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Healthcare Scheduling through AI Control Towers

Long wait times, inefficient schedules, tons of no-shows, poor patient satisfaction, provider burnout – Have you ever wondered why, in an age of advanced technology, healthcare scheduling feels like it is from the Middle Ages? 

AI Control Towers can improve schedule capacity for health organizations by 20%. With this additional capacity, health organizations can prioritize how they use these improvements – in taking care of the providers, proactive healthcare strategies, or working through critical backlogs. 

Here are some things that need to be considered for an effective healthcare scheduling solution (hint… the EHRs are not providing this)

-Patient criticality - this is of course what it is all about, ensuring the health of the patients, so there needs to be a key consideration

-Scheduling time for proactive care - we can’t continue to be chasing our tails, we need to get ahead of this – my parents always told me that an ounce of prevention was worth a pound of cure

-Predicting future visit volumes – planning trumps expediting… if you have a good plan, you can avoid a lot of issues. The key for this is some good forecasting models on what patient volumes you can predict

-In outpatient predicting no-shows – a lot of healthcare is moving from in-patient care to outpatient care, this adds the additional complexity of people showing up.

-Predicting patient duration and duration variability – certain visits always take a fixed amount of time, while others are highly variable, this can be modeled and considered.

-Protecting the providers – how can we build schedules that don’t destroy morale, there are ways to balance the demands and protect the providers

-Giving the providers back some control – provider can set an individual schedule that aligns with their needs and the needs of the healthcare organization.

-Building a probabilistic schedule – think of the airlines and hotels, they don’t assume everyone will show up – they plan for variances to their scheduled visits. Prediction confidence in predictions is important to consider

-Building a properly loaded schedule – when block schedules are set, there is no lens to view the patient volumes and adjust as necessary. There are also important strategies to ensure that provider are working at their top of license to ensure we’re getting the most value through the system and providing the greatest care.

-Influencing demand (patients visits) in context of the schedule capacity – and optimizing across a health system. It may mean that we can proactively take care of certain visits or procedures a different time periods or at different facilities

-Integrating virtual and in-person visits to maximize flexibility – by incorporating virtual visits into the equation, we can dramatically improve the throughput of the system while reducing wait times. 

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