Austin Health is running a feasibility study on the two applications designed to improve and model patient flow.
Researchers at the CSIRO’s Australian eHealth Research Centre have developed two applications designed to assist with waitlist management in outpatient clinics.
One is a next available appointment tool to improve clinic scheduling and management, and the other is a template planning tool that can simulate patient flow two years into the future.
Both are being tested for feasibility in Austin Health’s IT environment on a virtual machine as a standalone tool using a Docker container, and are transferable to other health jurisdictions.
CSIRO research scientist Vahid Riahi told the MedInfo conference in Sydney last month that the NAA solution was aimed at providing a realistic timeframe for patients for their follow-up appointments at the time of consultation with the clinician.
The tool allows the clinician during the appointment to visualise what is likely if they want to book the patient’s follow-up appointment in two months, taking into account backlogs in the waiting list that make it more likely that the appointment will take place in five months.
“Using this information, the clinician now can make a decision,” Dr Riahi told PulseIT. “For example, if the delay is long, they can discharge the patient and send them back to their GP, or if this patient really needs to be seen in the intended timeframe, they can ask for another booking for the patient in the timeframe.”
Dr Riahi said this will allow clinicians to manage the risk and help to reduce the number of clinical incidents resulting from appointment delays.
The TPT is a simulation engine that uses a collection of patient-related data to provide a series of models, such as a model for referral, for discharge, and for “abandoned” patients, who are on the waiting list for a period of time but leave without an appointment.
“Using those models, this tool will capture patient flow and also provide a view of up to two years in the future and some insights into their backlog,” he said.
It will also give them an ability to investigate “what if” scenarios up to two years in the future by changing key parameters, such as discharge rate and referral pathways.
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