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Model for Predicting Hospital Readmission in Elderly Male

Purpose: To evaluate an elderly male admitted to a general medical service for probability of readmission using the model of Burns and Nichols.

Description

Burns and Nichols developed a logistic regression model for predicting risk of hospital readmission in an elderly male. This can help identify patients who may benefit from more aggressive management and monitoring. The authors are from the Veterans Administration Medical Center and the University of Tennessee in Memphis.


Patient selection: general medicine male patients >= 65 years of age admitted to a VA hospital

 

Parameters:

(1) admitted with congestive heart failure (CHF) and/or chronic obstructive pulmonary disease (COPD)

(2) type of admission

(3) admission disease severity using the Computerized Severity of Illness (CSI) Index

 

Parameter

Finding

Points

admission diagnosis

CHF and/or COPD

1

 

other

0

type of admission

emergent

1

 

non-emergent

0

severity of illness index on admission

mild to moderate with good prognosis

1

 

mild to moderate with fair prognosis

2

 

severe and progressive with fair prognosis

3

 

severe and progressive with poor prognosis

4

 

X =

= (1.50 * (points for admission diagnosis)) + (1.14 * (points for type of admission)) + (0.58 * (points for severity of illness)) - 3.01

 

probability of readmission =

= 1 / (1 + EXP((-1) * X))

 

Performance:

• The accuracy was 76%, with a positive predictive value of 73% and negative predictive value of 77%.


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Objective

ICD-10