#240 Driving to Better Healthcare Patient Outcomes Through Data - Interview w/ Smriti Kirubanandan

Sign up for Data Mesh Understanding's free roundtable and introduction programs here: https://landing.datameshunderstanding.com/

Please Rate and Review us on your podcast app of choice!

If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here

Episode list and links to all available episode transcripts here.

Provided as a free resource by Data Mesh Understanding / Scott Hirleman. Get in touch with Scott on LinkedIn if you want to chat data mesh.

Transcript for this episode (link) provided by Starburst. See their Data Mesh Summit recordings here and their great data mesh resource center here. You can download their Data Mesh for Dummies e-book (info gated) here.

Smriti's LinkedIn: https://www.linkedin.com/in/smritikirubanandan/

Smriti's HLTH Forward Podcast: https://hlthforward.buzzsprout.com/

In this episode, Scott interviewed Smriti Kirubanandan, a Healthcare and Public Health Data Expert at a large consulting firm. To be clear, she was only representing her own views on the episode. Much of the challenges and opportunities discussed in this episode are more on the US side because of the not-so-well-functioning healthcare system there.

Some key takeaways/thoughts from Smriti's point of view:

1. In healthcare, it's easy to lose sight of the patient in the data - focusing solely on a condition, an area of the body, or a set of data instead of a person. It's vitally important to be focused on the data through a lens of treating the patient as an entire person.
2. !Controversial!: It can sound time consuming to interact with data "in a much more intimate format" much like a 1:1 conversation but it's very important to drive to better outcomes. Instead of automated decisioning, we can point our tooling to compile the relevant information better to make decisions faster without removing the care or the person. Machines making automated decisions leads to worse patient outcomes.
3. "Obviously, privacy is important. Ethics is important. How do we interconnect this data and how do we get to communicate amongst" the payers and providers? So physicians can look at a much more complete picture of the patient to treat them better.
4. There are many organizations collecting important health data about people. We need to rally around the patient outcomes instead of the financial outcomes and combine the data. Easier said than done of course.
5. ?Controversial?: Companies with important health data need to lean forward at the table, to buy-in on collaborating around sharing data or we will continue to have suboptimal patient outcomes.
6. More organizations should make it possible to 'act local' relative to individual health. Instead of every decision being a very complex one, can we make things easier to simply make health progress if not 'fix' everything for someone's health. Basically, make it easier to make small decisions around more concrete and focused areas, much like a domain in data mesh.
7. It's very important to empower people to leverage their own health data so we have to focus on getting them access and then giving them the power to do something with their data to drive better outcomes.
8. There are 3 big issues we need to tackle simultaneously: 1) How do we give access to relevant and useful data to caregivers? 2) How do we ensure digital equity? And 3) how do we share data ethically?
9. Think about interoperability - can I pull data from one system to integrate into my system - and interconnectivity - a more two-way interoperability/integration. We need to focus on interconnectivity far more.
10. Especially in something as important and complex as healthcare, it's crucial for the data and engineering people to stay focused on target outcomes and not get lost in the code/work. A shared vision at the project and organization level are key.
11. Many data projects go wrong because we still struggle with communication. Not that we aren't communicating but keeping all parties to data work aligned and in sync as learnings emerge is very hard. And data work needs to allow gray areas, which it often doesn't do well currently.
12. Value-based care is a really important aspect of getting people the best care and data can help support that well. But it requires a lot of ethics and transparency to get there.
13. ?Controversial?: Digital twins of actual people could change healthcare in major ways. If done right, it could greatly improve the ability to treat patients because of the ability to test against negative health outcomes and find more optimal treatment plans.

Smriti started out the conversation with a bit about her background and then jumped right into a key challenge in data around healthcare today: treating the patient as a person and not a set of data points and measurements. How do we look holistically at a person and focus on what would be best for their health AND life - the two are intrinsically linked. We still want to drive insights but personalized care, at least in the US, seems to be on the out and we can bring it back better with better data.

Can we actually interact with healthcare data at the person level instead of at the billing code level? Smriti believes we can - that instead of letting the automated tooling make the calls on important health decisions - such as if key procedures or tests are authorized by insurance - we can use the tooling to allow a more "intimate" interaction with what the person is going through and how can we serve them best. That we can better leverage tools to make more humane decisions for folks.

For Smriti, it's still a very tough challenge for how do we get data to interact across the various healthcare data silos, how do we smoothly exchange this data. And how do we tackle the governance of making the data interconnect? Right now, physicians cannot see a large amount of crucial patient data; but is that on patients to connect the data between offices and facilities so doctors have a more complete view? How do we maintain privacy if we are sharing information across systems? What about ethics, do we really want to give a lot of these companies very intimate health data? Scott note: see the recent acquisition of One Medical by Amazon - they are now supposedly requiring patients to waive their HIPPA rights to get care.

Because there are so many challenges around integrating healthcare data across so many systems/silos, Smriti believes that one company itself can't make that big of an impact to the overall system. BUT each company being better about doing their part can help achieve a data-driven aspect to healthcare that leads to better patient outcomes. There needs to be more of a concerted effort to collaborate in the right ways.

In Smriti's view, it's very important to empower people to make better health decisions for themselves driven by data. That means giving them access to more of their data, giving them the capabilities to leverage that data to make decisions, and then empowering them to actually act on those decisions. There are some pretty basic things we can do to improve the health of our fellow citizens and it's on a number of people to keep the pressure on to move forward on that. Not one entity can do it alone but we should all be pressing for better solutions.

Smriti talked about 3 big challenges to sharing our data and driving better patient outcomes. The first is how do we actually get data in front of our care-givers? How can we empower the individual to share that data and how can the physicians or other care-givers access it and drive better patient decisions? The second is how do we ensure digital equity? Many people don't have access to good internet. Many are not digitally literate enough to actually participate in data sharing. How do we empower them to participate in better health outcomes? And the final challenge is how do we actually share this data ethically and with empathy? All of these are being worked on but it takes a very large cross-org contingent to move things forward. Everyone can play a part but it will take a lot of collective work.

Interoperability versus interconnectivity is something Smriti is passionate about because interoperability doesn't really ensure that two systems can share information all that well - it might be that your data is in a proper format but your definition is way different than mine. Interconnectivity is about a two-way collaboration and easy integration between systems around data in her definition. That interconnectivity is necessary to really supercharge our health data revolution :)

Smriti talked about a challenge in data that many past guests have touched on - how do you keep people focused on target outcomes instead of the minutiae of the work, keeping them from getting lost in the code instead of what you are trying to achieve. It's key to have a shared vision about what is the goal and why are you doing the work. And if people lose sight of that, you need to bring them out of the weeds or you'll get very interesting solutions that don't solve actual important problem.

When asked why data work seems to not net expected results so often - the 80%+ of analytics initiatives don't meet expectations statistic - Smriti pointed to difficulties in communication. Not that we aren't communicating but the challenges around how do we quickly iterate together and share small-scale incremental learnings so reality and expectations are not constantly drifting apart. Basically, communication is hard and we need to place more focus on getting it right - and having a wider tolerance range initially of what 'right means - but there's no silver bullet. We need to be able to be vulnerable with each other and operate in gray areas :)

Smriti really believes in the concept of value-based care. But to get there, we need transparency around price and care. Individuals need to have access to their information but also need to equip themselves with the knowledge of how to leverage their data to get better care. It isn't all on the care workers.

Digital twins in healthcare is something Smriti is really excited about. A digital twin of a person gives providers an ability to potentially test reactions to different treatment protocols, optimizing positive outcomes and hopefully minimizing negative outcomes. Physicians can test a number of treatments simultaneously without experimenting on the patients themselves :) Healthcare digital twins are in their very early stages but she is quite excited about the possibilities.

Data Mesh Radio is hosted by Scott Hirleman. If you want to connect with Scott, reach out to him on LinkedIn: https://www.linkedin.com/in/scotthirleman/

If you want to learn more and/or join the Data Mesh Learning Community, see here: https://datameshlearning.com/community/

If you want to be a guest or give feedback (suggestions for topics, comments, etc.), please see here

All music used this episode was found on PixaBay and was created by (including slight edits by Scott Hirleman): Lesfm, MondayHopes, SergeQuadrado, ItsWatR, Lexin_Music, and/or nevesf