Integer Health Technologies, LLC

William McCallum

Ken Grifno

Scott Roloff

Jack McCallum

A prediction and navigation engine that identifies in real-time new workers' compensation cases likely to be high-cost-sometimes referred to as outliers. The engine employs artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) on the initial entries of the adjuster notes to do so, sending a warning back to the program or system into which the adjuster is typing those notes if the engine identifies the case as a potential outlier. The engine then predicts the likely costs of each new case, whether a potential outlier or not, by comparing the keywords, phrases and text that the adjuster uses in the initial notes for that new case, combined with any other available information, against the adjuster notes and actual costs of similar historical cases in the engine's library.

High-cost medical claim prediction and navigation engine

A navigation engine for medical and/or pharmacy claims (in combination with employer human resource records or on a stand-alone basis) that quantifies healthcare outcomes and ranks healthcare providers and other healthcare items by root diagnosis based on their overall average claims per healthy day (i.e., clinical efficiency). Claims per healthy day is the adjusted claims cost per day to keep a patient healthy (or in the case of an employer, keep an employee at work), so the lower, the better. The navigation engine uses drop-down menus and/or similar techniques that require the user to select a root diagnosis on which to search, as well as other variables (e.g., provider category, geographic proximity, in-network versus in or out of network, etc.), turning an open-ended question, e.g., 'Which doctor should I go to for back pain?' to a closed-ended one “Which surgeons in my network within 25 miles have the best outcomes for back surgery?”

Healthcare clinical efficiency claims per healthy day navigation engine

A method and/or system that is a navigation engine with a visual interface that evaluates wellness programs based on their effect on the participants' healthcare costs and absences from work, and then calculates the programs' ROIs (Returns on Investment). The engine can also generate a list of employees and/or other individuals who could benefit from a wellness program but who are not participating, and the impact on the healthcare costs, medically-related absence costs and ROI if they did. In addition, the engine can recommend wellness and safety programs that have not been implemented, but should be, along with the impact such programs could have on the medical and pharmacy claims and medically-related absences.

Wellness program navigation engine

A machine learning system and method utilizing artificial intelligence that improves the provisioning of healthcare and reduces the total cost of healthcare and lost productivity. The approach creates a quantifiable assessment of quality and a ranking number measuring a provider's quality of healthcare services. The machine learning system makes a determination of quality based on a clinical evaluation database, an employee related time and attendance database, and a costing database. The system analyzes how quickly a provider returns an employee to work at or near pre-absence productivity and at what cost. The system creates a ranking number that provides employees with a comparison of providers. Employees may then be incentivized to seek high value providers.

Healthcare occupational outcomes navigation engine

A computer navigation system that represents categories and sub-categories of material with functionally labeled objects connected in a hierarchical organization. Descending nodes represent more detailed subsets of material. Hovering the computer mouse over a node displays thumbnails of the items available under it, enabling the user to search for items without opening the respective pages, transforming a literal or verbal data filing and retrieval process into a more intuitive and easy to use visual one. Once the user hovers the computer mouse over the node with the desired item and sees its thumbnail the user clicks on the node, opening the screen from which the user can access that item (or upload a similar one), or clicks on the thumbnail to access the item directly. In addition, the system employs algorithms to group items into various categories and sub-categories and assigns them to the appropriate nodes.

Growing community of inventors

Fort Worth, TX, United States of America

William McCallum