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Advisory Council Explores COVID-19’s Impact on Commercial Health Insurance Coverage

In Blog by BHI

BHI’s Advisory Council members kicked off their research projects this year and in one COVID-19-focused effort, found that research often adds value through counterintuitive findings. BHI Advisory Council members Michael Chernew, PhD, of Harvard University and Vivian Ho, PhD, of Rice University have been looking specifically at COVID’s impact on Blue health insurance disenrollment rates and how the pandemic has …

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Transparent, Meaningful Physician Performance Metrics

In Blog by BHI

Last year, Blue Cross and Blue Shield of Louisiana (BCBSLA) set out to share actionable, credible, and accurate cost and quality reports with providers. BHI has been partnering with the Plan since March 2020 to design and implement such reports for practitioners in BCBSLA’s Specialty Care Insights program. In delivering enhanced “Provider Index” reports, BCBSLA utilizes BHI’s proprietary Episode of …

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Artificial Intelligence, Machine Learning, and Deep Learning — What is the Difference and Why it Matters

In Blog by BHI

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 …

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Care Analytics News profiles BHI’s Dr. Russ Robbins

In Blog by BHI

“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 …

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Bringing Women Back to Breast Cancer Screening, Safely and Seamlessly

In Blog by BHI

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 …

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Wearables at work and privacy concerns

In Blog by BHI

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.) …

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In Blog by Sanket Shah

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 …

Achieving Equity in Healthcare Modeling

In Blog by BHI

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 …

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Top 10 “Must Haves” for Effective Predictive Modeling

In Blog by Russ Michael

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 …