Harry Glorikian

By: Harry Glorikian
Subjects: Business & Management, Healthcare, Information Technology, Life Science, Medicine

Q&A with Harry Glorikian

Congratulations on the publication of your book, MoneyBall Medicine. What do you want your audience to take away from the book?

Thank you! The biggest takeaway I’d like readers to have is that data and technology are already starting to make big differences in patient care, drug development, and nearly every aspect of healthcare; but it’s time to go from being something that just a few places are taking advantage of, to an industry where everyone is using them. When we have systems in place for collecting and analyzing the data, we can use those insights to transform healthcare.

What inspired you, and your co-author Malorye Allison Branca, to focus on the advances in health information technology?

I’ve been in healthcare for decades and had seen how technology transformed other industries, like banking. We’ve moved from standing in line at a bank to taking a picture of a check with my phone to make a deposit. That’s a giant leap forward because of the technology, like ATMs and online banking, and because of the consumer adoption of and attitudes about the technologies.

I began to question why we weren’t seeing technology and data transform healthcare in the same way. Why can’t patients easily share their health information with doctors and hospitals across the country? How can doctors quickly determine which clinical trial a patient should enroll in—and then make it simple for the patient to do so? Why is there still so much trial and error when it comes to picking the right treatment for a patient? What can Pharma do to shorten the length of time it takes to bring a drug to market and how can they make it less expensive and minimize the risks of failure? How can we diagnose patients with rare diseases faster? What can health systems do to streamline their processes and operations while improving patient care? I think the answers to these questions lies in leveraging technology and data.

Why is your book relevant to present and future healthcare professionals?

MoneyBall Medicine takes a look at the current state of how the industry is using data and technology and then goes one step further—where can it take us if we embrace the technology instead of fighting it? The book also ties in the business aspect for healthcare. I think it has broad appeal, not just to those who are already in the field, but also to people who might come to healthcare from a strictly tech background. I think we’ll start to see more of our future healthcare professionals come from different industries with skills we haven’t traditionally associated with healthcare. I think this book can help them see where they fit into the new healthcare reality.

What makes this book stand out from its competitors?

From the very beginning of brainstorming for this book, I knew it was essential to have conversations with the industry’s thought leaders, to find out how their organizations were adapting to an increasingly technical field and where they saw things moving in the future. More than 30 interviews later, we have stories from people like Christoph Wald, chairman of the Department of Radiology at Lahey Hospital and Medical Center, who described how they used data analytics to take a hard look at their department, from equipment utilization and radiation exposures to technician and radiologist performance, reducing their imaging defect rate to less than 1%. I spoke to Kathryn Teng, Physician Executive Director at MetroHealth Medical Center who uses data analysis to research what their patient population needs and uses it to strategically determine where the health system should locate physician practices and how staffing should fluctuate to accommodate those needs. I spoke with Jeff Rice, CEO of Healthcare Bluebook and Leah Binder, President and CEO of The Leapfrog Group about using data to help price and quality in healthcare become more transparent for patients and employers. It’s real-world examples like this, from across the healthcare spectrum, that sets MoneyBall Medicine apart.

Is there a piece of research or interview included in the book which surprised you or challenged your previous understanding of this industry?

Despite decades working in the industry, I am constantly surprised to see the resistance in healthcare to using data and technology. Take medical records—there are still doctors that use paper charts! That does a huge disservice to their patients who can’t easily view their own medical record, share that information with a different doctor—it keeps the utility of the data locked up.

Doctors are pulled in a million directions and have less time with patients. They’re expected to stay on top of the latest research, but it’s nearly impossible with the number of scientific studies being published every week. Standardizing patient care is a difficult sell, even when the data and studies suggest it gives patients better outcomes and can reduce healthcare costs. There’s a big disconnect between payer incentives and provider incentives and patients are caught in the middle. 

Disruption is messy. There’s a lot of uncertainty in figuring out how technology like artificial intelligence and machine learning can best change the role of the pathologist and radiologist. Patients are feeling the financial squeeze of healthcare costs but are unable to treat healthcare like other consumer goods and services. I was surprised just how much resistance to change there would be in healthcare, given the successes in other industries, but I think now we’re on the cusp of transformation—a true evolution of healthcare.

Finally, what did you enjoy most about writing the book?

Listening to the experts describe how their companies are using Big Data and analytics to transform their work had to be the highlight. It’s happening across every facet of the industry in very different ways. Some are patient-centric, others are focused on health systems. How scientists are doing research is changing—we have new models for clinical trials because of the power of data.  Taking these different threads and weaving them together while finding the business angle in each story.