Health care as an ultra large-scale system
To solve the problems of interoperability and health IT, we should think city planning, rather than building architecture
Last month, Senator Romney proposed a new agency within HHS focused specifically on public health data. The Center for Public Health Data would be a stand alone agency focused specifically on collecting de-identified data to inform the general public and support government and public health decision makers. In the wake of the performance of the CDC with the COVID pandemic (and the influx of money for data modernization) there are a number of similar initiatives aimed to modernize the public health infrastructure (HIMSS , Bipartisan policy report , Executives for health innovation, and many more) .
Some propose a one-size-fits all, closed garden approach with public health as a one-off, separate from the rest of the health IT infrastructure. Others propose that we should take what we know about enterprise architecture and “super size it” to fit into a national framework.
While there isn’t a “wrong” framing, some ways to frame the problem are better than others. Einstein is quoted as having said, “If I had an hour to solve a problem I’d spend 55 minutes thinking about the problem and five minutes thinking about solutions.” This is the same issue with framing. How you frame the problem is critical to what solutions you get.
I believe that we have been framing the problem incorrectly–and we continue to get solutions that don’t solve the problem until we change our perspective.
My assertion: we need to frame health care as an ultra large-scale system .
We’ve all interacted with a ULS before — the world wide web is an example of a highly distributed, ultra large scale system that handles billions of websites, searches, and information. Other examples of ultra-large scale challenges include solutions for climate change, networked transportation (with autonomous vehicles), homeland security and military preparedness. Most hard, interconnected, complex problems are ultra large-scale problems. And framing the problem as an ultra-large scale system gives you a set of underlying features of the problem, and a different way to evaluate solutions..
Decentralized
Health care in the US is decentralized. Public health is decentralized with states and local agencies having wide latitude for how to address public health issues. This means that any solution for health IT or for public health will require a decentralized solution. Creating centralized databases or development approaches won’t match the way that our health care system is organized.
Conflicting/Unknowable and diverse requirements
In software and architecture development, we often want to get the requirements of the system first, and then build a system that is capable of meeting those requirements. The problem is that it is nearly impossible to get the requirements for health IT systems before you begin, and even if you do, the requirements are likely to change. This means that we need to take an incremental, modular development design approach that allows for flexibility as the systems evolve and grow. Otherwise we end up with a “rip and replace” solution that never achieves the kind of success that is needed.
Continuous and evolution with heterogeneous capabilities
Not every hospital or public health agency is at the same level of sophistication when it comes to electronic data. Some academic medical centers have fully digital solutions, sophisticated data analytics, and interoperable systems that can communicate seamlessly with the outside world. Other hospital and public health agencies are trying to get their fax machines to work more efficiently, still struggle with the simplest reports, and revert to sneakernet systems to work around problems. We need a health IT system that is capable of letting everyone participate where they are, and supporting evolution and growth for those organizations that are lagging.
Normal failures
Someone wise once asked “how do fail safe systems fail?” — the answer: “Fail safe systems fail, by failing to fail safe”. When system are complex, it is normal for things to fail from time to time. What that means is that we need to build for resilience and recovery, not just to pull up the draw bridge. Systems need to be able to prevent negative feedback loops that propagate failures, and need to have the resilence to recover from a data breach, a system failure, or a
Sociotechnical systems
This is perhaps the most important feature on an ultra large scale system. Patients and health care providers are not just interacting with the Health IT systems, but they are part of those systems. We need to build systems that include people in the processes, the technology and make sure that human computer interaction is not just an interface, but a part of the system.
What does this framing mean for health IT?
We need to change the way we approach the problem. Often we think that if we build a single system, we can solve the health care problem. This is the equivalent of trying to build one enormous building and having it work for every purpose that a person might need. I believe that healthcare IT is not a problem of “architecture” (and building a particular building) but of “city planning”. It’s the difference between a blueprint for a building, and the elements that help a city thrive: basic underlying infrastructure (water, roads, security), incentives for certain kinds of behaviors (zoning incentives for growth, building codes for safety), and a focus not on building a particular building, but creating a rich ecosystem that creates value for everyone.
What does this mean for healthcare?
- Healthcare is decentralized: Fragmentation of data is a natural side-effect of our fragmented and decentralized health care system. Rather than trying to centralize data, we need to find ways to link and aggregate data in dynamic ways that match how healthcare delivery is organized..
- Understanding the technical needs of healthcare is hard: Because it is hard to know the requirements apriori, we need to build incrementally in a flexible and modular way. All in one solutions that try to integrate all aspects of data, linking, normalization and analysis may be attractive at first glance, but as requirements change, they become less resilient to change. Modular, integrated, and standards-based ways of integrating data are far more effective in the long term.
- Make health IT systems simple, interoperable, and extensible: We need to make sure that sophisticated organizations are not held back in the work that they do, while we enable those with fewer resources to participate in the Health IT ecosystem. Systems that can provide backward (and forward) compatibility allow the individual hospitals and public health agencies to be able to mature at their own pace.
- Data breaches will happen–build in privacy from the ground up: We should anticipate that identifiable data is at risk for breach, and should do everything we can to mitigate that. This means we need to build privacy into the foundation of the health IT system, and recognize that it’s not if, but when data may become compromised. Reducing that risk by limiting the amount of PPI that is shared is essential to preventing a failure of our systems to ensure privacy.
- Never forget the people are part of the system: In everything we do, we need to see these systems from the patient and the health care providers perspective. Patients are not the objects that we “do” things do in health care, but they should be active participants in their care, and the technology that we use to support them should also acknowledge the way that patients and healthcare providers interact with the systems.
Everyone has their role in an ultra-large scale system
When we frame healthcare IT as an ultra-large scale system, everyone plays a role: We need basic standards for collecting, securing, moving, and understand health care data from standards organizations and public-private partnerships. We need the government to establish rules for safety, access and enforce following the rules. We need incentives for organizations to build useful tools and systems that fit into this healthcare city. And we need to recognize that we are building this system to support the providers and patients who live in it every day.
Framing health care systems right will lead to better solutions
The Romney proposal is on the right track, but it needs to rely on a distributed health care system, protect the privacy and security of patient data, and create a valuable tool for public health to use. It shouldn’t try to create a one-size-fits all solution, but identify the importance of data to inform decision making.
Framing matters. And when we get the framing wrong, we run the risk of suggestion solutions that don’t match the problem we are trying to solve. Framing the health care system as an ultra large scale system allows us to consider the unique characteristics of such a system, and create resilient, capable health IT systems that can adapt and grow as our data and health IT needs change.
