Mary Goldstein's CDS System at VA Palo Alto Health Care System

Mary Goldstein, an expert on evidence-based clinical practice guidelines, gets recognition for her work from the 1990s — a knowledge-based clinical decision support (CDS) system still serving the VA Palo Alto Health Care System today.
Health-care providers looking at electronic medical records Getty Images

A knowledge-based clinical decision support (CDS) system that was built upon software tools developed by BMIR remains in use after nearly a quarter century at VA Palo Alto Health Care System. Stanford Health Policy's Mary K. Goldstein, MD, and the Office of Geriatrics and Extended Care in the Veterans Health Administration, said the system was developed to support primary-care staff in providing evidence-based treatments for patients with hypertension, one of the most prevalent diagnoses in adult medicine.

In the late 1990s, Goldstein collaborated with fellow Stanford faculty member Brian B. Hoffman, MD, at VA Palo Alto and Mark Musen, MD, PhD, and his group in BMIR. They initially encoded a computable knowledge base of hypertension clinical knowledge using Protégé, the knowledge-acquisition software that BMIR developed. There was further work in knowledge representation with BMIR academic staff, including the internationally recognized expertise of Samson Tu, MS, and with VA Palo Alto, whose health informatics staff understood the importance of providing evidence-based CDS for clinical providers.

Mary Goldstein of Stanford University Mary Goldstein
Those innovative approaches to implementing technologies led to development of an architecture for extracting patient data, processing it with the knowledge base, generating recommendations, and displaying recommendations to primary care providers (PCPs) in a computer window that displayed on top of the patient’s electronic health record and could be viewed on the screen in real time.


The original system was created to help PCPs in managing hypertension. Over time, the VA Palo Alto-based team has built on that system so that today it has evolved into a new CDS system that can be displayed within a clinical dashboard for additional diseases including diabetes. The current program, known as Med Safe CDS, still uses Protégé and a lot of the concepts—and program code—from the original work.

“Many decision support systems are based on simple rules with branching logic that reach a limit of how much complexity they can handle," Goldstein said in an interview for the newsletter of the Stanford Center for Biomedical Informatics Research. "At the VA, we wanted to be able to take account of more patient complexity so that multiple patient clinical characteristics would be processed at the same time. The underlying system for doing this has allowed us to generate much more complex recommendations than could be done with a rule-based branching logic system."

Read More

Read More

A man exits a Los Angeles County store where masks are required.

Team Builds Robust Database of CA COVID-19 Public Health Orders

California and its 58 counties have issued more than 1,500 public health orders since the beginning of the COVID-19 pandemic. A team of Stanford researchers has put those orders into a dataset to help policymakers and public health officials plan and protect.
cover link Team Builds Robust Database of CA COVID-19 Public Health Orders
A blue ribbon represents colon cancer awareness.

Task Force Urges Younger People to Screen for Colon Cancer

Most Americans think colorectal cancer is a disease of the elderly. But more young people — particularly Black men and women — are falling to the country's third deadliest type of cancer. The U.S. Preventive Services Task Force hopes to change that by lowering the age of routine testing to 45.
cover link Task Force Urges Younger People to Screen for Colon Cancer
COVID-19 research illustration

An Impact-Oriented Approach to COVID-19 Epidemiological Modeling

Epidemiological modeling has emerged as a crucial tool to help decision-makers combat COVID-19, with calls for non-pharmaceutical interventions such as stay-at-home orders and the wearing of masks. But those models have become ubiquitous and part of the public lexicon — so Nirav Shah and Jason Wang write that they should follow an impact-oriented approach.
cover link An Impact-Oriented Approach to COVID-19 Epidemiological Modeling