Revenue model
The data generated as a byproduct of clinical and diagnostic services is a valuable asset. This data can be leveraged by various consumers within the healthcare ecosystem to create significant value. For example, it can be used to improve discovery of new therapies, evaluate medical policy and reimbursement decisions, and develop AI-based diagnostic tools.
The revenue model offered by datma aims to share the benefit of the value creation more equitably between data consumers and data custodians.
The potential revenue that can be generated through datma.FED is influenced by several factors:
Scope of data
The scope of data made available by the data custodian is categorized into the following data domains. Each combination of these domains leads to a unique base value for the data
Patient Demographics
EHR - Structured data
EHR - Notes & Reports
Diagnostics - Pathology
Diagnostics - Genomics
Radiology
Volume of unique patients
The number of unique patients present in the dataset
Data tokenization
The presence or ability to tokenize the data to facilitate linking of de-identified data across multiple data custodians.
Data utility
A composite score representing the utility of the data for its intended use, defined by the following concepts:
Completeness - Measures the number of unique patients where key attributes are populated with valid values
Recency - Measures the number of unique patients with recent events (e.g., diagnosis, medication, diagnostics, procedures, etc.) within the last 12 months
Longitudinal Coverage - Measures the number of unique patients who have multiple years of historical data associated with them
Number of data consumers
As each data consumer accesses a data custodian’s data and generates value from it, the revenue model enables shared value with the custodian. Each data consumer accessing the data custodian’s data results in an incremental increase in revenue, building on the base revenue