Mobile Technology Applications in the Healthcare ...

Available online at www.sciencedirect.com

ScienceDirect Procedia - Social and Behavioral Sciences 195 (2015) 2014 – 2018

World Conference on Technology, Innovation and Entrepreneurship

Mobile Technology Applications in the Healthcare Industry for Disease Management and Wellness Güler Kalema, *dL÷GHP7XUKDQa a

$WÕOÕP8QLYHUVLW\'HSDUWPHQWRI6RIWZDUH(QJLQHHULQJøQFHNAnkara, Turkey

Abstract Technology is an unavoidable fact of today’s life. Attractive advantages of wireless technology accelerated the rapid development of mobile applications. With the increase of the usage of mobile devices in the recent years, new solutions come to mind including mobile technologies to fulfill requirements or suggest better solutions in the vast area of medical informatics to the existing ones. Augmentation in the area of wireless technology positively affects the medical applications. In the healthcare industry, mobile applications provide better personalized health care, disease management and services to patients and their relatives, as well as a better and flexible way of communicating with physicians, patients and medical suppliers. It is obvious that the applications using mobile technologies has the potential to bring better conditions both for the patients for their disease management and for the humanity for checking their self wellness. In this paper, the current mobile technology utilized in healthcare such as relapse prevention in schizophrenia, aged people’s care and wellness, diagnosis and management of attentiondeficit etc. is reviewed in detail outlining the current mobile technologies and wireless revolution of today and examining some of the outstanding applications using these technologies in the clinical area. The results of this study can provide clues to researchers to further the mobile technology in healthcare. © 2015 byby Elsevier Ltd.Ltd. This is an open access article under the CC BY-NC-ND license © 2015 The TheAuthors. Authors.Published Published Elsevier (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Istanbul University. Peer-review under responsibility of Istanbul Univeristy.

Keywords: Disease management; healthcare applications; mobile technology; wellness; wireless revolution

* Corresponding author. Tel.: +90-312-586-8714; fax: +90-312-586-8091. E-mail address: [email protected]

1877-0428 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of Istanbul Univeristy. doi:10.1016/j.sbspro.2015.06.216

Güler Kalem and Çiğdem Turhan / Procedia - Social and Behavioral Sciences 195 (2015) 2014 – 2018

2015

1. Introduction Since competition of medical applications accelerated and the usage of internet increased in all areas of people’s life, the need to convince healthcare professionals like physicians and nursing staff to use the applications of mobile technology arises. This incredible popularity has coincided with technological advances in the power of computing, memory size, colorful and thin screens, functionalities and wireless connectivity. The computing devices like Personal Digital Assistants (PDAs) and Pocket Personal Computers (Pocket PCs) are today highly mobile and easily internet accessible.

2. Literature Review And Hypotheses In the clinical area, some outstanding and distinguished applications such as relapse prevention in schizophrenia (Španiel, Vohlídka+UGOLþND.RåHQê1RYiN0RWORYiýHUPiN%HGQDĜtN1RYiN +|VFKO), diagnosis and management of attention-deficit in other words hyperactivity disorder (Foy & Earls, 2005), management of asthma (Ryan, Cobern, Wheeler, Price, & Tarassenko, 2005) and using mobile phone technology for recording and gathering asthma data (Cleland, Caldow, & Ryan, 2007), intelligent biomedical clothing for disease management and personalized health care (Lymberis & Olsson, 2003), automated speech recognition for time recording in out-ofhospital emergency medicine (Gröschel, Philipp, Skonetzki, Genzwürker, Wetter, & Ellinger, 2004), evaluating the impact of mobile phone technology on type 2 diabetic patients’ self-management (Faridi, Liberti, Shuval, Northrup, Ali, & Katz, 2008), and (Årsand, Frøisland, Skrøvseth, Chomutare, Tatara, Hartvigsen, & Tufano, 2012). Moreover, patients with headache disorders (Hundert, Huguet, McGrath, Stinson, & Wheaton, 2014) prefer to use mobile applications, also in the prevention and management of mental disorders (Proudfoot, 2013), mobile phones are used. So far in these areas, mobile applications have been developed and tested; and valuable and acceptable results have been reached.

3. Mobile Technology Applications in the Healthcare The development of mobile technologies steered both the manufacturers to compete with the existing firms, and the solution developers to produce new and talented applications using mobile technologies (Price & Summers, 2006). In the healthcare environment using mobile technology and mobile devices has proven to be effective. While developing such applications, patient requirements and the level patient accept the impact of technology on their health care and disease management should be considered (Siau & Shen, 2000). It is a must to make it balanced between the cost of deployment and the use of device and satisfying patients’ requirements. Some of the outstanding mobile applications in healthcare environment, their advantages and disadvantages from different points of view are presented below. ITAREPS (Information Technology Aided Relapse Prevention Programme in Schizophrenia) (Španiel, Vohlídka, +UGOLþND.RåHQê1RYiN0RWORYiýHUPiN%HGQDĜtN1RYiN +|VFKO) is a program which aids relapse in the prevention of schizophrenia using information technology. It provides a mobile phone based telemedicine solution for this purpose. With the help of the home telemonitoring system via a PC to mobile phone SMS (Short Message Service) platform which recognizes prodromal symptoms of relapse, the system warns to take the action before hospitalization which is both costly and stressful both for the patient and the family of the patient. This program offers an authorized web based interface both for the physician and for the patient to analyze the dynamics and development of possible prodromes. The early warning signs data is collected through a SMS platform using a mobile phone, from the patient himself/herself and from his/her family members.

2016


As a second application, in the management of asthma (Ryan, Cobern, Wheeler, Price, & Tarassenko, 2005) peak flow monitoring is widely recommended and used. This study includes an observational study using handheld electronic peak flow meter monitoring and mobile phone technology in a time period of nine months. Patients who are at the ages of between 12 and 55 requiring treatment with regular inhaled steroids and bronchodilators were recruited from nine general practices. In this study, from all of the participants 69% of them who has filled in the post-study questionnaire form were marked as ‘satisfied’ or ‘very satisfied’ by the study, citing the ease of use and the increased autonomy and understanding of the asthma as the main advantages. Totally, 74% of them have indicated that the system had helped to improve their ability to manage their symptoms. The most attractive features of the telemedicine system were increased awareness and information about asthma, improved ability to monitor and manage the condition with the feedback screens on the mobile phone and ease of use. As a result it is possible to say that a server based peak flow asthma telemedicine system that analyses peak flow values in real time and feeds information back to the patient within seconds would be a valuable tool to enhance self management. The usage of mobile phone technology for recording and gathering asthma data (Cleland, Caldow, & Ryan, 2007) is another valuable study in this field. In this study a qualitative interview study using a purposeful sample of 10 patients with asthma and two research staff were conducted. The patients’ diary information was collected twice a day using an electronic peak flow meter linked to a mobile phone with an interactive screen to record current asthma symptoms and this information is stored in a server. Both the patients and the staff believed that mobile phone technology would be useful in clinical practice as well as research Cornelius & Gordon, 2008. Its main uses were seen as identifying poor control more quickly and facilitating communication with healthcare professionals without the need of face-to-face consultation and there was a high degree of acceptability by both patients and staff. As another application, the intelligent biomedical clothing for personal health care and for disease management (Lymberis & Olsson, 2003) is a revolution in clinical area. The growths of developments in microsystems and nanotechnologies as well as in information processing and communication technologies allow miniaturization and non-invasive smart monitoring of physiological and physical data. From the multidisciplinary point of view, research in textile fibers, biomedical sensors, and wireless technology and mobile telecommunications is integrated together with telemedicine. This integration aims to develop IBCs (Intelligent Biomedical Clothings) that could open the way to support personalized management of health and diseases at any time needed. For many purposes such as health monitoring, disease prevention and management, rehabilitation, and sports medicine, IBC may offer wearable non-obtrusive telemedicine platform for individualized services that is readily accessible with good quality (Dee, Teolis, & Todd, 2005). In addition, automated speech recognition (Gröschel, Philipp, Skonetzki, Genzwürker, Wetter, & Ellinger, 2004) for time recording in out-of-hospital emergency medicine is a medical treatment in emergency medical missions and for resuscitation. It is essential from a medical, legal and quality assurance point of view. All current methods of time recordings are either too inaccurate or elaborate for routine applications. In this study standard speech recognition software was adapted and installed on two different computer systems. One of them was a stationary PC (Personal Computer) and the other one was a mobile pen-PC that had already proven its value during emergency missions before. On both of the computers two different microphones were tested. One of them was a standard headset that came with the recognition software on it and the other one was a small microphone, which could be attached to the physicians or operators collar. With the results at hand, time recording with automated speech recognition seems to be possible in emergency medical missions. Although results show an average recognition of only 75%, it is possible to make it higher by reconstructing the missing elements more precisely. Furthermore, the NICHE (Faridi, Liberti, Shuval, Northrup, Ali, & Katz, 2008) pilot study is about the evaluation of the impact of mobile telephone technology on type 2 diabetic patients' self-management. This study utilizes information technology, such as Internet and mobile phones in enhancing diabetic care. With this study it is aimed to


2017

examine the feasibility of utilizing mobile technology to assist with diabetes in self-care in a clinical population as well as its impact on clinical outcomes. The methods used in this study can be summarized as the following; thirty patients with a diagnosis of type 2 diabetes at two Community Health Centers were randomly selected to intervention or control. Then intervention patients participated in a brief intervention and received tailored daily messages via their mobile phone prompting them to enhance their diabetic self-care behavior. The patients at the control site continued with their standard diabetes self-management. With this study an acceptable mean improvement is reached in different levels and it was apparent in the intervention group, compared with a mean deterioration in the control, yet without statistical significance. Self-efficacy scores improved significantly in the intervention group compared with the no improvement in the control group. The participants encountered many technological barriers when attempting to adhere to the intervention protocol. At the end of the study, the results indicate the intervention had a positive impact on some of the clinical outcome and self-efficacy. The FTA (the Few Touch Application) (Årsand, Frøisland, Skrøvseth, Chomutare, Tatara, Hartvigsen, & Tufano, 2012) is another study for diabetic patients. It provides support to diabetic patients for their self-management using a diabetes diary by the help of a mobile phone. Data can be updated both automatically and manually with user input. This tool has different opportunities such as transferring of blood glucose data automatically, food advice, monitoring of physical activity, etc. This study is useful since it provides personalized decision support for personal health goals, with the automatic transfer of physical activity, giving advice to motivate users, and the blood glucose data automatic transfer makes patients feel more confident. As a result, this tool is useful and valuable, and helps patients in their self-management. Another area is in headache disorders (Hundert, Huguet, McGrath, Stinson, & Wheaton, 2014) where mobile technologies are used by the patients very commonly. Mobile applications help patients by creating a headache diary and health care professionals try to name the type of the headache. Since headache problem varies too much from person to person and even for a person it varies also from different conditions and time periods, it is difficult to say whether mobile applications are useful or not, but in the long run, applications promise to help patients. Moreover, the role of mobile phones usage in the prevention and management of mental disorders (Proudfoot, 2013) is promising as well because they are successfully deployed in the therapeutic situations. There are different studies that are useful and motivational such as activity recognition for disease diagnosis/treatment, sports training and child/elderly care using mobile devices (Martin, Bernardos, Iglesias, & Casar, 2013), and physical fitness activity supervising system that is adapted to the user and the context (Buttussi & Chittaro, 2008).

4. Conclusion As seen in the reviewed literature mobile applications for disease management and wellness encompass various areas such as asthma, psychological disorder, diabetes, headache, wearable technologies, physical activity recognition, etc. with promising results. As a conclusion, with the help of mobile technologies in healthcare environment, patients are able to track their symptoms, gather more data correctly, improve self-efficacy and provide more information to their doctors, which in turn help with their recovery and wellness. References Årsand, E., Frøisland, D. H., Skrøvseth, S. O., Chomutare, T., Tatara, N., Hartvigsen, G., & Tufano, J. T. (2012). Mobile Health Applications to Assist Patients with Diabetes: Lessons Learned and Design Implications. Journal of Diabetes Science and Technology, 6, Issue 5, Diabetes Technology Society. Buttussi, F., & Chittaro, L. (2008). MOPET: A context-aware and user-adaptive wearable system for fitness training. Artificial Intelligence in Medicine, 42, 153-163.

2018

Güler Kalem and Çiğdem Turhan / Procedia - Social and Behavioral Sciences 195 (2015) 2014 – 2018 Cleland, J., Caldow, J., & Ryan, D. (2007). A qualitative study of the attitudes of patients and staff to the use of mobile phone technology for recording and gathering asthma data. Journal of Telemedicine and Telecare, vol. 13 /2, 85-89. Cornelius, F. H., & Gordon, M. G. (2008). PDA Connections: Mobile Technology for Health Care Professionals. Nurse Education Today, vol. 28, 129-129. Dee, C. R., Teolis, M., & Todd, A. D. (2005). Physicians’ use of the personal digital assistant (PDA) in clinical decision making. Journal of the Medical Library Association, 93/4, 480-486. Faridi, Z., Liberti, L., Shuval, K., Northrup, V., Ali, A., & Katz, DL. (2008). Evaluating the impact of mobile phone technology on type 2 diabetic patients’ self-management: the NICHE pilot study. Journal of Evaluation Clinical Practice, 14/3, 465-469. Foy, J. M., & Earls, M. F. (2005). A Process for Developing Community Consensus Regarding the Diagnosis and Management of AttentionDeficit/Hyperactivity Disorder. American Academy of Pediatrics,115, 97-104. Gröschel, J., Philipp, F., Skonetzki, St., Genzwürker, H., Wetter, Th., & Ellinger, K. (2004). Automated speech recognition for time recording in out-of-hospital emergency medicine – an experimental approach. Elsevier, Resuscitation, 60, 205-212. Hundert, A. S., Huguet, A., McGrath, P. J., Stinson, J. N., & Wheaton, M. (2014). Commercially Available Mobile Phone Headache Diary Apps: A Systematic Review. JMIR Mhealth Uhealth. 2(3): e36. doi: 10.2196/mhealth.3452. Lymberis, A., & Olsson, S. (2003). Intelligent Biomedical Clothing for Personal Health and Disease Management: State of the Art and Future Vision. Telemedicine Journal and e-Health, 9/4. 0DUWLQ+%HUQDUGRV$0,JOHVLDV- &DVDU-5 $FWLYLW\ORJJLQJXVLQJOLJKWZHLJKWFODVVL¿FDWLRQWHFKQLTXHs in mobile devices. Pers Ubiquit Comput, 17:, 675–695, DOI 10.1007/s00779-012-0515-4. Price, S., & Summers, R. (2006). Mobile healthcare in the home environment. EMBS Annual International Conference. Proudfoot, J. (2013). The future is in our hands: The role of mobile phones in the prevention and management of mental disorders. Australian & New Zealand Journal of Psychiatry 47(2), 111–113. Ryan, D., Cobern, W., Wheeler, J., Price, D., & Tarassenko, L. (2005). Mobile phone technology in the management of asthma. Journal of Telemedicine and Telecare, 11/1, 43-46. Siau, K., & Shen, Z. (2000). Mobile Healthcare Informatics. Medical Informatics and the Internet in Medicine, 31/2, 89-99. âSDQLHO)9RKOtGND3+UGOLþND-.RåHQê-1RYiN70RWORYi/ýHUPiN-%HGQDĜtN, J., Novák, D., & Höschl, C. (2008). ITAREPS: Information Technology Aided Relapse Prevention Programme in Schizophrenia. Science Direct, Schizophrenia Research, 98, 312-317.