Are we making progress with the transparency of health care and use of data? The 10th Anniversary Health Datapalooza prompted reflection among stakeholders on how the use of data in healthcare has evolved and revolutionized the industry in a relatively short period. A decade ago, EHRs were somewhat new to the scene and researchers, consumers, and policymakers had a difficult time getting access to data. Today, things are different. We’re inundated with data and our challenge is what to do with it all. How can we best leverage this information to inform consumer decision-making? Clinician decision-making? Adapt payment models and reward value of care? The industry is grappling with big questions, and the continuous advancement of technology and proliferation of data make it hard to get ahead.
In March, we surveyed Datapalooza participants on where we are and what’s in store for health data, technology, and policy matters. Here are some broad insights from our community of data enthusiasts…
Impact: Health Data Liberation Movement
Over the past ten years, the government has been making more and more data available from clinical, administrative, and public health sources. We were curious about what Health Datapalooza participants thought about the impact of this “Health Data Liberation Movement.” The responses varied with no clear consensus, suggesting that this movement has had wide-ranging effects. 22% of participants feel the movement sparked technology innovation, while 21% say it has led to greater understanding about disparities in spending and outcomes. The remaining responses were about evenly split, with participants responding that these efforts have enhanced transparency about cost and quality, inspired consumer advocacy for access to data, and fueled value-based healthcare practices. Undoubtedly, the benefits have been many. Perhaps most importantly, patients are more knowledgeable and engaged in their care.
More Data, More Power
Consumerism in health care represents a major cultural shift that’s here to stay. Key attributes of a consumer-oriented system – transparency, value, and choice – are powered by data. As people have easier and comprehensive access to their health information, they’re becoming more informed and empowered to make decisions about their care. Within the broader context of a health care system transitioning to one that pays for quality over volume of services, more patient engagement and choice may significantly affect industry practices and norms.
Datapalooza participants think one facet of patient-engaged care will only continue to grow, and that is the use of remote health devices that collect and transmit data. Our survey respondents predict that by 2025, at least a quarter of people in the U.S. will be using some kind of wearable. Almost one-third of respondents think it will be more than 50% of people. More remote health devices mean more involvement in health, and yes, even more data.
Key questions remain, such as, how can we best capitalize on this additional data? Will the evidence support its use to improve outcomes? As our reliance on data and its utility continue to grow and deepen, it will be important to recognize its limitations and not lose sight of the role of humans. In a recent article in Health Affairs, a mother of a child who is chronically ill cautions against the pervasive use of “consumer” in health care. Health care is inherently different than other consumer-driven industries (do you really have a choice about what doctor to see when you’re in the Emergency Department?) and she argues, likening patients to traditional consumers is not always appropriate or appreciated. Another recent piece echoes these sentiments and underscores that while data is a powerful resource, how it’s used to facilitate human-to-human interaction must remain the key issue. The author quotes, “Trust is the touchstone of consumerism.”
Changing Views on Data Privacy and Security
This trust relies heavily on privacy and security of health information. We asked respondents, what is the prevailing attitude toward the current state of privacy and security protections? Two answers emerged as leading perspectives on this issue. 37% responded, “a general lack of understanding about the issues,” and 35% responded, “consumers’ desire for greater sharing and use but with more control over uses and users.” A minority of participants feel it’s the consumers’ desire for more control of personal data or, the consumers’ wish to opt out and decline having data shared under any circumstances.
Despite all of our progress with data and innovation in health care, there are formidable barriers to the seamless exchange of information. In our survey, we asked—what are the biggest barriers to interoperability? And the response was markedly divided. About one-quarter of respondents feel the largest barrier is lack of standards for data exchange, while another quarter thought data blocking by providers or software companies is the most substantial problem. The rest of the responses are about evenly split among insufficient experience with business process that facilitate exchange of data, security concerns, and the inability to effectively manage data sources.
Recently published rules and regulations (e.g., Trusted Exchange Framework and Common Agreement, CMS interoperability rule), intend to expedite interoperability and enhance liquidity of data. Time will tell how the rollout of new policies will affect the system.
AI in Health Care is Happening
One topic with much more agreement among our community of data experts is what the future holds for health IT. We asked meeting participants what kind of technology is likely to have the biggest impact in the next few years and more than 40% responded, “the use of analytics and artificial intelligence to gain better insights from health-related data.”
This response certainly reflects movement in the field. In a recent analysis of the most-funded private digital health companies, the majority provided data analytics services, including AI. The possibilities seem endless but in the short to medium-term, what might this look like?
We can’t know precisely of course but leading trends can give us a glimpse. And the utility of AI in health care extends far beyond robot-assisted surgery. Examples of what we’re talking about include:
- Prevention and diagnosis. Predictive analytics and modeling to enable prevention and earlier diagnosis.
- Personalization of treatment options. In a previous blog post, we discussed an emerging form of AI, called “reinforcement learning” and the use of algorithms that draw from experience to map the most effective treatment options that we know.
- Research. Machine learning and AI are becoming powerful tools in health outcomes research, and helping to understand issues such as health disparities and cost and quality.
The health care system has seen a lot of change over the past 10 years and much, if not all, of this change can be credited to advancements in the use of data and health IT. From time to time, it's important for all of us to take note of progress that has been made and challenges that lie ahead. The insightful community of Health Datapalooza participants have enlightened us with their thoughts and predictions on what’s to come, and we look forward to continuing the conversation, including at our upcoming Health Data Leadership Institute convening in September.