Fixing the Systems Professionals Depend On–The Hidden Operational Drivers of Hospital Financial Performance [PODCAST]

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Fixing the Systems Professionals Depend On–The Hidden Operational Drivers of Hospital Financial Performance

In this episode, John D’Alesandro, Founder at Amplefi OPS, discusses fixing the systems professionals depend on the hidden operational drivers of hospital financial performance.

Highlights of this episode include:

• Why hospitals invest heavily in technology but still struggle with coordination problems
• How small operational delays can translate into longer length of stay and reduce capacity
• The financial impact of everyday coordination breakdowns that happen inside hospitals
• How operational improvements can increase capacity without adding beds or staff
• Why metrics like length of stay do not explain the operational causes behind delays
• The connection between operational systems and clinician burnout
• Operational blind spots hospital finance leaders should watch for in the coming years

Kelly Wisness: Hi, this is Kelly Wisness. Welcome back to the award-winning Hospital Finance Podcast.  We’re pleased to welcome John D’Alesandro. John is a former manufacturing engineer who has spent more than 25 years working inside hospitals, helping teams remove operational friction and improve how care moves across departments. Before healthcare, he worked in strategy and systems roles with organizations including General Motors, Alkan Aluminum, and Cap Gemini, gaining exposure to operations across multiple industries. Today, he helps hospital teams identify the coordination breakdowns, delays, and missed signals that quietly affect capacity, staff burnout, and financial performance.

In this episode, we’re discussing fixing the systems professionals depend on the hidden operational drivers of hospital financial performance. Welcome, and thank you for joining us, John.

John D’Alesandro: Thanks for having me.

Kelly: Well, let’s go ahead and jump in today. So, John, why do hospitals invest heavily in technology, but still struggle with coordination problems that affect financial performance?

John: Well, I think the biggest problem with big technology is that it’s designed for someone else. And what hospitals do is they invest in the platform and then get into a change management thing. They start trying to fix how they use the system rather than how they practice medicine. That makes sense. They try to get people into compliance to the new way of doing things. And there’s always friction with that. On top of it, the technology isn’t always very reliable. That’s just inherent to any kind of big system. So, what you get is you get workarounds. And those workarounds are the seed cord for just about everything that is wrong with a hospital. Things slipped through the cracks, people get frustrated, and you start getting new problems that you didn’t have. And some of the audience might be thinking, well, gee whiz, that isn’t true at my place. Well, the fact of the matter is, is that these things are hidden. We can’t see them. But those workarounds, they’re sinister. That’s what starts the errors, the mistakes, the slip through the cracks. When somebody calls and complains that they waited for four hours for something that should have taken 10 minutes, it gets blown off as no big whoop. Well, it is a big whoop because those things start to accumulate. It impacts the culture. And unless you work for a hospital that isn’t currently struggling with clinical burnout or even staff retention, which is the number one issue on everyone’s radar screen, we might want to consider that what we’re doing is we’re forcing technology onto the frontline staff and just adding to their load. And I heard a phrase. It’s called I’m nursing the system or that I’m nursing the patient. And that is really why these technology projects look good on paper, sound good, but don’t really deliver the real benefit, which is smooth, seamless operation where patients come in, they get the care they want, and they go home.

Kelly: So, John, how do small operational delays translate into longer length of stay and reduce capacity?

John: When it comes to capacity, what we’ve discovered during the pandemic is we have no idea what our capacity is. The word was we needed more ventilators. Well, okay. So General Motors started making ventilators. And what happened? Well, the same thing that happened when we sent the big white boat to all the cities. It lied dormant. The issue isn’t how many beds we have, how many ventilators we have. The issue is how many nurses do we have? Because on a ventilator, you need one-on-one ratio. And you can put all the ventilators you want, but you can’t find the nurses. So we need to focus on what we’re doing to nurses.

This is almost like the laws of physics, first principles. We have to have nurses attentive and able to handle things. But what are we doing with the nurses? We are putting them into constant crisis. Somebody shows up unexpectedly. Somebody stays unexpectedly. Why is it unexpected? Well, because the handoff didn’t work. So, we give people problems to solve that they didn’t have to solve to take care of the patients. They had to solve because we haven’t engineered the processes correctly. We just tried to automate them without really considering. An example might be having a nurse doing barcode bed administration, okay? So, she is supposed to scan the bed, scan the bed, scan this, scan that.

Well, guess what? Sometimes the scan doesn’t work. Sometimes the label’s messed up, and she can’t get the scan to work. So now she’s in a place where she has to figure out how to get the barcode scanner to work rather than how to get the patient to have the med. And because of that, her capacity to do work starts to shrink. And she creates, and I should say she likes that, but she creates an environment where now she’s late. She’s giving vancomycin. Well, that’s time sensitive. But what’s going to happen now? If she doesn’t have that thing on board, she’s got to solve that.

And the only reason why she didn’t solve it on time is because the technology failed her. And that’s bothering her. So that’s in her head. So, when you start to think about staffing and delays and overwhelmed and sick of it and going home and complaining about her job, it’s all tied to the fact that we haven’t really precisely engineered the process to fit the technology that seemed like a no-brainer. So those CFOs out there are listening greenlighted the project as a financial executive to introduce this technology that was supposed to make the patients safer. But instead, what they have is a technical problem to solve. And we don’t have money for this. We don’t have time for it. Just do it. If you think of all the reasons why that didn’t work out, it’s all future work that has no value. It is robbing the hospitals of capacity. So, we really need to do a better job of bringing the technologies and the process change that’s very common in today’s world. Bring those things to life in hospitals that are constantly adapting to what’s happening to them every day. So I hope that doesn’t sound like a difficult thing to comprehend, but the bottom line is we have to do a much better job of integrating the technologies into the way the process works so that the process delivers without robbing the hospital of the nursing time and the cognitive load of all our clinicians.

Kelly: That makes a ton of sense, John. I know we were just talking about technology. And it’s great when it works, not so much when it doesn’t.

John: That’s right.

Kelly: Can you tell us about the financial impact of everyday coordination breakdowns that happen inside hospitals?

John: Sure. Let me tell you a real story that is extreme, but I think everybody can understand. I have a children’s hospital, a client who has invested nine figures in Cerner. But the oncology clinic wasn’t implemented. But the hospital was. What happens next is because the oncology clinic wasn’t integrated yet, they kept putting their paperwork the way they used to do it. But upstairs at a hospital, they’re using EBAR and Cerner. And you have brand new nurses walking around up there who are all trained up on that and how to deliver in the new world. Well, what happens is that the paperwork gets shoved under the patient’s pillow where they wheel them upstairs for the patient stay after they had chemo. When they go upstairs to have chemo, the nurse on the floor checks the EBAR and thinks that they haven’t had their chemo yet. So, they order Vincristine… I think it’s called. Well, if mom wasn’t sitting there, that nurse would have double dosed her. And that would have turned into probably a death. Make the evening news. And that is not where we all want to be. So yes, it was a serious event. And yes, they called in their consultant, John D, to help them solve that.

But the bottom line here is it was just a matter of not really thinking through how this technology could lead to something very serious. It wasn’t Cerner’s problem, and it wasn’t any of the nurses doing anything wrong. It was just not engineered in a way that makes sense.

Kelly: Wow. What a story, John. Thanks for sharing that with us. Yeah. How can operational improvements increase capacity without adding beds or staff?

John: I think one of the things that we’ve discovered in the– I’ve been in about 100 different hospitals at this kind of grassroots level. We’ve discovered that the reason why people are in the hospital is not always clinical. There’s a whole bunch of factors, including socioeconomic. They couldn’t get a ride, blah, blah, blah. We need to quit focusing on admission and start focusing on discharge. We need to get people out of the hospital. The hospital is really a pull system. If they leave the hospital, we could pull in more people. But we’re focused on pushing people in. But you hear the emergency department is boarding and there’s four people waiting for a bed. That’s a push. But in manufacturing, we’ve discovered 40 years ago that it’s really a pull that you want. What you want is patients to come into the hospital, but they can’t come in until they leave. And why haven’t they left yet? Well, they’re waiting. What are they waiting for? They’re waiting for a ride. They’re waiting for a script. They’re waiting for case management to arrange for or a walker or whatever. There’s always a reason. And those reasons start to stack up people in the ICU, stack up people in the ER. And those stacked up people are not only waiting and getting frustrated, in an inappropriate department. They don’t meet criteria to be in the ICU, but they can’t get out because some lady in a med-surge is still waiting for a script from the pharmacy. And these things compromise the quality of care, and in some cases, lead to other problems.

A person, I myself have been in the hospital, and it was time for me to go and I was waiting. And you know what I did when I waited? I got up out of bed. Well, I hadn’t been out of bed three days. So, I got out of bed and I fell. Thank God I wasn’t 65 because I didn’t break my hip. I just hurt my back. But people are going to walk around the hospital and hurt themselves. Hospitals are dangerous places. We need to get people out. And if they’re there for reasons that don’t make any sense, we need to get rid of that stuff. And the only way to do that is to really understand who could go and why are they here? If I’m ready to go and I’m sitting waiting for a doctor’s consult to sign off on it, I need to get that person out of bed because everybody loses when it doesn’t happen timely.

Kelly: Right. Such great points, John. Thanks for sharing. So why do metrics like length of stay not explain the operational causes behind delays?

John: Well, it’s pretty simple. We’re focused on length of stay. That’s what’s important to everybody. But the bottom line here is that, like the stay does not tell what happened. Length of stay tells you how long everyone was there. But tomorrow I could discharge 15 people, and one person who’s been here a year could go along with them. What’s the length of stay now? Well, the average length of stay is going to be artificially high. You can’t see what really happened with length of stay. However, you could change the metric. You could say, “What’s the velocity?” If you do this a little bit with the ED, you’ll hear visit volume per day. “We saw 350 patients in the ED.” Well, that tells you right away how the ED went. But when you say they all stayed for an hour, what am I going to do with that? All we have is benchmarks that say, “Length of stay for a congestive heart failure should be three days.” Well, what if it’s four? Now what are you going to do? So, if you really want a story, it’s how many people can this hospital say goodbye to every day? And why haven’t they done that every day? And that’s the C chord for continuous improvement.

Kelly: No, I really like what you’re saying there, John. And I never really heard it explained that way. And it makes a ton of sense that it’s really more important about how many people are going home. So, I really, really like that perspective. Can you share with us the connection between operational systems and clinician burnout?

John: I’ve been at this for a while. The problems that we’re dealing with now, unfortunately, are the same problems that people were talking about 25 years ago. Nothing has really changed if you look at it at a high level. You have nursing burnout, staff shortages, frustration. People are leaving the practice. I have four daughters. All four of them said, “I want to get into healthcare.” I encouraged them not to. Who wants to do this? And on top of it, we are injecting tons and tons of money trying to fix it, but it’s not working. It’s time for us to start thinking about capacity as a complex system rather than capacity like we are a manufacturer of healthcare. And that’s one of the reasons why I’m kind of a unicorn when I go into a hospital, because I know how the factory works. So Lean Six Sigma, these tools that were designed for manufacturing, that healthcare, thanks to GE and others, 25 years ago, embraced. And when they embrace Six Sigma, they can’t do it, because a hospital just doesn’t work that way. So, what we could do is focus on the realities of a complex system, rather than the realities of a complicated system, which is building a car. Hospitals are like raising a child. You never know what you’re going to get. It matters the context.

Kelly: Yeah.

John: Right?

Kelly: Yes. So, John, what are some operational blind spots hospital finance leaders should watch for in the coming years?

John: AI. Is anybody thinking about AI?

Kelly: No, nobody’s thinking about that.

John: Let’s be really careful about AI. We use AI in our business. AI is really built by computer guys. So, computer guys can build applications really fast. It’s also good for writing ad copy, stories, helping with email, and even all these other little things. But you know what? AI needs to be taught how to do things. And what hospital do you want AI to be taught at, your hospital or your health system? Do you want somebody to go to the Cleveland Clinic and learn how to run your hospital with AI? Be very careful about AI because here’s what happens. AI is still going to be making mistakes. If you haven’t fundamentally thought through what’s going through your hospital, these little problems I’m talking about. AI will make it worse, not better. We’re seeing people do pilots with AI. And what they’re trying to do is prove return on investment to CFOs. And what’s happening is AI is not only not producing the benefits they hope for. It’s actually worse. AI is not equipped today to understand the nuances of the context of the situation. They know what should happen if John Delisandro is ready to go home, but they don’t know what’s happening with the family who’s in the background bothering the nurse about their dad needs its Coke or any other little thing. AI doesn’t know the context. All AI knows is what it’s been taught. And if you can predict what’s going to happen tomorrow in the hospital, well, you’re worth a billion dollars because no one else can, AI or not. So, you’re using tools to help you look at things that change every day. A person’s insurance and their biological variation is so crazy that you really just can’t trust the flow or the operations to AI. You can’t do it. Before you spend a lot of money on your pilots, maybe I could strengthen this with a little story. I watched a very smart person put in a robot to bring a lab from the ICU and take it to the lab. That process was being automated with AI. And you know what they didn’t think of? They didn’t think of the robot that’s like Aruba, a robot going into an elevator with a patient in it. How’s that going to work? Well, they didn’t think of that, but they certainly spent $250,000 to find out that third parties played with a robot in the elevator.

Kelly: I bet that was interesting.

John: That project ended.

Kelly: Right. Well, John, thank you so much for sharing your insights with us on fixing the systems professionals depend on, the hidden operational drivers of hospital financial performance. If a listener wants to learn more or contact you to discuss this topic further, how best can they do that?

John: I have a website, johndalesandro.com. And I have an email, john@johndalesandro.com, spelled without the apostrophe. J-O-H-N D-A-L-E-S-A-N-D-R-O.com. And we’ll get them all hooked up.

Kelly: Awesome. Thank you for providing that. And thank you all for joining us for this episode of the Hospital Finance Podcast. Until next time…

[music] This concludes today’s episode of The Hospital Finance Podcast. For show notes and additional resources to help you protect and enhance revenue at your hospital, visit besler.holdings/podcasts. The Hospital Finance Podcast is a production of Besler Holdings.

If you have a topic that you’d like us to discuss on The Hospital Finance Podcast or if you’d like to be a guest, drop us a line at contact@besler.holdings.

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