Abstract
Patients have to carry out various complex tasks when they visit hospitals. In this context, workflow management systems offer a structured solution for modeling these tasks with workflows in order to guide patients. Furthermore, the integration of smartphones and pervasive technologies with workflows facilitates both the collection of relevant data and the delivery of timely information to users. In this chapter, we present a mobile application working in conjunction with a pervasive workflow management system, highlighting the design of mobile health (mHealth) solution, named HealthGuide. As advocated by the socio-technical system design (STSD) approach, the system design is guided by incorporating the user perspective in order to reduce the risk of failure. Accordingly, we design HealthGuide by considering critical adoption factors in the mHealth literature in addition to identifying user needs through user involvement. The system aims to provide guidance to users regarding their tasks in a hospital so that they can accomplish their tasks accurately and in the correct order, both inside and outside the hospital. Hence, HealthGuide empowers patients and helps improve the user experience and satisfaction by providing personalized services in a timely manner while also increasing the quality of healthcare services and the efficiency of healthcare providers. The outpatient treatment process is given as a sample scenario to demonstrate the capabilities of HealthGuide from the perspective of users. Benefits and challenges associated with HealthGuide are also discussed to highlight the implications of the system.
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References
Abrahamsson P, Salo O, Ronkainen J, Warsta J (2002) Agile software development methods: Review and analysis, VTT publication 478, Espoo, Finland, 107p
Aggelidis VP, Chatzoglou PD (2009) Using a modified technology acceptance model in hospitals. Int J Med Inform 78:115–126
Aitken M, Lyle J (2015) Patient adoption of mHealth: Use, evidence and remaining barriers to mainstream acceptance. IMS Institute for Healthcare Informatics, New York
Amazon EC (2012) SLA. Retrieved from: https://aws.amazon.com/ec2/sla/
Barton AJ (2012) The regulation of mobile health applications. BMC Med 10:1
Becker S, Miron-Shatz T, Schumacher N et al (2014) mHealth 2.0: experiences, possibilities, and perspectives. JMIR mHealth uHealth 2:e24
Berg M (2001) Implementing information systems in health care organizations: myths and challenges. Int J Med Inform 64:143–156
Berg M, Aarts J, van der Lei J (2003) ICT in health care: sociotechnical approaches. Methods Arch 42:297–301
Beyer H, Holtzblatt K (1999) Contextual design. Interactions 6:32–42
Boye N (2008) Pervasive healthcare: problems and potentials. human, Soc Organ Asp Heal Inf Syst IGI Glob New York, Hershey, pp 84–102
Buntin MB, Burke MF, Hoaglin MC, Blumenthal D (2011) The benefits of health information technology: a review of the recent literature shows predominantly positive results. Health Aff 30:464–471
Chaudhry B, Wang J, Wu S et al (2006) Systematic review: impact of health information technology on quality, efficiency, and costs of medical care. Ann Intern Med 144:742–752
Chen J, Park Y, Putzer GJ (2010) An examination of the components that increase acceptance of smartphones among healthcare professionals. Electron J Heal Informatics 5:16
Chomutare T, Fernandez-Luque L, Ă…rsand E, Hartvigsen G (2011) Features of mobile diabetes applications: review of the literature and analysis of current applications compared against evidence-based guidelines. J Med Internet Res 13:e65
Collins SA, Vawdrey DK, Kukafka R, Kuperman GJ (2011) Policies for patient access to clinical data via PHRs: current state and recommendations. J Am Med Informatics Assoc 18:i2–i7
Connor YO, Connor SO, Heavin C et al (2016) Chapter 10 – sociocultural and technological barriers across all phases of implementation for mobile health in developing countries. In: Al-Jumeily D, Hussain A, Mallucci C, Oliver C (eds) Applied computing in medicine and health. Morgan Kaufmann, Boston, pp 212–230
Davis, FD (1989) Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS quarterly, 13(3):319–340
Drazen EL, Metzger JB, Ritter JL, Schneider MK (2012) Patient care information systems: successful design and implementation. Springer Science & Business Media, New York
Ducey AJ, Coovert MD (2016) Predicting tablet computer use: an extended technology acceptance model for physicians. Health Policy Technol 5(3):268–284
Duhm J, Fleischmann R, Schmidt S et al (2016) Mobile electronic medical records promote workflow: physicians’ perspective from a survey. JMIR mHealth uHealth 4:e70
Emery FE, Trist EL (1960) Socio-technical systems. In: Churchman CW, Verhulst M (eds) Management Science Models and Techniques, Vol. 2, Harmondsworth, Penguin Books, Pergamon
Estrin D, Culler D, Pister K, Sukhatme G (2002) Connecting the physical world with pervasive networks. IEEE pervasive computing, 1(1):59–69
Gagnon M-P, Ngangue P, Payne-Gagnon J, Desmartis M (2016) M-health adoption by healthcare professionals: a systematic review. J Am Med Informatics Assoc 23:212–220
Giardina TD, Menon S, Parrish DE et al (2014) Patient access to medical records and healthcare outcomes: a systematic review. J Am Med Informatics Assoc 21:737–741
Hale K, Capra S, Bauer J (2015) A framework to assist health professionals in recommending high-quality apps for supporting chronic disease self-management: illustrative assessment of type 2 diabetes apps. JMIR Mhealth Uhealth 3(3):e87
Hsieh F-S, Lin J-B (2014) Development of context-aware workflow systems based on petri net markup language. Comput stand. Interfaces 36:672–685
Hung S-Y, Y-C K, Chien J-C (2012) Understanding physicians’ acceptance of the Medline system for practicing evidence-based medicine: a decomposed TPB model. Int J Med Inform 81:130–142
Intelligence M (2016) Global mobile health (mHealth) Market – Growth, trends & forecasts (2016–2021)
Kim S, Lee K-H, Hwang H, Yoo S (2016) Analysis of the factors influencing healthcare professionals’ adoption of mobile electronic medical record (EMR) using the unified theory of acceptance and use of technology (UTAUT) in a tertiary hospital. BMC Med Inform Decis Mak 16:1
Kitchenham B (2004) Procedures for performing systematic reviews. Keele, Keele Univ 33:28. https://doi.org/10.1.1.122.3308
Kumar S, Nilsen WJ, Abernethy A et al (2013) Mobile health technology evaluation: the mHealth evidence workshop. Am J Prev Med 45:228–236
Kushniruk AW (2008) Human, social, and organizational aspects of health information systems. IGI Global, New York
Leonard D, Rayport JF (1997) Spark innovation through empathic design. Harv Bus Rev 75:102–115
Lin S-P (2011) Determinants of adoption of mobile healthcare service. Int J Mob Commun 9:298–315
Lo C-C, Chen C-H, Cheng D-Y, Kung H-Y (2011) Ubiquitous healthcare service system with context-awareness capability: design and implementation. Expert Syst Appl 38:4416–4436
Mans RS, Schonenberg MH, Song M et al. (2008a) Application of process mining in healthcare-a case study in a dutch hospital. In: International joint conference on biomedical engineering systems and technologies, BIOSTEC 2008 Funchal, Madeira, Portugal, pp 425–438
Mans RS, van der Aalst WMP, Russell NC, Bakker PJM (2008b) Flexibility schemes for workflow management systems. In: International conference on business process management. Springer, Berlin, pp 361–372
Mans RS, Russell NC, van der Aalst WMP et al (2010) Proclets in healthcare. J Biomed Inform 43:632–649
Nah FF-H, Siau K, Sheng H (2005) The value of mobile applications: a utility company study. Commun ACM 48:85–90
Okazaki S, Castañeda JA, Sanz S, Mukherji P (2016) Physicians’ motivations to use mobile health monitoring: a cross-country comparison. Behav Inf Technol 36:1–12
Payne TH, Bates DW, Berner ES et al (2013) Healthcare information technology and economics. J Am Med Informatics Assoc 20:212–217
Prinyapol N, Fan JP, Lau SK (2009) A hospital based dynamic platform workflow management. IAENG International Journal of Computer Science 36(2):192–198
Pryss R, Tiedeken J, Kreher U, Reichert M (2010) Towards flexible process support on mobile devices. In: Forum at the conference on advanced information systems engineering (CAiSE). Hammamet, Tunisia, pp 150–165
Riggins FJ, Dewan S (2005) The digital divide: current and future research directions. J Assoc Inf Syst 6:13
Sarker S, Wells JD (2003) Understanding mobile handheld device use and adoption. Commun ACM 46:35–40
Schuler D, Namioka A (1993) Participatory design: principles and practices. CRC Press, Boca Raton
Sezgin E, Yıldırım SÖ (2014) A literature review on attitudes of health professionals towards health information systems: from e-health to m-health. Procedia Technol 16:1317–1326
Simon SK, Seldon HL (2012) Personal health records: mobile biosensors and smartphones for developing countries. Glob Telehealth 182:125–132
SNS Telecom (2016) The mHealth (Mobile Healthcare) ecosystem: 2015–2030 – Opportunities, challenges, strategies & forecasts
Tang PC, Lansky D (2005) The missing link: bridging the patient–provider health information gap. Health Aff 24:1290–1295
Tüysüz G, Avenoglu B, Eren PE (2013) A workflow-based mobile guidance framework for managing personal activities. In: 2013 Seventh international conference on next generation mobile apps, services and technologies. IEEE, pp 13–18
Uppu S, Hoang DB, Hintz T (2006) A mobile hand held computing system for out patient workflow in hospital environment. In: 2006 IEEE 63rd vehicular technology conference. IEEE, pp 751–755
Van der Aalst WMP (2011) Getting the data. In: Process mining. Springer, Berlin, pp 95–123
Venkatesh V, Thong JYL, Xu X (2012) Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Q 36:157–178
Visvanathan A, Gibb AP, Brady RRW (2011) Increasing clinical presence of mobile communication technology: avoiding the pitfalls. Telemed e-Health 17:656–661
Whetton S (2005) Health informatics: A socio-technical perspective. Oxford University Press, South Melbourne, pp. 260
WHO (2004) International statistical classification of diseases and health related problems (The) ICD-10
Wu J-H, Wang S-C, Lin L-M (2007) Mobile computing acceptance factors in the healthcare industry: a structural equation model. Int J Med Inform 76:66–77
Wu L, Li J-Y, C-Y F (2011) The adoption of mobile healthcare by hospital’s professionals: an integrative perspective. Decis Support Syst 51:587–596
Xu W, Liu Y (2015) mHealthApps: a repository and database of mobile health apps. JMIR mHealth uHealth 3:e28
Yamin CK, Emani S, Williams DH et al (2011) The digital divide in adoption and use of a personal health record. Arch Intern Med 171:568–574
Yoo S, Jung SY, Kim S et al (2016) A personalized mobile patient guide system for a patient-centered smart hospital: lessons learned from a usability test and satisfaction survey in a tertiary university hospital. Int J Med Inform 91:20–30
Zini F, Ricci F (2011) Guiding patients in the hospital. In: International conference on user modeling, adaptation, and personalization. Springer, Berlin, pp 309–319
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Eren, P.E., Gökalp, E. (2018). HealthGuide: A Personalized Mobile Patient Guidance System. In: Sezgin, E., Yildirim, S., Özkan-Yildirim, S., Sumuer, E. (eds) Current and Emerging mHealth Technologies. Springer, Cham. https://doi.org/10.1007/978-3-319-73135-3_11
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