Clinician-created decision rules to assist you in identifying clinical conditions based on your practice.
With Pallas solutions:
Automate clinical conditions identification before patient visits.
Flag all clinical conditions that risk adjustment models need to identify complex patients.
Deliver more without having to hiring more coders or leaning on payers.
Provide clinically accurate, specific information to clinicians in identifying clinical conditions.
Ensure clinical condition flags are ready for all clinicians on day one (and not have rolling input from coding team.)
Identify clinical conditions that are consistent and compliant with best practices.
Blog
Understanding Clinical Risk in Value Based Arrangements
I welcome comments, feedback and opportunity to learn more or collaborate. Tweet @manas8u What is risk? In this document, I will be focussing on elements of risk relevant to Value […]
CMS-HCC Prospective Risk Adjustment
I am learning in public and welcome comments, feedback and opportunity to learn more or collaborate. Tweet @manas8u This is working draft of my understanding of ACO Risk score. This […]
In the News
What’s in Population Health benchmarks?
Accountability and improvement is a key tenet of population health and organizations invest significant data and human effort in tracking performance. However, to establish accountability is important to identify appropriate […]