Whole-of hospital occupancy management through the ED

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With millions of patient records now sitting in the healthcare system, health informatics researchers have been able to transform this data into an effective patient management system, incorporating emergency department admission predictions, patient flow throughout the hospital and even predicting readmission rates for regular patients known as ‘frequent flyers’.

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Starting at the door
Approximately 20-25% of patients start their journey through the health system by arriving at an Emergency Department in an ambulance. Ambulance services often maintain separate databases from hospital admissions services, and identify patients in different ways⁵, which is where the research first began.
The Patient Admission and Prediction Tool (PAPT) was developed at the Australian e-Health Research Centre by CSIRO in partnership with Queensland Health, Griffith University and Queensland University of Technology.
The web-based PAPT delivers real-time forecasting based on admissions data from previous years in similar circumstances – for example, prediction of admissions for the Easter long weekend would be based on what admissions had been received at the target’s own site and surrounding medical facilities for up to 10 years. Allowances are made for other factors such as specific events (large public events), current or additionally forecasted outbreaks of communicable illnesses and commonly repeating patterns (day of week, other identifiers that hospital bed managers can easily pinpoint for their facilities). The Gold Coast University Hospital tested the system at Schoolies Week to great success.
After developing the model at two Queensland public hospitals over 2002-2007, the research team ran a further five-year study across 27 additional Queensland facilities representing approximately 95% of the ED presentations across the state.² Mean daily presentation rates ranged from 60 to 190 patients/day and it was in the regional facilities with lower ED presentations that something important was discovered: to forecast a particular category of interest, there needed to be roughly more than 10 admissions or presentations per day.²
It was also found that poorer forecast performance was experienced over winter months, particularly the winter of 2009 (and to a lesser extent 2007), which correlates with significantly increased influenza-like ED presentations experienced across this season.²
Those in the test study were presented with forecasts for daily admissions and presentations, patient-flow in 4-hourly blocks, hourly admissions, gender, medical specialty and criticality (Australasian Triage Scale), as it was expected that this would be the most useful format for users.² A bed manager commented however, through a follow-up interview, “I use it usually on a weekly basis. Print off usually at the start of the week, and have a look at what’s predicted for that week.”¹
This was the executive management response during the study, particularly with regard to their own experiences during the regular walk-arounds.
“[it was] implemented in response to a crisis point, but there started to be some backlash. I was hearing from team members that every time they would see executive would be in this negative, punitive … ‘You’re hiding beds’. We’d never say that, but that’s why I moved toward a weekly meeting with the executive and the nursing directors where we’d use the PAPT information with the DADs [daily admissions and discharges report] to say, well actually, let’s not wait until Friday. Let’s have a look at what we’re likely to be experiencing over the next seven days and put in place some proactive strategies to deal with it.”¹
Lead researcher Dr Justin Boyle said the team added a few components to the software following user feedback. “The inclusion of detailed breakdowns shown on the dashboards has been at the request of patient flow units at hospitals, who not just wanted to know what’s coming in and out (admissions and discharges) but specifically wanted a better understanding of admitted patients in hospital at midnight for any particular day.
“Illustrating net patient flow is considered useful for communicating the required decision making around opening or closing hospital beds. It shows the onset and duration of the annual winter bed crisis and periods where it is quieter and where a hospital could close a ward representing significant cost savings,” he said.
Beyond the ED
Using the model developed for the prediction of emergency admissions, CSIRO was able to extrapolate the information and apply it to other problem areas within the residency management issues that the Labor government had targeted as part of its National Health Reform Act, promising to reduce access block and overcrowding.
Modern hospital systems have the ability to operate efficiently above an often-prescribed 85% occupancy level, with optimal levels varying across hospitals of different size. Operating over these optimal levels leads to performance deterioration defined around occupancy choke points. Understanding these choke points and designing strategies around alleviating these flow bottlenecks would improve capacity management, reduce access block and improve patient outcomes. Effecting early discharge also helps alleviate overcrowding and related stress on the system.⁵
References
1. Jessup M, Crilly J, Boyle J, Wallis M, Lind J, Green D, Fitzgerald G. Users’ experiences of an emergency department patient admission predictive tool: A qualitative evaluation. Health Informatics Journal 2015; 27 April 2015; doi: 10.1177/1460458215577993 [epub ahead of print].
2. Boyle J, Jessup M, Crilly J, Green D, Lind J, Wallis M, Miller P, Fitzgerald P. Predicting emergency department admissions. Emergency Medicine Journal 2012; 29:358-365.
3. Khanna S, Boyle J, Good N, Lind J. Unravelling relationships: Hospital occupancy levels, discharge timing and emergency department access block. Emergency Medicine Australasia 2012; 24; 510–517.
4. Commonwealth of Australia. Expert Panel Review of Elective Surgery and Emergency Access Targets under the National Partnership Agreement on Improving Public Hospital Services. National Health Reform 2010. Accessed 28 January 2016 (page last updated 27 June, 2010).
5. Dods S, Boyle J, Khanna S, O’Dwyer J, Sier D, Sparks R, Good N, Ireland D, O’Keefe C, Hansen D. Evidence driven strategies for meeting hospital performance targets: The value of patient flow modeling. CSIRO Health Services 2013; February 2013: 1-16.
Hospital departments and areas are interconnected, and so a ‘holistic’ approach has been taken while focusing on:
1. Linking ambulances, ED and admissions data – to manage ED admissions and the throughput to inpatient admissions.
2. Disease surveillance – such as outbreaks of influenza, the tracking for which is now used Queensland-wide.
3. ED length of stay performance – for measuring NEAT performance targets of 90% of ED patients being discharged within 4 hours of admission.
4. Bed demand prediction – using the PAPT to plan for numbers and types of beds needed for ED admissions.
5. Patient flow visualisation – user friendly statistical information for bed managers to monitor all aspects of their patient management requirements.
6. Patient flow and hospital occupancy – managing the hospital occupancy rate to be more flexible than the often-stated 85% which does not work for every facility.
7. Bed configuration – using predictive and real time statistics to optimise bed use through specialty clustering and pre-emptive prioritisation.
8. Adverse event analysis – using current data to improve future adverse event mitigation.
9. Early discharge strategies – managing reasonable occupancy levels through flexible discharge times.
10. Readmission prediction – identification of potential ‘frequent flyers’ who are likely to need readmission in the near future while they are still being treated.
In developing the PAPT and the 10-point blueprint for patient flow modelling the CSIRO is aiming to change the culture of retrospective planning and last minute cancellation of elective surgery patients, to proactive planning, enabling hospitals to better manage their resources and hence reduce overcrowding and its associated consequences.
An interview with Dave Piggott, Executive Director of Health IQ, and Fiona Webster from Austin Health, was published in our Summer 2016 issue discussing their PAPT trial.
Sharon Smith
Sharon Smith is the past Editor of Australian Hospital and Healthcare Bulletin. She works as a freelance journalist covering healthcare and the STEM sector. Her website is smsmith.com.au and she is on Twitter @smsmithwriter

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“Understanding these choke points and designing strategies around alleviating these flow bottlenecks would improve capacity management, reduce access block and improve patient outcomes.”

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