Taha et al developed a simple score for predicting hospital readmission for a medical patient. This can help to identify a patient who may benefit from more aggressive management. The authors are from the University of Kansas in Kansas City.
Patient selection: adult (>= 18 years of age) medical patient in the hospital
Outcome: 30-day readmission rate
Parameters:
(1) age in years
(2) history of non-elective hospitalization within the past 6 months
(3) high-risk diagnosis
(4) high-risk medication at discharge
(5) polypharmacy (> 10 scheduled medications at discharge, in text on page 272 it says >= 10)
(6) psychological (depression)
(7) palliative care
High-risk diagnosis:
(1) congestive heart failure (CHF)
(2) COPD
(3) cancer
(4) diabetes mellitus
(5) pneumonia
(6) stroke
High-risk medications at discharge:
(1) aspirin with clopidogrel
(2) warfarin
(3) enoxaparin
(4) fondaparinux
(5) digoxin
(6) insulin
(7) opiods
|
Parameter |
Finding |
Points |
|
age in years |
< 65 years of age |
0 |
|
|
>= 65 years of age |
1 |
|
history of non-elective hospital admission within past 6 months |
no |
0 |
|
|
yes |
1 |
|
high-risk diagnosis |
0 |
0 |
|
|
>= |
1 |
|
high-risk medication |
0 |
0 |
|
|
>= 1 |
1 |
|
polypharmacy |
no |
0 |
|
|
yes |
1 |
|
psychological |
no |
0 |
|
|
yes |
1 |
|
palliative care |
no |
0 |
|
|
yes |
1 |
total score =
= SUM(points for all 7 parameters)
Interpretation:
• minimum score: 0
• maximum score: 7
• The higher the score the greater the risk of readmission.
• The risk of readmission is roughly (4 * (RRS)) + 8%
|
Score |
Readmission Rate |
|
0 |
5% |
|
1 or 2 |
13-14% |
|
3 or 4 |
18-19% |
|
5 |
27% |
|
>= 6 |
38% |
Performance:
• A RRS >= 1 had a positive predictive value of 18% and negative predictive value of 95%.
