Hi, I'm Kresimir at DocOne. Our API infrastructure enables any health-tech startup or an established company to quickly build an intelligent search for different types of end users, including patients, physicians and life science companies.
A user can run ultra-specific searches for physicians, specialties, medical conditions, procedures, therapies, articles and clinical trials. We're adding new data types such as healthcare/life science organizations, conferences, social media and industry relations/payment data.
The basis of the platform is a comprehensive, continually updated knowledge graph, built with the help of data science, especially NLP.
We'd love your feedback and we'll be here to answer any questions.
There are lots of publicly available databases and coding systems for healthcare / life science, but many of them are complicated for normal people (even normal developers) to use and understand.
For instance, SNOMED is an ontology. A lot of people try to use it like a taxonomy, but it is supposed to be used as an ontology. Kieth in Accounts does not know what an ontology is and doesn't want to know. He should not have to know - he just wants a lookup for medical procedure billing.
I can see the value in your attempt to present a gentler interface ontop of these more complicated and intermeshing databases. Can I recommend that you figure out how to make it play nice with Excel, PowerBI, and maybe R?
Right now we're relying on publicly available data (e.g. CMS claims, publications, clinical trials, conferences). We plan to add commercial claims in the future. If a client has a specific dataset on physician procedures they want to use, we can easily intake that file and build them a search endpoint that uses their data.
Yes, we support searches based on CPT codes. We will add ICD-10 (conditions and procedures) soon. We can also accomodate a client's own physician dataset. Do you have a use case? We can chat.
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A user can run ultra-specific searches for physicians, specialties, medical conditions, procedures, therapies, articles and clinical trials. We're adding new data types such as healthcare/life science organizations, conferences, social media and industry relations/payment data.
The basis of the platform is a comprehensive, continually updated knowledge graph, built with the help of data science, especially NLP.
We'd love your feedback and we'll be here to answer any questions.
For instance, SNOMED is an ontology. A lot of people try to use it like a taxonomy, but it is supposed to be used as an ontology. Kieth in Accounts does not know what an ontology is and doesn't want to know. He should not have to know - he just wants a lookup for medical procedure billing.
I can see the value in your attempt to present a gentler interface ontop of these more complicated and intermeshing databases. Can I recommend that you figure out how to make it play nice with Excel, PowerBI, and maybe R?
This looks like a great tool. I just had some questions about DocOne.
Does DocOne support searches across CPT and ICD-10? Do you guys have a pricing model to use the API?