The dashboard is the potent symbol of our age. It offers the elegant visualization of data, and is intended to capture and represent the performance of a system, revealing at a glance current status, and pointing out potential emerging concerns. Dashboards are a prominent feature of most every “big data” project I can think of, offered by every vendor, and constructed to provide a powerful sense of control to the viewer. It seemed fitting that Novartis CEO Dr. Vas Narasimhan, a former McKinsey consultant, would build (then tweet enthusiastically about) “our new ‘control tower’” – essentially a multi-screen super dashboard – “to track, analyse and predict the status of all our clinical studies. 500+ active trials, 70+ countries, 80 000+ patients – transformative for how we develop medicines.” Dashboards are the physical manifestation of the ideology of big data, the idea that if you can measure it you can manage it.
I am increasingly concerned, however, that the ideology of big data has taken on a life of it’s own, assuming a sense of both inevitability and self-justification. From measurement in service of people, we increasingly seem to be measuring in service of data, setting up systems and organizations where constant measurement often appears to be an end in itself.
My worries, it turns out, are hardly original. I’ve been delighted to discover over the past year what feels like an underground movement of dissidents who question the direction we seem to be heading, and who’ve thoughtfully discussed many of the issues that I stumbled upon. (Special hat-tip to “The Accad & Koka Report” podcast, an independent and original voice in the healthcare podcast universe, for introducing me to several of these thinkers, including Jerry Muller and Gary Klein.)
The 2016 21st Century CURES Act is the law. It is built around two phrases: “information blocking” and “without special effort” that give the administration tremendous power to regulate anti-competitive behavior in the health information sector. The resulting draft regulation, February’s Notice of Proposed Rulemaking (NPRM) is a breakthrough attempt to bend the healthcare cost curve through patient empowerment and competition. It could be the last best chance to avoid a $6 Trillion, 20% of GDP future without introducing strict price controls.
This post highlights patient-directed access as the essential pro-competition aspect of the NPRM which allows the patient’s data to follow the patient to any service, any physician, any caregiver, anywhere in the country or in the world.
The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have proposed final rules on interoperability, data blocking and other activities as part of implementing the 21st Century Cures Act. In this series, we will explore the ideas behind the rules, why they are necessary and the expected impact. Given that these are complex and controversial topics open to interpretation, we invite readers to respond with their own ideas, corrections and opinions. In part three of this series, we look at how the new USCDI draft helps foster innovation.
The U.S. Core Data for Interoperability
(USCDI) draft is a step forward toward expanding the 21st Century
Cures Act. The Cures Act was helpful in moving the needle for interoperability
and defining data blocking. The latest draft of the USCDI is meant to further specify
what data should be shared freely.
In this article, we’ll look at the data added
to the Common Clinical Data Set (CCDS) used for ONC certification. We’ll walk
through the proposed plan to add more data over time. And we’ll explore why
this is a step in the right direction toward increased data sharing.
The bulk of the datasets in the USCDI comes
from the Common Clinical Data Set (CCDS), which was last updated in 2015. The
new USCDI draft adds two types of data:
Clinical notes: both structured
and unstructured. EHRs store these notes differently, but both are important
and helpful in data analysis.
Provenance: an audit trail of the data, showing where it
came from. It is metadata, or information about the data, that shows who
created it and when.
The Fast Healthcare Interoperability Resources (FHIR) have created standards around APIs used to access health care data. APIs developed under the FHIR standard aligns with the USCDI to meet the proposed certification rules. The USCDI draft recommends using a FHIR compliant API to access the data.
The Office of the National Coordinator (ONC) and the Centers for Medicare and Medicaid (CMS) have published proposed final rules on interoperability and data blocking as part of implementing the 21st Century Cures act. In this series we will explore the ideas behind the rules, why they are necessary and the expected impact. Given that these are complex, controversial topics, and open to interpretation, we invite readers to respond with their own ideas, corrections, and opinions.
Health IT 1.0, the basic digitalization of health care, succeeded in getting health care to stop using pens and start using keyboards. Now, Health IT 2.0 is emerging and will build on this foundation by providing better, more diverse applications. Health care is following the example set by the rest of the modern digital economy and starting to leverage existing monolithic applications like electronic health records (EHRs) to create platforms that support a robust application ecosystem. Think “App Store” for healthcare and you can see where we are headed.
This is why interoperability and data blocking are two of the biggest issues in health IT today. Interoperability – the ability of applications to connect to the health IT ecosystem, exchange data and collaborate – is a key driver of the pace and breadth of innovation. Free flowing, rich clinical data sets are essential to building powerful, user-friendly applications. Making it easy to install or switch applications reduces the cost of deployment and fosters healthy competition. Conversely, when data exchange is restricted (data blocking) or integration is difficult, innovation is stifled.
Given the importance of health IT in enabling the larger transformation of our health system, the stakes could hardly be higher. Congress recognized this when it passed the 21st Century Cures Act in 2016. Title IV of the act contains specific provisions designed to “advance interoperability and support the access, exchange, and use of electronic health information; and address occurrences of information blocking”. In February 2019, ONC and CMS simultaneously published proposed rules to implement these provisions.
On one hand, regulators are reluctant to limit private corporate action lest we reduce innovation and patient choice and promote moral hazards. On the other hand, a privatized marketplace for services requires transparency of costs and quality and a minimum of economic externalities that privatize profit and socialize costs.
For over two decades, the HIPAA law and regulations have dominated the way personal health data is used and abused to manipulate physician practice and increase costs. During these decades, digital technology has brought marvels of innovation and competition to markets as diverse as travel and publishing while healthcare technology is burning out physicians and driving patients to bankruptcy.
Abbott Ventures chief Evan Norton may have spent part of his youth on a farm, but there’s no manure in his manner when speaking of the medical device and diagnostics market landscape. The key, he says, is to avoid being blindsided by the transformational power of digital data.
“We’ve been competing against Medtronic and J&J, so that has the risk of us being disintermediated by other players that come into the market,” Norton told attendees at MedCity Invest, a meeting focused on health care entrepreneurs. “Physicians are coming to us and asking for access to data for decisions, and they don’t care who the manufacturer [of the device] is. Are we enabling data creation?”
Abbott, said Norton, wrestles with whether they are simply data creators or want to get paid for providing algorithmic guidance on how the data is used. (Full disclosure: I own Abbott shares.) Other panelists agreed making sense of the digital data deluge remains the central business challenge.
What’s received little attention from physicians or the public is the company’s quiet metamorphosis into a powerhouse focused on the actual practice of medicine.
If “data is the new oil,” as the internet meme has it, Google and its Big Tech brethren could become the new OPEC. Search is only the start for Google and its parent company, Alphabet. Their involvement in health care can continue through a doctor’s diagnosis and even into monitoring a patient’s chronic condition for, essentially, forever. (From here on, I’ll use the term Google to include the confusing intertwining of Google and Alphabet units.)
Amazon has transformed the way we read books, shop online, host websites, do cloud computing, and watch TV. Can they apply their successes in all these other areas to healthcare?
Just last week, Amazon announcedComprehend Medical, machine learning software that digitizes and processes medical records. “The process of developing clinical trials and connecting them with the right patients requires research teams to sift through and label mountains of unstructured clinical record data,” Fred Hutchinson CIO Matthew Trunnell is quoted saying in a MedCity News article. “Amazon Comprehend Medical will reduce this time burden from hours to seconds. This is a vital step toward getting researchers rapid access to the information they need when they need it so they can find actionable insights to advance life-saving therapies for patients.”
Deriving insights from data and making those available in a user-friendly way to patients and clinicians is just what we need from technology innovators. But these tools are useless without data. If an oncology patient is hospitalized, her provider may not be informed of her hospitalization for days or even weeks (or ever). And the situation is repeated for that same patient receiving care from cardiologists, endocrinologists, and other providers outside of her oncology clinic. When it comes to personalized health and medicine, both the quantity and quality of data matter. Providers need access to comprehensive patient health data so they can accurately and efficiently diagnose and treat patients and make use of technology that helps them identify “actionable insights.”
Making Sense of Blue Button, Meaningful Use, and What’s Going on in Washington …
At the recent Health 2.0 Conference in Santa Clara, co-chair Matt Holt expressed frustration about the difficulty of getting copies of his young daughter’s medical records. His experience catalyzed a heated discussion about individuals’ electronic access to their own health information. Many people are confused about or unaware of their legal rights, the policies that support those rights, and the potential implications of digital access to health data by individuals. The Health 2.0 conference crowd included 2000 entrepreneurs, consumer technology companies, patient advocates, and other potentially “disruptive” forces in healthcare, in addition to more traditional health system players.
Why is this topic so important? Until now, most people haven’t accessed their own health records, whether electronically or in paper, and I believe that making it easier to do so will help tip the scales toward more meaningful consumer/patient engagement in healthcare and in health. Access by individuals and their families to their own health records can empower them to coordinate care among multiple healthcare providers, find and address dangerous factual errors, and take advantage of a growing ecosystem of apps and tools for improving health-related behaviors, saving money on health services, and getting more convenient, personalized care.
A shorthand phrase for this kind of personal empowerment through access to digital health data is “Blue Button,” which is also the name of a public-private initiative in which hundreds of leading healthcare organizations across the US participate. The Blue Button Initiative is bolstered by the electronic access to health information requirements for patients in the “Meaningful Use” EHR Incentive Program, which is administered by CMS (the Centers for Medicare & Medicaid Services) with companion standards and certification requirements set by ONC (the Office of the National Coordinator for Health Information Technology).Continue reading…
Recently the Centers for Medicare and Medicaid (CMS) made troves of data publically available. CMS released data on hospital charges, physician utilization, in addition to other data sets. Journalists and academics were excited to potentially confirm their theories on healthcare spending.
We at The Engelberg Center hosted an event, Hacking America’s Health where experts from the Brookings Institution and the government spoke to participants regarding the impacts of data transparency on the nation’s healthcare system. The purpose of the festival is to focus on “innovators from around the world and their transformative solutions to global challenges.”
Out of this discussion emerged a consensus that data transparency could spur disruptive innovation in the health sector but overcoming several key barriers was essential to maximizing the benefits to the public.
Benefits of Data Transparency
1. Help Consumers Make Informed Decisions
Open data offers numerous benefits to consumers. The CMS data unveils the enormous variation in the cost of different treatments. Enabling consumers to find high value care providers improves the efficiency of the market. Price transparency can also uncover providers that charge unusually high prices and puts pressure on them to lower those charges. Finally utilization can reveal if a doctor uses a rare treatment with regularity. All of these data empower health care consumers to choose wisely.
2. Identify Vulnerable Patients
CMS has used open data for numerous projects to help patients. One project involves collaboration with local and state governments. Using Medicare claims information they identified specific patients who could be in special danger in the aftermath of a natural disaster. Without electricity it’s impossible to operate a lifesaving device like a ventilator or nebulizer. The claims data allows emergency officials to notify such individuals about the locations of shelters.
3. Data Mashups
Combining together data sets could help identify bad actors in the health system. For example merging data from the Sunshine Act which describe payments and items given to physicians combined together with utilization data from CMS. This could identify doctors who were using a drug or procedure due to a financial relationship rather than best practice. Other data mashups could also uncover unexpected patterns.