Centre For Orthopaedics installs Patient Flow Solution | NEXA

The Patient Flow Challenge

The Louisiana Centre for Orthopaedics is the region’s largest, independently owned musculoskeletal group, offering a comprehensive range of services for patients of all ages. With a catchment area of 300,000 people, the Centre has grown from 10,000 visits to 47,000 in the past two years and from four specialist providers to 12, making the management of patient flow an increasingly challenging issue. Here’s how Q-Flow help them to increase service levels and visits.

The Patient Flow Solution

Q-Flow was installed at the Centre in 2009. On arrival, the patient collects a ticket from one of six kiosks installed at reception, and is placed in a virtual queue. A map of the building is printed on the back of each ticket to help patients find their way around the Centre. The patient scheduling technology extends beyond queue management to enable surgeons and other hospital staff to accurately monitor the time they spend with each patient, to improve patient scheduling and reduce waiting times. Medical and administrative staff can review appointment calendar and manage patient queue flow remotely from their smart phone, bringing a new level of accessibility to the healthcare industry. Q-Flow is integrated into the patient management system used to track medical history and patient records. Patients can also use Q-Flow to remotely check-in for their appointment via a web based portal on the Centre’s website.

“Q-Flow has helped us to focus on providing patient-centred, not doctor-centred care,” Dr Noble said. “It’s not a replacement for face to face interaction, but rather a way for us to dramatically improve our patient flow and appointment scheduling, which allows us to spend more time with patients to recapture the personal aspect of the service, which has been lost in some areas of health care.”

Dr Noble added that the system’s capabilities will be further explored in the next 12 months at the Centre. “We will analyse the Q-Flow data against approximately 20 patient categories such as age, morbidity, medical history and current medical issue to determine the average time per patient from the moment they enter our facility until the moment they leave. This can allow us to virtually eliminate waiting times, outside of unforeseen issues,” he said.

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