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Collecting healthcare data with registries has never been more urgent or meaningful. Registries allow providers to set up a virtuous feedback cycle, improving quality initiatives and patient care. However, the time and effort required to contribute your data are costly and affect the quality of patient care today.
Getting data into a registry is time-consuming and expensive. It takes the skills and time of a data abstractor to make it happen—most often taking time away from caring for patients. Atlas is Carta Healthcare’s solution for that data abstraction. We use artificial intelligence to translate the data from your clinical notes and medical records into content recommendations. It then auto-fills fields, assisting abstractors so they can process registry cases with greater efficiency. LEARN MORE »
As part of the abstraction process, Atlas organizes the data. To maintain your connection with the process, Atlas is a “glass box” process, so abstractors can trace data back to its source and view it in context. This enables the recommendations to be more trustworthy because you can understand how they came to be. We also support a powerful search of the patient’s medical records to help complete difficult fields. Standardized data also allows for other internal analyses. LEARN MORE »
We’re excited to announce our collaboration with the American College of Cardiology (ACC) to provide one unified interface for all National Cardiovascular Data Registry (NCDR) registries. The NCDR worked with Carta to establish efficiency gains for completing submissions and validating the quality of the data produced by Atlas. Providers can now start working with Atlas to manage submissions and normalize their data to industry standards (FHIR). LEARN MORE »
Our team of experienced data abstractors can do your data abstraction. We take care of backlogs of cases, training, retention, and submission for you. Do more with your FTEs and budget. Of course, your internal team can leverage the software instead. LEARN MORE »
Maintain your participation in data registries by boosting efficiency and combating burnout in data entry.
The need for relatively few structured data fields makes integration time significantly lower than the industry standard.
Unify disjointed data types into a single model to provide a more complete snapshot and full analysis.
The promise of AI is here. Natural Language Processing (NLP) algorithms parse clinical notes more quickly and accurately to help you or our experts interpret the data.
Simply put, you have information in your computer system already. That information needs to be pulled back out of the EHR and clinician notes and processed in such a way so it can go back into a data registry.
Artificial Intelligence uses mathematical equations or algorithms to read through data and process it to assist in your decision making. Many times, those algorithms are hidden and mysterious. That is referred to as a “black box.” Data goes in, something unknown happens, and data comes out. “Glass box” simply means that you can see what’s going on during that middle step. It’s not a mystery.
We know, another acronym. FHIR stands for Fast Healthcare Interoperability Resources. It just means that data meeting this standard can be shared more easily between different healthcare systems. The standard was created by the Health Level Seven International healthcare standards organization.
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