Qualification: 
EMBA-MS, B-Tech
s_mariasabastin@blr.amrita.edu
ssebastin@mites.amrita.edu

Maria Sabastin S. currently serves as Assistant Professor at the Department of Management, Bengaluru Campus.

Qualification : B.Tech (Computer Science), Amrita Vishwa Vidyapeetham, EMBA- MS (Amrita Vishwa Vidyapeetham in Collaboration with University at Buffalo, New York), currently pursuing Ph.D. at Amrita School of Business.

With the passion for teaching and research Maria Sabastin S. started his career with Department of Management, Bangalore campus, and now he is also pursuing his Ph.D. in the area of Health Care Analytics and Management. His key area of interest is to explore what are the determinants to manage Information Technology in Health Care to increase their efficiency and improve their performance. He has presented papers on Health Care Management in National and International Conferences. He has taught various courses such as Management Information Systems, IT Fundamentals for Business Analytics, RDBMS and PYTHON programming language.

Publication Award and Achievements

  • Won "Best Track Paper Award" for the paper titled “A system dynamic approach of patient satisfaction in India’s leading Health care” at the International Conference on Industrial Engineering and Operations Management, Bandung, Indonesia.
  • Published a research paper “Physician Engagement: A Key to Purchasing Excellence in Healthcare Supply Chains” in the International Conference on Industrial Engineering and Operations Management, Bandung, Indonesia.
  • Published a research paper “Efficiency of Radiology services: A Case study in Karnataka, India”, in the International Conference on Industrial Engineering and Operations Management, Bandung, Indonesia.
  • Published a research paper “Enhancing the Quality of Processes in Healthcare in India” in 7th International conference on Advances in computing, communication and Information, Bangalore, India.
  • Published a research paper “Performance and Purchasing effects of Healthcare Supply Chain” in 7th International conference on Advances in computing, communication and Information, Bangalore, India.
  • Presented a research paper “Data Mining in Healthcare Records: A Review Based on the Kind of Knowledge” in the International Conference on Industrial Engineering and Operations Management, Bangkok, Thailand.
  • Presented a research paper “A Study on Awareness of Block Chain Technology among Human Resources Executives in India “in the International Conference on Industrial Engineering and Operations Management, Bangkok, Thailand.

Publications

Publication Type: Conference Proceedings

Year of Publication Title

2019

Maria Sabastin S. and Nair, V. Kumar, “A Study on Awareness of Block Chain Technology among Human Resources Executives in India”, Proceedings of the International Conference on Industrial Engineering and Operations Management Bangkok, Thailand, March 5-7, . 2019.[Abstract]


Human Resource Management is the process of recruitment and selecting employee, providing orientation and induction, training and development, assessment of employee, providing compensation and benefits, motivating, maintaining proper relations with employees and with trade unions, maintaining employees safety, welfare and health measures in compliance with labor laws of the land. The planning function of management controls all the planning that allows the organization to run smoothly, Staffing, Coordinating, and Controlling. HR practices can made simple with the emergence of new technology like Block chain, it is a open decentralized database of any transaction involving value money goods or even votes creating a record whose authenticity can be verified by the entire community, transactions can be recorded on a public and distributed ledger which will be accessible by anyone. Block chain is an electronic ledger of digital records, events, or transactions that are hashed cryptographically, authenticated, and controlled through a distributed or shared network of participants using a group consensus protocol. The block chain is distributed among millions of computers with mechanisms for validating transactions that utilize a group consensus protocol. Block chain technology is the way of looking differently the inner functions of the normal database which gives the power to a single authority like administrators who have the ability to change the information in the database if they want to. This power can be abused by unfaithful administrators. Normal database suffers the problem of single point of failure and makes them depend much on backups in case of failure and when both running database and backups are harmed can bring very serious problem the block chain works differently compared to normal database whereby the information is encrypted and stored in every node connected to the network and eliminate the possibility of having single point of failure, fraud, and corruption. Block chain is more commonly associated with areas like payments and capital markets, its effects on HR will be profound and pervasive. HR functions should consider the benefits block chain delivers such as trustworthy verification of counter parties, identify without the involvement of a third party, giving people a comprehensive, trust worthy block chain-based record of their education, skills, training and work place performance. The objective of this paper is to understand the scope and awareness of Block chain among HR executives and also to check whether the HR executives are willing to adopt block chain in future.

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2019

Maria Sabastin S. and Sahay, M., “A system dynamic approach of patient satisfaction in India’s leading Health care”, International Conference on Industrial Engineering and Operations Management, Bandung, Indonesia, vol. 61. 2019.[Abstract]


Healthcare systems face challenges including diminishing resources and increasing demands. The challenges need to be balanced in this complex system of systems to ensure a sustainable quality of life. Sustainability considers the needs of future generations without compromising the needs of current generations. The social component of sustainability is one of the important areas in healthcare sustainability. The social component focuses on considerations such as equity, empowerment, accessibility, participation, cultural identity, and institutional stability. Patient satisfaction is a key factor in the social element. Patient satisfaction represents patient fulfillment in regards to the cost, accessibility to services and resources, and patient wellbeing. It is analogous to “customer satisfaction”. A systems thinking approach is applied to analyze the social aspect in healthcare systems. This paper explores important factors and factor relationships in healthcare social sustainability related to patient satisfaction using a system dynamics approach.

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Publication Type: Journal Article

Year of Publication Title

2019

Maria Sabastin S., Nair, A. Anil, and R, R., “Data Mining in Healthcare Records: A Review Based on the Kind of Knowledge”, Proceedings of the International Conference on Industrial Engineering and Operations Management Bangkok, Thailand , 2019.[Abstract]


There is a tremendous amount of attention being focused on improving human health these days. The World Health Organization (WHO) statistics show that disease and mortality rate greatly depend on access to proper healthcare, which is not available to a vast majority of the global population. The healthcare environment is generally perceived as being ‘information rich’ yet ‘knowledge poor’. The knowledge discovery in database (KDD) is alarmed with development of methods and techniques for making use of data. One of the most important step of the KDD is the data mining. Data mining is the process of pattern discovery and extraction where huge amount of data is involved. The analysis of medical records is a major challenge, considering they are generally presented in plain text, have a very specific technical vocabulary, and are nearly always unstructured. It is an interdisciplinary work that requires knowledge from several fields. The analysis may have several goals, such as assistance on clinical decision, classification of medical procedures, and to support hospital management decisions. There is a wealth of data available within the healthcare systems. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. Knowledge discovery and data mining have found numerous applications in business and scientific domain. Terabytes of data are generated every day in many organizations. To extract hidden predictive information from large volumes of data, data mining (DM) techniques are needed. Organizations are starting to realize the importance of data mining in their strategic planning and successful application of DM techniques can be an enormous payoff for the organizations. Valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, we briefly examine the potential use of classification based data mining techniques such as Rule based, decision tree and Artificial Neural Network to massive volume of healthcare data. This paper also discusses the requirements and challenges of DM, and describes major DM techniques such as statistics, artificial intelligence, decision tree approach, genetic algorithm, and visualization. Knowledge discovery in databases is well-defined process consisting of several distinct steps. Data mining is the core step, which results in the discovery of hidden but useful knowledge from massive databases. A formal definition of Knowledge discovery in databases is given as follows: “Data mining is the non-trivial extraction of implicit previously unknown and potentially useful information about data”. Data mining technology provides a user- oriented approach to novel and hidden patterns in the data. The discovered knowledge can be used by the healthcare administrators to improve the quality of service. The discovered knowledge can also be used by the medical practitioners to reduce the number of adverse drug effect, to suggest less expensive therapeutically equivalent alternatives. With the digitalization of medical records and the large amount of medical data available, this is an area of wide research potential. It provides a comprehensive contextualization to all those who wish to perform an analytical work of medical records, enabling the identification of fruitful research.

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