Overstay2 scoring model for Grace Hospital: Difference between revisions

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| Plegia  || 0.2515 || 0.0649 ||
| Plegia  || 0.2515 || 0.0649 ||
|-
|-
| Motor || 0.4485 || 0.0133 ||
| GCS_Motor || 0.4485 || 0.0133 ||
|-
|-
| Bath || 0.3843  || <.0001 ||
| ADL_bath || 0.3843  || <.0001 ||
|-
|-
| Toilet || 0.1612  || 0.0027 ||
| ADL_toilet || 0.1612  || 0.0027 ||
|-
|-
| Continence || 0.1567  || 0.0001 ||
| ADL_continence || 0.1567  || 0.0001 ||
|-
|-
| Adlmean_age || -0.00064 || 0.01 ||
| ADL_Adlmean_age || -0.00064 || 0.01 ||


|}
|}
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How to calculate OS:
How to calculate OS:


OS = exp(Y) / (1 + exp(Y)
* OS = exp(Y) / (1 + exp(Y)


Heart rate (HR), respiratory rate (RR), White Blood cell Count (WBC), systolic Blood Pressure (sBP, AP Sys BP Field) - are continuous data
* Homeless, PCH, OutsideWPG, InterImplantDevice, Opioids, Dementia, are binary categorical variables (present/yes=1, absent/no =0) .
The cut-off probability for R is 0.088 . "A cut-off point of 0.088, or a predicted probability of adverse outcome of 8.8%, was used to classify patients into two groups; high-risk and low-risk of adverse outcome." (from publication)
* CHF, Plegia, GCS_Motor, ADL_bath, ADL_toilet, ADl_continence are points or scores.
 
{{DJ| JM to be continued
The cut-off probability for OS is 0.088 . "A cut-off point of 0.088, or a predicted probability of adverse outcome of 8.8%, was used to classify patients into two groups; high-risk and low-risk of adverse outcome." _--[[User:JMojica|JMojica]] 11:53, 10 June 2025 (CDT)}}


== Log ==
== Log ==

Revision as of 10:53, 10 June 2025

This page describes the Overstay2 scoring model for Grace Hospital for the Project Overstay2, one of the site-based Overstay2 scoring models. The model was developed in Re-analysis and generation of Overstay2 model and is used to generate the Overstay2 colour, which in turn drives the Overstay2 processes on the units to reduce discharge delay.

Data elements and assigned coefficients

The binary logistic regression Y (Overstay GE 10 Days) which gave the AUC C-index =0.835 implying better predicted model and Hosmer and Lemeshow Goodness of fit test Chi-Square value of 6.1731 (prob=0.6278) is :

LN(OS/1-OS) = Y 

Y = sum of all (the Parameter values multiplied by the  Estimate)  listed below:
Parameter Estimate Prob > ChiSq
Intercept -9.9707 <.0001
Age 0.0281 <.0001
Homeless 1.2558 0.0166
PCH -3.6064 <.0001
OutsideWPG 2.0009 0.0311
InterImplantDevice 0.9103 0.0004
Opioids -1.6117 0.0363
Dementia 1.1715 <.0001
CHF 0.2820 0.0223
Plegia 0.2515 0.0649
GCS_Motor 0.4485 0.0133
ADL_bath 0.3843 <.0001
ADL_toilet 0.1612 0.0027
ADL_continence 0.1567 0.0001
ADL_Adlmean_age -0.00064 0.01

Where OS is the likelihood to overstay 10 days and beyond.

How to calculate OS:

  • OS = exp(Y) / (1 + exp(Y)
  • Homeless, PCH, OutsideWPG, InterImplantDevice, Opioids, Dementia, are binary categorical variables (present/yes=1, absent/no =0) .
  • CHF, Plegia, GCS_Motor, ADL_bath, ADL_toilet, ADl_continence are points or scores.


JM to be continued The cut-off probability for OS is 0.088 . "A cut-off point of 0.088, or a predicted probability of adverse outcome of 8.8%, was used to classify patients into two groups; high-risk and low-risk of adverse outcome." _--JMojica 11:53, 10 June 2025 (CDT)

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