Saturday, June 5, 2010

Doctor finds multidimensional opportunities at SDM - SDM Pulse Summer 2010

By Dr. Sahar Hashmi, SDM ’09

Dr. Sahar Hashmi, SDM ’09
Arriving at MIT as a systems thinker, I was immediately impressed by the diverse opportunities offered by MIT’s System Design and Management Program (SDM). SDM allows students to do anything and everything they can possibly imagine, with innovation and creativity. You can be an entrepreneur, a scientist, an engineer—you can even enhance your managerial skills to help improve the health-care system, which is my area of interest.
I chose to learn data collection analysis and model-building skills by working as part of a team in Innovation in Health Care, a class taught by Dr. Stan Finkelstein and Institute Professor Joel Moses.
Students participating in this course were assigned field work with doctors at Boston’s Beth Israel Deaconess Medical Center (BIDMC). My team looked at planning for the 2009 H1N1 flu pandemic at the hospital level and built a model to predict how many patients BIDMC could expect at the peak of the pandemic.
We discovered that predicting and managing a potential H1N1 surge is a dynamic problem because data inputs change daily. Using the Centers for Disease Control and Prevention’s H1N1 Impact 2009 model, which simulates the impact of the disease on the community, and the proprietary BIDMC filter, we were able to predict flu volume, flu spread, and impact on BIDMC.
The model results did confirm reports that H1N1 has reached a peak in the United States, with top volume occurring between Nov. 30 and Dec. 7, 2009. On the other hand, the patient volume to BIDMC predicted by our model was less than the volume actually experienced by BIDMC, which suggests that the model assumptions may be conservative here.
Figure 1. This chart reflects the SDM team’s
comparison of its forecasts with actual visits to
Beth Israel Deaconess Hospital for influenza-like illness.

A comparison between our forecast and BIDMC’s actual visits for influenza-like illness (ILI) is show in Figure 1.
Comparing our forecasts to benchmarks (Figure 2) indicate that our model is more conservative on total infections but aggressive on hospitalizations. (We must continually focus on the impact of our assumptions on the model’s fidelity.) The President’s Council of Advisors on Science and Technology (PCAST) published a study that predicted that 40 percent of the population could be infected, which was deemed too high by BIDMC. Our model in comparison indicates a 13.4 percent infection rate. However, our forecasted hospitalization rate of 1.5 percent is higher than benchmark forecasts, indicating that the 42 percent ILI and/or the 30 percent hospitalization assumption maybe too aggressive.
Figure 2: This chart compares our model and benchmarks.
Taking this class helped me realize that such prediction models could be very useful and give us some idea of the situation but we can’t simply rely on them. We have to take important preventive measures to slow disease spread in a pandemic or epidemic. I am currently looking at the use of non-pharmaceutical interventions at the time of pandemic H1N1 2009. I am interested in finding out whether or not the health policies at MIT Medical, the Institute’s health center, were implemented by the MIT students or not and find ways to improve them.
Since education and awareness are important aspects of disease and health management, I also got involved in making a math flu video that teaches high school students how to protect themselves and the community from spreading infection.
My involvement with the video illustrates one way in which SDM gave me opportunities to pursue all my interests in an amazing style. I had the privilege to meet and work with an inspiring couple, Professor Richard Larson and M. Elizabeth Murray, who have created an initiative to educate the world in an innovative and creative, systems-based way—though Blended Learning Open Source Science or Math Studies (BLOSSOMS).
I learned about the BLOSSOMS initiative when I first joined SDM in 2009 and met Larson and Murray. I had been involved with educational projects in Pakistan and India that aimed to spread health awareness to minorities and to the general population. It was a natural follow-up to get involved in an initiative that spreads knowledge to developing nations.
BLOSSOMS is a program sponsored by MIT LINC (Learning International Networks Consortium, linc.mit.edu), a group of educators from around the world who are interested in using distance and e-learning technologies to help their respective countries increase access to quality education.
The vision of BLOSSOMS is to develop a large, free repository of video modules created by gifted volunteer teachers from around the world. It was seeded initially by MIT faculty members with partner educators in underdeveloped countries.
I was privileged to participate with a team in developing and creating the flu math video module that was aimed at spreading preventive measures and awareness of flu pandemics in the community. Although it specifically focused on the H1N1 pandemic, we made sure to generalize the measures and knowledge for any type of viral respiratory infection. We even developed statistical math games and used an animated cartoon character to help keep the student viewers interested. This video is now available and can be downloaded at blossoms.mit.edu/video/larson2.html.
We also created a flu website for the MIT community called “Flu101,” which is now also part of the Engineering Systems Division website. It contains recent postings, games, and flu information. We’ve also collaborated with the “health map” team at Harvard, which uses Twitter as one way to disseminate global updates on various infectious diseases around the world.
I hope that this illustrates the diverse dimensionality of SDM and the “infectious nature” of the program that allows students to create the path that’s right for them. In my case, “system design and management” implies designing systems to prepare for and respond to serious infectious diseases, such as pandemic influenza, and to manage those health systems well once they are activated.

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