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"We are pitting the enthusiasm of the futurists...against the public health perspective that says ‘be careful what you screen for,’”  the prominent genomicist says.

Skirmishes, Uncertainties, and Great Promise: Robert Green on Precision Medicine

The FDA, GINA, and variants of unknown significance all muddy the waters of genomic research and data storage.

Mayo Clinic Attorney Tiptoes Through the Legal Landmines of Genomics

Certainly, Walton believes greatly in the potential of genomics to change medicine at its core, but the obstacles preceding that shift are numerous and substantial, he argued.

Nephi Walton Stresses Realism Regarding Precision Medicine

Over the last decade, technology in healthcare has made incredible strides. From AI outperforming human experts to smartwatches that monitor a patient's heartbeat, it’s safe to say that the digitization of healthcare is improving outcomes and experiences. 

On this episode of Data Book, Shereese Maynard, M.S., MBA, a healthcare strategist and key opinion leader, discusses the technologies that influenced the last 10 years and makes projections on what the industry might expect in the future. Maynard also provides opinions about some past disappointments and the technologies and ideas she thought she would see but have not yet come to fruition.

Make sure you like this podcast, subscribe and follow Inside Digital Health on Twitter, LinkedIn and Facebook to stay up-to-date on the latest health tech news.

 and let me know what you want to hear on upcoming episodes of the podcast.

Using Analytics, Precision Medicine to Improve Preterm Infant Outcomes

How FDA Is Navigating the Digital Transformation

Playing a Medical Video Game for CME Credit

Shereese Maynard, M.S., MBA, discusses the influence of health tech in the 2010s and makes projections on what's to come.

Podcast: Health Tech in the 2010s and Beyond

Investigators are leveraging precision medicine to tailor treatment for an individual patient and improve outcomes.

Astarte Medical is a precision medicine company that uses software and predictive analytics to improve premature infant outcomes. Tracey Warren, Astarte Medical’s CEO and co-founder, is featured on this week’s episode of Data Book.

Warren discusses how the company was conceived, the importance of focusing on the gut microbiome of preterm infants, the ways in which Astarte Medical uses predictive analytics and precision medicine and the direction she sees the company going in the future.

 and let us know what you want to hear on Data Book this season.

Tracy Warren, CEO and co-founder of Astarte Medical, discusses leveraging predictive analytics to measure the gut microbiome in preterm infants.

Podcast: Using Analytics, Precision Medicine to Improve Preterm Infant Outcomes

Artificial intelligence (AI), machine learning, and revolutionary conclusions from population-level insights produced by fast and accurate new electronic tools.

Much of the digital health space can indeed be considered “glamorous.”

But what of the grunt work — the work of achieving interoperability, making all the tools work together so researchers can reach those splashy breakthroughs? What of the toil in the trenches of terabytes, coordinating deals and cooperation between agencies and hospitals, and writing the code which will make all the machines speak the same language, using standards that everyone can agree to?

That may be considered the less glamorous part of the job.

In this latest episode of the Data Book podcast, our hosts Tom Castles and Jack Murtha frame a discussion with Mona Siddiqui, M.D., MPH, the chief data officer of the U.S. Department of Health and Human Services.

Siddiqui said the work she does has a crucial role in making some of the headline-grabbing developments possible.

It might be “the hard thing” — but the challenge is worth it, she said.

“When I was asked to take on this role, I had a very clear sense of what I wanted to do, which is the not-glamorous part of the job,” she said. “People don’t want to work on creating a foundation and an institutional infrastructure that enables the use of data, people want to go on the data analytics, and people want to work on AI, and you know, all of the sort of the buzzword pieces—but nobody wants to create the hard thing, which is how do you connect the data?”

Check out the fourth episode of the fourth season, above, or on iTunes or wherever else you find your podcasts.

Navigate the digital transformation with confidence. 

Data Book Podcast: Rediscovering Healthcare's 'Why' With Rasu Shrestha

Why Health Systems Should Build Their Own AI Models

In the latest episode, our hosts speak with the chief data officer of HHS Mona Siddiqui, M.D., MPH.

Data Book Podcast: The 'Not Glamorous' Part of the Job

It’s an incredible time to be in the world of health IT. Innovators from inside and outside healthcare are developing solutions that may well change the lives of our clinicians, patients and health systems. Technologies like artificial intelligence (AI), mobile health apps and virtual care are forging new paths to more effective treatments, greater efficiencies and expanded access. And we’re even making progress toward interoperability. But still, 

This week on Data Book, we explore this problem and how it harms clinical and enterprise progress. We also look at the human side of the tech equation — is an innovation worth anything if it flails in the adoption and scaling stages? We examine marketing’s role in perpetuating premature, if not unrealistic, hype. Finally, we discuss ways to see through the noise.

What it all comes down to is a question of value, as displayed in last month’s 

 by Ezekiel Emanuel, M.D., Ph.D., and Robert Wachter, M.D. In the piece, they explore whether AI’s value will live up to all the cheerleading surrounding the technology. And they conclude that behavior change is the key piece. AI’s value lies in its ability to influence decision-making, they argue. But if physicians and other clinicians decline to embrace AI in their work, what good is it?

Clinical validation is, of course, necessary. But the story doesn’t end there. Adoption, implementation and scalability are also critical. If a health IT solution lacks the potential to meet these challenges, it might not be a solution at all.

Now, let’s pivot to marketing. (It should go without saying, but full disclosure: We are 

 the health IT marketing business.) Glitzy, vague, overly confident marketing campaigns provide the fuel that powers the health IT hype train. Speaking to a reporter 

 last year, Wachter underscored this problem when he said, “They came in with marketing first, product second, and everybody got excited.” And when the algorithms entered health systems, he said, adding to a body of 

We could all do better to adopt more restraint. Broadly, health IT’s potential is almost unfathomable, immeasurable. It 

 bring profound change to our healthcare system. We are, however, only in the early stages of this new era. Let’s not lose sight of the important thing — value, in terms of quality care and stronger efficiencies &mdash; because we’re blinded by the bright, shiny things.

By the way, this is the final episode of 

. We’ll return in about a month with new episodes featuring great stories and even better expert guests. Until then, thanks for listening.

Get the best insights in healthcare analytics 

Executive Voices: Michael Hogarth, M.D., Chief Clinical Research Information Officer at UCSD Health

Data Book discusses how leaders can ignore noise and embrace effective healthcare technology.

Podcast: Who Else Hates the Health IT Hype?

Gail Zahtz was in New York when she got the call that no founder wants: The money had run out. She had to either sign on a new investor or watch her startup, a health-focused dotcom called Working Weekly, crumble. Soon enough, she was in Houston, meeting with a potential backer about a $5 million investment. They sat at a table, paperwork before them and lawyers at their sides, ready to ink the deal. And that’s when the financier’s lawyer got another horrible call: The Nasdaq had crashed.

That’s where we left you on the last episode of Data Book — with a burning cliffhanger that might have been a bit unfair. But we make amends this week, running full speed ahead with the story of 

 and Working Weekly. Along the way, we analyze the death of the dotcom startup and attempt to draw lessons for today’s healthcare innovators.

If you haven’t listened to the first installment of this two-part series, we recommend you do. 

Now for a quick refresher: Our story began in 1998 when Gail received almost $2 million in funding to jumpstart Working Weekly. It was the glory days of the dotcom boom, and founders like Gail really thought they were changing something — maybe even the world. Working Weekly was a digital-print-hybrid publication that covered all things workplace health. It was supposed to attract high-value readers and higher-value, long-term advertisers.

Things didn’t work out. But the life and death of Working Weekly were curious. They highlighted the ambition and optimism, the passion and risk, the innovation and ingenuity of a startup. Working Weekly, though different from today’s healthcare startups, shined a light on some lessons that may well apply to the innovators and decision-makers of 2019, whether they work for big health systems or small startups.

A big theme in this episode is risk. What drives healthcare leaders to make an impressive investment in data analytics or digital patient-engagement tools? And how about when a health system institutes a value-based payment model?

Well, if you ask Gail, she’ll respond with another question: Why would we be in something as important as healthcare if we weren’t willing to take risks to improve patients’ lives?

The Roles of Health Systems in Sparking Disruption

Data Book details the demise of a dotcom startup and offers lessons for healthcare innovators.

Podcast: When a Startup Goes Bust, Pt. 2

When healthcare communications entrepreneur 

 sat down to meet with her client, she couldn’t have known how much her world was about to change.

“If you had some money, what would you do with it?” the client asked.

“Well, let’s say we start with $800,000 and we cap it somewhere around $2 million.”

Writing on a napkin, Gail sketched out a business plan for 

. The publication would focus on workplace health — mental, physical, emotional &mdash; and make its money from hungry employers with advertising dollars slated for recruiting. It might not seem like it now, but Gail’s project was indisputably high-tech for the era, even requiring the expertise of a chief technology officer and a chief information officer.

The year, after all, was 1998. Websites cost a million bucks. The internet was a new, mostly untapped frontier. The dotcom age had yet to boom, much less bubble up and burst.

And with this stroke of good fortune, Gail secured $1.8 million and launched 

 into orbit. In almost no time, she had a sprawling office in Charlottesville, Virginia, 60 dedicated employees and a burn rate of $250,000 per month.

But it wouldn’t last. In just a few short years, Gail and her project were swept away in the 

What Healthcare Can Learn from Failed Tech Projects

Perhaps the greatest challenge for any writer in health tech is getting innovators to discuss their disappointments or shortcomings. But it’s through these experiences — dead startups, tech implementations gone array and so on &mdash; that healthcare leaders can learn so much. Maybe it’s how to 

 for your health system, or it could be a greater lesson reflecting on the 

frantic, hype-driven state of health tech

This is the reason why we wanted to talk to Gail, and it’s precisely why she agreed to speak with Data Book: What might we learn from the tale of 

Before we go, yes, we understand that a health-focused digital media outlet doesn’t face the same challenges or enjoy the same benefits as, say, a company that develops artificial intelligence systems for clinical use. But this dispatch from the dotcom bubble draws overt parallels to health tech’s continued evolution in 2019.

Here’s another note: This is a very special episode of Data Book. It’s the opener of our first ever two-part series. We even broke our traditional format — you know, story and then interview &mdash; by using all 23 minutes and 48 seconds to tell this cohesive story. Half of the story, at least. Our conversation with Gail is interspersed throughout the narrative. We’ll drop the second and final episode on Friday, June 14.

And we must extend a final thank-you to Shereese Maynard, our friend and colleague, who tipped us off to this story. Thanks, Shereese!

The High-Tech Hospital the World Wasn’t Ready For

Lost in the CRISPR Hype, a Gene-Editing Giant Is Fighting Back

Data Book examines the story of Gail Zahtz and her dotcom startup, Working Weekly, for insights into healthcare’s digital transformation.

Podcast: When a Startup Goes Bust, Pt. 1

Now that FDA Commissioner Scott Gottlieb, M.D., has resigned, questions linger about 

. After nearly two years of the FDA trying to catch up to innovation in data, artificial intelligence, digital health and even cybercrime, the regulator stands at a crossroads: Will efforts like the software precertification program continue? Or will the FDA retreat from its goal of better 

Simply put, Gottlieb’s resignation from the FDA means that we don’t know what’s next for digital health regulation.

This week on Data Book, we welcome Arti Rai, J.D., Elvin R. Latty Professor of Law and faculty director of Duke Law’s Center for Innovation Policy, to discuss Gottlieb’s legacy, the state of innovation inside the FDA and what the agency needs to do going forward. Rai is an expert in innovation policy and health law, and artificial intelligence has consumed much of her time as of late. For her, healthcare is at an inflection point, and it’s critical that the FDA get its next steps right — and that means pushing the 

While Gottlieb has his critics, few will argue that he’ll leave the FDA the same as he found it. During his tenure, 

 took centerstage. These two years represented, by most accounts, a drive toward digital health.

 evolve, this episode of Data Book starts by examining how it 

Less than 100 years ago, innovation at the FDA meant something far different than cybersecurity and mobile health apps. For starters, the regulator as we know it wasn’t even born until the 1930s. And throughout much of the 1900s, the 

 was less encompassing, especially regarding 

Many turning points — dramatic moments of death and innovation, horror and hope &mdash; occurred for the public and Congress to take the actions that created today’s FDA. So, tune in for a condensed look at how this FDA came to be and what the regulator could look like tomorrow.

Implementing AI Is Simpler Than You Think

After the resignation of FDA Commissioner Scott Gottlieb, Data Book examines agency history & welcomes Duke Law’s Arti Rai to discuss its digital health future.

Podcast: A Pivotal Moment for the FDA & Digital Health

CRISPR. TALEN. Gene editing. It sounds like the stuff of the future, the keys that open the door to a new frontier in medicine. But what about zinc finger nucleases?

Amid all the CRISPR hype and pushback, zinc finger nucleases have mostly flown under the radar, but they are very much a promising player in the gene-editing landscape. And just one company—Sangamo Therapeutics&mdash;is using zinc fingers in this way, an arrangement created by its forward-thinking leaders and their aggressive acquisition of intellectual property.

Today on Data Book, we tell the story of Sangamo and its fascinating zinc finger technologies. Along the way, co-hosts Jack Murtha and Tom Castles tackle bigger ideas in precision medicine and gene editing, exploring the gold rush surrounding the industry and its promise and pitfalls.

Our guest is writer Danny Funt. He reported and wrote a top-shelf feature story on Sangamo for 

. (Worth noting is that Funt spent more than a month researching genomic medicine, searching for the ideal candidate to profile, before selecting Sangamo. We ultimately published the story online just a day before Sangamo announced 

 with Gilead. We tip our hats to Funt and his sharp reporting instincts.)

Before Data Book dives into the Sangamo story, however, we tell the story of the origins of CRISPR. It dates back to the late 1980s, in a beach town in Spain. An amazing discovery that occurred there blossomed into a movement that gripped researchers, commercial ventures, and the mainstream public. But what might CRISPR mean for medicine?

Tune in to this episode of Data Book and find out.

And come back next week for a story of cultural change in healthcare. Our guest will be tech-centric cardiologist and media personality Kevin Campbell, MD.

, and all of your favorite podcasting apps. We publish new episodes on the best stories and insights in big data, artificial intelligence, and cybersecurity at 8 a.m. every Friday.

Sangamo’s innovations recently earned it $3 billion. Why? But first, the CRISPR origin story.

Podcast: The Gene-Editing Company That Didn't Need CRISPR

 I heard old-timers repeat a command so often it began to sound like a cliché, or perhaps a prayer: 

Don’t tell me the story. Show me the story. 

For a young journalist, that idea posed a challenge. It was, after all, easier to simply tell someone what happened. To show meant to stumble across a cold college campus and raise a digital recorder to a stranger’s face, asking them to recall the color of the walls, the reactions of their peers, how the plot unfolded. Showing required me to see the sweat form on the brow of the person who lost her home during the hurricane, to tail the lovers who lost their apartment to heroin addiction, to witness the launch of the start-up company. Telling, meanwhile, warranted only a recap.

My mentors had the right idea. Now, I, too, pressure myself and my writers to show, not tell. The imagery and the human element make editing more difficult, but they form a better article—or a better podcast.

™ are launching our first-ever podcast, Data Book, and its foundation is a commitment to strong storytelling. Every week, for 20 to 30 minutes, join me and co-host Tom Castles for a journey that plucks you from the car or cubicle and brings you to the most promising and treacherous frontiers in health tech. Data Book tells great stories, with great insights, from the realm of healthcare big data, artificial intelligence, and cybersecurity.

Our first episode, “Who Is the Dark Overlord?,” details a shadowy hacker collective that has hammered healthcare organizations of every size and specialty, in many areas of the world. But what is it about these black hats that has earned them such notoriety? And what does their existence mean for healthcare, an industry feverishly searching for cybersecurity solutions? We examine these questions by looking at the day the Dark Overlord clawed its way to prominence, and through a conversation with writer Gautham Thomas. Afterward, Tom and I discuss key takeaways for healthcare leaders and everyone else, in a section we call The Insight.

Data Book’s first chapter gets published at 8 a.m. ET this Friday, March 30. From there, expect a new episode around the same time each week.

In health tech, it’s often difficult to tell the story behind the data, the venture capital, the data breach, the algorithm. Maybe that’s why so few media outlets pursue ambitious, character-driven reporting in this space. But healthcare and technology are inherently linked to humans and tension, ingredients that are essential to the recipe for any great story. Tom and I know the industry holds many gripping tales. We’re busy unearthing them, and Data Book is where we’ll share them.

™ podcast if it were to lack practical, actionable advice and big-picture views. Data Book is certainly home to bright ideas, and they will shine through, in expert commentary and the stories themselves.

 profiles, or open your favorite podcast app to dive into Data Book. We promise to show you great stories and great ideas.

We’re all about great stories and great insights. And that’s what you can expect from Data Book, the first-ever Healthcare Analytics News™ podcast, dropping this Friday.

Introducing Our New Podcast, Data Book

A real-time testing solution could lead to more precise treatment and better outcomes.

Transforming Lab Data into Personalized Healthcare Insights

The firm will invest in biotech companies focused on drug discovery and development.

Wellington Management Closes $393M Biomedical Innovation Fund

The platform could help create new treatments for patients with muscle disorders.

Avidity Biosciences Earns $100M for Precision Medicine Platform

The partnership could improve the speed, cost and success rate of drug development.

PercayAI and Canopy Biosciences Partner to Improve Drug Research and Development

New AI-enabled technologies can improve patient outcomes.

PercayAI Launches, Offers AI Software to Accelerate Drug Development

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.

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

Precision Medicine

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