Preventing dangerous and costly episodes of DKA is a goal of diabetes care, but clinicians currently lack the tools to predict DKA events. This study sought to compare performance characteristics of an RNN model with that of a LR model to predict hospital admission for DKA in the next 180 days.
With the risk of COVID-19 overwhelming hospital systems, many healthcare organizations are considering how best to use their existing resources (primary care providers, advanced practitioners, nurses, care managers, etc.) to help prevent COVID-19 related hospital admissions.
Listen to Cyft’s VP of Clinical Improvement, Caitlin Brennan, as she explains how the combination of data and value based payment models can help improve care for people with serious illness.
See how Cyft is turning data into better surgical care.
Do you think Amazon purchases a 3rd party machine learning tool to tell them what books you might want to order? No. So why do we expect 3rd party algorithms to solve our core business problems in healthcare?
Grand Rounds by Cyft CEO Dr. Leonard D'Avolio at Children's Mercy Kansas City.
Dr. D’Avolio spoke at BrightHealth’s client conference on the difference between traditional analytics and the need for performance improvement in value-based care.
In this episode of the In Context podcast, we welcome Len D’Avolio. In his conversation with Kathryn Hume, they talk about what does and doesn’t work in helping companies shift from a deterministic to a probabilistic operating model through the lens of the healthcare industry.
Painfully little has been written for non-technical healthcare leaders whose job it is to successfully execute in the real world with real returns. It’s time to address that gap for two reasons.
We usually deal with smaller sets of rich but messy data (sample sizes in the hundreds or thousands). 10k rows vs 10M rows of claims data tend to be equally useful (or useless) for most problems.