Empowering the healthcare worker using the Portable Health Clinic Eiko Kai 1 , Andrew Rebeiro-Hargrave 1 ,Sozo Inoue 2 , Yasunobu Nohara 4 , Rafiqul Islam Maruf 3 , Naoki Nakashima 4 and Ashir Ahmed 1 1 Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka, Japan 2 Faculty of Engineering, Kyushu Institute of Technology, Fukuoka, Japan 3 The global communication center in Grameen Communications, Bangladesh 4 Kyushu University Hospital, Fukuoka, Japan Abstract—We present a remote healthcare consultancy system that enables healthcare workers to identify noncommunicable diseases in unreached communities. The healthcare system combines medical sensors with mobile health and is called a Portable Health Clinic. The Portable Health Clinic fits into a briefcase and is operated by the healthcare worker. The goal of this research is to empower the healthcare worker further by allowing her to recognize spurious measurements and to make lifestyle recommendations. In this paper, we show how to process the data: combine, link and compare – captured in patient electronic health records stored in database. We applied association rule technique to find common set of rules in order to build a clinical decision support system. We also showed examples of the meaningful information from the analyzed data to build a better clinical decision support. Keywords Remote Healthcare Consultancy, Electronic Health Records (EHR), Medical information, Clinical Decision Support System (CDSS), Data mining, Healthcare worker empowerment I. INTRODUCTION The world is facing a situation without precedent: We soon will have a greater number of older people than children and more people at extreme old age than ever before. Accompanying aging populations is a ubiquitous increase of lifestyle related diseases. According to the World Health Organization over the next 10 to 15 years, people in every world region will suffer more death and disability from noncommunicable diseases as heart diseases, cancers, and diabetes than from infectious and parasitic diseases [1]. To accommodate the social cost of aging population and lifestyle diseases, there is a strong need for affordable primary care. In particular, for healthcare delivery models that places less reliance on doctors and more on other health workers. Affordability is tightly coupled with information and communication technologies that integrate primary healthcare and the curative models and make healthcare environments more accessible for older and morbid people [2]. The provision of primary healthcare is not evenly distributed - one billion people are unreached in terms of accessing to quality healthcare service [3]. Most of the unreached people are from rural areas in developing countries [4]. Healthcare service does not exist there for two major reasons: (1) Doctors do not want to stay in the village as they do not find their livelihood requirements fulfilled (2) Quality hospitals/clinics do not sustain without stable income. Information Communication and Technologies (ICT) remote healthcare consultancy systems have been deployed in the global market. Mobile health has increased access to healthcare and health-related information for many unreached communities. Health consultancy over mobile phone is popular in developing countries such as Bangladesh and provides an alternative solution for partial healthcare delivery [5]. To the extent that one such service holder receives 15000 calls per day for health consultancy [6]. However, these mobile health services do not test the patient against a diagnosis process or use Electronic Health Records and this reduces the primary care impact. In addition, there is little scope to empower the local healthcare worker with the mobile phone procedures. The research problem is to provide a remote healthcare consultancy system that mitigates the effects of lifestyle diseases in unreached communities and aging populations. To empower the healthcare worker to enable her to make recommendations that may diminish the likelihood of lifestyle diseases within the local environment and reduce the reliance on the doctor. In Sect.II, we describe the PHC architecture and introduce its business model for a female health worker. We discuss the PHC operation and telemedicine procedure. In Sect.III, we apply the one of the popular and well researched data mining tools, association rule, and discuss its results. In Sect.IV, we conclude that the health care worker can be empowered by PHC, and furthermore by our on-going CDSS.