Xiang Zhong Uses Systems Engineering to Transform Healthcare Practices

Xiang Zhong profile picture superimposed over the Mayo Clinic

Industrial & Systems Engineering Assistant Professor Xiang Zhong, Ph.D., has received $286,655 from the Agency for Healthcare Research and Quality (AHRQ) in support of her research methods to improve specialized medical care for people with serious illness, also known as palliative care.

Due to advanced technology in healthcare, the life-expectancy rate has increased significantly. As a result of the growing aging population, the need for palliative care and focused efforts on providing relief for patients, as well as their families, is at an all-time high. While there is a national consensus for quality palliative care, Dr. Zhong believes there is room for improvement of current care practices.

“The challenge of reliably measuring diagnostic error and delays in treating acutely ill patients needs to be addressed. Critically ill patients have a high frequency of unplanned Intensive Care Unit (ICU) admissions and triggers of rapid response teams. They are also very vulnerable to increased morbidity and mortality due to delay in therapeutic intervention and among the most costly patient populations to treat in a hospital. These factors make this population an ideal target for study and intervention,” said Dr. Zhong.

According to the National Academy of Medicine, diagnostic error and delays are a leading cause of preventable harm and death in the U.S. It is estimated that 34,000 out of the 540,000 annual deaths in ICUs alone are a result of diagnostic errors, such as preventing or delaying appropriate treatment or even providing unnecessary treatment.

The Acute Care Learning Laboratory project has a focus on reducing threats to diagnostic fidelity in critical illness cases and is specifically aimed at improving the care and safety of patients before, during and after ICU admissions or transfers. As a systems engineer, Dr. Zhong, along with Mayo Clinic physicians from the Multidisciplinary Epidemiology and Translational Research in Intensive Care Lab, will work collaboratively to develop a “Control Tower” to inform the design, development, evaluation, and refinement of the solutions to diagnostic error and delay.

The multidisciplinary team plans to re-invent the current organizational work design with three overall goals, including: enabling a palliative care specialist to deliver medical care effectively, efficiently educate ICU providers of best palliative care practices, and facilitate communication between providers and family members in order to aid families in making informed decisions. The anticipated goal of this approach is to improve patient outcomes, symptom control and satisfaction, reduce time to necessary specialist interventions, and have a measurable reduction in inpatient hospital mortality. Measurable patient outcomes include clinical results such as mortality, as well as improved patient-clinician interactions and patient and family satisfaction.

The project hopes to establish replicable models of this sociotechnical system to be implemented in critical care safety labs in diverse pre-hospital, emergency departments and ICU units around the globe.