Health data and analytics companies

This is a very interesting space in the industry. I have attempted to create a classification framework. It is primarily based on three pillars - data (relationship/closeness with source), scale of technical solution, level of insights. A lot of the data and analytics companies would fall into one of the three categories. 

1. Data Providers

For the data providers I am using the Nikhil Krishnan's work here.

Originators 

• Providers or insurance companies trying to record/document the medical or claims data related to patient
• Hospitals, Clinics, Labs, Clinical Research Sites 

Data Collectors

• Being the tech side of originators, these collectors will always have access to the data flowing through their system
• Depending on the characteristics of the data it might be biased (geography, demographics etc).
• Examples include the EMR vendors like Epic, Cerner, Meditech or EDC vendors for clinical trials.

Data Brokers

• Expensive per patient record but likely to present a more complete and less biased picture of the landscape
• Tokenization works better at the stage due to multiplicity of sources
• The risk here is total dependence on data originators and data collectors
• Example include HealthVerity, Datavant etc.

Collectively these 3 segments can be called as patient registry market.

source: outofpocket health

2. Data + Analytic Solutions providers

• These companies are taking the value generated for the customer to another level. There is no value of a data unless we can draw an actionable insight from it. So that is what these companies sell - think of them as data-insights-as-a-service.
• Group 1 - IQVIA, Optum, Premeire
• Generally you can ask multiple questions but confidence-level of the answer would be moderate to high. Kind of old guards of the industry.
• Group 2 - Clarify Health, Komodo Health, Tempus (comprehensive insights-as-a-service)
• Generally you can ask multiple questions but confidence-level of the answer would be moderate to high.
• Technology is the cornerstone of these companies compared to group 1.
• Group 3 - Aetion, Flatiron Health, Kota, Concerto (Evidence-as-business)
• You can ask one precise question and confidence-level of the answer would be significantly high.
• These companies either will do lot of hand-holding while heading towards the answer or they will derive it for the customer. The customer doesn't have to worry about getting the right data or tech or experiment planning
• A few of them generate their own data having a highly stable business as compared to providers who buy the data.
• Some companies started in #2 but are now well known names in #4 are FlatIron, Medidata/AcornAI

3. Analytics Solution providers

• BYOD where D stands for data
• These companies provide software or platform services. You can come up with multiple interesting ways to group these companies.
• Group 1: SnowFlake, DataBricks etc. The platform stack for data analytics. 
• Group 2: Innovaccer, Health Catalyst etc. The application stack for data analytics.
• Group 3: HuggingFace, H2O etc. High-end tech providers (AI)
• Group 4 - Syntegra, Synthesized, Owkin High-end tech providers (Privacy)
• Unless you grow quickly, offering variety of solutions it would be difficult to survive in this section. Because as you do not have a differentiating data the success to some extent depends on being one of the first one with better execution in your swim-lane.
• Better execution is this case means extreme ease of use, significant gain in value (performance, privacy whatever is the metric) and continuous modernization of your tech stack.
• Advantage of being part of this class is you don't share the burden to ensure your data is comprehensive, high-quality, relevant and recent. All previous 4 categories would have to consider these factor seriously.

General notes on aggregated health data analytics business 

• Big players can be categorized as legacy players and new companies. Old guards include IQVIA, Optum, Premiere. New wave companies include Komodo Health, Clarify solutions 
• Key difference with the new wave companies is they are technology-first companies - started with the vision of technology being the centerpiece of the platform. And now offers SaaS platform based solutions. 
• New companies and their tech generally creates a lot of buzz but also at times FDA admissible evidence and commercially viable business  
• Business is generally generated by providing aggregated and de-identified data or insights based on that data or tech-powered-workflow which can enable generating insights.
• Out of the 5 listed above, only number 4 offers complete outsourcing options. All other categories involve the end-users getting their hands dirty while trying to figure out the data piece or the tech-piece. In a way you can view these four categories as whatever is your weakness, tech or data, the solution provider would help you deal with it.