Divya Gupta, MD, of the Stanford Cancer Center, discusses an intervention utilizing a computer model and lay care coaches to improve advance care planning conversations with patients who have metastatic cancer. The study, Dr. Gupta reports, showed a trend toward less intensive care for patients at the end of life.
Katherine E. Reeder-Hayes, MD, MBA, of the University of North Carolina at Chapel Hill, discusses the timeliness of breast cancer care for Black women compared with non-Black women in North Carolina. Her data showed that greater geographic variation exists in the timeliness of breast cancer care for Black women, with regions surrounding larger urban centers having the largest disparities.
Tina Shih, PhD, of The University of Texas MD Anderson Cancer Center, discusses the rising cost-sharing requirement from private insurance, which has worsened the financial burden for patients with cancer. She believes that cost-containment policies alone may not be enough to ease this hardship.
Jenny Jing Xiang, MD, of Yale University School of Medicine, discusses a universal, standardized clinical trial prescreening protocol, which streamlined research recruitment and was associated with yearly increases in patient enrollment at the Veterans Administration (VA) Connecticut Cancer Center. The Center became the top-accruing VA site for National Cancer Institute–sponsored trials and was ranked in the top 10 enrolling sites nationally for VA and non-VA hospitals.
Divya A. Parikh, MD, of Stanford University School of Medicine, discusses findings that suggest an evidence-based tool, the Serious Illness Conversation Guide, may engage patients with metastatic or recurrent urologic cancer in goals-of-care conversations, potentially resulting in an increase of documentation of their goals in the electronic medical record.
Morgan R.L. Lichtenstein, MD, of Columbia University Medical Center, discusses a single-center prospective study examining the complex relationship between time to oral oncolytic receipt and clinical or process-related factors, such as prior authorization, diagnosis, and insurance type.
