HoNOS and HoNOS65+:Is it a Useful Tool in Predicting Length of Stay?

Peter Thomas, Glen Bowcock

Andrea Taylor & John McMurray

Mental Health Drug and Alcohol Directorate, Northern Sydney Local Health District

June 2013

Introduction

Access and Demand Management is gaining increasing importance as LHDs seek greater control over resource management.

In NSW, all jurisdictions are required to use Estimated Date of Discharge (EDD) & Patient Flow Portal to manage bed resources

EDD has no credibility with MH Clinicians as MH lacks an accurate predictive tool

Variability in MH LOS makes Diagnostic Related Groups a poor predictor of MH LOS

Background

Background

Previous studies have examined the relationship between HoNOS and LOS with varying and inconclusive results

Tom Trauer et al. 2008 : Psychotic symptoms and disability are associated with longer length of stay

Harnett et al. 2005 : No association between HoNOSCA and Length of Stay

Page et al. 2001: HoNOS Scores could predict length of stay

Goldney et al. 1998: No correlation between HoNOS Scores and Length of Stay

Boot et al. 1997: HoNOS Scores moderately predict length of stay

Methodology Source of Data

Local Health District’s (LHD) Health Information Exchange (HIE) Database

NSLHD MH-OAT and Activity Collection Database (FISCH)

Definitions Length of Stay includes only Days in Pysch taken from HIE episode

table

Inclusions

1st Admission during the study period for each consumer HoNOS/HoNOS65+ collection occurred in the period 2003 - 2012 HoNOS/HoNOS65+ Collection occurred on or after the admission date All 12 individual items had a valid rating (0 – 4) MH-OAT Collection linked with Inpatient data using State Unique

Patient Identifier (SUPI)

Methodology Exclusions

Non-Acute units One mixed use Facility (ie. Acute and Non-Acute units) where frequent

transfers between Acute and Non-Acute Units distorted the results All subsequent admissions during the study period for each consumer

Sample Size 22,364 Acute Mental Health Admissions were recorded in NS LHD

during the study period. 11,311 Consumers admitted during the study period 3,231 Admissions met the criteria for inclusion

2,530 consumers had valid HoNOS collections 701 consumers had valid HoNOS65+ collections

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

Results

A moderately high correlation between HoNOS rating on Admission and ALOS has been found in NSLHD MH Acute Units

Removing the Behavioural Sub Scale when reviewing the ratings increases the correlation

Possible implications for developing tools to assist in standardising EDD practices and resource management planning

Generalising these results for potential ABF classification weighting would require care to avoid potential rater bias, as the need to maintain or increase funding may lead to inflated ratings

Summary

Thank You