By Russ Michael, senior director, Methodology and Data Science, Blue Health Intelligence® (BHI®) Artificial intelligence (AI)-driven technologies are increasingly prevalent in all parts of our lives, including healthcare and health insurance. The pace of change in healthcare AI and data analytics has been breathtaking, as new products and technologies promise to improve quality, reduce costs, and help health plans better … Read More
SDOH-Related Z Codes: Documentation to Aid Health Equity
Z Codes are a powerful tool to track SDOH factors. They can help data scientists understand how such factors affect medical outcomes.
Care Analytics News profiles BHI’s Dr. Russ Robbins
“When I left private practice, there was no way to learn other than on the job,” Robbins says. “Now, there are many good healthcare informatics programs. I tell younger colleagues to have some experience of clinical medicine before going into the business side. My knowledge of direct patient care has helped me understand the data and what is or isn’t … Read More
Bringing Women Back to Breast Cancer Screening, Safely and Seamlessly
A year ago, Thrive Earlier Detection (Thrive) won the BlueCross BlueShield Data Innovation Challenge. Healthbox, a HIMSS solution company, collaborated with the Blue Cross Blue Shield Association and Blue Health Intelligence® (BHI®) to implement that contest. As oncologists gather this week for the San Antonio Breast Cancer Symposium (SABCS), Healthbox shares recent independent insights from Thrive about breast cancer screening and … Read More
Wearables at work and privacy concerns
BHI’s senior vice president of product management and business development, Mary Henderson, is quoted in a recent BBC Worklife article on the rise of employee health tracking via wearable devices. BBC’s full Q&A with Henderson and Sanket Shah, BHI’s assistant vice president for account management, is featured below. BBC Worklife: We’ve seen interest from various corporations (particularly in the U.S.) … Read More
Healthcare options
In this guest post featured on Upjourney.com, BHI’s Sanket Shah provides a firsthand account of how following physician instructions can sometimes fail to account for lower-cost treatment settings. He explains the costly lesson of getting x-rays and CT scans in numerous locales after an ankle injury, and how the higher costs he experienced might have been avoided. His personal experience … Read More
Achieving Equity in Healthcare Modeling
As the pandemic has made painfully clear, healthcare utilization and cost do not always indicate true healthcare needs. People of color are contracting the novel coronavirus and dying at rates that are staggeringly out of line with their share of the U.S. populace. Recent social injustice events in the U.S. have heightened industrywide discussion of healthcare equity. BHI’s data scientists … Read More
Top 10 “Must Haves” for Effective Predictive Modeling
BHI® developed a top 10 list of significant factors that contribute to successful predictive modeling based on our deep experience working with really big data.Answering the “so what” question before you startNo matter how interesting your model’s output might be, if the analysis isn’t actionable, it won’t get used.Using massive databasesMassive databases ensure that large enough cohorts, with multiple diseases … Read More
Big Data Holds the Keys to Unlocking Barriers to Healthcare Cost and Quality
There has been much discussion about the role of third parties and healthcare data. Healthcare data comes from a wide array of public, nonprofit, and for-profit sources. It is used for an equally broad set of purposes, including the delivery of higher-quality care and efficiency. Applying the modern tools of big data – such as predictive modeling and machine learning … Read More
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