Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Norm Good is active.

Publication


Featured researches published by Norm Good.


Emergency Medicine Australasia | 2012

Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block

Sankalp Khanna; Justin Boyle; Norm Good; James Lind

To investigate the effect of hospital occupancy levels on inpatient and ED patient flow parameters, and to simulate the impact of shifting discharge timing on occupancy levels.


The Medical Journal of Australia | 2016

The National Emergency Access Target (NEAT) and the 4-hour rule: time to review the target.

Clair Sullivan; Andrew Staib; Sankalp Khanna; Norm Good; Justin Boyle; Rohan Cattell; Liam Heiniger; Bronwyn Griffin; Anthony Bell; James Lind; Ian A. Scott

Objective: We explored the relationship between the National Emergency Access Target (NEAT) compliance rate, defined as the proportion of patients admitted or discharged from emergency departments (EDs) within 4 hours of presentation, and the risk‐adjusted in‐hospital mortality of patients admitted to hospital acutely from EDs.


Emergency Medicine Australasia | 2013

New emergency department quality measure: from access block to National Emergency Access Target compliance.

Sankalp Khanna; Justin Boyle; Norm Good; James Lind

The study aims to investigate the effect of time of day and ED occupancy on the ability of EDs to admit or discharge patients within 4 h in accordance with the National Emergency Access Target (NEAT), and to compare this with corresponding levels of access block, the measure for ED performance before NEAT.


Clinical and Experimental Pharmacology and Physiology | 2010

Efficacy of butyrate analogues in HT‐29 cancer cells

Cheng C Ooi; Norm Good; Desmond B. Williams; Tanya Lewanowitsch; Leah J. Cosgrove; Trevor Lockett; Richard Head

1. Butyrate is a well known product of starch fermentation by colonic bacteria and is of interest owing to its ability to induce in vitro apoptosis and cell differentiation, as well as to inhibit cell growth in colorectal and other cancer cells. Synthetic analogues of butyrate may also possess cellular activities in a variety of cultured cells. The aim of the present study was to evaluate the effects of butyrate analogues on apoptosis, proliferation and histone deacetylase (HDAC) activity in HT‐29 colorectal cancer cells. In addition, the effects of these analogues on lactate dehydrogenase leakage, as a measure of non‐specific cytotoxicity, were evaluated in HT‐29 cells.


Clinical and Experimental Pharmacology and Physiology | 2010

Structure–activity relationship of butyrate analogues on apoptosis, proliferation and histone deacetylase activity in HCT‐116 human colorectal cancer cells

Cheng Cheng Ooi; Norm Good; Desmond B. Williams; Tanya Lewanowitsch; Leah J. Cosgrove; Trevor Lockett; Richard Head

1. Butyrate, a bacteria fermentative product in the colonic lumen, has been shown to produce a wide variety of biological effects in human cancer cells in vitro. However, there are pharmacological drawbacks associated with the use of butyrate therapy and there are limited published data on the structure–activity relationship of butyrate analogues in colorectal cancer cells. Previously, we determined structure–activity relationship using HT‐29 human colorectal cancer cells. However, it was viewed as important to explore similar relationships in another colorectal cancer cell line.


Studies in health technology and informatics | 2013

Hospital level analysis to improve patient flow.

Sankalp Khanna; Justin Boyle; Norm Good; Simon Bugden; Mark Scott

The complexity of hospital operations ensures that one-size-fits-all solutions seldom work. As hospitals turn to evidence based strategies to redesign flow, it is critical that they tailor the strategies to suit their individual service. This paper analyses the effect of hospital occupancy on inpatient and emergency department patient flow parameters at the Caboolture hospital in Queensland, Australia, and identifies critical levels, or choke points, that result in performance decline. The effect of weekdays and weekends on patient flow is also investigated. We compare these findings to a previous study that has analysed patient flow across Queensland hospitals grouped by size, and discover several differences in the interaction between rising occupancy and patient flow parameters including rates of patient flow, length of stay, and access block. We also identify significantly higher choke points for Caboolture hospital as compared to other similarly sized Queensland hospitals, which suggest that patient flow here can be redesigned to operate at higher levels of occupancy without degrading flow performance. The findings support arguments for hospitals to analyse patient flow at a service level to deliver optimum service improvement.


Therapeutic Advances in Respiratory Disease | 2016

Development of a novel image-based program to teach narrow-band imaging

Cédric Dumas; David Fielding; Timothy R. Coles; Norm Good

Objectives: Narrow-band imaging (NBI) is a widely available endoscopic imaging technology; however, uptake of the technique could be improved. Teaching new imaging techniques and assessing trainees’ performance can be a challenging exercise during a 1-day workshop. To support NBI training, we developed an online training tool (Medimq) to help experts train novices in NBI bronchoscopy that could assess trainees’ performance and provide feedback before the close of the 1-day course. The present study determines whether trainees’ capacity to identify relevant pathology increases with the proposed interactive testing method. Methods: Two groups of 20 and 18 bronchoscopists have attended an NBI course where they did a pretest and post-test before and after the main lecture, and a follow-up test 4 weeks later to measure retention of knowledge. We measured their ability to mark normal and abnormal ‘biopsy size’ areas on bronchoscopic NBI images for biopsy. These markings were compared with areas marked by experts on the same images. Results: The first group results were used to pilot the test. After modifications, the results of the improved test for group 2 showed trainees improved by 32% (total class average normalized gain) in detecting normal or abnormal areas. On follow-up testing, Group 2 improved by 23%. Conclusions: The overall class average normalized gain of 32% shows our test can be used to improve trainees’ competency in analyzing NBI Images. The testing method (and tool) can be used to measure the follow up 4 weeks later. Better follow-up test results would be expected with more frequent practice by trainees after the course.


Alzheimers & Dementia | 2015

Decreases in cerebral blood flow are associated with Aβ status in preclinical Alzheimer’s disease

Amir Fazlollahi; Fernando Calamante; Xiaoyun Liang; Norm Good; Ashley I. Bush; David Ames; Colin L. Masters; Fabrice Meriaudeau; Alan Connelly; Christopher C. Rowe; Victor L. Villemagne; Olivier Salvado; Pierrick Bourgeat

magnetic resonance imaging (fMRI) to assess the PFC-involved neural connections. Results:As expected, we found greater IIVRT in the MCI group compared to HCs. In the MCI group, IIVRT was positively correlated with the degree of connectivity in the fronto-basal ganglia circuit, and negatively correlated with the ECN in the right hemisphere. Conversely, IIVRT was negatively correlated with connectivity in fronto-basal ganglia circuit, and had no correlation with the ECN in the HC group. Conclusions: The altered relationship between IIVRT and two PFC-involved neural connections in MCI may indicate an early marker of the neurodegenerative process, though further work determining the causal link is needed.


pacific rim international conference on artificial intelligence | 2014

Predicting Procedure Duration to Improve Scheduling of Elective Surgery

Zahra ShahabiKargar; Sankalp Khanna; Norm Good; Abdul Sattar; James Lind; John O’Dwyer

The accuracy of surgery schedules depends on precise estimation of surgery duration. Current approaches employed by hospitals include historical averages and surgical team estimates which are not accurate enough. The inherent complexity of surgery duration estimation contributes significantly to increased procedure cancellations and reduced utilisation of already encumbered resources. In this study we employ administrative and perioperative data from a large metropolitan hospital to investigate the performance of different machine learning approaches for improving procedure duration estimation. The predictive modelling approaches applied include linear regression (LR), multivariate adaptive regression splines (MARS), and random forests (RF). Cross validation results reveal that the random forest model outperforms other methods, reducing mean absolute percentage error by 28% when compared to current hospital estimation approaches.


Artificial Intelligence and Applications | 2013

MODELLING THE ACUTE HEALTH SYSTEM: PATIENT FLOW ANALYSIS FOR IMPROVED HEALTH SERVICE DELIVERY

Justin Boyle; Sankalp Khanna; Derek Ireland; John O'Dwyer; Norm Good; David Sier; Ross Sparks

Routine collection of health care information by government agencies provides a wealth of potential for improving the delivery of healthcare through the analysis of patient flow. We describe our work in secondary analysis (i.e. differing from the purpose originally intended) of hospital information datasets comprising episodes of patient care. Our patient flow tools and analyses have application to public health agencies striving to improve the productivity and efficiency of service delivery, where evidence-driven strategies are desired to support improved health outcomes.

Collaboration


Dive into the Norm Good's collaboration.

Top Co-Authors

Avatar

Sankalp Khanna

Commonwealth Scientific and Industrial Research Organisation

View shared research outputs
Top Co-Authors

Avatar

Justin Boyle

Commonwealth Scientific and Industrial Research Organisation

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

K. Ellis

University of Melbourne

View shared research outputs
Top Co-Authors

Avatar

David Ames

Mental Health Research Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge