that meet the needs of people who want to use the statistics.

This section assesses the statistics against the European Statistical System dimensions of quality.

Relevance

Relevance is the degree to which the statistics meet user needs in both coverage and content.

There is a clear need for timely SSI statistics. Timely SSI statistics support hospitals and trusts in progress towards reducing their SSI risk, and demonstrating their adherence with the Department for Health and Social Care (DHSC) mandate to participate in one orthopaedic category in one surveillance quarter per financial year. The hospital staff users regularly feed back the data to their respective clinical teams to review their clinical practice, and make changes to reduce infections, and thus reduce the need for antibiotics. The surveillance, and the evidence provided in the annual report, contribute to achieving the UK 5-year action plan for antimicrobial resistance 2024 to 2029 including but not limited to reducing the need for, and unintentional exposure to, antimicrobials through strengthened surveillance, as well as providing information for action.

The statistics are published annually. Hospitals have access to more timely reports via the web application to monitor their risk of SSI and comparison to 5-year benchmark data. These are available after they reconcile their quarterly data submission. Changes in SSIs incidence tend to accrue slowly, so there is no need for more frequent publication of the national data at the present time.

The SSIS annual report is aimed at clinical staff in hospitals, surgeons, infection prevention practitioners, clinical governance teams, microbiologists, public health practitioners, commissioners, researchers and readers interested in healthcare-associated infections.

Accuracy and reliability

Accuracy is the proximity between an estimate and the unknown true value. Reliability is the closeness of early estimates to subsequent estimated values.

The accuracy of the statistics is to a large degree dependent on the accuracy of the source data. The design of the SSI web application helps prevent data entry errors and guidance and training provided to hospital staff involved in the data collection and entry helps ensure the correct information is collected and recorded.

The data is provisional and subject to change due to one-year follow-up for operations involving an implant (for example, a patient undergoing knee replacement operation on 1 January 2024 would be followed up to 31 December 2024). Eligible infections detected after the data extraction deadline have a small impact on the statistics presented in the annual report, and the trust tables published alongside the main report. The previous year’s trust tables are updated to reflect any SSIs reported after one-year follow-up (operations where implants were used).  

Timeliness and punctuality

Timeliness refers to the time gap between publication and the reference period. Punctuality refers to the gap between planned and actual publication dates.

The report is published as soon as possible after the data for the last surveillance quarter included in the report is submitted and validated, allowing time for production and quality assurance. The publication is usually scheduled for second or third week in December subject to variation due to review and publication processes.

Accessibility and clarity

Accessibility is the ease with which users can access the data, also reflecting the format in which the data is available and the availability of supporting information. Clarity refers to the quality and sufficiency of the metadata, illustrations and accompanying advice.

There are 4 statistical products as part of this statistical release:

1. Annual report
2. Data tables accompanying graphs in the annual report
3. Trust tables for last 2 financial years
4. QMI report

From financial year 2023 to 2024 (published in December 2024) the report is published as an HTML web page. This makes the report easier to access across different devices, and the HTML report has the accessibility features mentioned in the GOV.UK accessibility statement.

The report includes numerous visualisations that help understand the data. These are designed to be compliant with accessibility guidance for colour-blind users ensuring sufficient contrast between individual elements.

The commentary is written in plain English and the main messages are presented as bullet points to help users understand the statistics.

The supplementary tables are published in the open document source (ODS) format and follow accessibility guidance.

Coherence and comparability

Coherence is the degree to which data that is derived from different sources or methods, but refer to the same topic, are similar. Comparability is the degree to which data can be compared over time and domain.

Data included in the current and previous annual reports published on GOV.UK has been collected in a consistent manner over time using a web-based data capture tool (introduced in July 2008; paper forms prior to this). In July 2008, the hip hemiarthroplasty category was replaced by repair of neck of femur, the spinal surgery category was added and all hospitals were required to identify and report SSIs in patients who are readmitted to hospital. Cranial, breast and cardiac (non-CABG) surgical categories were added in April 2010.

The COVID-19 pandemic has had a complex effect on healthcare access and delivery, including postponing all non-urgent elective surgeries from March 2020, which reduced hospital participation and reported surgical volumes. Changes in the SSI risk between financial year 2020 to 2021 compared to 2019 to 2020 were observed for some categories of surgery. Further analyses are needed to understand the impact of COVID-19 on the epidemiology of SSI.

Inclusion of procedures within a surgical category is based on OPCS (a statistical classification for clinical coding of hospital interventions and procedures undertaken by the NHS). Surgical site infection definitions are based on those published by the CDC in 1992.

Trade-off between timeliness and completeness

There is a trade-off between timeliness and completeness for the annual report. The data needs to be fully validated before the analysis, which causes 8 to 10 weeks delay between the data submission deadline (30th June) for the last quarter included in the annual report and analysis (January to March). Analyses, report drafting, rigorous review and publication process take further 12 to 16 weeks. This is necessary for the statistics to be accurate and reliable.

There is also a trade-off between timeliness and completeness for procedures including an implant. The follow up of up to one year for deep and organ or space SSIs is not complete at the point of data extraction for the annual report. Delaying the analyses for further 6 months would cause a long gap between the publication date and reference period for statistics negatively effecting the timeliness of the report.

Uses and users

Users of statistics and data should be at the centre of statistical production, and statistics should meet user needs.

This section explains how the statistics are used, and how we understand user needs.

Appropriate use of the statistics     

These statistics present reports of inpatient and re-admission surgical site infections (and operations) by NHS hospitals and NHS treatment centres for defined groups of procedures for mandatory orthopaedic surgical categories and voluntary surgical categories. Some procedure codes within these categories do not meet the inclusion criteria – for example, re-admission SSIs where a patient was admitted to a different hospital from the one where the operation took place may not be reported back to that hospital and other post-discharge detection methods are not included. Data for independent sector hospitals is excluded from the analysis. Several studies demonstrated seasonal trends in the reports of SSIs for some surgical categories, but the presentation of data by financial year in this report is not at the level of detail to show seasonality.

Known uses

We are aware that the statistics have been used in different ways, including:

• research and other publications
• the monitoring of SSI risk and comparison of local hospital or trust data to national benchmarks
• compliance with mandatory surveillance
• evaluating of clinical practise
• conference presentations and meetings

Known users

Know users include clinical and public health professionals, researchers, microbiologists and interested members of the public.

User engagement

The report is promoted in a newsletter that is sent to a hospital contact list registered on the SSISS web application and in the UKHSA Health Protection Report after the annual report is published.

Related statistics

No other SSISS-related statistics are produced and published by UKHSA.