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Activity Review | Mini Workshop on Data Analytics in Healthcare and Service Operations Was Held at CUHK-Shenzhen

  • 2019.07.01
  • News
Mini Workshop on Data Analytics in Healthcare and Service Operations was held at CUHK-Shenzhen on June 28, 2019.

Mini Workshop on Data Analytics in Healthcare and Service Operations was held by iDDA at CUHK-Shenzhen on June 28, 2019. This workshop invited professors and famous scholars from home and abroad to share the latest academic and scientific research results on “Data Analytics in Healthcare and Service Operations”. More than 50 participants attended the workshop and actively engaged in academic discussions and exchanges. At 8:50 a.m., Mini Workshop on Data Analytics in Healthcare and Service Operations began. Professor Jim Dai, the dean of Institute for Data and Decision Analytics of CUHK-Shenzhen and co-chair of the workshop, declared the workshop open.

Professor Jim Dai, the dean of Institute for Data and Decision Analytics of CUHK-Shenzhen and co-chair of the workshop

Subsequently, seven well-known overseas scholars gave academic reports. Present at the workshop were Prof. Hamsa Bastani from University of Pennsylvania, Prof. Galit Yom Tov from Israel Institute of Technology, Dr. Xin Shi from Manchester Metropolitan University Business School, Prof. Jing Dong from Columbia University, Prof. Joel Goh from National University of Singapore, Prof. Nan Liu from Boston College and Prof. Luyi Yang from Johns Hopkins University.

The first presentation was given by Prof. Hamsa Bastani from University of Pennsylvania. Professor Hamsa Bastani explained the process and results of her research on Predicting with Proxies. In the field of medical prediction, such as to predict the future risk of patients with a malignant disease, if hospitals use their own patient population as samples, there may be greater volatility due to the small number. However, if you use other hospitals’ data to enlarge sample size, there would be prediction errors caused by factors such as scales and levels of hospitals. Given this background, the model developed by Professor Hamsa and her team was able to achieve better predictive accuracy using proxy data.

Professor Hamsa Bastani giving a presentation on Predicting with Proxies

After a short break, Prof. Galit Yom-Tov from Israel Institute of Technology presented the findings and model targeted at online customer contact centers, proving one of the related theories of psychology, and that negative customer emotions can reduce service agent productivity, which would in turn increase negative customer emotions and hamper system efficiency. Professor Galit Yom-Tov’s model can predict the probability of customer emotion deterioration in the near future in real time and give early warning. It can also predict the response time of service agents according to customer emotions, providing a practical tool for customer service operation and management.

Prof. Galit Yom-Tov presenting a report on Do Customer Emotions Affect Worker Productivity? An Empirical Study of Emotional Load in Online Customer Contact Centers

Next, Dr. Xin Shi from Manchester Metropolitan University presented his team's model in the field of medical prediction: using regression analysis of historical data to provide disease warning for existing patients at the right time. The model can also be used in many studies, including a recent study by Dr Xin Shi on the distribution and trends of chronic diseases in Brazil.

Dr. Xin Shi giving a report on Big data for health management—early diagnosis, intervention and prevention

In the afternoon, the second half of the workshop began. Jing Dong, professor of Columbia University, conducted an academic report on Optimal Scheduling of Proactive Care with Patient Degradation. Professor Jing Dong and her team studied hospital attendance priorities. How to provide treatment for different patients with limited medical resources has always been one of the concerns of medical institutions. Professor Jing Dong's team divided patients into two classes of moderate and urgent, and designed a model for medical institutions to constantly evaluate the priority of medical resources allocation in these two classes of patients.

Prof. Jing Dong conducting an academic report on Optimal Scheduling of Proactive Care with Patient Degradation

Next, Prof. Joel Goh from National University of Singapore shared his research on tuberculosis in India. His team devised a model for tuberculosis patients who do not follow their doctors' advice and end up with a relapse. By offering patients monetary incentives at the right time and at the right price it can encourage them to complete the full treatment in order to reduce mortality and save resources for relapse.

Prof. Joel Goh from National University of Singapore giving a report on Design of Incentive Programs for Optimal Medication Adherence

After an afternoon tea, Nan Liu, a professor at Boston university, shared the results of a study called Managing Appointment-based Healthcare Services with Strategic Walk-in Patients. Hospitals usually accept both patients with scheduled appointments and walk-in patients. Professor Nan Liu and his team studied how hospitals should allocate capacity to these two channels. They divided the real appointment into two situations according to whether the patients could know the waiting time after the appointment, and designed a model to plan in real time whether the hospital should allocate more capacity to the appointment channel or walk-in channel according to each situation.

Prof. Nan Liu presenting a report on Managing Appointment-based Healthcare Services with Strategic Walk-in Patients

Professor Luyi Yang from Johns Hopkins University brought us the final presentation of the workshop. Professor Luyi Yang and his team have used modeling to investigate the benefits of the rule behind “referral priority” when signing up for an application account today. Their model designed different “referral priority” rules for different market sizes of an application, which can increase new entrants at the lowest cost.

Professor Luyi Yang giving a report on Invite Your Friend and You’ll Move Up in Line: Optimal Design of Referral Priority Programs

Then Professor Pengyi Shi from Purdue University, the co-chair of the workshop, gave a closing speech and Prof. Jim Dai and she presented souvenirs to these seven guests.

Professor Pengyi Shi giving a closing speech

Group photo of the speakers

Group photo

The last part of the workshop was the Poster Session. Seven doctoral students from domestic and foreign universities also gave keynote presentations and had in-depth academic exchanges with many participants.

So far, Mini Workshop on Data Analytics in Healthcare and Service Operations has successfully concluded. Welcome more students and teachers to participate in iDDA activities in the future. For more information on lectures about data and decisions, please follow the WeChat official account of Institute of Data and Decision of CUHK-Shenzhen.

撰文 | 史筱桐、KL
编辑 | KL

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