Intro:
Findings of e-ESAS: A Mobile Based Symptom Monitoring System for Breast Cancer Patients in Rural Bangladesh
http://dl.acm.org/citation.cfm?id=2208532
Authors:
Munirul M. Haque - Marquette University
Ferdaus Kawsar - Marquette University - Lecturer at The University of Asia Pacific
Md. Adibuzzaman - Marquette University
Sheikh I. Ahamed - Marquette University - Director of the Ubicomp Research Lab. His interests include Pervasive/Ubiquitous/Mobile Computing, Pervasive Security, Trust and Privacy, and Pervasive Healthcare.
Richard Love - International Breast Cancer Research Foundation - Professor of Medicine and Public Health
at Ohio State University and Scientific Director of the International Breast Cancer Research Foundation.
Rumana Dowla - AGBC Center
David Roe - International Breast Cancer Research Foundation
Syed Mozammel Hossain - AGBC Center
Reza Selim - AGBC Center
Summary:
e-ESAS stands for Edmonton System Assessment System and its a mobile based RSMS used to detect symptoms for cancer. The background for this invention stems from Bangladesh. Many women in Bangladesh never seek treatment for a variety of circumstances. The issues may be social or cultural but the end result is, they don't see a doctor till very late in cancer's development stage. This system has been designed with the rural resident's mindsets in mind so this means they will be able to use this simple application even if they haven't had much exposure to other types of technology.
They gathered 39 breast cancer patients who signed up and were affiliated with Amader Gram Breast Care Center (AGBCC). They interviewed these patients and found their conditions along with how well they knew how to use a cell phone. The ages of these interviewed ranged from 21 to 45 with their education, background, and income varying. The main issue was the health clinics since they lacked automation in their treatments and did little to motivate their community to come forth with any problems. e-ESAS remedies this confusion by incorporating some of the old paperwork into the app. They excised some less useful information and made it so once submitted, the information goes straight to the doctor's version of the app. The doctor can then set an alert, prescribe some medicine, and give the patient an idea where they might stand in the future.
The authors then went on some field trips to pick out 12 different test subjects. 10 of these were individuals with breast cancer of varying levels of soreness, normal mental status, life expectancy, and ability to cooperate with the protocol among other conditions. The other 2 test subjects were doctors. One of the major goals of this experiment was to teach the subjects how to learn e-ESAS and see if it improved their chances of visiting a clinic if their symptoms indicated the cancerous cells were progressing.
e-ESAS made a positive impact on the small rural community through increased awareness of breast cancer. It made more women come out of their bubbles and visit a clinic. The community also exhibited a small cultural shift with women being more open to asking their husbands for help and telling them they need to see a doctor. Missed appointments started to drop, video downloads increased for awareness purposes, and most importantly of all, the quality of life improved. e-ESAS has been a big help for this small rural town it would seem.
Related Papers:
This idea was probably the most novel I have blogged about yet. They developed a unique app and decided to help a small community that did not use technology that much where the cultural norm was the woman should not talk about problems for fear of costing the husband money. The data from this study should be extremely helpful when paired with similar studies.
I did not find many papers at all that did exactly what this paper did. Many of the papers I found just discuss breast cancer for instance, the first one, A survey of prediction models for breast cancer survivability, talks about data mining and breast cancer. This is similar to the e-ESAS paper since the main problem was getting information on patients before it progressed. The Breast cancer detection using cartesian genetic programming evolved artificial neural networks paper uses a unique way to detect breast cancer that might be useful for future prospects.
Evaluation:
There was plenty of data for this project, so I would say it was evaluated finely. There exists a ton of quantitative data and qualitative data alike. For Quantitative, they noticed a spike in the awareness of breast cancer on the application. The time spent per patient was also decreased at the clinic. In addition to those two statistics, there have been less appointments missed.
As far as qualitative data goes, I would say the individuals with breast cancer had great feedback on the system. The cultural shift of informing their partners of the pain of breast cancer would attest to this. Most of the opinions of the individuals are subjective however. The application did not work for everyone so that's why it is subjective. The objective parts of this experiment had to do with the % of missed appoints as talked about above.
Discussion:
The work that all of these authors did was the most novel subject I have blogged about so far. They tested innovative new technology on a town that may or may not have accepted and incorporated it. Its very to different to have implemented this in a small town in Texas since the values are so different from the ones in Bangladesh. The evaluation was also great and I enjoyed all the different facets of data they presented both subjective and objective. I enjoyed this paper and look forward to how this new technology will improve the quality of life in more rural areas.
Hi Colby, I am the 1st author of this paper. It was nice to read your blog summary. You will be glad to know that a big pilot study on 800 cancer patients in 4 different countries is going to be started soon based on the success story of this project. wish u all the best.
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