With many organizations moving towards a value-based care model, it is critical that clinicians have access to a patient’s complete medical history to ensure that the care delivered reflects a patient’s unique health needs when they need it most. However, with 80% of patient data unstructured, it is difficult for clinicians to access a clear picture of a patient’s health history, let alone manage the amount and various forms of patient data that they must sift through to make the appropriate clinical assessment.
Prior to electronic health record systems (EHRs), paper charts made it difficult for medical offices to keep patient data accessible and current, leading to an incomplete picture of the patient. Even now, with the developments of EHRs, there is still a large amount of patient data that is siloed across different systems and formats, still making it challenging to read through and filter down to relevant data…until now.
Artificial Intelligence (AI) is a technology that creates new possibilities for healthcare. The power of AI can assist clinicians from improving clinical decision-making to reducing administrative workload to driving financial performance in value-based care. AI enables these opportunities with its ability to:
- Extract patient data across various EHRs, formats, and other systems
- Enable the assembly of the data with NLP
- Scan through a patient’s data with machine learning and deep learning techniques to drive new insights about the patient
AI can arm clinicians with a clear picture of a patient’s longitudinal medical record and ultimately power a patient phenotype.
Understanding the Patient Longitudinal Medical Record and Patient Phenotype
The patient’s longitudinal medical record is needed to identify a patient’s current state of health based on a comprehensive view of the member’s healthcare history. In order to build this longitudinal patient record, it is imperative to have a system that can accurately capture a variety of patient health data such as past diagnosed conditions, lab results, medications, procedures, etc., from disparate systems.
This longitudinal summary of a patient care journey is only the beginning, as deriving relevant and timely insights is more challenging but necessary for a successful value-based care program. That is why Apixio has developed its Apicare prospective solutions suite. This suite includes two solutions, Apicare Analytics and Apicare Pre-Visit, that identify and predict patient health insights in near real-time to empower healthcare decision-makers to drive better outcomes and more affordable healthcare.
How Apixio Utilizes the Patient Phenotype Today with its Apicare Prospective Suite
With Apixio’s Apicare prospective suite, organizations have access to a patient’s phenotype. Our solution utilizes AI to structure and analyze a patient’s longitudinal medical record to create critical characteristics and signals on future health conditions. As a result, clinicians are provided with evidence-based insights about existing and suspected member conditions, and with this data, clinicians can deliver more complete precise care.
With a member’s health constantly evolving, it is imperative to have a solution that is consistently working to capture the patient data for a complete and accurate patient health record. With Apixio’s Apicare prospective suite, teams will be able to access trusted patient data when and how they need it, analyze patient health history more efficiently, and deliver care with high confidence – all to support their organization’s value-based care programs.
Contact us to learn more about our Apicare suite and how it can improve your value-based care program.