Value-based medicine demands more from providers at a time when administrative burden and burnout are on the rise. According to Medscape, nearly half of physicians reported feeling burned out, exhausted and detached from their work. Additionally, studies show 25% more providers participate in value-based care this year than in 2023, and the pressure to improve the quality and reduce the cost of care continues to grow.
With this increasing pressure, healthcare organizations need to implement new strategies to simultaneously help improve the quality of patient care and reduce the cognitive load on clinicians. Today, artificial intelligence (AI) can help deliver clinical insights into provider workflows during patient encounters to help make that work easier.
From pre-encounter to coding
Studies have found that AI can reduce administrative work for clinicians by 30%. AI-powered patient insights solutions integrated directly into clinical systems can help providers make better decisions about treatment and stay focused on care. AI does not replace a provider’s judgement but can assist clinicians by surfacing up historical patient data into the clinical context. It can even predict diagnoses based on past encounters and supplemental clinical data.
Below is how AI can play a role before, during, and after the patient encounter:
Before the patient encounter
Before the patient encounter, AI can analyze multiple sources of clinical data to create a holistic summary of a patient’s health history and uncover insights such as missed diagnoses and possible care gaps. In preparation for a patient's visit providers can access these insights ahead of time to guide them conducting a more personalized patient encounter.
During patient care
During a patient visit, AI clinical insights tools can surface insights directly into the provider’s EHR to make the information easily accessible at the point of care. Providers can use these insights to ask interview the patient with relevant questions, schedule screenings, or order lab tests, focusing the limited time during the patient visit.
Post Patient Encounter
After the patient visit, AI-assisted documentation can streamline the process of capturing clinical notes and treatment plan by following M.E.A.T. guidelines (short for monitoring, evaluating, assessing/addressing, and treating). This eases the administrative burden on providers, resulting in more comprehensive and accurate clinical evidence claims and risk adjustment submissions.
Supporting Providers with Highly Accurate Insights
For example, Reveleer worked with an Accountable Care Organization (ACO) in Florida to test our AI clinical insights solution’s ability to generate accurate insights into patient health that exceeded their existing capability. They needed a more accurate picture of patient health across their populations. However, they knew they had a large seasonal population who often accessed care out of state, making it challenging to get a holistic view of health status.
The ACO tapped our Clinical Intelligence solution to create a more complete picture of their patient’s health status. Testing a small cohort of 200 patients, the Reveleer Platform found new clinical data for 98% of the sample patients beyond what the ACO had access to in the charts alone. Using these additional clinical data sources, our AI, EVE (evidence validation engine) also surfaced potential undiagnosed HCCs for more than 60% of their patients.
Without the support of EVE, the ACO and its providers would have likely missed several critical diagnoses simply because they lacked the full picture of patient health.
Enhanced Provider Workflows
Some estimates indicate that AI-powered solutions can save the healthcare industry close to $150 billion. These advanced solutions can surface up to providers better, more accurate, and highly relevant data to support clinical decision-making. There’s an abundance of clinical data available but healthcare organizations need technology to help discern what matters most without sacrificing accuracy and or increasing cost.
To meet the needs of providers, AI solutions should be able to:
1. Provide advanced analytics with real-time clinical insights
Providers need to access insights in real-time, not at discrete points throughout the year that may not line up with patient visits. These insights must be highly accurate and transparent to be effective and support the provider’s decision-making.
2. Include interoperability and multi-channel data integration
Leveraging data from multiple sources including the EHR, health information exchanges (HIEs), and other external data sources to supplement charts and build the most accurate picture of the patient journey.
3. Prioritize point-of-care integration
Finally, clinical insights can only make an impact if providers can access this patient information easily – during the patient encounter and directly from within the EHR.
Ultimately, AI clinical insights solutions empower providers with the data they need to make the best decisions for their patients’ health while saving time and reducing costs. When integrated into the point of care, these solutions transform the provider workflow by making it more efficient and allowing providers to do what they do best – deliver the best care possible to their patients.
For more information about how AI can better personalize and improve patient encounters, learn more here.
OIG is auditing more health plans for Medicare and Medicaid Overpayments at a time when payers are already concerned about lower reimbursements.
Learn More →Value-based care companies are using AI to understand patient health and find undiagnosed conditions through prospective risk adjustment programs.
Learn More →Value-based care companies are using AI to more completely understand patient health status and find undiagnosed conditions through prospective risk adjustment programs.
Learn More →