A new study examines past and present research to determine changes in Hispanic population health findings over the years and necessary improvements still to be made.
In demographic and health...
Population health analysis is closely intertwined with value-based care. Not only can population health analytics help identify patient care gaps, but strategies can identify patient-wide interventions...
Through data analytics, Spinal Cord Injury Model System researchers identified residential mobility as a social determinant of health in individuals with spinal cord injuries.
The study’s...
Using artificial intelligence technology, Terasaki Institute for Biomedical Innovation (TIBI) researchers developed and validated an image-based detection model for COVID-19. The model analyzes lung...
Using predictive analytics is a critical step toward chronic disease prevention, allowing providers to recognize early signs of illness and intervene. While some may be at a higher risk of chronic...
By using data analytics, Parkview Medical Center and Pieces Technology addressed social determinants of health and decreased their average length of stay rates among patients.
Parkview Medical Center...
University of Michigan researchers are developing a model that uses predictive analytics to determine an individual’s survival and recurrence outcomes for patients recently diagnosed with...
Many healthcare systems have made creating high-quality and value-based care a top priority. Southwestern Health Resources (SWHR) used clinical data and predictive analytics to put a total cost of care...
UT Southwestern Medical Center researchers have discovered a method to predict which skin cancers are highly metastatic with the help of artificial intelligence. The study in Cell Systems examined how...
To effectively document the severity of patient conditions and use risk stratification, the Community Health Network (CHN) in Indiana has streamlined hierarchical condition category (HCC) coding to...
The National Committee of Quality Assurance (NCQA) has launched a new Data Aggregator Validation program that will assist in ensuring the validity of clinical data used for quality reporting. The new...
Medical University of South Carolina (MUSC) researchers discovered a biomarker in blood samples that with predictive analytics can determine which patients will develop COVID-19 symptoms.
It remains...
University of Pittsburg researchers used a data analytics algorithm to algorithmically cluster individuals with chronic pain by pain distribution, paving the way for better more personalized medicine....
Moffitt Cancer Center researchers discovered a link between cutaneous human papillomavirus and squamous cell carcinomas that could contribute to the development of keratinocyte carcinomas, also known...
By examining specific regions of the human genome, Baylor College of Medicine researchers developed a machine learning algorithm called SPLS-DA to look for epigenetic markers for schizophrenia.
The...
As the COVID-19 pandemic swept across the world in 2020, hospitals and providers had to determine a course of action to continue administering quality care to their patients. At Ann & Robert Lurie...
Michigan Medicine researchers have found a protein that could predict the severity of a chronic lung disease that is often fatal in patients with scleroderma. These findings could indicate how...
To understand the relationship between pre-existing conditions and complications of COVID-19 infection, researchers are using natural language processing (NLP) to sift through unstructured EHR...
Researchers have determined that vaccinating children ages 12 and older is a critical component of protecting population health against future COVID-19 surges. However, data shows that racial...
Researchers used population health data modeling to determine how COVID-19 restricts impact infections and gross domestic product (GDP).
This study was conducted in Australia and uses Victoria,...
