Solving the New Patient Unassigned Dilemma

New patients frequently enter a practice without being referred to a particular provider.

Issues arise when some providers feel there is a misappropriation of new patients within the practice because schedulers often don’t have a process set in place to fairly and equally distribute these new patients among practice providers.

Opargo has found a solution in their New Patient Unassigned feature.

New Patient Unassigned is intended for groups who have patients who are referred to the practice but not an individual provider and equally distributing those patents amongst the providers that can see them so that everyone is getting their equitable share.

A lot of times, practices who have many physicians who see the same type of patients are sensitive to the fact that patients who are referred to the practice but not an individual provider are not equally distributed amongst the providers who can see those patients. And so, sometimes certain providers get more than their fair share.

Providers are very well aware to the point that they’re looking at their appointment schedule and seeing how many new patients they had for the day and then comparing that to other providers who see similar types of patients and recognizing that one person got more than they did.

In the orthopedic world, they have a group of doctors and ten of these doctors see patients with knee injuries. They might have one that they know specializes in knees and is maybe more proficient and prefers them. And so, if they had a patient present themselves with a knee injury, they might be more inclined to schedule the patient with that doctor.

Not all doctors in an orthopedic group treat feet, treat spines, do total hips, total knees. And so what we have to do first is to figure out what groups of providers that accept the same types of patients do we need to set and configure against. So all doctors who are willing to see a knee go in this group. All doctors willing to see feet go in this group. We first start with how many different groups do there need to be, based on all the different variants of body parts that people accept – and then assign providers to those groups.

Then we assign a quota so that Opargo can, to some extent, equally distribute one for you, one for you, one for you. We don’t really provide a one-to-one relationship because first, we want Opargo to be able to use its tools to optimize within the practice. So we set those quotas a little higher so we can first look at the visit as an individual entity and optimize what’s best for the practice first, and then equally distribute among the providers that are within those groups.

And so once a tool like this has gone into place we’ve seen where schedulers are pushing back on scheduling a certain type of visit with a doctor because they didn’t think they were supposed to.  But because this configuration has taken place and it’s only presenting doctors who see knees, they know that if it’s on the list, this doctor can see knees: “Wow! I never would have put this patient with that doctor before. I didn’t know.”

It’s taking a programmatic approach to apply technology to a problem that people have had for a long time, which is a lot of what Opargo does. We fix the things that doctors know are broken, but they don’t know how to fix it.

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