Pulmonary embolism

Metric

Number of Pulmonary Embolisms per 1,000 spells

Numerator

Pulmonary Embolism as secondary diagnosis of either Type A, B or C as defined below:

• (Type-A) Secondary diagnosis of PE (I26 Pulmonary embolism) in any episode and where PE is not a primary diagnosis in any episode.
• (Type-B) Primary diagnosis of PE in an episode which is neither the first episode of the superspell nor the second episode if the first episode has a vague diagnosis (“R” code).
• (Type-C) Where the patient was readmitted as an emergency with a first episode primary diagnosis of PE within 90 days of discharge from the final spell.

Denominator

All surgical discharges age 18 and older defined by specific HRGs and excluding all non-operating room procedures (Appendix C).

See Appendix B: Non-operating Room Procedure Codes

See Appendix C: List of HRGs

Data Source

SUS - CDS

Time frame

January 2009 - December 2009

Basis

Acute Trust

Statistical methods used

Case-mix adjusted using a logistic regression model.

• Presence of cancer diagnosis (“C” code) in any diagnosis field in any episode of the superspell
• Agegroup (18-44, and 5 year age-bands from 45+ based on ADMIAGE in the first spell)
• Sex (first spell)
• Presence of any Operating Room (OR) Procedure
• Charlson (CHARLSON_RTM in SPELL=1, DX_EPI=1)
• Method of admission (emergency/elective/maternity/transfer/other)

Logistic regression

The ratio 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.

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.

Your feedback

Please share any concerns or suggestions for improvement that you might have regarding this indicator. In particular, please consider these questions:

• Are there any diagnosis or procedure codes that have been included that you believe should be removed? Please give your reasons
• Are there any diagnosis or procedure codes that have been omitted that you believe should be included? Please give your reasons
• What are the strengths and weaknesses of this metric as an indicator

You can use the feedback box below to submit comments to HSJ. Alternatively, you can email Dr Foster directly at HGconsult2010@drfoster.co.uk. Please submit your response by 31 August 2010.