NEW YORK — Embracing digital health is key to curbing out-of-control health care costs, increasing access to care, improving care quality and encouraging patient engagement. But the current regulatory and policy landscape could get in the way of the U.S. realizing the full potential of health IT.
That was the message from speakers and attendees at the New York eHealth Collaborative’s fourth annual Digital Health Conference in New York City this week.
Why the U.S. Health Care System Is Ripe for a Digital Health Intervention
Ezekiel Emanuel — vice provost for Global Initiatives and chair of the Department of Medical Ethics and Health Policy at the University of Pennsylvania — said that the most important number in health care is $3.05 trillion. That’s the amount of money the U.S. is set to spend on health care this year. For comparison, Emanuel, a former adviser to President Obama, noted that France’s gross domestic product is $2.73 trillion, meaning the U.S.’ health care system is actually the fifth-largest economy in the world.
He explained that chronic disease care is a huge contributor to health care spending. According to Emanuel, half of the U.S. population accounts for just 2.7% of all health care spending, while 10% of the population is responsible for 65.3% of spending.
Health IT — including electronic health records, telehealth and mobile health tools — could be leveraged to improve preventive care, boost care coordination, increase adherence to clinical guidelines and lower costs when treating individuals with multiple chronic diseases, Emanuel argued.
Further, health systems could tap “health data analytics to identify next year’s high-cost patients in advance,” he said.
Eric Topol, director of the Scripps Translational Science Institute, said medical care is currently provided at the population level, which is “incredibly wasteful, imprecise and, in many ways, harmful.”
Topol said that providing the same prescription to all patients with a certain disease doesn’t make sense, noting that the top three prescription drugs in the U.S. work for only 35% of patients. Instead of the current one-size-fits-all approach, Topol said patients should be analyzed to determine which treatments will work best for them.
Because of the availability of new tools, the U.S. health care system has an opportunity to shift toward individualized medicine where there is a “Google Map of each individual” that helps determine the best course of treatment, Topol said.
Topol predicted that the U.S. will move toward a “doctorless patient model.” While physicians won’t be replaced and, in fact, “their importance will be magnified,” digital health will democratize health care and create a partnership between patients and physicians, Topol asserted.
Emanuel offered his own predictions for the future of U.S. health care, highlighting six “megatrends”:
- Diffusion of VIP care for the chronically and mentally ill;
- Expansion of digital medicine and closure of hospitals;
- End of insurance companies as we know them;
- End of employer-sponsored health insurance;
- End of health care inflation; and
- Evolution of academic health centers.
Speakers throughout the two-day conference echoed the sentiment that digital health holds the promise to help transform care.
John Brownstein — an associate professor at Harvard Medical School and director of the Computational Epidemiology Group at Boston Children’s Hospital — discussed how social media can quantify population health in a way that traditional public health interventions cannot. He cited several areas where social media can help, including:
- Infectious disease;
- Chronic disease;
- Prescription drug safety;
- Patient experience; and
- Drug diversion and abuse.
Martin Coulter, CEO of PatientsLikeMe, discussed how social networking sites can “elevat[e] the patient voice to the level of medical evidence.”
Based on PatientsLikeMe’s experience, he said:
- Members are engaged and want to participate;
- Sensors, such as wearable devices, help increase patient engagement, activation and data donation;
- Members share sensor data with doctors;
- Objectively captured sensor data correlates with measures of functional disability as reported subjectively by patients; and
- The pharmaceutical industry is systematically learning from patients and applying those lessons to business needs.
Will the Health Care System Be Able To Realize Promise of Digital Health?
Despite all the optimism surrounding the promise of digital health, there are a host of regulatory and policy issues that could impede progress.
Privacy and Consent
Throughout the conference, privacy was continuously cited as a barrier to greater adoption of health information exchange, mobile health and data analytics.
Health information organizations have struggled with how to acquire consent from patients to share their health information.
Deven McGraw — a partner in the health care practice of Manatt, Phelps & Phillips and a member of the Health IT Policy Committee — said patients have a dual interest of wanting to have their data shared to improve the care they receive and protecting their privacy. She said that an “opt-in” consent approach might feel more patient-centered, but it’s very expensive and ends up emphasizes patients’ privacy interests over patients’ data-sharing interests. Instead, she said federal work groups came down on the side of “meaningful opt-out” as the best consent approach.
McGraw added that offering patients a portal where they can access their own data will help them understand the value in health data sharing and help the “needle move.”
Meanwhile, Ann Waldo, a partner at Wittie, Letsche & Waldo, said HIPAA’s “data culture” is “highly resistant to sharing, even with patients.” She added that “uncertainty among innovators as to the rules of the road outside HIPAA” is holding the market back.
Waldo said that extending HIPAA to consumer health data would be a “terrible idea” because its complexity would add additional burdens and hurt innovation. Instead, she suggested developing a self-regulatory framework of best practices for consumer health data. According to Waldo, organizations that comply with the framework could put a seal to alert consumers on their website or applications.
Even after consumers are on board with mobile health apps or devices, there can be controversy over how collected data are used.
For example, Andrew Rosenthal, group manager of wellness and platform at Jawbone, discussed how after an earthquake in the San Francisco area in late August, the company’s data science team looked at sleep data of Jawbone users across the region and was able to accurately identify the epicenter of the earthquake and to quantify the amount of sleep lost because of the earthquake.
Although the analysis used anonymized and aggregate data, some critics said the company overstepped in its use of the data.
Julia Bernstein — strategy and sales operations lead at Ginger.io, a health data platform — said vendors should be very clear from the beginning about the value of their product and the trustworthiness of the system.
Arthur Levin — co-founder and director of the Center for Medical Consumers — added that firms can build trust by being transparent and delivering on what they say they’re going to do.
Data Usability and Interoperability
Other commonly cited barriers are limitations surrounding health data and interoperability.
Andrew Kasarskis — co-director of the Icahn Institute for Genomics & Multiscale Biology and an associate professor at the Icahn School of Medicine at Mt. Sinai — noted that EHRs have a data limitation because people do not actually spend much time in hospitals or with doctors. He added that learning how to incorporate the data individuals generate every day into their health records is essential.
McGraw noted that some patients still intentionally withhold sensitive health information because they are concerned about it getting into the wrong hands. She called it “a myth” that EHRs hold complete records.
Further, Jonathan Hirsch — founder and president of Syapse, a software company that allows health care providers to deploy precision medicine programs — noted that because EHRs were built for billing and compliance, the systems are not able to handle genomic information or other big data.
Health care lags other industries when it comes to data analytics and interoperability, according to experts.
Kasarskis noted that he can use his smartphone to find out the menu and prices of all the restaurants within 20 miles, but “if a patient comes into Mount Sinai from another hospital, we may not know anything about them except what they’ve told us.”
Citing his experience with a financial spinoff company, Colin Hill, CEO of GNS Healthcare, said he’s seen big differences between the finance and health care industries. For example, he noted that financial data are “much cleaner” than health care data and that it is much faster and easier to validate or invalidate financial data.
Hill said there are a lot of regulatory forces and structures holding the health care industry back.
From keeping patients out of the hospitals to improving medication adherence to personalizing treatment, digital health has the potential to reduce costs, improve care quality and increase efficiency. However, under the current payment structure, health care providers are not incentivized to embrace digital health. In fact, doing so could hurt their bottom line.
Kasarskis said the progress made in other industries offers a “glimmer of hope” that the current barriers can be overcome and digital tools can be embraced with the “proper incentives.”
Emanuel said that technology “can’t fix everything,” arguing for payment reform. He said the U.S. needs to move from a fee-for-service system to:
- Bundled payments;
- Two-sided risk; and
He said, “If we really want the digital medicine of the future, we’re going to have to push hard on payment reform.”