Elizabeth Standish Gill Associate Professor of Nursing; Columbia University Medical Center; Columbia University Data Science Institute; Visiting Nurse Service of New York; Harvard Medical School & Brigham and Women’s Hospital

 

 

 


Data for good

I grew up in a former Soviet Union and I always loved technology, especially computers! To use my first computer in late 1980, I had to find a way to connect it to a TV and upload a software from tape to make a simple computer game work. I remember the excitement of understanding this complex mechanism and making it work and I still feel the same type of excitement when I develop new software or adapt machine learning algorithms to nursing. I was first exposed to medical technology, such as electronic health records, while being a medic in the Israeli army. I completed my Bachelor degree and Master degrees in Nursing at the University of Haifa, Israel, and worked at an internal medicine ward of one of the largest Israeli hospitals. During my clinical work, I was fortunate to work with some of the best electronic health records at the time, but I could still see much potential in technology being supportive of nursing processes.

During my PhD studies as a Fulbright Fellow at the University of Pennsylvania (Philadelphia, USA), I was fortunate to work with some of the leaders in nursing informatics. I started focusing on developing innovative computer systems that support nursing decision making. For example, in my dissertation, I developed a clinical decision support tool PREVENT that helps nurses to prioritize high risk patients during care transitions.

During my postdoctoral studies at the Harvard medical School and Brigham Women’s Health Hospital, I worked with a large interdisciplinary team that developed and implemented a set of tools that help to make sense of large volumes of narrative clinical notes. In general, this field is called natural language processing and I became one of the pioneers in applying natural language processing on data generated by nurses. Today, my team develops a free and open-source software for natural language processing called NimbleMiner. NimbleMiner was applied to mine millions of nursing notes to extract information about patient outcomes and safety.

Throughout the years, I learned the value of peer advice and providing support to my fellow nurse informaticians have become one of my passions. I was fortunate to be a co-founder of a very active working group of young professionals called “Students and Emerging Professionals” with the International Medical Informatics Association, Nursing Informatics Special Interest Group. Together with a group of emerging international nurse informaticians, we provided many opportunities for professional development and conducted the largest international survey of nursing informatics.  Today, the Student and Emerging Professionals group is active and we encourage anybody interested to join our work. In addition, I was funded by the Israeli Ministry of Education to develop an introductory massive open online course (MOOC) on health informatics called “Health Informatics for better and safer healthcare”. So far, the course was attended by several thousands students from more than 50 countries and anybody is welcome to make use of this free and readily available education resource.

Currently, I am an Associate Professor at Columbia School of Nursing (New York, USA) and my work focusses on using the most advanced data science methods to improve patient outcomes. I truly believe that our field of nursing and health informatics will help people to achieve better health across the globe.