Standardised Mortality Ratio
Reviewed and revised 26 August 2015
- Standardised Mortality Ratio SMR is the ratio of the observed or actual hospital mortality and the predicted hospital mortality for a specified time period.
- Requires an estimate of predicted mortality rate using a scoring system (e.g. APACHE, ANZROD, SAPS, MPM…)
- a value of 1 is considered normal or as expected
- > 1 worse than expected, and
- < 1 better than expected
Used as a surrogate for good quality of care
- comparison of different ICUs
- monitor improvements or decline in ICU care over time
- widely used
- better than a comparison of non-adjusted mortality data
- mortality is a hard endpoint that is clinically meaningful
- acceptable deviations from SMR are not defined, therefore whether a unit significantly deviates from normal is unquantifiable
- needs to be considered in the context of case-mix and calibration
- inconsistencies and inaccuracies associated with data collection and scoring
- missing data limits inclusion of all patients
- original population used to calculate formulae possibly not generalisable
- model used for prediction may be inaccurate
- relies on mortality as a surrogate for quality care
- ideally samples should be very large
- does not account for post-ICU mortality or morbidity that may be related to ICU care
Comparison between different ICUs are limited by the following assumptions:
- that all pre-ICU care identical and that it has no impact on ICU or hospital outcome
- patients from different hospitals are all drawn from the same case-mix
- sample sizes are large enough to obey the laws of logistic regression
- data acquisition is flawless with respect to the rules of scoring systems and consistent between units
REASONS FOR A CHANGE IN SMR FOR AN ICU
- Need to ensure data entry is correct and accurate and consistent with prior practice (i.e. comparable)
- Issues like quantifying GCS accurately will have an impact on APACHE scores and consequently SMR. Quantification of GCS is a major source of inaccuracy in APACHE scores. Also source of admission and diagnosis;
- SMR reflects system wide performance rather than ICU performance alone, because based upon hospital mortality, not ICU mortality. Look at pre ICU and post ICU facilities in the hospital
- SMR affected by case-mix, so changes in case mix may account for increase in SMR and increased other hospital admissions
- Has there been increased practice variation and a deviation from clinical protocols in the ICU?
- Lead time bias (pre ICU care) has been shown to impact on SMR and this needs to be considered
- Any unusual events such as influenza epidemic or terrorist attack?
- Assess for changes in personnel, staffing levels, protocols and equipment
- New services introduced? (e.g. ECMO retrieval)
Chris is an Intensivist and ECMO specialist at the Alfred ICU in Melbourne. He is also a Clinical Adjunct Associate Professor at Monash University. He is a co-founder of the Australia and New Zealand Clinician Educator Network (ANZCEN) and is the Lead for the ANZCEN Clinician Educator Incubator programme. He is on the Board of Directors for the Intensive Care Foundation and is a First Part Examiner for the College of Intensive Care Medicine. He is an internationally recognised Clinician Educator with a passion for helping clinicians learn and for improving the clinical performance of individuals and collectives.
After finishing his medical degree at the University of Auckland, he continued post-graduate training in New Zealand as well as Australia’s Northern Territory, Perth and Melbourne. He has completed fellowship training in both intensive care medicine and emergency medicine, as well as post-graduate training in biochemistry, clinical toxicology, clinical epidemiology, and health professional education.
He is actively involved in in using translational simulation to improve patient care and the design of processes and systems at Alfred Health. He coordinates the Alfred ICU’s education and simulation programmes and runs the unit’s education website, INTENSIVE. He created the ‘Critically Ill Airway’ course and teaches on numerous courses around the world. He is one of the founders of the FOAM movement (Free Open-Access Medical education) and is co-creator of litfl.com, the RAGE podcast, the Resuscitology course, and the SMACC conference.
His one great achievement is being the father of three amazing children.
On Twitter, he is @precordialthump.
| INTENSIVE | RAGE | Resuscitology | SMACC
Hi there! I have been asked to compute SMRs using APACHE IV predicted mortality, and have already been asked to compute 95% CIs. What formula do you recommend for CIs in this case, since the SMR is not a mean nor proportion? Do you know of any examples of SMR CIs? Thanks in advance!