*This data is false, made-up, and any other words to describe not real. It was built in Excel and has 100 rows.*

A historic local health clinic in Janesville, WI, called JHC is trying to improve the experience that it’s patients are having since a lot of negative comments have been coming in putting them in a tough situation and on top of that new competition is coming into town promising great service. JHC is using Lumira to gather insight on their patients and their ailments so they can quickly, effectively, and intimately treat their patients.

So at the head of the surge to improve the experience, is the PSAT Analysis dashboard. This dashboard is for JHC upper management to examine how patients rate JHC’s performance by month and/or physician, by county and/or also which gender appreciates JHC more. The dashboard is very flexible and can get some high level analysis done if JHC is looking for a good baseline of how they are doing. With the input controls (Month and Physician) you can drill down and slice through to many insights such has seeing the female/male comparison in January for Food Poisoning by Dr. Grey and Dr. Shepard individually and separate.

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It’s pretty common everywhere around the world that we get more ailments as we climb in age. This next visualization shows the number of visits JHC has, what ailment and the average age of the person who has it. This can help determine what medications JHC needs to ramp up on since most medications have age restrictions such as 2 tablets for adults or 1 tablet for kids 12 and under. If you notice you have lots of people coming in with pertussis over age 50 JHC can start ordering lots of safe medications for seniors and decreasing the need for medications that treat being too hairy and sprained ACL’s. Clinics may rarely run out of medication but clinics don’t have an endless supply of money, ordering too much of one medication can be a waste since some can expire.

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So the diagnosis and age analysis may bring up questions such as, “Which patients had it and what was there experience like?” The next visualization answers the question from a wait time perspective. Let’s take a closer look at the PSAT on Waiting Times visualization. In a secure clinic you don’t want information about patients given if it’s not needed which visualization mimics, but the main point here is to analyze that just because you didn’t wait long doesn’t mean the experience was good. For instance, notice how some patients waited 20+ minutes and still gave a PSAT 10. Why is this? This determines that people don’t mind waiting if “X”. Maybe there was a good TV show on in the waiting or maybe the waiting area is really comfortable whatever the “X” may be people tend to not mind waiting so much if they are acknowledged this can be done by saying hi or buying a bunch of nice furniture and having a Starbucks themed Keurig machine to show guests you really care.

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The last visualization I wanted to highlight focuses in on another culprit of why patients may or may not be having a different experience than others. What you pay at the clinic is a huge factor on satisfaction. A patient may pay higher fees but feel the service is worth it and another might feel that it doesn’t even come close. This visualization looks at who’s being charged based on the medications that are most commonly bought or needed. Analysis shows that females generally pay more for medication at this clinic than males whether they have insurance or not. It also shows that Intravenous Therapy is the most expensive form of treatment overall.

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With these basic tools of insight JHC can gain an advantage over the competition by having more insight about their patients to produce a more intimate level of service and know what ailments the patient is fighting or what things a patient may need. Happy Analyzing. datageekchallenge;

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