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In our latest episode of the Data Book podcast, Justin Norden talks about the emergence of ChatGPT and what it means for healthcare.

Norden is a physician who teaches about digital health at Stanford Medicine. He’s also a partner at GSR Ventures, an investment firm focusing on early stage digital health companies. In this conversation, he talks about how AI is going to eventually touch every part of the healthcare journey.

Growing up in a family of physicians, he graduated from Stanford University School of Medicine. He became fascinated with the idea of merging technology and healthcare. He helped start the Stanford Center for Digital Health.

As Norden says, “You can’t spend that long in Silicon Valley without starting a few companies of your own.” He was CEO and co-founder of Trustworthy AI, which was acquired by Waymo, Google’s self-driving vehicle company. He also worked on the healthcare team at Apple. He’s been at GSR Ventures for nearly four years.

ChatGPT could be the fastest-growing consumer technology project ever, Norden says.

When asked about ChatGPT’s implication for healthcare, Norden says, “That is the million, if not billion dollar question.”

Justin teaches about digital health at Stanford Medicine and is a partner at GSR Ventures. He talks about the potential of ChatGPT, the ethical questions, and how AI will transform the industry.

Data Book podcast: Justin Norden talks about ChatGPT and AI in healthcare

In this episode of the Data Book podcast, we talked with Ajay Khanna, the CEO of Tellius.

Tellius, a technology firm, operates an AI-driven decision intelligence platform. Khanna talks about machine learning and artificial intelligence, and its potential to help healthcare organizations gain new insights into their operations in areas ranging from hospital readmissions to supply chain challenges.

Khanna also talks about "decision intelligence," which he describes as bringing the what, why and how together. With AI, and decision intelligence, organizations can gain better insights into trends, such as why patients are choosing a certain medication.

And he talks about the steps needed for healthcare organizations to move forward and embrace new technologies. "It's a culture change," Khanna says. But it's also about gaining greater ease with AI and other new technologies.

Reminder: You can subscribe to Data Book on Apple, Spotify, Google, iHeart Radio and virtually everywhere you get your podcasts.

In the latest episode, Ajay Khanna explains how healthcare organizations can use artificial intelligence to gain new insights into their business. 

Data Book podcast: Ajay Khanna, Tellius CEO, talks about 'decision intelligence'

On this week's episode of Data Book, Chief Healthcare Executive spoke with Terri Casterton, Director of Healthcare Product and Strategy at Bottle Rocket, a consultancy that provides business strategy, product, design and technology services. We discussed the latest Apple Watch features, the use of patient supplied data in healthcare and the use of technological innovations in healthcare.

Terri Casterton, director of Healthcare Product and Strategy at Bottle Rocket, discussed the latest Apple Watch features, the use of patient supplied data in healthcare and the use of technological innovations in healthcare.

Podcast: Getting Health Systems and Hospitals to Utilize Data From Wearables

On this week's episode of Data Book, Chief Healthcare Executive spoke with Steve Wigginton, CEO of Icario, platform that promotes health action to connect everyone to better health. We discussed how value-based care and artificial intelligence are helping health systems and health plans to provide more personalized care and to address social determinants of health.

Steve Wigginton, CEO of Icario, discussed how value-based care and artificial intelligence are helping health systems and health plans to provide more personalized care and to address social determinants of health.

Podcast: Joining Technology and Value-Based Care to Provide More Personal Care

On this episode of Healthy Bottom Line, Barry Sample, PhD, director of science and technology at Quest Diagnostics, discusses the rise in drug positivity rates among healthcare professionals over the course of 2020 and the consequences of drug use among employees in healthcare settings. He also talks about the role that marijuana legislation has played a role in this increase as well as some solutions to reduce positivity rates.

Barry Sample, PhD, director of science and technology at Quest Diagnostics, discusses the rise in drug positivity rates among healthcare employees, the reasons behind the rise, and what can be done to combat them.

Healthy Bottom Line:  COVID-19 and Marijuana Laws: Why Employee Drug Positivity is on the Rise in Healthcare

On this week's episode of Data Book, Chief Healthcare Executive™ spoke with Punit Soni, CEO and founder of Suki, an artificial intelligence (AI) platform that streamlines administrative work for providers as a means to reduce burnout. We discussed how this tool helps reduce burnout among healthcare professionals and how this technology can be used in a post-pandemic world. We also talked about some of the misconceptions about how AI can be used in healthcare and the role that it should serve.

Punit Soni, CEO and founder of Suki, delves into how artificial intelligence (AI) can be used to address burnout among healthcare professionals, as well as misconceptions about the purpose that this technology should serve in healthcare.

Podcast: Addressing Provider Burnout and Work Overload: What is the True Purpose of AI in Healthcare?

On this week's episode of Data Book, Chief Healthcare Executive™ spoke Blair Childs, senior vice president of public affairs at Premier. We discussed potential for the Improving Seniors’ Timely Access to Care Act (

) to be signed into law and how it will improve access to care for patients by changing how prior authorizations are done. We also talked about how machine learning and artificial intelligence (AI) technologies can help health systems adjust if the bill is signed into law and how they can help automate prior authorizations.

Blair Childs, senior vice president of public affairs at Premier, explains how the Improving Seniors’ Timely Access to Care Act could revolutionize how prior authorizations are conducted and how machine learning technologies can help health systems adapt if it is signed into law.

Podcast: How AI and the Improving Seniors’ Timely Access to Care Act Can Revolutionize Prior Authorizations

On this week's episode of Data Book, Chief Healthcare Executive™ spoke with Tom Knight, founder and CEO of Invistics, to discuss the dangers of drug diversion in healthcare institutions and how machine learning technology can help solve this issue and prevent it in the future. We also discussed how the COVID-19 pandemic has impacted the frequency at which drug diversion happens and how that’s expected to change as the pandemic comes to an end.

Tom Knight, founder and CEO of Invistics, discusses how the COVID-19 pandemic has highlighted the need for better solutions for drug diversion, where healthcare employees commit medication theft, within their healthcare organizations and how technology can help resolve the issue.

Podcast: Addressing the Dangers of Drug Diversion in Healthcare Settings with Tom Knight

On this week's episode of Data Book, Chief Healthcare Executive™ spoke with Tanvi Abbhi and Nora Zetsche, MD, cofounders of Veta Health, a remote patient monitoring (RPM) platform designed to improve disease management capabilities for patients with chronic diseases. We discussed how this platform works and how it can impact conditions for patients and providers. We also talked about the pandemic’s effect on RPM utilization and where they see this technology going in the future.

Tanvi Abbhi and Nora Zetsche, MD, cofounders of Veta Health, discuss the company’s remote patient monitoring (RPM) platform and how RPM can be used to personalize and improve healthcare for patients with chronic diseases.

Podcast: How Remote Patient Monitoring Can Improve Chronic Disease Management

Leslie Trigg, CEO of Outset, the creator of Tablo, a home-based dialysis machine that incorporates cloud-computing technology. We discussed how these machines work, why they would be attractive to patients, and how the COVID-19 pandemic has affected the demand for these machines. We also talked about the potential for home dialysis machines to be eligible for reimbursement and what the future looks like for this technology.

Leslie Trigg, CEO of Outset, discusses how imbedded cloud-computing technology in home dialysis machines can improve quality of care for patients, and how the pandemic has boosted demand for these machines.

Podcast: Home Dialysis Machines and Cloud-Computing with Leslie Trigg

The popularity of ChatGPT has triggered a surge of interest in artificial intelligence. But AI's promise also comes with some potential problems.

Managing the benefits and risks of AI in healthcare | Jon Moore

A solid majority said they would feel uncomfortable if doctors were relying on artificial intelligence for a diagnosis. Some see the potential for greater health equity.

Many Americans leery of AI in healthcare

We need a level of care between preventative medicine and catastrophic case management: preemptive care. 

Can healthcare data lessen disease burden for aging Americans? | Lonny Reisman

Many older hospital patients develop delirium. Johns Hopkins researchers used artificial intelligence models to identify patients that were likely to develop delirium. 

Using AI to detect the risk of delirium in patients

With the deal, the combined company says it’s providing software solutions, from patient flow to automation, to more than 180 health systems.

LeanTaaS acquires Hospital IQ, merged company touts $1B in value

Using and analyzing data for some subpopulations is still in the early stages and there remain a lot of questions around what is the right data to collect, said George Van Antwerp, MBA, managing director, Deloitte Consulting.

I would say we're still at a point where we're trying to figure out what is the good and bad data. And it may vary dramatically. In some cases, we could think about something like oncology where nutrition is important for somebody diagnosed with cancer, somebody going through chemotherapy. So, thinking about, there's about 37 million people in the U.S. that suffer from food insecurity, so how do we think about food access? And how do we get that food access information? Is that looking at food stamp data? Is it looking at income data? Is it looking at credit card data? If they have a credit card. Which of those are fair?

And I think also understanding behavioral patterns that may vary by a certain ethnicity or others. I did a paper a few years ago on different Hispanic subpopulations and how they use, you know, the healthcare system in the U.S., but really understanding that they're not all the same, and as we get into some of these populations, thinking about what the type of care they're looking for is? Who they trust or don't trust?

I think one of the things you've seen a few pilots out there over the years is using barbershops to be an effective way to interact in certain populations. And so being able to do things around behavioral health, in the barbershops. We did something years ago around colonoscopy screening in the barbershops. I've seen others do things around adherence.

So, figuring out what the right approach is to engage a specific subpopulation, and then what data to, your point, can be used to get that, because it might have to be proxy data. You may not be able to get direct data at scale to be able to make those decisions.

Using and analyzing data for some subpopulations is still in the early stages and there remain a lot of questions around what is the right data to collect, said George Van Antwerp, MBA, managing director, Deloitte Consulting. 

George Van Antwerp on Understanding the Right Data to Address Health Disparities

Hospitals and health systems are largely not equipped to handle all the patient data they could receive and turn it into actionable information, explained Edmondo Robinson, MD, MBA, MS, FACP, senior vice president and chief digital officer at Moffitt Cancer Center.

Oh, absolutely not they have they don't know what to do with those data. Especially we start talking about wearables, right? So, you think about it, a patient says, "Hey, I, I'm averaging 10 more steps this week than I was last week." What does that mean? You know, other than saying, "Yes, keep going. That's wonderful," it's hard to know what that means.

And so I think there's a process around structuring your approach to understanding, in this case, remote patient monitoring, wearable types of data, to say, are there criteria whereby a certain change — because it because some of those data are even continuous, right, continuous monitoring — so are the criteria whereby a change would trigger an intervention of some sort? Are there summaries? You know, a weekly summary, a monthly summary, whereby understanding those data at that level across over time is important for many intervention perspective. It depends by the data. And that's not even including all the research you want to do, which is going to ask the questions differently and attack them differently, depending on the  hypothesis being built in that particular research study.

So, you know, it could be everything from "I have a patient on a particular chemotherapeutic intervention; they're now at home after getting their infusion in the infusion center, and I want to monitor adverse drug reactions or events." Well, I could use wearables for that. But what does it mean, if the heart rate went up a little bit? Or if the heart rate went down a little bit? Is that a 88 [heart rate]? Or is that just normal variation in a heart rate?

You've got to set those parameters and you've got to understand what it means to have those data; but just looking at it constantly, it's not gonna be helpful. So, again, you really got to be disciplined about your approach to those data.

Will health systems and hospitals need to implement things they don't currently have, like artificial intelligence (AI) or different algorithms?

It could. That could absolutely accelerate your ability to sift through those data and get to...separate the signal from the noise, right? You absolutely could leverage machine learning to do that. You need a ton of data to train those models really well. But, ultimately, I think that's where it's going to go, whereby what happens is, the AI surfaces up, "hey, this, look at that, that's important."

But even short of that, you can just set some hard parameters around some of these things, right? Where, you know, they're not always perfect, but they at least signal that you should pay attention. So, for example, if your heart rates over 100 [bpm], I'm going to pay attention. Now, it could just be that you were out for a run — not a big deal. Or it could be that you are having some kind of reaction. And I'm thinking about even for patients who are on the inpatient side. It could be that I caused that high heart rate or I know the reason for their high heart rate. Or it could be that I don't know the reason. And I better go figure out what the reason is, right? So though that's just a hard, it's not even AI driven. That's just a hard line, that 100 right. So, there's some of that.

The reason why machine learning might be really critical is often it can pull signal from noise that we can't see normally. Right? And it might do it sooner. And that's actually really important.

Dr. Edmondo Robinson Outlines Hospital Readiness to Receive Large Amounts of Patient Data

Craig Newman, the chief strategy officer at HealthChannels for ScribeAmerica, discusses how technology can be used to help reduce the amount of time and energy providers spend doing administrative tasks.

How can technology help reduce the administrative workload for doctors so that they can provide better care to patients?

Great question. I think everything is all about how do you make it easier for physicians to focus in on patient care? The last thing we want to do is actually create new sequential processes or new workflows that take the provider away from the patient.

And so, when I think about the model itself, and this is going to be different, again, based on the care environment that the providers working in — I'll just use an ambulatory clinic — I think about segmenting that work pre-visit, during the visit, and post-visit and looking at how we can offset some of that work with technology. For some, the technology is still not up to snuff to offload everything for that provider.

So, let me give you a prime example. So, let's talk about documentation of the physician itself and doing a clinical documentation. There's a whole notion of how do we leverage artificial intelligence (artificial intelligence) to actually drive value at the point of care to help with physician documentation. AI is incredibly effective when we talk about like radiology, or coding, or billing practices because there's tremendous data and very little variability.

Think about your primary care office. You've got different voices, different templates, different processes, different people coming in and out, maybe different caregivers, a ton of variability that exists for providers today. Technology alone — AI and machine learning models — can't solve the problem. And so, I think what we're seeing happen in the market, and what we've done with our product line Speke, is actually blend front-end technology that creates a seamless workflow for the provider. Imagine being able to walk into a room, hit a single button, and it could capture the entire conversation between a patient provider. No periods, no stop phrases, no clicking around in the EMR (electronic medical record), no nothing. And then, you leave the room, you hit stop, you can verbalize something after the fact, move on to your next patient, and never be tethered to the computer. And then, within moments to 24 hours, that note is structured in the EMR.

How did that happen? Well, we take that smart technology optimization process — sort of audio preprocessing, and speaker segmentation and machine learning — we route it to back-end labor to do QA (quality assurance) and CDI (computer design and integration) and then offload the clerical task from the doctor, doing that work behind the scenes a little bit asynchronously. Just by doing that little step, you can free up time. And getting back to that what we talked about previously around time driven activity-based cost, you've got to create time for the physician and offload those clerical tests.

We're seeing the same thing to providers, pre- and post-visit who were using technologies like chatbots or robotic process automation technologies, that can help make sure that we automate as many processes as possible. But then, we still need to make sure that there's human glue involved, who can help them with support strategies like doing comprehensive chart prep, helping tee up where there are care gaps to close, helping them with their specificity, acuity, documentation, or even making sure their charts are completed, efficient, and on time so the bills get out, so they don't have outstanding charts and their DSOs [daily sales outstanding] don't get screwed up throughout the course of the week or month.

So, I think it's a balance of technology and labor working in concert together. It's not an and/or [situation]; it's a both.

Craig Newman: How Technology Can Reduce Administrative Burden for Physicians

Personal health information is extremely sensitive. And healthcare organizations could have access to millions of medical records.

Now, health systems are migrating to the cloud to keep the health data secure.

At HLTH2019 in Las Vegas, Nevada, Luke Bonney, co-founder and CEO at Redox, discussed the emerging trend.

Editor’s note: This interview has been lightly edited for style and clarity.

We've been at this for about five years at Redox. And over those five years, we've seen a massive acceleration in the overall adoption of technology in healthcare organizations, which is really exciting.

One of the big initial shifts we saw, really in the 2017 time period, was a growing acceptance of cloud-based technology. Before that, healthcare was really primarily about on-premises software solutions. That shift, number one, is huge, because obviously the world of mobile and consumer-driven technology is dependent on the cloud.

Now what we're starting to see is the beginnings of a shift from what is predominantly a B2B technology ecosystem, to start to see more of this B2C driven approach. We've seen this in finance as a great example or retail, where major leaps occur when we see the consumer really start to take control through their own data.

Key Considerations for Securing Your Digital Healthcare Cloud

How Edge Computing Can Advance Healthcare

The healthcare industry has seen a massive acceleration in the overall acceptance of cloud-based tech.

Emerging Trends: Migrating to the Cloud

From Fitbit to Apple to Samsung to Google, the wearable device market is competitive. These technology solutions give patients the opportunity to take more control over their health and health data. All the while, physicians can intervene if they notice alarming trends.

Amy McDonough is the senior vice president and general manager of Fitbit Health Solutions, a business division of Fitbit. At HLTH 2019 in Las Vegas, Nevada, she shared with 

™ how health systems can benefit from these devices.

Editor’s note: The following transcript has been lightly edited for style and clarity.

Amy McDonough: Wearables have the opportunity to more deeply integrate into healthcare to help improve the healthcare system, both in terms of outcomes, as well as cost savings, by providing data, guidance and tools in a very personalized way, and in some cases, even early detection to help individuals improve on their own health.

We see great examples of everyone in the research community, as well as with health plans and health systems understanding the power that a wearable can bring to that in terms of providing that data and an ongoing touch point with a patient or a user.

One great example of this is in Cedar Sinai, which is doing a research study looking at the impact of wearables on post-operative surgery. So, what's the optimal number of steps you should take after a knee or hip surgery and how can that help prevent hospital readmission and help optimize for recovery? That's one example in the hospital space.

On the payer side, there are great examples of with Medicare Advantage and with the senior population of helping to motivate and engage seniors in health. Fitbit is really excited to partner with United Healthcare. We were in 42 Medicare Advantage plans this year, and that's going to be expanding to 59 plans across 27 states in the next plan year. There is also a program called Renew Active. That program is going to allow for seniors to have access to a social community providing community and social support to help them reach their goals.

Fitbit Premium to Offer Personalized Health and Fitness Programs to Subscribers

Fitbit Is Pushing Its Way Back Into the Wearables Competition

Fitbit and NIH Launch Digital Health Tech Initiative for All of Us Program

At HLTH2019, an expert at Fitbit discusses wearable devices. 

How Health Systems Can Benefit from Wearables

Artificial intelligence (AI) has the potential to revolutionize healthcare. But, like digital health tools and other health technologies, AI needs to be implemented into a health system effectively.

Nagi Prabhu, chief product officer at Solutionreach, a digital health company, told 

™ at Expo.Health in Boston, Massachusetts, that there are two main things that healthcare executives and health systems should do when looking to implement AI.

“No. 1 is getting the right application of the AI and at the right pace,” Prabhu said.

Despite the hype around AI and many experts thinking they can apply the technology to virtually anything, Prabhu said it’s important to recognize the right applications.

For example, health systems might not want to apply AI when the patient’s life is dependent on it, he suggested. Instead, he said AI can be applied for a patient’s communication preferences and patterns.

The second thing is to walk before you run.

“You don’t want to get into too much AI too fast where you are going to create chaos, confusion or dissatisfaction from the patient and provider,” Prabhu said.

Health systems should start slowly with the implementation of AI to test the waters. That way, both the providers and the patients are more familiar with the power of the technology and how it will be implemented into the provider’s workflow and how it will be used to improve the patient’s outcomes.

Why Health Systems Should Build Their Own AI Models

Where Health Systems Are with AI Algorithms

An expert gives two tips for healthcare executives looking to use AI.

How Health Systems Can Effectively Implement AI

It appears as if now more than ever, health systems, patients and consumers alike are focused on health data privacy. With 

 of Facebook reaching a $5 billion settlement with the Federal Trade Commission for data privacy lapses, it’s clear that even the biggest companies have real security concerns.

 aims to protect personal health data, health systems still need to do their best to ensure that patients’ data remain safe.

David Harlow, J.D., MPH, is a healthcare attorney and blogger for HealthBlawg. At Expo.Health in Boston, he told 

™ that there is great concern about how people are treating and caring for data.

“Data really needs to be protected and that is often an issue that is not addressed sufficiently by healthcare providers, by technology vendors and other folks in the ecosystem,” Harlow said.

When it comes to protecting data, Harlow said that it’s not a “set it and forget it” kind of thing, but something that needs constant updating. This ensures that the health system is doing its best in terms of data privacy and security, he added.

Having a well-documented system could make things better for a health system and can keep it from suffering debilitating fines and penalties from the government, Harlow suggested. It’s important to do this to show that the health system was doing best practices all along and just got hacked or had a breach anyway.

Wearable Medical Devices Can Raise Issues for Healthcare Professionals

Patients More Willing to Undergo Genetic Testing if Given Control of Their Data

Data privacy practices need to be updated regularly, he said.

David Harlow: Understanding Data Privacy Concerns

With new innovations entering the market and different priorities from one healthcare executive to another, it is essential for health systems to create a strategic plan. The strategic plan should be a comprehensive document based off the health system’s mission and core values. The plan can give employees and the communities in which the health system serves, a clear understanding of the roadmap to achieving better outcomes.

John Colmers, MPH, is the vice president of healthcare transformation and strategic planning at Johns Hopkins Medicine. Since the start of his tenure in 2011, Colmers works to position the health system to respond to healthcare reform and other near-term and long-term market forces. He played a vital role in the creation of the Innovation 2023 strategic plan, which has six pillars that encapsulate the mission of Johns Hopkins.

Colmers received his bachelor’s degree from Johns Hopkins University and obtained his master’s in public health degree from the University of North Carolina at Chapel Hill. Before his work at Johns Hopkins Medicine, he served as the secretary of the Maryland Department of Health and Mental Hygiene, where he was responsible for protecting and improving the health and well-being of people in Maryland. 

I spoke with him about his approach to developing a strategic plan, how the community has helped create the goals of the plan and how other health systems can build theirs.

Editor’s note: This interview has been lightly edited for length, style and clarity.

Samara Rosenfeld: The Johns Hopkins Medicine Innovation 2023 strategic plan has six pillars. What are they?

 JHM has created a strategic plan for our entire enterprise. The plan is built on the three parts of our mission: improving and leading the world in clinical care, discovery and the training of the next generation of health professionals. This is the second strategic plan we have created, and it went into effect in fiscal 2019.

The six goals are to: improve the quality and affordability of healthcare, support the well-being of our people and our communities, work like one organization, push the boundaries of science and education, aim for precision in everything we do and make JHM easy. All of the goals we established have very precise sets of outcome measures of the next four years and include specific strategies and implementation components that filter their way throughout the organization.

S.R.: What makes these six goals so important?

 In light of the environment in which academic medical systems are operating today and the changing pressures that are placed on us financially by payers, the government and others, it is important for us to advance largely through innovation. It is what has created us to be the leading organization that we are. In order to continue to be a leader, we think it’s essential to be leaders in all of these areas.

In improving the quality and affordability of healthcare, it is recognition of both improving outcomes for individuals and populations and to make healthcare more affordable for all. Some of that will come through the innovation that we are able to produce.

We strive to support the well-being of our people and communities. We can’t operate without having a workforce that is composed of people who are able to bring their best and have proper balance in their work life. At the same time, we recognize that for the communities that we serve — in thinking about the world from a population health standpoint &mdash; it’s essential for us to think of their well-being more broadly than medical care.

Working like one organization and making JHM easy means that we want to internally and externally operate in a way that’s easy for our patients and the people who work here and take advantage of the system we have created.  

Pushing the boundaries of science and education is at the core of who we are. We want to continue being leaders in that.

Finally, aiming for precision in everything we do begins with an understanding of the role of precision medicine going forward. It’s essentially saying to the organization as a whole that we want to bring data and analytics to everything we are doing. That would include things such as precision education to make sure our training programs, for example, are geared toward the individual learner. An understanding of big data in education and in areas of quality and affordability but also in business decisions that we make.

We adopted this plan in language we think is more approachable by those in our community, our employees. Rather than use language that is less approachable, these statements are designed so that people can understand these things in a clearer fashion than had been the case previously.

S.R.: How have changes in innovation changed your approach to creating a strategic plan?

 At the core, and the reason we titled the strategic plan “Innovation 2023,” is that we think that is who we are. We have been that way since our founding in the 19th century, when the idea of academic medicine in this country began. Throughout our history, we have been on the cutting edge of innovation. We are of the belief that in order to thrive in the 21st

 century, we have to continue to support that type of innovation in all that we’re doing. And in light of the complexities I mentioned earlier, it’s essential that we’re able to be as efficient as we can in our operations.

Making ourselves more affordable. Continuing to produce great outcomes. Generating the types of efficiencies that are associated with working like one organization. But doing so in the same way that we can be sure that for people who are trying to innovate, we are making their job as easy as possible.

All of these are driven by supporting innovation.

S.R.: Your priority is to help you achieve Johns Hopkins’ mission. What does that look like and what are some challenges you might face in getting there?

 We want to advance the type of treatment in care for individuals as we move from focusing on individual disease states to a greater understanding of the way in which environment and many other factors come into play in the years going forward.

We’re living now in an age where there has been an explosion of data, computational capabilities and the ability to understand how systems operate. When we think of precision medicine, we want to take advantage of it going forward. Our understanding of a particular disease is advancing by us understanding that it is likely not a single disease, but in clinical, meaningful subsets of those diseases, which are explained and derived through the use of large data and computational abilities. Going forward, we want to lead the way in disease and understanding that. Our true competitive advantage, if we have one, is in our ability to discover those subsets of diseases and implement meaningful treatments for those faster than the next guy. We are not likely to be as nimble or less expensive than others. But if we can operate in a way that is advancing that understanding of disease and the treatment of it, we will be successful.

Our goal all along, from our initial founding, was to take the science and marry it to the clinical care. That’s the combination of the school and the hospital. And in the 21st century, the application of that is essentially what we’re attempting to do.

The challenges that we’re facing are challenges of execution and funding. The execution is around our ability to stop doing things that we no longer need to do and redirect resources to those areas that we do need to improve. The challenges are also associated with the way in which we are being funded and our ability to generate sufficient margins to continue to attract and retain the best talent and to support the cost of research, which continues to need to be supported by clinical activity and philanthropy.

How health systems can construct an effective strategic plan for innovation.