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4th International Conference, Society for Acute Medicine, Edinburgh 7-8 October 2010
The Amb ScoreA pilot study to develop a scoring system to
identify which emergency medical referrals
would be suitable for Ambulatory Care.
Les Ala1, Jennifer Mack2, Rachel Shaw2, Andrea Gasson1
1. Department of Acute Medicine, Royal Glamorgan Hospital, South Wales
2. 3rd Year Medical Student, Cardiff University
Format
• Background
• Aim
• Methods
• Results
• Conclusions
• Questions
Background
• In our DGH
– 30 – 40 patients seen by ‘on call Medical team’ in 24 hours
• 30 -40 % discharged same day
• Many medical emergencies can be managed in ambulatory care1,2
1. Strang G (2008)
2. Connolly v, Hamad M (2008)
Acute Medical Unit
(Admissions ≥ 12-24 hours
Which patients do not require admission?
• MEWS1 identifies acutely ill patients at risk of immediate deterioration
• Other Scores (HOTEL2, SCS3) predict mortality
• SEWS4 correlates with in-hospital mortality and length of stay
• Current scores rely on clinical parameters and tests (eg ECG) measured after arrival in hospital
• Limited data on identifying ‘ambulatory patients’
1.Subbe CP, Kruger M, Rutherford P, Gemmel L. Validation of a modified Early Warning Score in medical admissions. Q J Med 2001; 94: 521-526
2. Kellet J, Deane B, Gleeson M. Derivation and validation of a score based on Hypotension, Oxygen saturation, low Temperature, ECG changes and
Loss of independence (HOTEL) that predicts early mortality between 15 min and 24 h after admission to an acute medical unit. Resuscitation 2008; 78:
52-58
3. Kellet J, Deane B. The Simple Clinical Score predicts mortality for 30 days after admission to an acute medical unit. Q J Med 2006; 99: 771-781
4. Paterson R, MacLeod DC, Thetford et al. Prediction of in-hospital mortality and length of stay using an early warning scoring system: clinical audit. Clin
Med 2006; 6: 281-284
Why the need to know beforehand if
admission or ambulatory?
• Appropriate arrangements for
– Home
– Work
– Social services
– Care agencies
• Appropriate amount of personal belongings
• Admission paperwork
• Bed Management
Aim• Identify factors for a scoring system
– Predict who could be discharged
same day (within 12 hours)
• A surrogate marker for
‘ambulatory care’
– Clinical, demographic, social
– Simple to use
– Easily calculated in community
Methods• Cross-sectional study (RGH)
• All emergency referrals to Medicine from GPs
• Over a 4 week period (May / June 2010)
• Study population divided into 2 groups
– Discharged ≤ 12 hours (Ambulatory cases)
– Admitted for ≥ 48 hours (Admission cases)
• Routine data extracted from GP letter, Ambulance notes, Bed Management notes, Medical & Nursing notes
• Data on Social, demographic and clinical aspects collected using questionnaire
• Analysis using Epi Info 2000 Version 3.5.1 (CDC Atlanta 2008)
Results
• 282 patients
– 64 % females, 36% males
• Age
– Males (Mean age 67, SD 16)
– Females (Mean age 63, SD 19)
• Number in each group
– Ambulatory Cases: 143 (50.7%)
– Admission Cases: 139 (49.3%)
Which factors were NOT significant?
Which factors WERE significant?
Which factors WERE significant?
Independent factors
Independent Factor Ambulatory or
Admission
Adjusted Odds
Ratio (95% CI)
Male sex Admission 1.9 (1.1-3.5)
Age ≥ 80 Admission 2.4 (1.1-5.2)
Access to transportation Ambulatory 0.1 (0.05-0.2)
IV treatment not anticipated Ambulatory 0.1 (0.009-0.08)
Not acutely confused Ambulatory 0.1 (0.02-0.6)
MEWS zero Ambulatory 0.5 (0.2-0.9)
Not discharged within last month Ambulatory 0.3 (0.2-0.7)
The Amb Score
Amb
score
Admission group.
Number (%)
Ambulatory group.
Number (%)
Odds Ratio (95% CI) p
0 1 (0.7) 0 (0.0) undefined 0.495
1 3 (2.2) 0 (0.0) undefined 0.112
2 12 (8.6) 1 (0.7) 13.3 (1.7-103.9) <0.001
3 28 (20.1) 1 (0.7) 35.6 (4.8-265.5) <0.0001
4 35 (25.2) 6 (4.2) 7.6 (3.1-18.8) <0.0001
5 31 (22.3) 12 (8.4) 3.1 (1.5-6.3) <0.001
6 20 (14.4) 53 (37.1) 0.3 (0.2-0.5) <0.0001
7 9 (6.5) 69 (48.3) 0.1 (0.03-0.16) <0.0001
An Amb Score of 6 or 7 is associated with a likelihood of being in the
‘Ambulatory’ group
An Amb Score of 5 or below is associated with a likelihood of being in the
‘Admission’ group.
Conclusions
• Simple, readily available parameters
• Does not require extra information from ‘hospital tests’
• Useful guide for GPs and patients to predict likelihood of same day discharge, before arrival in hospital
• BUT: Informed clinical judgement of referring GP takes precedence
Limitations
• Small pilot, limited numbers
• Specific local setting (in hospital)
• Ideally, need larger community-based study to:
– Verify the factors
– Validate the scoring system
• Within current locality
• Within different locality (eg urban area, different
rural area)
Any questions?