Predictive Maintenance in Healthcare Services with Big Data Technologies

Advances in medical technology is not sufficient alone to satisfy the growing and emerging needs such as improving quality of life, providing healthcare services tailored to each individual, ensuring efficient management of care and creating sustainable social healthcare. There is a potential for substantially enhancing healthcare services by integrating information technologies, social networking technologies, digitization and control of biomedical devices, and utilization of big data technologies as well as machine learning techniques. Today, data has become more ubiquitous and accessible by virtue of advancements in smart sensor and actuator technologies. This in turn allow us to collect significant amount of data from biomedical devices and automate certain healthcare functions. In order to get maximum benefit from the generated data, there is a need to develop new models and distributed data analytics approaches for health industry. Big data has the potential to improve the quality and efficiency of health care services as well as reducing the maintenance costs by minimizing the risks related with malfunctions of biomedical devices. Hospitals grasp this noteworthy potential and convert collected data into valuable information that can be used for several purposes including management of biomedical device maintenance. To this end, in this study, by leveraging the latest advancements in big data analytics technologies, we propose a scalable predictive maintenance architecture for healthcare domain. We also discussed the opportunities and challenges of utilizing the proposed architecture in the healthcare domain.
11th IEEE International Conference on Service-Oriented Computing and Applications (SOCA)


CMOS Cell Sensors for Point-of-Care Diagnostics
Adiguzel, Yekbun; Külah, Haluk (2012-08-01)
The burden of health-care related services in a global era with continuously increasing population and inefficient dissipation of the resources requires effective solutions. From this perspective, point-of-care diagnostics is a demanded field in clinics. It is also necessary both for prompt diagnosis and for providing health services evenly throughout the population, including the rural districts. The requirements can only be fulfilled by technologies whose productivity has already been proven, such as comp...
Assessing hospital information systems processes: a validation of prise information systems success model in healthcare
Ozkan, Sevgi; Baykal, Nazife; Sincan, Murat (null; 2008-12-01)
Although there is limited research and evidence base, it is reasonable to expect that high quality information technology is an integral factor in the success of today’s health care sector. However, the health care sector is considered to be low level investor in Information Technology (IT) when compared to other sectors. There are studies that look at the sums spent on health IT as a basis for determining how effective the IT systems are. We support the idea that the effectiveness of IT systems, is not an ...
Survival modelling approach to time to first claim and actuarial premium calculation
Akbulut, Derya; Kestel, Sevtap Ayşe; Department of Actuarial Sciences (2011)
Health problems of the human beings in a society are one of the main components of the social security systems due to the dimension of the financial burden it might bring on individuals, employers, insurance companies and governments. Morbidity measures, such as incidence and prevalence of a specific disease in a certain population enable researchers to estimate for individuals the probability of being diagnosed or being prone to the diseases. This information is usually not tractable because of the non-ava...
Finding potential serious adverse events of drugs by using clinical trial data and machine learning tools
Demir, Veysel Buğra; Acar, Aybar Can; Can, Tolga; Department of Biotechnology (2021-12-30)
Healthcare is improving day by day and these developments make healthcare more accessible and this leads to production of large amount of data. The interpretation of these data, making assumptions and revealing significant results by using data analysis methods are important here as in every field that produces big data. Analysed data that are collected during clinical trials have great effect in ensuring developments in healthcare. Adverse event reports are one of the important parts of the clinically stud...
Usability testing of a family medicine information system
Öz, Saba; Çakır, Murat Perit; Özkan Yıldırım, Sevgi; Department of Medical Informatics (2012)
Healthcare is an important part of life in most societies that attract a significant amount of public investment. Primary healthcare is a fundamental branch of the healthcare system where patients and doctors initially meet. Family Medicine Information Systems are developed in an effort to ease the daily work of family doctors with the help of information technology. Such systems are generally used for handling critical tasks such as managing health records of patients, monitoring pregnancy and keeping trac...
Citation Formats
S. Coban, M. O. Gökalp, E. Gökalp, P. E. Eren, and A. Koçyiğit, “Predictive Maintenance in Healthcare Services with Big Data Technologies,” presented at the 11th IEEE International Conference on Service-Oriented Computing and Applications (SOCA), Paris, FRANCE, 2018, Accessed: 00, 2020. [Online]. Available: