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  • Poster presentation
  • Open Access

Can we distinguish patients at risk of deterioration?

  • 1,
  • 1,
  • 1,
  • 1 and
  • 1
Critical Care200610 (Suppl 1) :P414

https://doi.org/10.1186/cc4761

  • Published:

Keywords

  • Public Health
  • Emergency Medicine
  • Early Warning
  • Warning System
  • Early Warning System

Track and trigger scores such as the Modified Early Warning System (MEWS) score are currently used in many hospitals throughout the United Kingdom. Calculating the scores for only those patients judged to be 'at risk' may potentially miss patients who actually are at risk.

We carried out a survey in our hospital looking at which patients were having their MEWS scores calculated, and therefore judged to be at risk of deterioration, and compared their MEWS scores and outcome (inpatient mortality) with those who were not having a formal scoring system carried out. For those patients not being scored we carried out the appropriate observations to enable a MEWS score to be calculated.

We reviewed 389 patients; four patients were on care of the dying pathways and were excluded. Of the remaining 385, 89 (23%) had a MEWS score calculated. The difference in mortality was calculated using a chi-square test. Table 1 shows our results.

Mortality figures were available for 373 patients. Overall mortality for those patients having MEWS calculated was 13/84 (15.5%), while for the other group mortality was 31/289 (10.7%) (NS).

From these data it would appear that we are not able to predict which patients are at risk of dying and many patients not scored were sicker than expected. It may therefore be prudent to calculate MEWS scores for all patients who are having observations carried out, which may enable us to identify those patients who are beginning to deteriorate, and institute measures to prevent this.

Table 1

MEWS score

Recorded: number

Recorded: mortality

Not recorded:number

Not recorded: mortality

0

13 (15%)

1/12 (8.3%)

62 (20.8%)

1/62 (1.6%)

1

48 (55.2%)

3/46 (6.5%)

136 (45.6%)

18/133 (14.2%)

2

9 (10.3%)

0/9 (0%)

61 (20.5%)

6/60 (10%)

3

9 (10.3%)

4/9 (44%)

27 (9.1%)

2/23 (8.7%)

4

4 (4.6%)

2/4 (50%)

6 (2%)

2/6 (33%)

>4

4 (4.6%)

3/4 (75%)

6 (2%)

2/5 (40%)

Authors’ Affiliations

(1)
Royal Liverpool University Hospital, Liverpool, UK

Copyright

© BioMed Central Ltd 2006

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