Meeting Title: Pharmacy Data Integration Discussion Date: 2025-11-11 Meeting participants: Henry Zhao, Pete
WEBVTT
1 00:01:35.700 ⇒ 00:01:37.320 Henry Zhao: Hey, Pete, how’s it going?
2 00:01:37.320 ⇒ 00:01:38.079 Pete: Hey, Henry.
3 00:01:40.180 ⇒ 00:01:41.809 Henry Zhao: How’s your week going so far?
4 00:01:41.810 ⇒ 00:01:43.300 Pete: I’m busy.
5 00:01:43.860 ⇒ 00:01:44.320 Henry Zhao: No, I bet.
6 00:01:44.320 ⇒ 00:01:46.040 Pete: I was… yeah.
7 00:01:47.010 ⇒ 00:01:48.800 Henry Zhao: Is now still a good time?
8 00:01:48.800 ⇒ 00:01:50.240 Pete: Yeah, absolutely.
9 00:01:50.400 ⇒ 00:01:53.879 Henry Zhao: Okay, perfect, thank you. After this, hopefully I won’t need to bother you anymore.
10 00:01:53.880 ⇒ 00:01:54.850 Pete: No worries.
11 00:01:55.260 ⇒ 00:01:57.810 Henry Zhao: I do have a ton of questions for you at the end.
12 00:01:57.810 ⇒ 00:01:58.240 Pete: Absolutely.
13 00:01:58.240 ⇒ 00:02:04.349 Henry Zhao: It’s because I’m getting a lot of requests on pharmacy data, and the only data I have right now is from BASC, so…
14 00:02:04.430 ⇒ 00:02:18.470 Henry Zhao: they’re missing a lot of data, and in order for me to get the work that I need done, I need to figure out where this data lies, so it might be Pharmedica, we might need to figure out another way to get it, but I’d like to have that discussion with you before we end the call.
15 00:02:19.390 ⇒ 00:02:29.979 Pete: Yeah, it probably would be with Pharmedica. We, in fact, just had a problem with Pharmacy API. It got out, somehow over the weekend, and I…
16 00:02:29.990 ⇒ 00:02:41.780 Pete: there’s only one or two methods that it could have gotten out. So basically, the end of the day, it has to be requested directly from Pharmedica, because they need an NDA disclosure, kind of per what was,
17 00:02:42.070 ⇒ 00:02:47.509 Pete: I can’t remember if it was an email where Rebecca sent it, or in Slack, but
18 00:02:48.980 ⇒ 00:03:04.910 Pete: So, that’s where a lot of the data is gonna live. The BASC data is just stuff that are coming from Eden telehealth providers, specifically, and ultimately, the biggest repository of the pharmacy data is going to be in Pharmedica, so…
19 00:03:05.450 ⇒ 00:03:15.390 Pete: depending on… on who else within Eden you’re developing for, for the pharmacy, everything we need is going to come out of… out of Pharmedica.
20 00:03:15.390 ⇒ 00:03:20.660 Henry Zhao: Okay, what did you mean the last week when you said that they’re very strict on their API?
21 00:03:22.790 ⇒ 00:03:33.090 Pete: They, they require an NDA signed, and then they will give you the API necessary. There’s, like, a process involved, so,
22 00:03:33.440 ⇒ 00:03:41.170 Pete: Yeah, that’s… that’s why. And part of the reason why is because it just made its way out, and some providers got ahold of it, and…
23 00:03:42.240 ⇒ 00:03:53.759 Pete: in their provider portal integration, and it’s kind of… it kind of messed things up… things up. So that’s just a… just an example of… of why they’re kind of stingy with it.
24 00:03:54.700 ⇒ 00:04:00.159 Henry Zhao: Okay, but like, that’s the… like, the technical capabilities are there, they just need to make sure that it’s gatekeeped.
25 00:04:00.540 ⇒ 00:04:02.980 Pete: Correct. Correct. Yep.
26 00:04:03.350 ⇒ 00:04:08.029 Pete: So the outflow of data shouldn’t be a problem. I mean, heck, we have a…
27 00:04:08.470 ⇒ 00:04:15.599 Pete: Google extension that was coded that pulls data out of Pharmetica, so, like, it’s there, it’s available, it’s just a matter of…
28 00:04:15.800 ⇒ 00:04:19.190 Pete: Going through the proper hoops to get ahold of it, so…
29 00:04:19.950 ⇒ 00:04:35.440 Henry Zhao: Okay, so if you want to just show me whatever you didn’t get to show me last Friday, after that we can jump into my questions, and then I can afterwards make a list of who’s requesting this data, so we can make sure that we are able to provide that data, and that we’re not breaking any, like, privacy rules.
30 00:04:35.440 ⇒ 00:04:45.909 Pete: Sounds good. I made a flow chart for you, so that way you can, kind of give you a high-level overview of how this thing is going.
31 00:04:46.110 ⇒ 00:05:00.239 Pete: it’s… Pharmetica’s internal process is kind of convoluted, so, like, it’s not linear. That’s part of the problem with it, is that there’s multiple steps that need to be hit, and they’re housed in different areas, and instead of following a linear…
32 00:05:00.320 ⇒ 00:05:20.099 Pete: processing workflow, it does the entire workflow by… out of, like, the same queue, and it’s just managed by filters. So, a pharmacist could be in the same queue as a technician, and depending on which filters they pull, will pull the workflow, or tailor the workflow
33 00:05:20.580 ⇒ 00:05:22.369 Pete: Needed to be completed.
34 00:05:23.270 ⇒ 00:05:30.070 Pete: in that same queue. So it’s just… it’s really weird the way that that works. So, like, when you get into Pharmetica, you have to…
35 00:05:30.080 ⇒ 00:05:49.220 Pete: everybody working out of a queue has to make sure that their filters are set properly, because they don’t auto-clear either every time you log in. So, if you were looking at something because you needed to look at something very specific, you log out for the day, and then you come in in the morning, you need to make sure your filters are, like, completely reset, so that it’s following the workflow.
36 00:05:49.650 ⇒ 00:05:59.699 Pete: just letting you know that, because if you were poking around inside the system, it’s… again, if you’re looking at these workflows that I’m describing here, it’s not gonna be…
37 00:06:00.130 ⇒ 00:06:19.659 Pete: kind of linear, the way that it’s housed. And hopefully the way that this is depicted, it’s a little… a little bit, obvious, too. So, process starts over here, and we kind of talked through some of this. So the prescription information is received, and it goes to data entry, where the prescription is transcribed from the hard copy.
38 00:06:19.660 ⇒ 00:06:23.979 Pete: And typed in by a technician. So that’s the data entry technician’s role.
39 00:06:24.040 ⇒ 00:06:41.049 Pete: Then it goes to the PV1 pharmacist, and so they will complete PV1 on it. Basically, that data entry process is just a data dump, so all they’re doing is the transcription. They’re not making any judgment calls on it whatsoever. So if it needs a new formula.
40 00:06:41.050 ⇒ 00:06:46.050 Pete: For the lab to create, because it’s a custom compound, or if it needs provider clarification.
41 00:06:46.050 ⇒ 00:06:51.409 Pete: whatever the reason is, that’s really up to the PV-1 pharmacist to evaluate. So…
42 00:06:51.440 ⇒ 00:07:04.439 Pete: First thing they’re evaluating is, does it have the necessary information? Is it correct? Was that data transcription, correct? And so if it’s no, it goes into one of these three fields.
43 00:07:04.500 ⇒ 00:07:06.660 Pete: Which leaves it in the same queue.
44 00:07:06.930 ⇒ 00:07:23.670 Pete: But, flags it a certain way, so again, if you put on certain filters, it’ll pull these out. So, for example, if it’s an errand data entry, then the data entry technician can do a filter and show what was sent back to them for correction. If it’s a formulation needed.
45 00:07:23.710 ⇒ 00:07:25.170 Pete: Same type of thing.
46 00:07:25.170 ⇒ 00:07:48.840 Pete: So on the other hand, if it’s yes, then you have another decision where you, have to know, do you have a handoff method? So, aka, patient’s gonna pick it up, it’s getting shipped to the clinic, it’s getting shipped to the patient. So that’s the handoff method. And then, do we have permission to process payment? So, right now, we gather that permission first before we do
47 00:07:48.840 ⇒ 00:07:58.720 Pete: anything else with the prescription, so we don’t have a handoff method and or don’t have payment permission. The pharmacist still verifies the prescription.
48 00:07:59.060 ⇒ 00:08:04.140 Pete: But it gets placed on hold, and it’ll be filled at a later time when we get that patient contact.
49 00:08:05.590 ⇒ 00:08:13.489 Pete: So, if we do have all of this already preloaded, then it goes to fill. So, then the fill technician will
50 00:08:13.490 ⇒ 00:08:25.769 Pete: count out medication, put it in a vial, you know, whatever the case is. And then from there, it gets bagged and goes on to the PV2 pharmacist, which is a different station than the PV-1 pharmacist.
51 00:08:25.790 ⇒ 00:08:41.300 Pete: So, really what the process is for PV2 pharmacists is to ensure that the medication was filled properly. They’ll do a light scrub of data, again, to kind of make sure that everything’s entered right, proper drug was selected, the proper patient profile is selected, all of that.
52 00:08:41.340 ⇒ 00:08:43.820 Pete: But,
53 00:08:45.280 ⇒ 00:08:57.389 Pete: they will, you know, their main purpose is to make sure that the physical drug selected is matching what it was typed for, so that it’s being dispensed properly.
54 00:08:58.010 ⇒ 00:08:59.000 Pete: Sorry.
55 00:08:59.110 ⇒ 00:09:01.430 Pete: Also, here I forgot to include…
56 00:09:03.660 ⇒ 00:09:11.130 Pete: So the P1 pharmacist also does a DUR review, which is a manual process right now, because Pharmedica doesn’t pull… pull…
57 00:09:11.360 ⇒ 00:09:16.749 Pete: DUR, it’s supposed to, but it doesn’t pull DUR…
58 00:09:17.020 ⇒ 00:09:21.810 Pete: Interaction information from any sort of database.
59 00:09:21.930 ⇒ 00:09:24.090 Pete: Because…
60 00:09:24.340 ⇒ 00:09:39.730 Pete: compounding pharmacy software has a hard time looking inside a formula, a compound formula, and picking up an active ingredient, and then comparing that active ingredient with other drugs on a patient profile. I don’t know why that’s so difficult, because the active ingredients have data, and
61 00:09:39.810 ⇒ 00:09:58.139 Pete: that information should be out there somewhere in some sort of repository, but they just don’t do that. So, the DUR review has to be done manually, and then it also has to be checked manually, so a pharmacist can’t just hit mark verified, and then it pop up with the DUR screen, and then you… the pharmacist initials it as reviewed.
62 00:09:58.260 ⇒ 00:10:08.129 Pete: and then Pharmedica automatically marks it as a DUR completed. It has to be manually checked off, which is another thing that I think is pretty stupid in a pharmacy management system.
63 00:10:08.300 ⇒ 00:10:13.730 Pete: But anyway, I don’t want to digress too much, so that’s… you know, I didn’t mean to take a step back, we’re really up here right now.
64 00:10:15.150 ⇒ 00:10:33.539 Pete: And so, was the medication filled properly? If it’s no, it’s returned to the fill station for correction, you know, recounting if the quantity’s off, drug selection, all that kind of stuff, then comes back to the PV2 pharmacist. If it was correct, then…
65 00:10:34.750 ⇒ 00:10:44.309 Pete: it goes on to the billing and shipping technician. And so, what ends up happening here is that it’s billed first.
66 00:10:44.440 ⇒ 00:10:52.580 Pete: before anything else happens. So billing and shipping are kind of decoupled, and that’s another, I think, workflow inefficiency.
67 00:10:52.650 ⇒ 00:11:00.410 Pete: I’ll get into that a little bit more later. So it’s billed, and then the decision is made, is it a shipping or pickup? So if it’s shipping, then…
68 00:11:00.410 ⇒ 00:11:17.200 Pete: a label gets printed, it gets sent to a shipping associate and packed… associate and packed for the carrier pickup, and then the parcel carrier comes, gets it. If it’s a pickup, it gets, put in the will call area, and then a patient comes in… comes and picks it up.
69 00:11:17.320 ⇒ 00:11:33.440 Pete: in any e-commerce, which is essentially the same paradigm that this pharmacy should function on, any e-commerce environment, billing should be… really be done up here after PV1, so billing should be somewhere over here.
70 00:11:33.600 ⇒ 00:11:39.280 Pete: And either processed by…
71 00:11:39.330 ⇒ 00:11:46.299 Pete: an associate, or a technician, or even the pharmacist. Honestly, it would be ideal if it was processed automatically.
72 00:11:46.300 ⇒ 00:12:03.890 Pete: there’s some logistical things that we have to take care of beforehand. We have to reset expectations with the patients, because right now we don’t… you know, we get… even though they give us a credit card, we get their permission to bill it first. Again, not optimal in an e-commerce paradigm.
73 00:12:03.890 ⇒ 00:12:23.430 Pete: So, we would have to reset the expectation with, you’re giving us the credit card because we are going to fill your prescription. So, there’s no question around that. And then, if you decide you don’t want it later, we can refund you and return it, but you’re going to get pre-billed. And then, also, Pharmetica, when you do the billing up front like that, it doesn’t mark it as
74 00:12:23.660 ⇒ 00:12:24.610 Pete: Filled.
75 00:12:25.370 ⇒ 00:12:40.249 Pete: or something. There’s another indicator that it doesn’t do properly. So it creates an issue in the downstream workflow. Again, another pharmetica limitation. So, ideally, this is where we want to go, is we want to pull this billing
76 00:12:40.410 ⇒ 00:12:43.730 Pete: Process up towards the front here.
77 00:12:43.850 ⇒ 00:13:01.970 Pete: So it’s more front-loaded, and then the end process is literally just shipping. Whether you’re billing that out, or we’re supposed to get that from Pharmetica with our new enterprise platform, I don’t know. I’m just letting you know, kind of holistically, where we’d like to live. And whatever your mandate is your mandate. So…
78 00:13:03.010 ⇒ 00:13:08.980 Pete: That’s just, you know, an inefficiency that I noticed there, as well as the DUR inefficiency up here.
79 00:13:11.080 ⇒ 00:13:19.819 Pete: you know, in a perfect world, if there was an event sequence that could be processed in Pharmedica, rather than,
80 00:13:20.150 ⇒ 00:13:35.900 Pete: you know, a clunky workflow based off of filters. In other words, you know, the event sequence would be triggered by barcode scans of the actual prescription. That would be a lot more ideal. So, in other words, data entry types it, it slides into PV1 review.
81 00:13:35.960 ⇒ 00:13:45.449 Pete: Those two stages don’t have barcodes, but basically from fill on, it would. So, you know, you fill the prescription, you have a barcode, you build it out.
82 00:13:45.540 ⇒ 00:13:51.120 Pete: Etc, etc. So, you know, the downstream effect is that it would just…
83 00:13:51.570 ⇒ 00:14:01.430 Pete: follow a sequence, a linear sequence of events through… through processing, rather than kind of the roundabout weight that it does now. So, any questions on the high-level overview?
84 00:14:02.150 ⇒ 00:14:07.289 Henry Zhao: What happens if the patient never comes to pick it back… pick it up?
85 00:14:07.290 ⇒ 00:14:19.899 Pete: So essentially what would happen is on a cycle, usually every couple of weeks, a technician will go through the will call shelves and return to stock. What we’re trying to do now is…
86 00:14:20.120 ⇒ 00:14:31.819 Pete: Actually, call patients and offer ship… offer to ship them to them to try to recoup the revenue, because basically, with pharmacies, revenue stays in accounts receivable, but it’s not collected.
87 00:14:31.820 ⇒ 00:14:41.059 Pete: Until the patient comes and picks them up, right? So, it can be returned, and then that reduces revenue, because that accounts receivable all of a sudden disappears.
88 00:14:41.060 ⇒ 00:14:43.920 Pete: And so those returns greatly impact the bottom line.
89 00:14:43.920 ⇒ 00:14:49.690 Pete: So we’re trying to do something proactive about, you know, actually getting it out the door.
90 00:14:49.690 ⇒ 00:15:06.609 Pete: And being that we offer free shipping now, we try to call patients and say, hey, you haven’t been able to come pick this up, do you want me to send it to you? And then recoup some of that. And if they decline, or if they end up not showing up, then we reverse the prescription,
91 00:15:06.640 ⇒ 00:15:11.920 Pete: Refund the billing, and then put the medication back for as long as the…
92 00:15:11.990 ⇒ 00:15:16.820 Pete: the beyond use dating allows. So hopefully we’re able to re-dispense it to somebody.
93 00:15:17.600 ⇒ 00:15:18.439 Henry Zhao: Oh, okay, gotcha.
94 00:15:18.440 ⇒ 00:15:18.770 Pete: Yeah.
95 00:15:18.770 ⇒ 00:15:21.410 Henry Zhao: We refund it, but then we still can resell it.
96 00:15:22.480 ⇒ 00:15:38.660 Pete: Theoretically, it all depends on the kind of testing and beyond use stating that we have on a particular drug. Orals and topicals tend to have a little bit longer, it’s the injectables that are kind of tricky, and those are the big ticket items, so those are the ones that we want to try to use
97 00:15:38.700 ⇒ 00:15:42.910 Pete: more. So, if we had data around
98 00:15:43.560 ⇒ 00:15:56.690 Pete: who hasn’t picked up, or how many prescriptions haven’t picked up, and that was a dashboard item, that would be a, like, a, you know, a metrics item. That would be very beneficial, because it would be helpful. It wouldn’t take a manual process of somebody having to walk through the shelves.
99 00:15:56.690 ⇒ 00:16:06.570 Pete: and identify things. They could just go in the system, it would show them, hey, this prescription in this bag is still ready, it’s been ready for a while.
100 00:16:06.580 ⇒ 00:16:08.970 Pete: And they would be able to do that, so…
101 00:16:16.530 ⇒ 00:16:20.100 Pete: So did you want me to go back into Pharmetica and walk you through the…
102 00:16:20.100 ⇒ 00:16:20.720 Henry Zhao: Yes, please.
103 00:16:20.720 ⇒ 00:16:24.670 Pete: process a little bit more? Okay, so… Let me see…
104 00:16:33.130 ⇒ 00:16:41.439 Pete: Okay, so… again, this is the PV1 queue, but this is also, I think, the data entry queue. Let me see real quick.
105 00:16:42.320 ⇒ 00:16:44.590 Henry Zhao: Yeah, I think the data entry is a piece that I would like to see.
106 00:16:46.200 ⇒ 00:16:48.460 Henry Zhao: It’s still very abstract for me.
107 00:16:48.460 ⇒ 00:16:49.280 Pete: Okay.
108 00:16:49.550 ⇒ 00:16:55.619 Pete: This should be the data entry queue. If you notice, I have, a lot of filters on here.
109 00:16:56.570 ⇒ 00:17:01.170 Pete: And so, I have to clear some of these, unless I remember how to do that.
110 00:17:01.170 ⇒ 00:17:02.150 Henry Zhao: Mizzou Meltz.
111 00:17:02.380 ⇒ 00:17:05.779 Henry Zhao: I’ll zoomed in to see the flowchart. It’s not zooming out.
112 00:17:08.030 ⇒ 00:17:09.180 Henry Zhao: One second.
113 00:17:09.440 ⇒ 00:17:10.570 Pete: No worries.
114 00:17:11.079 ⇒ 00:17:14.809 Henry Zhao: Why is it not zooming out? Hold on a second. I can only see, like, middle part of your…
115 00:17:15.759 ⇒ 00:17:17.989 Henry Zhao: What in the world? One second, please.
116 00:17:18.339 ⇒ 00:17:19.049 Pete: Huh.
117 00:17:19.159 ⇒ 00:17:27.569 Henry Zhao: This is so weird, fit to window. Alright, now we’re good. It was not zooming back out, so I couldn’t see anything. Okay, alright, now I can see the filters.
118 00:17:31.659 ⇒ 00:17:32.849 Pete: Let me do this.
119 00:17:34.290 ⇒ 00:17:36.440 Henry Zhao: Sorry, I’m also taking notes, let me rearrange my screen, so…
120 00:17:36.440 ⇒ 00:17:36.870 Pete: You’re good.
121 00:17:36.870 ⇒ 00:17:39.210 Henry Zhao: Alright, I’m good to go now.
122 00:17:42.890 ⇒ 00:17:44.360 Pete: Workflow tag…
123 00:17:51.700 ⇒ 00:18:05.030 Pete: Okay, so the status is where it would go. So, these statuses are the filters that I was talking about. So, ready for verification would be the filter that pharmacists select, and they would do
124 00:18:05.050 ⇒ 00:18:18.000 Pete: these three types, so they would do all three types. So with this status filter selected, these are prescriptions that are ready to verify for pharmacists. Prior to that, when you’re doing data entry, it would be new.
125 00:18:18.410 ⇒ 00:18:19.860 Henry Zhao: or rework.
126 00:18:20.320 ⇒ 00:18:23.330 Pete: And then these would be ones that are in…
127 00:18:23.510 ⇒ 00:18:25.630 Pete: The process for data entry.
128 00:18:25.770 ⇒ 00:18:26.120 Henry Zhao: Okay.
129 00:18:26.120 ⇒ 00:18:26.880 Pete: So, let me see…
130 00:18:26.880 ⇒ 00:18:29.979 Henry Zhao: It would match that to Monica Cedillo? Like, the hard copy?
131 00:18:30.060 ⇒ 00:18:32.150 Pete: Correct. Oh, this is the hardest part.
132 00:18:32.150 ⇒ 00:18:32.969 Henry Zhao: Copyright, okay.
133 00:18:32.970 ⇒ 00:18:38.740 Pete: Yeah, this is an actual paper hard copy, which is pretty unusual, but this is what it looks like.
134 00:18:38.740 ⇒ 00:18:42.379 Henry Zhao: They’re not getting any, like, mail with physical copies, right? It’s all digital.
135 00:18:42.640 ⇒ 00:18:52.470 Pete: It’s… it should be fax. Very rarely does a patient walk in with an actual paper hard copy anymore. Those are, you know, basically scanned in and reduced.
136 00:18:52.720 ⇒ 00:19:01.310 Pete: to electronic, so it’s not really very common anymore. This one was… was faxed. That’s just an example of one.
137 00:19:01.820 ⇒ 00:19:04.760 Henry Zhao: Okay, but when you say hard copy, all of it, you mean this kind of stuff, like, isn’t…
138 00:19:04.760 ⇒ 00:19:22.500 Pete: Correct. Yeah, it’s a euphemism for any prescription written, rather, versus what has actually been transcribed in the system. So what the data entry tech will do is they’ll come in here, they’ll ensure that the patient is selected properly, and that the address matches,
139 00:19:22.500 ⇒ 00:19:34.999 Pete: They’ll do a medication selection. So this is a compound med, it’s for semaglutide, 8mg sublingual anhydrous, so they can do partials, and they can do it this way.
140 00:19:37.410 ⇒ 00:19:47.579 Pete: you know, there’s a lot of different ways to look it up. It can be more complete, whatever the case may be. So we’re looking at this, looks like this one here.
141 00:19:47.580 ⇒ 00:20:01.659 Pete: And so, that’s what the drug selection would be. I’m not going to select that, because I’m not going to mess up her data entry process. And then these instructions are basically typed here. The origin will be selected, prescriber information will be selected.
142 00:20:01.660 ⇒ 00:20:02.040 Henry Zhao: Can you show me?
143 00:20:02.380 ⇒ 00:20:05.289 Henry Zhao: Yeah. Because that’s one of the data I’m gonna need.
144 00:20:06.840 ⇒ 00:20:08.850 Pete: This is…
145 00:20:08.850 ⇒ 00:20:11.540 Henry Zhao: Do we have a database of subscribers that…
146 00:20:11.540 ⇒ 00:20:12.520 Pete: We do.
147 00:20:12.520 ⇒ 00:20:12.960 Henry Zhao: Okay.
148 00:20:12.960 ⇒ 00:20:25.260 Pete: We do, if it… if we don’t, we would build it by, putting in the information from the clinic up here and the prescriber’s name down here. This is Rosenbaum.
149 00:20:29.350 ⇒ 00:20:34.539 Henry Zhao: Yeah, I just want to make sure Prescriber’s clean, which it looks like it is. It’s not like people just putting in random names, like…
150 00:20:34.870 ⇒ 00:20:36.319 Henry Zhao: It ends up being messy.
151 00:20:39.110 ⇒ 00:20:47.930 Pete: Gabriel… Garcia Rosenbaum… And then I would probably check an NPI.
152 00:20:48.800 ⇒ 00:20:54.179 Pete: Another thing you could do is if they have their MPI, you can put that in.
153 00:20:57.030 ⇒ 00:21:13.089 Pete: And that confirms that that’s that provider. Now, if they don’t exist in the database, you can ad hoc it, and you can add them, right? But, you know, and we’ll get new providers all the time, that’s very typical with pharmacy. But if they have a profile, we’ll pull one.
154 00:21:13.450 ⇒ 00:21:23.470 Pete: Then we’ll do a diagnosis code, we’ll put that in here. Date written should be whenever the fax date on this was, so the 11th, this should match.
155 00:21:23.470 ⇒ 00:21:24.200 Henry Zhao: That’s it.
156 00:21:24.490 ⇒ 00:21:26.650 Pete: This would be the prescribed date.
157 00:21:26.650 ⇒ 00:21:27.050 Henry Zhao: Okay.
158 00:21:27.050 ⇒ 00:21:35.909 Pete: So not the actual date received, it would have to be, like, what is written on the copy here. This one, November 11th.
159 00:21:37.580 ⇒ 00:21:42.980 Pete: So they could have written it yesterday, and then forgot to fax it in, and then they would have sent it. It has to be what’s on this one.
160 00:21:43.390 ⇒ 00:21:44.100 Pete: Okay.
161 00:21:44.330 ⇒ 00:21:52.940 Pete: Quantity should match here, refills, day supply, etc. Quantity to dispense, everything expires a year after.
162 00:21:55.430 ⇒ 00:22:03.840 Pete: DAW is usually zero, but, it can depend. So, like, this one says no, that means it’s a 0. It could be a 1, 2, 3, whatever.
163 00:22:05.010 ⇒ 00:22:15.480 Pete: And then they would do the fill options. This is… this is where the handoff kind of goes, and so they would select something, like…
164 00:22:15.930 ⇒ 00:22:24.939 Pete: usually it’s unknown handoff patient pay, unless there’s a note here that says how it goes. Like, if I put in
165 00:22:27.000 ⇒ 00:22:32.100 Pete: Rosenbaum, sometimes there’s clinic notes that will give other guidance.
166 00:22:32.550 ⇒ 00:22:51.349 Pete: So, like, this one is saying that if they prescribe this formulation of semaglutide, we have a standing order to be able to change it to what our particular formulation is. And so, you know, things like that. Or it could say, like, for these types of orders, this should be shipped to the provider.
167 00:22:51.360 ⇒ 00:22:53.579 Pete: Or chip to the patient.
168 00:22:53.700 ⇒ 00:23:00.339 Pete: Or the patient can pick it up, but the organization pays, whatever the case may be, whatever mix of the payment and the handoff are.
169 00:23:00.470 ⇒ 00:23:08.390 Pete: And so in the workflow, the handoff method is usually this one, like I said, unless it says something else. Priority is usually normal.
170 00:23:08.600 ⇒ 00:23:21.379 Pete: And then the handoff method is going to be, usually unknown patient contact required, unless we have direction from the organization, or the patient, like, has a standing request, like, oh yeah, I always come and pick it up.
171 00:23:21.460 ⇒ 00:23:40.770 Pete: Whatever the case may be. Oh, cool. They can also do… they can also add medications in here, if we know information on that. This is where they would add allergies and diagnosis. So that goes down there. Most typically, it would be no known drug allergies, because if we don’t get that information, that’s what we default to. So that’s the data entry process.
172 00:23:42.020 ⇒ 00:23:54.029 Pete: Then from there, it stays in the same queue, it just comes out of new and rework, and it goes to just ready for verification, and then this is what the pharmacist pulls.
173 00:23:54.030 ⇒ 00:23:54.810 Henry Zhao: One now?
174 00:23:54.810 ⇒ 00:24:00.620 Pete: this is PV1 now, and as you can see, the queue did not change, so this is not linear, it’s very, like…
175 00:24:01.520 ⇒ 00:24:09.029 Pete: all-encompassing, and it entirely depends on… on these filters. And so…
176 00:24:09.030 ⇒ 00:24:14.259 Henry Zhao: Are you one… the one that’s responsible for checking for, like, drug allergies and, like, cross-effects of other drugs?
177 00:24:14.620 ⇒ 00:24:19.130 Pete: Yeah, and so let me show you… let me invert this and show you one.
178 00:24:19.350 ⇒ 00:24:20.389 Pete: Okay.
179 00:24:22.840 ⇒ 00:24:26.529 Henry Zhao: Invert just means, get it back out from ready for verification.
180 00:24:26.800 ⇒ 00:24:35.249 Pete: No, it just means to choose, ones that aren’t… don’t have a priority, so I’m looking at ones with a low priority instead.
181 00:24:35.790 ⇒ 00:24:39.519 Pete: That way I don’t… I don’t mess up one of the pharmacists out there.
182 00:24:41.330 ⇒ 00:24:44.690 Pete: organization, I think this is from Sweden.
183 00:24:45.540 ⇒ 00:24:49.050 Pete: Even telehealth. That’s what I want.
184 00:24:50.140 ⇒ 00:24:51.459 Pete: Then I’ll convert it.
185 00:24:52.430 ⇒ 00:25:03.069 Pete: I’ll go further down out of these. These are the ones that are urgent and, elevated and urgent, so they get flagged. I’m gonna go down here, I’ll pick this one.
186 00:25:03.070 ⇒ 00:25:05.069 Henry Zhao: How does someone become urgent for semaglutide?
187 00:25:05.580 ⇒ 00:25:11.229 Pete: It would be, like, if they’ve been waiting for a long time, if they’re out of SLA, you know.
188 00:25:11.230 ⇒ 00:25:11.589 Henry Zhao: Yeah, gotcha.
189 00:25:11.840 ⇒ 00:25:30.810 Pete: we’re trying to prevent a gap in therapy, you know, there’s reasons why we flag it, and I don’t know all of them yet, but there’s reasons why we’d flag it. Urgent is the most elevated, so that would have been the ones in red, and then elevated just flags them as orange.
190 00:25:30.970 ⇒ 00:25:38.930 Pete: Urgent is also usually to, like, indicate people who might be waiting… waiting in the store, for their… for their prescription pickup, so…
191 00:25:38.930 ⇒ 00:25:40.330 Henry Zhao: Okay. Interesting.
192 00:25:40.670 ⇒ 00:25:43.850 Pete: This is…
193 00:25:44.040 ⇒ 00:25:54.540 Pete: Where the pharmacist would do verification one, so they’re looking at the patient information, making sure that matches, making sure the address is correct.
194 00:25:54.590 ⇒ 00:26:04.490 Pete: you know, making sure the provider matches as well. They didn’t put diagnostic codes on these, because they might already have some.
195 00:26:04.640 ⇒ 00:26:08.379 Pete: Yep, that’s why we didn’t put those.
196 00:26:08.760 ⇒ 00:26:23.499 Pete: So here’s the medication, medication’s right here, so we’re making sure that matches. Here’s the instructions, right here. Spray one, spray twice a day, but intramasal route, that’s fine.
197 00:26:25.440 ⇒ 00:26:27.930 Pete: If it were me, I’d probably do…
198 00:26:29.650 ⇒ 00:26:37.399 Henry Zhao: Still, just because, as a pharmacist, we look for detail orientation. Is that field what we call medication instructions?
199 00:26:37.400 ⇒ 00:26:38.120 Pete: Yes.
200 00:26:38.340 ⇒ 00:26:41.960 Henry Zhao: Okay, that’s saved in, Pharmedica also, right?
201 00:26:41.960 ⇒ 00:26:42.890 Pete: Correct.
202 00:26:42.890 ⇒ 00:26:43.600 Henry Zhao: Okay, got it.
203 00:26:43.600 ⇒ 00:26:47.140 Pete: Everything we’re looking at right here is Pharmetica, so…
204 00:26:47.140 ⇒ 00:26:50.280 Henry Zhao: But all of this, I mean, like, can be exported by API, right?
205 00:26:50.810 ⇒ 00:27:07.669 Pete: Can be exported by API, and if it’s… so BASC is the originator for eating telehealth prescriptions. BASC is also a pharmacy management system, but like I said, this will be the ultimate repository, because we’re the pharmacy that it gets dispensed from, so…
206 00:27:07.840 ⇒ 00:27:10.859 Henry Zhao: And does every pharmacy on the Eden Network use Pharmedica?
207 00:27:12.050 ⇒ 00:27:19.620 Pete: We only have one pharmacy in ownership by Eden, the rest are partner pharmacies, so I don’t know what they use. Yeah.
208 00:27:19.620 ⇒ 00:27:22.410 Henry Zhao: So I actually don’t know how to get the data from them.
209 00:27:22.980 ⇒ 00:27:26.110 Pete: That would be a question, and I don’t know that…
210 00:27:26.680 ⇒ 00:27:33.289 Pete: just off the top of my head, I don’t know what your mandate was, but I don’t know if that’s necessarily what Josh and Adam were looking for, either.
211 00:27:33.290 ⇒ 00:27:34.020 Henry Zhao: Oh, okay.
212 00:27:34.220 ⇒ 00:27:43.399 Pete: The reason why is because, ultimately, Eden, all pharmacies will be owned by Eden at some point in the future. Okay. So…
213 00:27:43.640 ⇒ 00:27:55.840 Henry Zhao: So, worst case, I would tell my stakeholders, like, right now, we can just get this data for Eden Pharmacy, but eventually when we get owned… when all Eden is fulfilled by our pharmacies, then we’ll have that data, at least from.
214 00:27:56.430 ⇒ 00:27:59.239 Pete: Right, and again, I don’t think…
215 00:28:00.170 ⇒ 00:28:14.259 Pete: the struggle is to get data from partner pharmacies, because they probably have different software platforms that have better reporting. Really, with them, to my understanding, again, it’s, you know, there’s more high-level stuff going on, but to my understanding, there’s…
216 00:28:14.690 ⇒ 00:28:26.280 Pete: The concern with them is just SLAs. With us, it’s more holistic because our revenue impacts overall eat-in revenue.
217 00:28:26.490 ⇒ 00:28:28.550 Pete: and…
218 00:28:28.940 ⇒ 00:28:40.779 Pete: supports, you know, the overall company, because we’re part of the same company. With the partner pharmacies, we’re literally just paying them to fulfill prescriptions for us, so the need for data is not quite as deep.
219 00:28:41.240 ⇒ 00:28:45.209 Henry Zhao: What is the timeline for all drugs to be going through Eden Pharmacy?
220 00:28:45.460 ⇒ 00:28:53.649 Pete: I think it’s 1 to 2 days for, injectables, and 3 to 4 for oral.
221 00:28:53.650 ⇒ 00:28:57.879 Henry Zhao: Well, I mean… I mean, by when do we plan to have all of our medicines fulfilled by.
222 00:28:57.880 ⇒ 00:28:58.520 Pete: Oh.
223 00:28:58.520 ⇒ 00:28:59.450 Henry Zhao: We’ll see.
224 00:28:59.450 ⇒ 00:29:05.810 Pete: Gotcha. I… I’m not sure on that. Right now, the only one owned by Eden is ours in Albuquerque, and we’re…
225 00:29:06.520 ⇒ 00:29:16.789 Pete: I believe they’re looking at purchasing one or two more, but I don’t know what the timeline is on that. You’d have to talk to Josh and Adam for more insight there.
226 00:29:16.790 ⇒ 00:29:17.449 Henry Zhao: Okay, sure.
227 00:29:19.200 ⇒ 00:29:34.839 Pete: And interestingly, they may even be on a different pharmacy platform for a period of time, because typically, when you buy a pharmacy, you use whatever platform they have until you’re at a point where, you know, you’re building out the uniformity, so…
228 00:29:35.890 ⇒ 00:29:50.850 Pete: I can tell you, pie-in-the-sky future dreams is to have a pharmacy management system built by Eden for Eden Pharmacies. So, something akin to, like, Walgreens’ proprietary platform or something like that, so…
229 00:29:50.850 ⇒ 00:29:58.819 Pete: You know, hopefully that later on, that would make things easier, because then that API would be owned by the company, but…
230 00:29:59.140 ⇒ 00:29:59.680 Henry Zhao: Boop.
231 00:30:00.200 ⇒ 00:30:14.569 Pete: So, just continuing through, you know, I make sure everything matches here, it looks good to me. One thing I will go check is I’m going to click this toggle and pop over to the patient profile to see what kind of outreach we’ve made.
232 00:30:14.830 ⇒ 00:30:18.020 Pete: So right now, it’s just saying,
233 00:30:26.360 ⇒ 00:30:34.149 Pete: Yeah, I’m not gonna verify this, because this isn’t exactly true, but we are waiting for a result from,
234 00:30:38.290 ⇒ 00:30:57.869 Pete: a response from the patient, so if I was going to verify this, theoretically, let’s say this was just a compounded medication, and we were going to fill it, it would say something like, we received medication for you, we need to know one of three things, or we need to know these three things. How would you like to pay? Are you going to pick it up, or would you like it shipped to you?
235 00:30:58.100 ⇒ 00:31:04.969 Pete: And something else, I can’t remember. And so, when the patient responds to this, we’ll see that response in this text thread.
236 00:31:05.030 ⇒ 00:31:24.709 Pete: And so, if it was responded to, I would do DUR perform, so I haven’t done the DUR yet, but I’ll go look at their medications. They don’t have anything else on their list. If I don’t manually click this, the DUR will not be performed. The pop-up will come up for DUR review, but it won’t mark it as actually completed.
237 00:31:24.780 ⇒ 00:31:40.110 Pete: So that’s that manual process I was telling you about. And so, if we did get a patient response that they do want the medication, and they do want it either shipped to them or pick it up, I would do this fill upon verification. Otherwise, I would leave that off, and I would mark it verified, as long as everything is correct.
238 00:31:40.840 ⇒ 00:31:45.889 Pete: So, that is the PV1 process.
239 00:31:46.510 ⇒ 00:31:56.739 Pete: From there, you’re no longer in the prescription entry queue. You go to the dispensing queue.
240 00:31:57.310 ⇒ 00:31:57.940 Henry Zhao: Okay.
241 00:31:57.940 ⇒ 00:32:08.259 Pete: And then this is what the technicians are actually filling from. And so, these are ones that are urgent, these are ones that are elevated, and then it just goes all the way down.
242 00:32:09.230 ⇒ 00:32:10.429 Pete: From what I…
243 00:32:10.430 ⇒ 00:32:14.869 Henry Zhao: Do they do it one by one, or do they get, like, a bunch of semaglutide and, like, do a batch of them at once?
244 00:32:15.260 ⇒ 00:32:31.470 Pete: They would batch them if there’s more than one for a specific patient, otherwise they would do them one by one, because it’s a pharmacy best practice. There’s a risk involved when you print out a whole bunch of labels for different patient orders, because there’s… you might get them mixed up. Okay.
245 00:32:31.740 ⇒ 00:32:33.679 Henry Zhao: That makes me feel better as a consumer, too.
246 00:32:33.810 ⇒ 00:32:41.200 Pete: Yeah, absolutely. Like, you know, there’s… there’s best practices and efficiencies, and sometimes the best practices supersede the efficiency, so…
247 00:32:41.200 ⇒ 00:32:41.700 Henry Zhao: Cool.
248 00:32:41.700 ⇒ 00:32:52.190 Pete: I’m gonna go further down in the list, just… just to show you, because again, I don’t want to mess up their workflow. And so this comes in here, and it shows,
249 00:32:53.940 ⇒ 00:33:13.770 Pete: you know, they… this is an example of the response, so these are the things we asked. Has anything changed? Do we have your permission to fill? Would you like pickup or shipping? They responded to all three. We’ll let you know when it’s ready. And so, looks like this one was already verified, and it probably has to do with…
250 00:33:13.770 ⇒ 00:33:17.119 Pete: me not… Having the right filters on.
251 00:33:17.800 ⇒ 00:33:20.550 Pete: So if I go back into the dispensing queue…
252 00:33:21.490 ⇒ 00:33:29.620 Pete: See, I have the ready for pickups selected, so I actually have to kill all those filters, and I have to do… the ones that say filled.
253 00:33:29.890 ⇒ 00:33:31.839 Pete: Should be the ones that…
254 00:33:32.200 ⇒ 00:33:40.480 Pete: the nomenclature’s off with Pharmedica 2, so filled really means that it should have been counted in in a bottle, but Pharmetica considers everything that’s PV1
255 00:33:40.810 ⇒ 00:33:44.620 Pete: verified to be filled. So,
256 00:33:44.960 ⇒ 00:33:49.509 Pete: this is what they’re processing right now, and so if I go look at this…
257 00:33:56.110 ⇒ 00:33:59.519 Pete: This one is probably on hold,
258 00:33:59.980 ⇒ 00:34:03.060 Pete: So there’s probably other flags that I’m not looking at.
259 00:34:03.370 ⇒ 00:34:11.459 Pete: Again, not too sure. Haven’t been through this process yet, as far as training goes.
260 00:34:12.290 ⇒ 00:34:14.310 Pete: Inventory ready…
261 00:34:15.800 ⇒ 00:34:18.989 Henry Zhao: Do we save data on the messaging between patients also?
262 00:34:19.620 ⇒ 00:34:27.010 Pete: Yes, that’s all complete… that’s all, maintained on every patient’s profile, and it’s reviewable through the process, so…
263 00:34:27.010 ⇒ 00:34:30.009 Henry Zhao: I honestly don’t know why they want to analyze that, because it’s gonna be so much data, but…
264 00:34:30.880 ⇒ 00:34:31.569 Henry Zhao: At least I need to.
265 00:34:31.570 ⇒ 00:34:43.359 Pete: I mean, retrievable, maybe? I don’t know. Oh, look, maybe that was it. That might have been the last one they needed to fill, because it just popped out of here. But anyway, that’s the… that’s the kind of fill process, as far as I can take you.
266 00:34:43.360 ⇒ 00:34:45.019 Henry Zhao: That’s good enough.
267 00:34:45.550 ⇒ 00:34:52.120 Pete: Okay. Then we have, pharmacist Verification 2.
268 00:34:52.949 ⇒ 00:34:55.310 Pete: I believe…
269 00:34:58.900 ⇒ 00:35:00.490 Pete: That’s here.
270 00:35:04.240 ⇒ 00:35:06.020 Pete: Okay, I don’t have any…
271 00:35:08.840 ⇒ 00:35:16.160 Pete: Yes, that’s here. So here, the pharmacist is, again, scrubbing it one more time, so they’re looking at the medication.
272 00:35:16.350 ⇒ 00:35:30.099 Pete: at the SIG, text information, it’s already got a bag assigned to it, so they’ll be just verifying what they have in their hand matches this, and it’s for the right patient, the right strength, all of that stuff.
273 00:35:30.240 ⇒ 00:35:34.720 Pete: And then at the end, they just click Mark Verified. Again.
274 00:35:36.120 ⇒ 00:35:49.210 Pete: we really need to be scanning barcodes, but we’re not, especially at a point of actual physical product verification. We really, really need to be scanning barcodes, but there’s… Pharmedica doesn’t have a way to do that,
275 00:35:49.230 ⇒ 00:36:06.470 Pete: Because manually typing an NDC to say that that was correct, or whatever the case may be, it’s risky. But anyway, once that’s all been checked, then they would hit mark verified, and then it would go to the shipping process. So then we’d be…
276 00:36:06.540 ⇒ 00:36:15.470 Pete: Over here. If… if it was… if there was something wrong with it, there should be a way to send it back. Let’s see…
277 00:36:26.910 ⇒ 00:36:32.270 Pete: Not sure that I know the way to send it back, like, if it was misfilled.
278 00:36:39.400 ⇒ 00:36:46.709 Pete: Yeah, I don’t know, I’d have to circle back on that piece. So then we go to the shipping process.
279 00:36:47.320 ⇒ 00:36:52.809 Pete: I don’t… I’m not too sure where that one’s at. Give me just a second. It might be in here…
280 00:36:54.080 ⇒ 00:36:55.420 Pete: Shit 2…
281 00:37:00.950 ⇒ 00:37:09.100 Pete: this is probably where billing would be completed. They probably go into a different queue for this, and then once billing is completed,
282 00:37:10.220 ⇒ 00:37:18.089 Pete: They send out the labels. They may be… It’s not a filter.
283 00:37:25.390 ⇒ 00:37:27.859 Pete: Let’s see if there’s another way to do this.
284 00:37:29.760 ⇒ 00:37:32.030 Pete: description handoff, it might be in here.
285 00:37:34.120 ⇒ 00:37:37.990 Pete: I believe it’s in here, so these would be the ones that are ready for the day.
286 00:37:38.150 ⇒ 00:37:45.580 Pete: They’d go find them in here, and they would transfer them this side to complete them. And then if it was shipping, it would generate a label.
287 00:37:46.110 ⇒ 00:37:53.160 Pete: I can even… do these. These would all be shipping.
288 00:37:53.700 ⇒ 00:37:56.850 Pete: Let me grab one a little further down.
289 00:38:01.460 ⇒ 00:38:08.860 Pete: This would, I believe, right here, print the manifest and the shipping label. But that’s the process there.
290 00:38:10.600 ⇒ 00:38:14.720 Pete: I think when you push…
291 00:38:14.720 ⇒ 00:38:18.170 Henry Zhao: Something label gets printed out just, like, right next to the workstation, right?
292 00:38:18.540 ⇒ 00:38:20.279 Pete: Correct, on a Zebra printer.
293 00:38:20.280 ⇒ 00:38:22.309 Henry Zhao: Okay, so then just put on the bag and then seal it.
294 00:38:22.620 ⇒ 00:38:35.169 Pete: That’s right. So then, well, not that quick, they kind of go back into their respective totes, and then get moved over to the shipping station, where the associates then pack them.
295 00:38:35.330 ⇒ 00:38:41.390 Pete: You know, with ice, if necessary, and then put them in a kangaroo pack, and… And…
296 00:38:41.940 ⇒ 00:38:57.179 Pete: put them, queue them up for the… for the… for the carrier to come pick them up. And so, essentially, that’s pretty much the process. That handoff, it looks a little bit different when it’s patient pickup, because then you’ll do just these ones.
297 00:38:58.430 ⇒ 00:39:09.489 Pete: You’ll find the drug, you’ll put it in here, a button will pop up to request a signature, they sign on a tablet, and then it goes, with the patient, leaves the pharmacy.
298 00:39:12.500 ⇒ 00:39:14.410 Pete: So that’s pretty much it.
299 00:39:14.740 ⇒ 00:39:20.269 Henry Zhao: Alright, thank you, let’s go over my questions now. We can just do it really quickly.
300 00:39:20.950 ⇒ 00:39:30.159 Henry Zhao: Yeah, I’m just gonna go through a list, and just ask you if we have this data in Pharmetica, just to go through. And if not, where I would be able to find it, okay?
301 00:39:30.690 ⇒ 00:39:31.310 Pete: Yep.
302 00:39:31.520 ⇒ 00:39:32.659 Henry Zhao: Okay, here we go.
303 00:39:34.730 ⇒ 00:39:35.820 Henry Zhao: Alright.
304 00:39:36.620 ⇒ 00:39:50.030 Henry Zhao: So I’ve gathered the list of all the things that we want to see from Rebecca, from you, from Josh, so I just want to make sure that we have all of these in Pharmetica. Alright, so the first thing we talked about last Friday was… you can see my screen, right?
305 00:39:51.590 ⇒ 00:39:57.539 Pete: that there’s a Google extension that comes from Pharmetica, but there’s no visibility in turnaround time.
306 00:39:57.560 ⇒ 00:40:04.379 Henry Zhao: So is turnaround time… in Pharmetica, or do we need to do something to add it there?
307 00:40:04.530 ⇒ 00:40:13.470 Pete: We probably need to add it based off of, like, how long the prescription has been in the system. So, for example, if it was received 5 days ago, what’s the holdup?
308 00:40:14.260 ⇒ 00:40:18.190 Henry Zhao: Can you… sorry, can you define turnaround time? It’s the time between…
309 00:40:18.720 ⇒ 00:40:21.040 Pete: Time between receipt and out the door.
310 00:40:21.630 ⇒ 00:40:28.870 Henry Zhao: Okay, do we have those two timestamps in Pharmetica? Because if we do, the API would give me those timestamps, and I could calculate it on my end.
311 00:40:29.200 ⇒ 00:40:35.979 Pete: The API would… would give you those for ones that left the door, so if we are looking for a metric on…
312 00:40:35.980 ⇒ 00:40:36.940 Henry Zhao: Oh, it’s fine.
313 00:40:37.650 ⇒ 00:40:38.590 Pete: Yeah.
314 00:40:39.750 ⇒ 00:40:40.250 Pete: So…
315 00:40:40.250 ⇒ 00:40:47.750 Henry Zhao: as the ones that left the door, because if there is no value for out the door, I would just take the current timestamp and subtract the time of receipt.
316 00:40:48.400 ⇒ 00:40:49.550 Henry Zhao: Yeah.
317 00:40:50.030 ⇒ 00:40:59.649 Pete: And that’s pretty much prob… I mean, we may want both metrics, like, we may want to see how long things took to get out the door, but then we may also want to know
318 00:41:00.990 ⇒ 00:41:06.710 Pete: You know, how long some are sitting there, and if that’s the case, we can call those two metrics two different things.
319 00:41:06.710 ⇒ 00:41:17.979 Henry Zhao: Yes, that’s fine. I just, right now need to know feasibility. After that, I can just figure it out. But right now, I’m just talking about feasibility, and getting that understanding from you, and also clarifying my understanding of things. Okay.
320 00:41:17.980 ⇒ 00:41:18.670 Pete: Okay.
321 00:41:18.670 ⇒ 00:41:25.990 Henry Zhao: So, micro-integration with Farm Market, that’s on me. Alright, so real-time status dashboard, RX count, obviously, that’s there, number of fills processed.
322 00:41:26.250 ⇒ 00:41:30.620 Henry Zhao: Processed do you mean by, like, what do you define as processed?
323 00:41:32.900 ⇒ 00:41:33.550 Henry Zhao: Pv2.
324 00:41:33.550 ⇒ 00:41:34.679 Pete: I’m looking for it.
325 00:41:35.990 ⇒ 00:41:44.960 Pete: I guess it’s… it’s the same thing as the RX count, honestly, so the number of…
326 00:41:45.180 ⇒ 00:41:50.489 Pete: No, number of fills processed are the ones that actually made it through the fill station.
327 00:41:50.930 ⇒ 00:42:05.029 Pete: So, yeah, they may be waiting for shipment, or something else, or they may be waiting for a patient to come pick them up, but at least we know how many we processed. Rx count can mean that, or it can also mean…
328 00:42:05.370 ⇒ 00:42:10.409 Pete: The number of prescriptions that left for the day.
329 00:42:10.600 ⇒ 00:42:16.470 Pete: So, we may need to redefine how we… what we call those metrics, but…
330 00:42:17.430 ⇒ 00:42:20.299 Henry Zhao: Do we have the timestamp of when it made it through the fill station?
331 00:42:20.300 ⇒ 00:42:27.870 Pete: Yes, everything at every point where something makes it through a workflow process, it’ll be timestamped.
332 00:42:27.870 ⇒ 00:42:31.410 Henry Zhao: Perfect. Shipped, obviously, we have, obviously, right?
333 00:42:31.410 ⇒ 00:42:32.080 Pete: Right.
334 00:42:32.650 ⇒ 00:42:34.820 Henry Zhao: This one, I’m not sure, so…
335 00:42:35.810 ⇒ 00:42:49.259 Pete: That one’s gonna be in the lab software. All those… all that data is in… so it’s a branch of Pharmetica, it’s just called, Pharmedica Lab, or something like that.
336 00:42:49.400 ⇒ 00:43:00.830 Pete: If you need to see information in here, I probably would have to get you with the lab manager, set up a meeting with her, but I know this data is in that portion of Pharmetica.
337 00:43:01.280 ⇒ 00:43:03.040 Henry Zhao: Okay, if I can’t figure this out.
338 00:43:05.130 ⇒ 00:43:12.719 Henry Zhao: Okay, and then I’ll look into this once I figure that part out. Shipping number, ship is completed. Do we know when the shipment is completed?
339 00:43:16.290 ⇒ 00:43:21.980 Pete: Yeah, you know what, I think I may have just been typing. This should be equivalent to the number of prescriptions shipped.
340 00:43:22.500 ⇒ 00:43:23.140 Henry Zhao: Okay.
341 00:43:23.330 ⇒ 00:43:24.569 Henry Zhao: I’ll just get rid of this one.
342 00:43:28.880 ⇒ 00:43:30.279 Pete: Okay.
343 00:43:30.360 ⇒ 00:43:37.979 Henry Zhao: So, revenue purposes of subscriber, we have prescriber, you just told me, but is revenue just the total sale price? Like, the…
344 00:43:38.960 ⇒ 00:43:39.980 Pete: Yes.
345 00:43:39.980 ⇒ 00:43:41.519 Henry Zhao: 49, if that’s what it is, right?
346 00:43:41.520 ⇒ 00:43:42.960 Pete: Correct. Okay.
347 00:43:43.810 ⇒ 00:43:45.350 Henry Zhao: And that’s in Pharmedica, obviously, right?
348 00:43:45.350 ⇒ 00:43:47.410 Pete: That should… yeah, that absolutely shouldn’t be.
349 00:43:50.800 ⇒ 00:43:53.770 Henry Zhao: thing as number 2, I already know we have it, obviously.
350 00:43:53.990 ⇒ 00:43:54.540 Pete: Yep.
351 00:43:54.540 ⇒ 00:43:56.279 Henry Zhao: Same as number 1.
352 00:43:56.690 ⇒ 00:43:58.450 Henry Zhao: Above and Pete’s.
353 00:43:58.990 ⇒ 00:44:02.269 Henry Zhao: Alright, prescribing habits, this one, obviously, I can calculate.
354 00:44:02.540 ⇒ 00:44:06.420 Henry Zhao: what is org pay versus patient pay clinics?
355 00:44:06.940 ⇒ 00:44:18.760 Pete: So, some clinics loop the price of their prescription into the patient’s visit at the clinic, and so they will have their
356 00:44:19.360 ⇒ 00:44:30.249 Pete: any of their patients’ prescriptions shipped to the clinic for dispensing to the patient, or even administration. So, some of them will actually inject the patient, so that they… that way they don’t have to. Those are the org pays.
357 00:44:30.250 ⇒ 00:44:31.769 Henry Zhao: Or clean. Okay, that makes sense.
358 00:44:31.980 ⇒ 00:44:38.579 Henry Zhao: So basically, they say the visit’s $500, part of that’s a visit, part of that’s the drug, and then they get the drug, they give it to the patient.
359 00:44:38.760 ⇒ 00:44:39.440 Pete: Correct.
360 00:44:39.730 ⇒ 00:44:43.549 Henry Zhao: Versus patient pays, patient pays for it, patient picks it up, patient administers.
361 00:44:47.040 ⇒ 00:44:54.950 Henry Zhao: Okay, so, I’m gonna extract all doctors I’ve prescribed in the last 90 days, percent change in the prescribing habits, new doctors, script counts… Do you know what script counts is?
362 00:44:55.270 ⇒ 00:44:58.150 Pete: It’s prescription counts, or RX counts, same thing.
363 00:44:58.550 ⇒ 00:44:59.269 Henry Zhao: Yeah, just…
364 00:45:03.350 ⇒ 00:45:07.929 Henry Zhao: Could… could the prescription get rejected, like…
365 00:45:08.060 ⇒ 00:45:18.209 Henry Zhao: if they… when we get all the prescriptions, we don’t fill all of them, right? Some of them could get rejected, some of them could not get accepted by the patient. Do those count in the Rx counts, or…
366 00:45:19.300 ⇒ 00:45:22.839 Henry Zhao: Do you want to look at just counts that are fulfilled, or just the ones coming in?
367 00:45:23.270 ⇒ 00:45:33.990 Pete: I think the most… the best information… well, we probably need both, honestly. We need their entire script count, but then we need, like, a fulfillment count out of that.
368 00:45:34.200 ⇒ 00:45:41.629 Pete: So basically ones that have actually been filled and picked up or shipped.
369 00:45:42.050 ⇒ 00:45:53.139 Pete: The reason I say that is because there’s value to knowing how many prescriptions the provider’s prescribing, but then there’s also value to know how many are coming or leaving
370 00:45:53.140 ⇒ 00:46:07.440 Pete: The pharmacy, because if the provider’s just writing a whole bunch, and we’re going through the effort of filling all of those, but then nobody’s getting them, or, you know, we’re going through the effort of data entering them, at least, that may be a provider that we need to follow up with.
371 00:46:11.190 ⇒ 00:46:15.870 Henry Zhao: My next question is, how do I know if revenue is eaten telehealth or non-telehealth?
372 00:46:16.230 ⇒ 00:46:20.999 Pete: There’s an indicator of what clinic it’s coming from in Pharmedica.
373 00:46:21.350 ⇒ 00:46:24.060 Henry Zhao: There’s an indicator of, which clinic…
374 00:46:24.060 ⇒ 00:46:25.370 Pete: Nick, yeah.
375 00:46:25.370 ⇒ 00:46:27.250 Henry Zhao: it’s… the RX is coming from.
376 00:46:27.250 ⇒ 00:46:28.200 Pete: Right.
377 00:46:28.200 ⇒ 00:46:29.459 Henry Zhao: Which tells me… Just like…
378 00:46:30.660 ⇒ 00:46:35.279 Pete: That should tell you who it is. So, like, we have a clinic that is literally named Eden Telehealth.
379 00:46:35.560 ⇒ 00:46:38.910 Henry Zhao: Oh, okay. So, telehealth is just all Eden Telehealth.
380 00:46:39.200 ⇒ 00:46:40.130 Pete: Right.
381 00:46:40.890 ⇒ 00:46:41.480 Henry Zhao: That’s it.
382 00:46:41.830 ⇒ 00:46:42.960 Pete: That’s it.
383 00:46:42.960 ⇒ 00:46:44.230 Henry Zhao: Everything else is non-ET.
384 00:46:44.680 ⇒ 00:46:47.790 Pete: Other than Eden Health Clinic, but yes.
385 00:46:47.990 ⇒ 00:46:48.670 Henry Zhao: Okay.
386 00:46:49.410 ⇒ 00:46:51.060 Henry Zhao: You didn’t tell the health clinic, right?
387 00:46:51.240 ⇒ 00:46:51.890 Pete: Right.
388 00:46:52.040 ⇒ 00:46:55.369 Henry Zhao: So there’s Eden Telehealth Clinic, that’s telehealth, everything else is non-ET.
389 00:46:55.530 ⇒ 00:46:56.230 Pete: Right.
390 00:46:56.680 ⇒ 00:46:58.029 Henry Zhao: Okay, so that I have.
391 00:46:58.220 ⇒ 00:47:06.119 Henry Zhao: new doctors… that would just be the… the entrance… the entry of prescribers in Pharmedica, right?
392 00:47:06.430 ⇒ 00:47:07.030 Pete: That’s right.
393 00:47:07.760 ⇒ 00:47:12.150 Henry Zhao: So, entering in… a new prescriber.
394 00:47:12.380 ⇒ 00:47:14.170 Henry Zhao: In Pharmetica. And then.
395 00:47:14.170 ⇒ 00:47:14.710 Pete: Great.
396 00:47:14.710 ⇒ 00:47:18.270 Henry Zhao: Do you know if Pharmedica logs a timestamp of when the prescriber was entered in?
397 00:47:18.710 ⇒ 00:47:19.360 Pete: Yes.
398 00:47:20.030 ⇒ 00:47:22.140 Henry Zhao: Because then I can pull in new doctors by a quarter.
399 00:47:22.320 ⇒ 00:47:27.009 Henry Zhao: Existing doctors… React… oh, doctor’s reactivation…
400 00:47:28.190 ⇒ 00:47:30.850 Henry Zhao: How would I know old doctor’s reactivation? .
401 00:47:31.510 ⇒ 00:47:33.210 Henry Zhao: prescribers in Pharmedica?
402 00:47:33.420 ⇒ 00:47:48.580 Pete: I think it’s… we don’t deactivate the clinics or prescribers, but what would happen is we would see a new prescription in, like, within a time parameter. So, like, a new prescription in 90 days or 6 months or something, where maybe they fell off before.
403 00:47:48.580 ⇒ 00:47:55.819 Pete: I do believe Pharmetica has reports around most of this stuff, so if it has reports, there’s definitely data there to pull.
404 00:47:56.540 ⇒ 00:48:01.200 Henry Zhao: Okay, I just need to later figure out the definition with you guys. Alright, so Sierra and I need to look at…
405 00:48:02.390 ⇒ 00:48:04.710 Henry Zhao: Look at micro-integration.
406 00:48:07.580 ⇒ 00:48:16.559 Henry Zhao: Playboy Contribution, marketing expansion, marketing… Okay, do we have, anywhere, like, the email increase we get?
407 00:48:18.460 ⇒ 00:48:23.199 Pete: Mmm… I have a mailbox.
408 00:48:23.560 ⇒ 00:48:35.600 Pete: that… it’s a Google group, really, and we could see, how many, you know, emails are pinging there. I don’t know how that integration would work.
409 00:48:35.920 ⇒ 00:48:36.990 Henry Zhao: But… hmm.
410 00:48:37.710 ⇒ 00:48:38.510 Henry Zhao: to Gmail?
411 00:48:39.010 ⇒ 00:48:43.639 Pete: Yeah, it’s… it’s essentially a Google… a Google, platform.
412 00:48:43.820 ⇒ 00:48:47.490 Pete: It’s coming through a group, but it functions the same way as Gmail.
413 00:48:49.360 ⇒ 00:48:50.600 Henry Zhao: Okay, I’ll have to look into that.
414 00:48:50.820 ⇒ 00:48:59.350 Henry Zhao: This one we can just analyze elsewhere. Gm list revenue at any given point, reset score, assumption count,
415 00:48:59.460 ⇒ 00:49:02.729 Henry Zhao: GM’s general manager… oh, is it gross margin or general manager?
416 00:49:03.480 ⇒ 00:49:11.400 Pete: Gross margin, probably. Well, no, I think Rebecca was, like, writing this out, so she’s the GM, so this is probably for her.
417 00:49:11.400 ⇒ 00:49:16.980 Henry Zhao: Oh, okay, revenue at any given point. Prescription count, we already have this. Top selling drugs and their respective revenue.
418 00:49:18.020 ⇒ 00:49:22.089 Henry Zhao: In Pharmedica, do we have drugs categorized?
419 00:49:24.220 ⇒ 00:49:30.230 Pete: We have them categorized, but they’re, they’re also, sortable based off of volume.
420 00:49:30.480 ⇒ 00:49:31.440 Pete: So…
421 00:49:31.870 ⇒ 00:49:40.560 Pete: The data exists on, like, how much a prescription drug… prescription gets… sorry, how much a drug gets prescribed.
422 00:49:41.000 ⇒ 00:49:43.379 Pete: How often? So that’s… that’s available.
423 00:49:44.260 ⇒ 00:49:45.610 Henry Zhao: Okay, so…
424 00:49:46.030 ⇒ 00:49:56.350 Henry Zhao: Because I wouldn’t need to, like, combine, like, the 25 milligram and the 50mg and the 100mg and the refill and all that stuff together, right? Just to see the top-selling drugs.
425 00:49:56.680 ⇒ 00:50:02.609 Pete: Right, you would not need to combine all of that. It could be… it’s already broken out, so…
426 00:50:03.650 ⇒ 00:50:07.510 Henry Zhao: And how would I figure out gross margin? Do you have…
427 00:50:08.030 ⇒ 00:50:12.279 Pete: It would just be a formula based off of a calculation. I could…
428 00:50:12.450 ⇒ 00:50:19.900 Pete: Grab it for you here real quick. Not… well, Pharmetica may have a gross margin. Let me… let me look at the reporting.
429 00:50:19.900 ⇒ 00:50:21.479 Henry Zhao: Or at least the pieces so that we can calculate it.
430 00:50:21.660 ⇒ 00:50:24.849 Pete: Yeah, I can get the formula, that’s not a problem.
431 00:50:25.470 ⇒ 00:50:29.890 Henry Zhao: Let’s just figure out that we have all this. So do we have… so we have revenue, but do we have cost of goods sold?
432 00:50:29.890 ⇒ 00:50:41.039 Pete: Yes. Yes, for what… for what is accurate. That accuracy is on me to start to build out. It was a legacy issue from when the pharmacy was bought, so…
433 00:50:41.410 ⇒ 00:50:41.980 Henry Zhao: Huh.
434 00:50:47.440 ⇒ 00:50:49.300 Henry Zhao: Almost there, almost there.
435 00:50:50.120 ⇒ 00:50:55.899 Henry Zhao: Alright, we need to record number of manual processes improve our quarter. Okay, this one we could talk about later.
436 00:50:59.520 ⇒ 00:51:02.320 Henry Zhao: This stuff I probably will talk about later, but,
437 00:51:02.450 ⇒ 00:51:06.229 Henry Zhao: Vial size we should have, right? Medication instructions you showed me we do have.
438 00:51:08.280 ⇒ 00:51:11.669 Henry Zhao: I’ll talk to you about this stuff later,
439 00:51:12.650 ⇒ 00:51:17.460 Henry Zhao: How would we know some of this other stuff? Would any of this stuff we know within Pharmetica?
440 00:51:18.150 ⇒ 00:51:22.050 Pete: Staff retention… no. Team size…
441 00:51:22.050 ⇒ 00:51:22.970 Henry Zhao: That action, I know.
442 00:51:23.410 ⇒ 00:51:24.530 Pete: Yeah, this is all outside.
443 00:51:24.880 ⇒ 00:51:27.490 Pete: LabQA score…
444 00:51:27.970 ⇒ 00:51:39.690 Pete: I don’t know what that QA score is… I don’t know what the variables for the QA score, adverse event rate, that would… we could track that based off of, like, a Google form.
445 00:51:42.260 ⇒ 00:51:51.460 Pete: which is how we’re gonna start dealing with adverse events and complaints, is some sort of form, either through Zendesk or…
446 00:51:51.910 ⇒ 00:51:54.220 Pete: you know, on a simple and a Google form.
447 00:51:55.170 ⇒ 00:52:07.690 Pete: But we’re not there yet. Order fulfillment accuracy, I guess that would… could be in Pharmetica, based off of how often things go back to…
448 00:52:08.430 ⇒ 00:52:15.840 Pete: to the fill station for correction, or… but the other part of it is going to be…
449 00:52:16.090 ⇒ 00:52:23.100 Pete: things that a patient actually receives, so errors that actually make it out the door, I don’t know how we track that.
450 00:52:26.040 ⇒ 00:52:32.959 Pete: So, internal errors that are near misses, we can definitely track by some sort of stamp in Pharmedica.
451 00:52:36.470 ⇒ 00:52:42.709 Henry Zhao: operations… Turnaround time, 2 business days. Yeah, so we have turnaround time.
452 00:52:42.820 ⇒ 00:52:46.139 Henry Zhao: And then refund rate, I’m sure. Are refunds in Pharmedica?
453 00:52:46.540 ⇒ 00:52:47.400 Pete: Yes.
454 00:52:49.570 ⇒ 00:52:58.499 Henry Zhao: Okay, so I will now work on the list of what I need from Formetica based on this list, and who needs it, and then we can take it from there.
455 00:52:59.270 ⇒ 00:53:00.360 Pete: Sounds good.
456 00:53:00.360 ⇒ 00:53:01.729 Henry Zhao: Alright, thanks, Pete, this has been really helpful.
457 00:53:01.730 ⇒ 00:53:03.300 Pete: Of course.
458 00:53:03.450 ⇒ 00:53:04.150 Henry Zhao: Take care.
459 00:53:04.320 ⇒ 00:53:04.960 Pete: Take care.
460 00:53:04.960 ⇒ 00:53:05.530 Henry Zhao: Alright.