In the early 80’s we expanded our independent pharmacy into providing Home Medical Equipment as hospitals’ reimbursement was changed to a new prospective DRG program. Basically, the hospital was paid a flat $$ when the pt was admitted, based on the pt’s diagnosis. If the hospital cost to treat the pt was more than the DRG amount – they lost money, if they spent less on treating this pt was less – they made money. Back then, the phrase came about of “discharging pts quicker and sicker”. It created a pt’s need for home medical equipment (HME).
Our small 1200 sq ft pharmacy quickly grew to have 5,000 sq ft for retail/display area and office space for our customer service and billing staff along with a fitting room for our prosthetic, orthotic, and mastectomy fittings, and off-site 2,800 sq ft warehouse for storing rental equipment and a place to provide maintenance and repair of our rental equipment pool.
We eventually became the largest HME vendor in two counties.
Is this Mobile, ALA hospital using artificial intelligent software to re-invent the “discharge pts quicker and sicker” to a new level to add to their bottom line?
Breaking throughput barriers: A hospital’s AI-powered approach to improved efficiency
In this session, Sharon Barincle, the hospital’s executive director of revenue cycle, will share their experience implementing predictive analytics and AI solutions to tackle operational challenges and increase patient throughput.
Find out how the 270-bed community hospital:
- Aligned care teams around precise discharge targets for proactive planning based on forecasted demands
- Streamlined patient discharges to reduce delays and optimize length of stay.
- Expedited evaluation of outpatients in inpatient beds to reduce prolonged stays and increase capacity
- Established effective communication between nursing, case management and administration to escalate barriers affecting length of stay and discharge planning
Filed under: General Problems
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