Healthtech, digital solutioning & more

 1. 3M Health Information Systems:**    - **Offerings:** Combines coding references with natural language processing (NLP) technology.    - **Key Features:** Automatically suggests codes for clinical documentation improvement, aiding coders in building a comprehensive data library. 2. Alpha II:**    - **Offerings:** Provides Easy Coder, a web-based coding tool, and CodeWizard for development solutions.    - **Key Features:** Enables administrative and clinical staff to look up codes, perform edits, and implements complex coding logic to improve the revenue cycle. 3. Care Communications (CIOX Health):**    - **Offerings:** Collaborates with hospitals and health systems for coding quality improvement, clinical documentation enhancement, and implementing solutions like RAC and MS-DRG. 4. ClinNext (SabiaMed Healthcare Technologies):**    - **Offerings:** Guides users to appropriate ICD-10 diagnoses, automates code conversion, ...

Data is a double-edged sword: it can help you understand the world or get you lost. But with the right tool to store and analyze your data, you can hold the world in your hand. Take a peek at Snowflake vs. Databricks vs. AWS Redshift, three cutting-edge software products to manage your data. Read more  Snowflake vs. AWS Redshift vs. Databricks: Comparison Guide (ideas2it.com)  

The role of data in the aviation sector has a storied history. Airlines were among the first users of mainframe computers, and today their use of data has evolved to support every part of the business. Thanks in large part to the quality and quantity of data, airlines are among the safest modes of transportation in the world. Read more here  https://www.databricks.com/blog/accelerating-innovation-jetblue-using-databricks

  Faced with clinician shortages, an aging population, and stagnant health outcomes, the healthcare industry has the potential to greatly benefit from disruptive technologies such as artificial intelligence. However, high quality and usable data are the lifeblood of any advanced analytics or machine learning system, and in the highly complex healthcare industry, data quality (DQ) has historically been poor, with limited standards and inconsistent implementations. With the potential to impact a patient's care and health outcomes, making sure healthcare data is of high quality and usable couldn't have higher stakes. As a result, healthcare companies need to ensure their foundational data is truly usable – defined as accurate, complete, timely, relevant, versatile and use case and application agnostic – before using it to train advanced machine learning models and unlock the promise of artificial intelligence. Read more on this page https://www.databricks.com/blog/driving-data-usa...

Claim adjudication is the process that every insurance payer goes through to determine how much they owe a provider based on a claim that they received. While working through this process, the insurance payer makes one of three decisions per claim… #To pay the claim in full #Reduce the amount paid to the healthcare organization #Deny the claim Ref https://etactics.com/blog/adjudication-of-claims Also see  The Five Steps of the Claim Adjudication Process https://www.linkedin.com/pulse/five-steps-claim-adjudication-process-jeanne-nicole-byers?utm_source=share&utm_medium=member_android&utm_campaign=share_via