Podcasts

AH064 - Empowering Plan Sponsors: Data Access & Analysis, with Bridget Mulvenna

May 2, 2025

Capital Rx

This episode of the Astonishing Healthcare podcast, Bridget Mulvenna joins us in the studio again for an insightful discussion about addressing data access hurdles and utilizing pharmacy claims data. Building on her previous episodes, we dig into the "how" here - how can plan sponsors get their data, analyze it, and use it to make more informed decisions. It's encouraging that things are getting a little better out there, but data transparency and sharing remain top concerns for channel partners and plan fiduciaries alike; everyone is trying to understand what's driving costs higher within their plans (aside from GLP-1s, of course)!

What data do you need? Who can/should do the analysis? What do contract definitions have to do with this? We cover it all, offering practical suggestions to hold partners accountable based on Bridget's experience. Listen below or on Apple, Spotify, or YouTube Music!

Transcript

Lightly edited for clarity.

[00:27] Justin Venneri: Hello, and thank you for listening to another episode of Astonishing Healthcare. This is Justin Venneri, your host and senior director of communications at Capital Rx. And Bridget Malvena is back in the studio with me because of all the recent talk about data and access to data, and that got her thinking about her past experience, and that got us talking, and here we are. So we're going to try and help clients, other plan sponsors, and our channel partners think through how we can help people get their data, and then once they have it, how to use it, making sure you have what you need. That's the topic for today.  

Also, Bridget recently presented a first swing at this at the North Carolina Business Coalition on Health Spring Forum. And it was really neat to see what resonated with the audience firsthand. I don't think there was anyone who didn't nod along at some point, chuckle, or sort of sit back and say, I've been saying that for years, as one of the audience members that was sitting near me did. And I was like, okay, this is a good podcast episode. So, Bridget, I'm glad you were up for joining me again.

[01:24] Bridget Mulvenna: Always a pleasure to be here, Justin.

[01:26] Justin Venneri: Thank you. So this is kind of like a mini series with you now. We're summarizing different aspects of your experience running pharmacy programs and being the benefits director at your previous employer. Episode 53 was an update of sorts to Episode 2. I can't believe that was over a year ago. We talked about your experience selling PBM solutions to plan sponsors, and then on episode 21, that. That was a fun discussion about GLP-1s and how to try to tackle that. Pretty big line item and fundamental quandary for most plan sponsors.

[01:57] Bridget Mulvenna: Yeah, I mean, that's still a huge challenge. In almost every conversation that I have with plan sponsors, finalist meetings, direct prospect meetings; the top two topics now are fiduciary duty and GLP-1s. Because stemming that GLP-1 spend, it's an important thing for plan sponsors to consider. But then, fiduciary duty, they're like, “Am I going to get sued?” So that's why this data talk is timely and hopefully helpful.

Related Content (Rx Data)

[02:25] Justin Venneri: Awesome. So that's a nice transition to the first actual question I have for you. Is data access getting better? I think with all the scrutiny of the traditional PBM model and the focus on fiduciary responsibility reform initiatives… that would help, right?

[02:39] Bridget Mulvenna: It is helping some. And so the short answer is yes. Specifically for self-funded plan sponsors. If you're fully insured, good luck to getting your data, and there's still fiduciary duty there, right? And so it's about figuring out what the right balance is and communicating with your TPA and your insurer. But for self-funded plan sponsors, it is getting better. The CAA has helped to clarify for people in the benefits space something that they didn't really understand before, which is that that PBM claims data, even medical claims data, not only is the property of belongs to the plan sponsor, but it is also the responsibility of the plan sponsor to obtain, analyze and use that data. Which is what we'll talk about a little bit today.

[03:28] Justin Venneri: Definitely. Our episode with Spencer Kramer – AH062 – was hopefully helpful for people out there on just the process and making sure that that RxDC submission happens on time and is as painless as possible. So I think these, these topics all tie together nicely. So, whether by luck or a little bit of solid planning, I think we're trying to get some things done here with this podcast.

So, what sorts of questions should plan sponsors be asking or thinking about relating to getting their data?

[03:54] Bridget Mulvenna: Okay, I'm probably going to rattle off a bit of a laundry list here.

[03:58] Justin Venneri: Sounds good.

[03:59] Bridget Mulvenna: One of the first things that people need to be thinking about is: “How am I supposed to honor my fiduciary duty without access to the information that will help me make faster and better decisions on behalf of the members?” Because that's really what it's all about. I think another question that was asked – obviously when I was doing this work from a pharmacy benefits management and data analytics perspective, is we can't get that data because of HIPAA. And I was like, wait, wait, wait, no, that's not true. So, does HIPAA prevent you from getting access to an appropriate data set that would serve your fiduciary needs? I will definitively say the answer to that is no. Stop worrying about HIPAA. You have a right to know, you have a need to know, and in these cases, you are a covered entity and you need to know.

Another important thing, and a lot of plan sponsors, I'm seeing this more and more, especially in larger employers, are engaging internal expertise, which is great, but smaller groups or groups that haven't done that yet. The big question is: “Do I need to engage outside service providers to analyze the data?” If you don't have internal in-house expertise, the answer to that is absolutely yes. You need a pharmacy consultant; you need a pharmacy actuary. You need someone with expertise in analyzing pharmacy data to help you with this. And we'll talk a little bit later about why pharmacy data is different than other data sets.

You know, the other thing that people ask is: “Do I need to purchase a pricing reference service to analyze data access to Wolters Kluwer. If you ask ChatGPT how much the average cost to access Wolters Kluwer is so that you can get access to Medi-Span, it doesn't know the answer. So it's not available. It's not like to a menu like going to a restaurant, and here's all your menu options, and you know the steak is $52 and the fish is $35, right? There's not even transparency, and how much it would cost you to get there. So you literally need to call, negotiate with them. Trust me, when I did it, it was protracted negotiation and a lot of arm wrestling and me just saying, “Okay, I'm not going to do it…” until they would come down on price. So just be mindful of that. So you will need a pricing reference service unless you're with Capital Rx, and then you can just go find it publicly under NADAC pricing on Medicaid.gov. So, there are PBMs where you don't need to do that, but for the bulk of the PBMs out there, you need a pricing reference [service].

[06:14] Justin Venneri: And just a quick question on that because it sounds like that's, you know, added cost, added time. And then I had a quick question on just the type of skills that someone would need to be helpful and analyze. Is it just someone on your team with crazy good Excel skills, or are we talking much more advanced database-like analytics running queries, you know, comparing and contrasting, you know, the NDC and the price like the units like. I know we'll get into some of this later in the discussion, but I'm just wondering about the type of person that might be good to help from an internal perspective at a plan.

[06:44] Bridget Mulvenna: So if you're looking at pharmacy data, specifically someone who understands the nuances of pharmacy and how pharmacies dispense drugs and the differences between the way different pharmacies identify units of measure and things like that. And this is deep supply chain stuff, so a deep understanding of the pharmacy industry is part of the picture. To answer your question about Excel skills, I would say that I was very successful in doing this. And I have better-than-average Excel skills. It's not like… I'm not “expert level.” You really need to know how to do a VLOOKUP, indexing, and matching… writing if-then scenarios. And I'll make a little joke here. Everybody that joked that you'll never use calculus again or algebra after you graduate high school is wrong. You absolutely do writing Excel formulas.

[07:34] Justin Venneri: Okay. And then. So sorry to interrupt you. You were kind of rolling there. Any other questions people should think about?

[07:40] Bridget Mulvenna: I think another one is: “What do I do if my vendor does not provide me with my data?” And that's a really big one, right? And so there are going to be situations where your consultant, if you're working with a pharmacy consultant or a health and welfare benefits consultant, can really drive that for leverage language in the contract to help you get it. But in my experience, there's a lot of gamesmanship there. So when I requested data sets, I worked with a consultant, I went directly to the PBM. I got two different things, I had to push back multiple times. The first data set I got in order to analyze my pharmacy data didn't contain NDC's (national drug codes). And there's no, you can't price drugs based on the name of the drug.  

You have to have the NDC because there could be 50 different NDCs for any given drug based on how long it's been generic, the number of manufacturers, just a million different factors. So what if my vendor won't provide me with my data? My advice here is push and then push harder and then keep pushing and keep asking for more elements until you get what you need. It can be a long, protracted process. In 2016, it took me six months, starting and asking once, twice, three times a week to get a full data set. That was actually something that I could analyze.

[09:02] Justin Venneri: I mean, there are, there are lawsuits over this now, right? And I know Jeff Hogan suggested on his episode. I think he was the first one to say, you know what if somebody's not going to give you the data, just say, we're going to RFP. Doesn't matter, we're done.

[09:14] Bridget Mulvenna: But even in RFP – I had a conversation with a consultant yesterday. A prospect that I'm working with is with a very large PBM, you know, one of the Big 3. And he goes, “I am very frustrated because I wanted to release this a month ago.” But even during an RFP process, consultants are struggling to get adequate data sets. And so the gamesmanship is still there. It's up to plan sponsors, consultants, folks like me, folks like you out there being vocal, talking about this, and plan sponsors getting really, really direct with their partners and saying if you don't help me, you won't be my partner anymore.

[09:51] Justin Venneri: Yeah.

[09:52] Bridget Mulvenna: And you have to be hard. I used to be very soft when I was younger. After spending 10 years negotiating contracts in the supply chain, I got really hard. Because you learn that you only get what you push for.

[10:05] Justin Venneri: I don't think we can get to the true full picture. And to get to the answers and the full analysis that plan sponsors need. If only one side of the equation has the data right.

[10:14] Bridget Mulvenna: Exactly. That's the most important question: “Can transparency exist if the entity that controls the data and produces the data is the only one that has access to it?” And I'm going to flat out say no, the answer is no. No. Real transparency doesn't exist in that scenario.

[10:31] Justin Venneri: So the data that plan sponsors need, I know there's a lot, probably 20 plus different fields and we don't have a full hour to talk about each data point and what it is and what are like the top say handful of data points or data fields that a plan sponsor needs to be able to do a decent job analyzing the data. And then we'll get into some nice-to-haves too.

[10:52] Bridget Mulvenna: Yeah, absolutely. So the first thing I'll say is you need a full de-aggregated claims data set; so you don't need by NDC how many times Humira was dispensed. You need every single individual claim listed out with National Drug Codes, who the physician was, what pharmacy dispensed it. A unique patient identifier. That's the only way we can identify any type of disruption. How many pills were dispensed, or how many milliliters or units were dispensed. What was the cost? The total cost of the drug, not just what the plan paid. What was the total cost, including dispensing fee, any administration fees, the members share and all of that stuff.  

Those are really need to have things because that's the core information that you need in order to conduct an actual analysis of any type of cost. There are a bunch of nice to have things, but we're going to write a very long, hopefully not too boring article or eBook that will really detail for folks what they need to do here and then dig into some of the nuances of the data because you know there's a fair amount of parsing of data that needs to happen. If you understand the pharmacy supply chain.

[12:07] Justin Venneri: Got it. And manufacturer revenue; rebates included in manufacturer revenue. Can you spend a moment on that? Because I know it's become a hotter topic and more important lately. As it turns out, there are more forms of manufacturer revenue than just rebates. And all of those should pass through to the employer.

[12:23] Bridget Mulvenna: They absolutely should. Now, for the most part, they don't. With the big three and obviously PBMs that don't behave in a fully transparent fashion, I know for certain that CapitalRx provides NDC9 level reporting on rebates. I think that I've heard in the industry that there may be one other provider that will provide those rebates at an NDC level. I don't have that validated. It's not verified. Other than that, getting that data is like getting into Fort Knox. It's virtually impossible to get a full report of what rebates were paid. And the reason for that is probably obvious, but very simple. The PBMs are benefiting from retaining that pharma, that manufacturer revenue. And because they're retaining revenue and they're also telling you they're passing through a guarantee, they're technically not wanting to share that because they're not in full compliance with their contract with you. And so I think it's very important for plan sponsors to understand if you can get it, get it and use it. And what you will achieve is visibility into what your true net costs are, which at the end of the day is all that matters.

Related Content (Pharmaceutical Rebates, Pass-Through PBM Model)

[13:32] Justin Venneri: So, assuming you get your data, you understand what drugs are being dispensed to the members, you understand how much of the medication is being utilized over time, what do you do with that data? You can see everything. You have all the data in front of you. What do you do with it? How did you approach figuring out how to use it?

[13:49] Bridget Mulvenna: Well, first thing I did was I broke it out into a very detailed, very nerdy Excel-based answer. So maybe I'll try to distill it down. The reality is, is that you need to have someone, either in-house or externally, with the expertise to understand the supply chain and parse out that data in a way that makes sense. You can't look at generics and brand in the same bucket. You can't look at tablets and capsules in the same bucket that you look at creams and ointments or injectables. So that's important. And being able to parse that data so that you can get it into a format that you then can start to analyze it, and then having that comparison. And I mentioned VLOOKUP comparing the data between spreadsheets, pulling in the cost basis, and then getting it down to the lowest possible unit of measure, and then expanding it out.

And then what I did was I reverse-engineered what the actual AWP formula was for every claim at every claim level. So I understood what I was paying at the per-claim level. Now, large PBM contracts, non-transparent contracts, are not reconciled at the claim level; they're reconciled in the aggregate. So you may have an aggregate rate of say AWP minus 75, but a fair amount of your claims are going to be at AWP minus 20, and some are going to be at AWP minus 95, and you're going to spread the gamut in between. And so you have to understand how to analyze that and then how to hold your PBM accountable with the actual aggregate rate, even though they may have met their contractual guarantees, and then figure out any over or underperformance so that you can go back and say, look, if they overperform, great, you don't have to go back and ask them for money.

But when they underperform, there should be contractual guarantees that enable you to go back and say, you owe me a couple hundred thousand dollars here, and then fight to get that through the proof that's there in the data. But the other thing that you do with it is what I did was I collected over a number of years, I started analyzing data for my former employer in 2017. I had them send data back to 2015. And then over a number of years, I was able to analyze that data set every single year, do an audit, analyze the data, figure out what was going on, and then also start to identify prescribing trends, watching member counts going up, watching the per member per month costs going up, watching utilization shifts, Seeing there was the Harvoni experience where we had a couple of years blip where we had dozens of employees that were getting this really, really expensive drug and then watching it just sort of go away as those conditions were cured. So maybe that was a good thing, right?  

And just kind of going through that trend, the most important trend, and I'll never forget sitting in front of the committee and talking about this was I came to them, I had been looking at utilization over a period of years. And in 2021 I was like, guys, something weird is happening here. Because we had seen for years Trulicity utilization creep up. And then all of a sudden in 2021, it starts dropping off the cliff, and Ozempic data utilization starts crossing the line. And then as 2022 came in and I stayed there until the end of 2023 when I started here. As 2022 utilization came in, you started to see even more creep. So Trulicity dropped even more. And then Mounjaro started to join Ozempic up the climb. And so I think that being able to read the story of your data gives you the ability to say, “I've got trend issues and there are other things that I can control.” Right? I can put things in place to control these trend issues. I can employ point solutions, I can change coverage options, I can adjust co pays, I can employ a new copay maximizer program so it enables you to understand what's happening with your data and the levers you need to pull so that you can make those necessary adjustments and keep your plan spend from running out of control.  

Because the thing is, is that what plan sponsors can never do is fully prevent disease. You're always going to get people with new cases of cancer, people who with new cases of type 2 diabetes. Your population is going to age, and as they age, they're going to get sicker. And it is our job to look at the trends so that we can pivot and be nimble and make changes that will continue to support the wellness of those members and the health and the well-being, but also support the financial and fiduciary goals of the plan.

[18:32] Justin Venneri: Makes sense. Okay. And then you've touched on this twice already, but the contract, that's another layer of this. And I don't want to get into like a crazy deep contractual discussion, but whether it's, you know, the way rebates might be defined or the expertise needed to evaluate the contract, because that dictates the terms and the guarantees and such. What would you suggest to plan sponsors regarding kind of their, their contracts, their PBMs, and holding the PBM as accountable as they possibly can?

[19:00] Bridget Mulvenna: Well, first I would say, “Do you know where your contract is?”

[19:04] Justin Venneri: Really? Is that true?

[19:05] Bridget Mulvenna: Yeah, absolutely. And, “Do you know what it says?” I can't tell you how many times in my career working with contract and negotiations and legal departments that, that some teams haven't looked at their contract since it was signed. It's not just my opinion. This is, this is reality. Your contract with your PBM or any other entity that you're contracted with is your source of truth. And so you have to be able to a know where it is, have looked at it in a while, understand what are my guarantees, what type of performance metrics are guaranteed in my contract? Is the PBM, and we're talking about PBM here. Is my partner doing what they said they were going to do contractually? Can they prove it, and is it visible to us? So there's that.  

What are the definitions? Are the definitions in the contract mutually favorable, meaning they favor both parties, which is what a good contract does, or are they more favorable to the PBM? And the way that some PBMs define generic drugs or brand drugs or specialty drugs to me is leading to more opacity in this industry, and it's not really providing the clarity that a contract should provide. And then make sure you've got someone on your team, whether it's someone in legal who has PBM contract expertise. I had to go to an outside counsel at my last job. We had lots of great experts and wonderful lawyers at my last company, but none of them had PBM expertise because they had never fully carved out and never gone with a standalone vendor. And so they depended on their consultants.

So if you don't have the in-house expertise, make sure you have a consultant you trust or hire outside counsel. There are plenty of compliance organizations that are helping PBM clients with this. And then understand what you are owed. Are you supposed to have X number of visits with your account manager? Are you supposed to have 30-second average speed of answer rate in your contract? You know, think about the things that are guaranteed and make sure you're getting what you are owed in a contract. If you're not, push back and hold them accountable. Accountability and contracts live in the same space. And at the end of the day, the goal is to ultimately understand not the aggregate rate. The aggregate rate is not mutually favorable. That is a bad contract. You need a per-claim rate so that you understand what you're paying at the per-claim level. If you can't get that, then you are, in my opinion, almost guaranteed to be paying too much for drugs.

[21:37] Justin Venneri: What's the best advice you can give everyone right now in 2025 as it relates to this topic?

[21:43] Bridget Mulvenna: Of course, I was about to say that's a long list. Once you have your data, use it. There is no point in collecting and getting your data together and analyzing all of the data if you're not going to use it. Again, if you don't have that in-house expertise, hire somebody that can help you use it because data uncollected and unused is worthless.

And don't just get stuck in that mindset that “well, you know, the data just tells a story about the past.” I think that we can all agree as especially as we get older. The past is not something we can go back and change. But studying the past allows us to make better decisions in the future. And that really is what data should do. So just make sure you're doing that. And then once you get the data, once you understand your contract, and once you've had this analysis performed, stand firm and hold your partner accountable.

[22:37] Justin Venneri: Okay, last question. What is the most astonishing thing that you've seen related to plan sponsors getting and using their data?

[22:45] Bridget Mulvenna: How difficult it is. It is astonishing to me that even today, in 2025. The CAA was passed in 2021, so we're four years into this. It was meant to provide transparency. Unfortunately, getting your CAA reports isn't enough, right? You have to understand that those are machine-readable files, and you're not going to be able to really understand everything they say. But the fact that even with legislation, even with all of this focus in Congress and states about PBM transparency and railing against drug pricing and all of that is that today, in 2025, standing in that room at the North Carolina Business Coalition on Health, five out of every seven people said to me that they are struggling to get their data from their PBM. And that is unacceptable.

[23:36] Justin Venneri: Yeah, it's not. Well, Bridget, thank you so much for taking the time today. Always enjoy having you in the studio and chatting about what you're dealing with out there in the field, and hope you have a great rest of the day, and look forward to having you back on.

[23:47] Bridget Mulvenna: Thanks, Justin. Talk soon.

If you would like to learn more about Capital Rx’s full-service benefit administration solutions, including our clinical programs, CLICK HERE to get in touch with our team.

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