Tasks Drive Data // Data Powers Decisions // Decisions Power Better Care at Lower Cost
I am an engineer by degree – chemical engineering to be precise. I didn’t stay in the engineering profession very long, but I have always appreciated the training. Engineering teaches one how to think in order to solve problems. From there, data becomes the key factor in analyzing a problem, knowing what you are trying to solve for, and ultimately solving it. A problem solver is, by requirement, a data geek.
How do we fix some of the problems in healthcare? We get data -- then we mine it, analyze it, act on it. This information resides in claims data, in EHRs, etc. There is an explosion of new healthcare companies mining that data to offer solutions to providers that address major issues, major waste, and to fortify the efficacy of healthcare. Additionally, Artificial Intelligence is changing the way this information is mined and used, at an unimaginable speed, with the hope that costs are reduced and outcomes are improved. This is great stuff; any data geek can get excited about this.
Dock is a HIPAA-compliant task management solution, so why are we interested in the power of data?
You may have read in prior blogs that we at Dock Health believe “Everything in healthcare is a task” – that tasks are the actionable, most elemental units of healthcare. These tasks can be simple, one-off tasks or part of complicated workflows. And, as we discussed in “What the EHR is not,” most of these tasks are administrative in nature and are, therefore, happening outside of the EMR. They are typically “managed” on sticky notes, Excel files and notebooks. No one ever hands back that sticky note and says, “Here, I completed this at 11:32 this morning of March 5, 2021, and it took me 15 minutes.” The sticky note ends up crumpled in the trash (with a very satisfied toss), but that data is never captured. The note in the notebook has a line drawn through it, but there is no timestamp and it's not connected in any way to a data lake or warehouse. The same is true of the Excel spreadsheet.
Without the ability to see when things happened, who did them, and how long they took, there is no opportunity to establish benchmarks and best practices and optimize resources. The great thing about data is that the more of it you get, across more processes, the more meaningful it becomes. It's easier to identify the outliers and analyze the why. It becomes easier to study whether that task above could be done consistently in 13 minutes, for example. It becomes easier to ensure that people are working at the top of their license.
Dock captures these administrative tasks and timestamps them: When was a task created, to whom it was assigned, was it reassigned, was it commented on, when was it due, when was it completed, are there any related next steps, and so forth. Anything that is done (or not done) with a task or workflow is captured. As we get more and more teams on the platform, connect them to other groups and these elemental units of healthcare fly around the ecosystem, meta data flows with them.
Therefore, Dock is a data-generating machine, capturing what was previously not captured (just thrown in the wastebasket), across every aspect of the healthcare ecosystem. Not just providers, but payers; not just payers, but pharma; not just pharma, but healthcare services (labs, pharmacies, etc), mental health, physical therapy, Social Determinants of Health, etc. – all available to the data lake, all able to be mined and analyzed for your optimization.
Think of this as a bottom-up approach -- collecting data that was likely always there, yet never captured nor available, at the most elemental level, at the point where most of healthcare gets done. This is what the EHR has done for clinical data (top-down) -- fueling AI engines like Olive. Then, whether we build it internally or use existing AI platforms, our vision is to be able to use this data to surface bottlenecks, delays in care, potential dropped balls, and more at the task level.
Better data, better decisions, better care. All thanks to data.