Competitive analysis
TL;DR
In most cases, Awell replaces documents (protocols in google docs / flowcharts in PDFs) and care flows that are hardcoded into patient app / EHR / care management app;
This means the biggest competitive force acting on Awell is a build mindset and sticking to the status quo. That’s also the reason why our growth strategy revolves around category creation.
Nevertheless, other solutions exist to help care teams streamlining their clinical operations. See the comparison of Awell vs. the different categories of competitors below.
Overview
Better Health’s co-founder & Chief Product Officer explains nicely what differentiates Awell from the competition:
Similarly to Awell, our competitors create compelling products that improve the lives of patients and caregivers. But as Adam said above, these products are not solving the same problem, or not in the most compelling way. So rather than trying to square peg a round hole, we want to emphasize our differences and what we can learn from each of the above.
Healthcare CRMs
Healthcare CRMs, like Tellescope, Phase Zero and Welkin, provide platforms to manage relationships with patients. They make it easy to store all patient information, to communicate with patients and manage tasks within the care team. This, most often, also includes some workflow capabilities to automate flows like patient onboarding and pre-consultation assessments.
Although most of these tools have a great user interface and can really facilitate caregivers’ lives, there is a big overlap in functionality with the EHR, and many care teams don’t want to use 2 different systems while providing care. Additionally, their workflows are, in contracts to Awell, mostly limited to communication with patients.
Digital health infrastructure
Digital health infrastructure companies, like Source and Avon, aim to provide one modular, API-driven platform to deliver “next-generation” care.
The jury is still out on the viability of this approach (as these companies are still fairly small) but we’ve heard from customers (e.g. Wellinks) that these companies have too many features that they don’t need. Additionally, we haven’t seen the same workflow capabilities as in the Awell platform yet.
Digital health EHR
Digital Health EHRs, like Healthie, Canvas and Elation, are the “next-generation” EHRs that have been developed for more digitally-native care providers (like virtual-first care providers).
Although they already provide some basic workflow capabilities, we consider this segment more as partners as many, like Healthie and Elation, have confirmed that they don’t see workflows as part of their core business. So far, EHRs like Healthie have been happy to refer their customers to Awell as we can immediately resolve a functionality that is missing in their platform.
Clinical decision support
Clinical decision support tools, like AvoMD and SaVia Health, aim to facilitate using clinical guidelines at the point-of-care. Especially AvoMD has done this well with an integration with Epic (the EHR market leader), something that would be a gamechanger for Awell.
The big difference with Awell, however, is that the clinical guideline remains a static document in these tools. It’s available in a digital form at the point-of-care but it doesn’t automate any care activies (as Awell does).
Clinical workflow / patient engagement
Clinical workflow / patient engagement tools, like Memora, Lumeon and Luma, have a similar value proposition as Awell and we have already identified several learnings from what these companies do well (e.g. embrace NLP & AI, offer a library of reusable care programs, etc.).
However, these companies rely heavily on services. Their teams listen to the requirements of the care teams and then set up the care flows in their systems. This was the approach Awell also took before the raise in April 2020, but we realized it created a bottleneck to growth (i.e. creating the workflows internally) and many of our customers were asking for the ability to create care flows themselves.
Our success in 2022 has confirmed that the API-driven, self-serve characteristics of the Awell platform provides is a better value proposition in the long-term.
Robot Process Automation (RPA) / smart bots
RPA provides “software robots” that use computers on our behalf. The category existed for a long time with notable companies such as UiPath and Automation Anywhere. However, the traditional RPA setup has 2 main challenges:
They rely on a lot of manual work that has to be done upfront to create rules and processes to get the job done.
Whenever the UI of a tool they integrated with changes, the RPA script breaks leading to (expensive) RPA developers spending various hours deblocking RPA requests.
However, with the development of Large Language Models, new types of RPA companies are emerging (not even sure if we should call them RPA).
How? Well, RPA is really good at doing tasks that follow clear rules and use structured data. On the other hand, large language models are really good at handling unstructured data and information, making decisions, and reasoning. When you put these two together, you get “agents” that can understand what people need through conversations, break down those needs into tasks, and actually do things for users. It’s a powerful combo that expands what RPA can do and makes users very happy.
These intelligent bots will solve the above mentioned challenges:
Problem 1: It takes time to set up these RPA scripts
Solved in 2 ways:
Describe, in plain English, what they want the machine to do.
Record your screen, and send the recording to the “smart RPA tool” which will automatically create an RPA script based on your recording.
Problem 2: When UI changes, the bot breaks
With LLMs these bots will become extremely intelligent, allowing them to figure out what to do even though the UI changed completely (the tasks are still the same).
There are a lot of companies already doubling down on this:
Luminai: Rik saw a demo of the platform in NYC and it’s literally 3 steps:
Step 1: Record your screen and show what you want to do.
Step 2: Bot is generated (takes a few hours to a few days depending on how difficult it is)
Step 3: Use in practice (they have a chrome extension that allows you to trigger the script)
Automat: Just raised $3M to do the same as Luminai (they are a 2-person team).
Other companies like adept or maya are doing +- the same (although it feels less RPA).
We are obviously not a pure process automation platform, but a lot of our use cases (e.g. creating a task inside the EHR whenever a Typeform is filled in) could be done by the tools mentioned above too. So definitely something to look out for.
Additionally, the above innovation also opens the room for an important discussion: should we double down on API first integrations or should we go for “smart RPA” to reduce time-to-live? To me, an API-first mindset is still the way to go but for integrations that take a ton of time to built we should leverage RPA more and more.