Abstract
While mobile Health (mHealth) holds much potential, the infusion of mHealth is still in its infancy and has yet to achieve sufficient attention in the Information Systems field. As a result, the objective of this paper is to identify the (a) determinants for successful infusion of mHealth by healthcare practitioners and (b) benefits healthcare practitioners perceive from infusing mHealth. A sequential mixed methods approach (case study and survey) is employed to achieve this objective. The study contributes to IS theory and practice by: (1) developing a model with six determinants (Availability, Self-Efficacy, Time-Criticality, Habit, Technology Trust, and Task Behaviour) and three individual performance-related benefits associated with mHealth infusion (Effectiveness, Efficiency, and Learning), (2) exploring undocumented determinants and relationships, (3) identifying conditions that both healthcare practitioners and organisations can employ to assist with mHealth infusion and (4) informing healthcare organisations and vendors as to the performance of mHealth in post-adoptive scenarios.
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Abdinnour-Helm, S., & Saeed, K. (2006). Examining Post Adoption Usage: Conceptual Development and Empirical Assessment. Paper presented at the AMCIS 2006 Proceedings, Paper 148.
Agarwal, R., & Venkatesh, V. (2002). Assessing a firm’s web presence: a heuristic evaluation procedure for the measurement of usability. Information Systems Research, 13(2), 168–186.
Aitken, M., & Gauntlett, C. (2013). IMS Institute for healthcare informatics patient apps for improved healthcare: from novelty to mainstream. http://obroncology.com/imshealth/content/IIHI%20Apps%20report%20231013F_interactive.pdf.
Ang, W. J. J., Hopkins, M. E., Partridge, R., Hennessey, I., Brennan, P. M., Fouyas, I., et al. (2014). Validating the use of smartphone-based accelerometers for performance assessment in a simulated neurosurgical task. Neurosurgery, 10, 57–65.
Anglada-Martinez, H., Riu-Viladoms, G., Martin-Conde, M., Rovira-Illamola, M., Sotoca-Momblona, J., & Codina-Jane, C. (2015). Does mHealth increase adherence to medication? Results of a systematic review. International Journal of Clinical Practice, 69(1), 9–32.
Basole, R. C. (2004). The value and impact of mobile information and communication technologies. In Proceedings of the 2004 International Federation of Automatic Control Symposium, Atlanta, GA, USA, 2004,(pp. 1-7)
Becker, S., Brandl, C., Meister, S., Nagel, E., Miron-Shatz, T., Mitchell, A., et al. (2015). Demographic and health related data of users of a mobile application to support drug adherence is associated with usage duration and intensity. PloS One, 10(1), e0116980.
Bergeron, F., Raymond, L., Rivard, S., & Gara, M. (1995). Determinants of EIS use: testing a behavioral model. Decision Support Systems, 14(2), 31–146.
Black, A. D., Car, J., Pagliari, C., Anandan, C., Cresswell, K., Bokun, T., et al. (2011). The impact of eHealth on the quality and safety of health care: a systematic overview. PLoS Medicine, 8(1), e1000387.
Boell, S. K., & Cecez-Kecmanovic, D. (2014). A hermeneutic approach for conducting literature reviews and literature searches. Communications of the Association for Information Systems, 34(1), 257–286.
Cavaye, A. L. M. (1996). Case study research: a multi-faceted research approach for IS. Information Systems Journal, 6(3), 227–242.
Cavus, N., & Munyavi, R. M. (2015). An assessment of the effects of widespread use of mobile applications in the health sector: an exploratory study of its success and failures. Global Journal on Advances in Pure & Applied Sciences, 7, 145–149.
Chen, H., Hailey, D., Wang, N., & Yu, P. (2014). A review of data quality assessment methods for public health information systems. International Journal of Environmental Research and Public Health, 11(5), 5170–5207.
Chin, W. W. (1998). The partial least squares approach for structural equation modeling. In M. G. E. (Ed.), (Ed.), Modern Methods for Business Research (pp. 295–336). Mahwah: Lawrence Erlbaum Associates.
Chiu, T. M., & Eysenbach, G. (2010). Stages of use: consideration, initiation, utilization, and outcomes of an internet-mediated intervention. BMC Medical Informatics and Decision Making, 10(1), 73.
Choi, A. L., Lai, D. A., & Lai, T. L. (2016). Health analytics, economics and medicine toward a twenty-first century health care system. Health, 8(05), 428.
Chung, W. Y., & Guinan, P. J. (1994). Effects of participative management on the performance of software development teams. In Proceedings of the 1994 computer personnel research conference on Reinventing IS: managing information technology in changing organizations: managing information technology in changing organizations. (pp. 252–260): ACM.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences Hillsdale. NJ: Lawrence Erlbaum Associates.
Compeau, D. R., & Higgins, C. A. (1995). Computer self-efficacy: development of a measure and initial test. MIS Quarterly, 19(2), 189–211.
Cooper, R. B., & Zmud, R. W. (1990). Information technology implementation research: a technological diffusion approach. Management Science, 36(2), 123–139.
Craig, K., Tams, S., Clay, P., & Thatcher, J. (2010). Integrating trust in technology and computer self-efficacy within the post-adoption context: An empirical examination.
Daniels, N., & Sabin, J. E. (2002). Setting limits fairly: Can we learn to share medical resources? Oxford University Press. http://EconPapers.repec.org/RePEc:oxp:obooks:9780195149364.
Darke, P., Shanks, G., & Broadbent, M. (1998). Successfully completing case study research: combining rigour, relevance and pragmatism. Information Systems Journal, 8(4), 273–289. doi:10.1046/j.1365-2575.1998.00040.x.
Davenport, T. H., & Prusak, L. (1998). Working Knowledge. How Organizations Manage What They Know. Boston, Mass: Harvard Business School Press 1998.
Dehzad, F., Hilhorst, C., de Bie, C., & Claassen, E. (2014). Adopting health apps, What’s hindering doctors and patients? Health, 2014.
Deng, X., & Chi, L. (2012). Understanding postadoptive behaviors in information systems use: a longitudinal analysis of system use problems in the business intelligence context. Journal of Management Information Systems, 29(3), 291–326.
DesRoches, C. M., Campbell, E. G., Rao, S. R., Donelan, K., Ferris, T. G., Jha, A., et al. (2008). Electronic health Records in Ambulatory Care — a National Survey of physicians. New England Journal of Medicine, 359(1), 50–60. doi:10.1056/NEJMsa0802005.
Devaraj, S., & Kohli, R. (2000). Information technology payoff in the health-care industry: alongitudinal study. Journal of Management Information Systems, 16(4), 41–67.
Diamantopoulos, A., & Siguaw, J. A. (2006). Formative versus reflective indicators in organizational measure development: a comparison and empirical illustration. British Journal of Management, 17(4), 263–282.
Dwivedi, Y. K., Shareef, M. A., Simintiras, A. C., Lal, B., & Weerakkody, V. (2016). A generalised adoption model for services: a cross-country comparison of mobile health (m-health). Government Information Quarterly, 33(1), 174–187.
Eady, A., Glasziou, P., & Haynes, B. (2008). Less is more: where do the abstracts in the EBM journal come from? Evidence-Based Medicine, 13(1), 3.
Ebell, M. H. (2009). How to find answers to clinical questions. American Family Physician, 79(4), 293–296.
El Morr, C., & Subercaze, J. (2010). Knowledge Management in Healthcare. MM Cunha, A. Tavares, & R. Simões, Handbook of Research on Developments in e-Health and Telemedicine: Technological and Social Perspectives. IGI Global.
Fadel, K. (2006). Individual Infusion of Information Systems: The Role of Adaptation and Individual Cognitions. Paper presented at the AMCIS 2006, Proceedings Paper 38.
Fornell, C., & Larcker, D. F. (1981). Structural equation models with unobservable variables and measurement error: algebra and statistics. Journal of Marketing Research, 18(3), 382–388.
Franz-Vasdeki, J., Pratt, B. A., Newsome, M., & Germann, S. (2015). Taking mHealth solutions to scale: enabling environments and successful implementation. Journal of Mobile Technology in Medicine, 4(1), 35–38.
Free, C., Phillips, G., Watson, L., Galli, L., Felix, L., Edwards, P., et al. (2013). The effectiveness of mobile-health technologies to improve health care service delivery processes: a systematic review and meta-analysis. PLoS Medicine, 10(1), e1001363.
Gagnon, M.-P., Ngangue, P., Payne-Gagnon, J., & Desmartis, M. (2016). M-health adoption by healthcare professionals: a systematic review. Journal of the American Medical Informatics Association, 23(1), 212–220.
Galliers, R. D. (1992). Choosing information systems research approaches. In R. D. Galliers (Ed.), Information systems research: Issues, methods and practical guidelines (pp. 144–162). Alfred Waller Ltd: Henley-on-Thames.
Gallivan, M., & Srite, M. (2005). Information technology and culture: identifying fragmentary and holistic perspectives of culture. Information and Organization, 15(4), 295–338.
Garfield, M. J., & Dennis, A. R. (2012). Toward an integrated model of group development: disruption of routines by technology-induced change. Journal of Management Information Systems, 29(3), 43–86.
Gebauer, J., & Tang, Y. (2007). Applying the theory of task-technology fit to mobile information systems: the role of user mobility. In Management of Mobile Business, 2007. ICMB 2007. International Conference on the, 2007 (pp. 38–38): IEEE.
Gefen, D., & Straub, D. (2005). A practical guide to factorial validity using PLS-graph: tutorial and annotated example. Communications of the Association for Information Systems, 16(1), 91–109.
Goodhue, D. L., & Thompson, R. L. (1995). Task-technology fit and individual performance. MIS Quarterly, 19(2), 213–236.
Hackman, J. R., & Oldham, G. R. (1976). Motivation through the design of work: test of a theory. Organizational Behavior and Human Performance, 16(2), 250–279.
Hamine, S., Gerth-Guyette, E., Faulx, D., Green, B. B., & Ginsburg, A. S. (2015). Impact of mHealth chronic disease management on treatment adherence and patient outcomes: a systematic review. Journal of Medical Internet Research, 17(2), e52.
Hasan, H., Linger, H., Kim, H.-W., Chan, H. C., & Gupta, S. (2016). Examining information systems infusion from a user commitment perspective. Information Technology & People, 29(1), 173–199.
Hsia, T.-L., Lin, L.-M., Wu, J.-H., & Tsai, H.-T. (2006). A framework for designing nursing knowledge management systems. Interdisciplinary Journal of Information, Knowledge, and Management, 1(1), 13–23.
Hsiao, J.-L., & Chen, R.-F. (2012). An investigation on task-technology fit of mobile nursing information Systems for Nursing Performance. Computers, Informatics, Nursing, 30(5), 265–273.
Hsieh, J. J. P. A., & Wang, W. (2007). Explaining employees’ extended use of complex information systems. European Journal of Information Systems, 16(3), 216–227.
Hsieh, J. P.-A., & Zmud, R. (2006). Understanding Post-Adtopive Usage Behaviors: A Two-Dimensional View. DIGIT 2006 Proceedings. Paper 3. http://aisel.aisnet.org/digit2006/3.
Igbaria, M., & Iivari, J. (1995). The effects of self-efficacy on computer usage. Omega, 23(6), 587–605.
Jahns, R. H. P. (2014). Mobile health market report 2013–2017 (Vol3). Research2Guidace Report. http://research2guidance.com/wp-content/uploads/2015/08/Mobile-Health-Market-Report-2013-2017-Graphical-Package-Preview.pdf.
Jarvenpaa, S. L., & Lang, K. R. (2005). Managing the paradoxes of mobile technology. Information Systems Management, 22(4), 7–23.
Jasperson, J., Carter, P. E., & Zmud, R. W. (2005). A comprehensive conceptualization of post-adoptive behaviors associated with information technology enabled work systems. MIS Quarterly, 29(3), 525–557.
Junglas, I., Abraham, C., & Ives, B. (2009). Mobile technology at the frontlines of patient care: understanding fit and human drives in utilization decisions and performance. Decision Support Systems, 46(3), 634–647. doi:10.1016/j.dss.2008.11.012.
Kahn, J. G., Yang, J. S., & Kahn, J. S. (2010). ‘Mobile’health needs and opportunities in developing countries. Health Affairs, 29(2), 252–258.
Kane, B., & Luz, S. (2009). Achieving diagnosis by consensus. Computer Supported Cooperative Work, 18(4), 357–392. doi:10.1007/s10606-009-9094-y.
Katz, J. E., & Rice, R. E. (2009). Public views of mobile medical devices and services: a US national survey of consumer sentiments towards RFID healthcare technology. International Journal of Medical Informatics, 78(2), 104–114.
Ke, W., Tan, C.-H., Sia, C.-L., & Wei, K.-K. (2012). Inducing intrinsic motivation to explore the enterprise system: the supremacy of organizational levers. Journal of Management Information Systems, 29(3), 257–290.
Kim, H.-W., Chan, H. C., & Lee, S.-H. (2012). A User Commitment Approach to Information Systems Infusion. In PACIS 2012 Proceedings, Paper 101.
Kim, S., Shim, B., Kim, J. A., & Cho, I. S. (2010). SW architecture for access to medical information for knowledge execution. Security-Enriched Urban Computing and Smart Grid, 574–580.
Kwon, T. H., & Zmud, R. W. (1987). Unifying the fragmented models of information systems implementation. In Critical issues in information systems research (pp. 227–251): Wiley.
Labrique, A. B., Vasudevan, L., Kochi, E., Fabricant, R., & Mehl, G. (2013). mHealth innovations as health system strengthening tools: 12 common applications and a visual framework. Global Health: Science and Practice, 1(2), 160–171.
Liang, H., Peng, Z., Xue, Y., Guo, X., & Wang, N. (2015). Employees’ exploration of complex systems: an integrative view. Journal of Management Information Systems, 32(1), 322–357.
Lim, S. Y., Jarvenpaa, S. L., & Lanham, H. J. (2015). Barriers to Interorganizational knowledge transfer in post-hospital care transitions: review and directions for information systems research. Journal of Management Information Systems, 32(3), 48–74.
Limayem, M., Hirt, S. G., & Cheung, C. M. K. (2007). How habit limits the predictive power of intention: the case of information systems continuance. MIS Quarterly, 31(4), 705–737.
Makinen, J., & Jaakkola, H. (2000) Representing infusion of mobile phones. In Engineering Management Society, 2000. Proceedings of the 2000 IEEE (pp. 476–480): IEEE.
Marshall, C., & Rossman, G. B. (1989). Designing Qualitative Research: Sage Publications.
McKnight, D. H., Carter, M., Thatcher, J. B., & Clay, P. F. (2011). Trust in a specific technology: an investigation of its components and measures. ACM transactions on Management Information Systems, 2(2), 1–25. doi:10.1145/1985347.1985353.
McKnight, D. H., Choudhury, V., & Kacmar, C. (2002). Developing and validating trust measures for e-commerce: an integrative typology. Information Systems Research, 13(3), 334–359. doi:10.1287/isre.13.3.334.81.
Muessig, K. E., Pike, E. C., LeGrand, S., & Hightow-Weidman, L. B. (2013). Mobile phone applications for the care and prevention of HIV and other sexually transmitted diseases: a review. Journal of Medical Internet Research, 15(1), e1.
Nair, P., & Bhaskaran, H. (2014). The emerging interface of healthcare system and mobile communication technologies. Health and Technology, 1–7.
Neupane, S., Odendaal, W., Friedman, I., Jassat, W., Schneider, H., & Doherty, T. (2014). Comparing a paper based monitoring and evaluation system to a mHealth system to support the national community health worker programme, South Africa: an evaluation. BMC Medical Informatics and Decision Making, 14(1), 69.
Ng, E. H., & Kim, H. W. (2009). Investigating information systems infusion and the moderating role of habit: A user empowerment perspective. Paper presented at the Proceedings of International Conference of Information Systems,
Nilsson, E. G. (2009). Challenges for mobile solutions for emergency response. In Position paper at the workshop for Mobile Information Technology for Emergency Response at the ISCRAM 2009 conference.
Nimkar, S. (2016). Promoting individual health using information technology: trends in the US health system. Health Education Journal. doi:10.1177/0017896916632790.
O' Connor, Y., O' Donoghue, J., & O' Reilly, P. Understanding mobile technology post-adoption behaviour: impact upon knowledge creation and individual performance. In 2011 Tenth International Conference on Mobile Business (ICMB), 20–21 June 2011 2011 (pp. 275–282).
O' Connor, Y., O’Raghailligh, P. J., & O' Donoghue, J. (2012). Individual Infusion of M-Health Technologies: Determinants and Outcomes. In ECIS 2012 Proceedings, Paper 164.
Oakley, R., & Palvia, P. A study of the impact of mobile self-efficacy and emotional attachment on mobile device infusion. In AMCIS 2012, Paper 15, 2012.
Owen, J. E., Jaworski, B. K., Kuhn, E., Makin-Byrd, K. N., Ramsey, K. M., & Hoffman, J. E. (2015). mHealth in the wild: using novel data to examine the reach, use, and impact of PTSD coach. JMIR Mental Health, 2(1), e7.
Patton, M. Q. (2001). Qualitative research & evaluation methods: Sage publications, Incorporated.
Pearce, J. L., & Gregersen, H. B. (1991). Task interdependence and extrarole behavior: A test of the mediating effects of felt responsibility. Journal of Applied Psychology, 76(6), 838–844.
Peijian, S., & Lihua, H. Innovative use of information technology: a role identity perspective. In Proceedings of the First China Summer Workshop on Information Management, Shanghai, China., 2007
Peng, G., Dey, D., & Lahiri, A. (2014). Healthcare IT adoption: an analysis of knowledge transfer in socioeconomic networks. Journal of Management Information Systems, 31(3), 7–34.
Prgomet, M., Georgiou, A., & Westbrook, J. I. (2009). The impact of mobile handheld technology on hospital physicians’ work practices and patient care: a systematic review. Journal of the American Medical Informatics Association, 16(6), 792–801.
Rahurkar, S., Vest, J. R., & Menachemi, N. (2015). Despite the spread of health information exchange, there is little evidence of its impact on cost, use, and quality of care. Health Affairs, 34(3), 477–483.
Ramamurthy, K., Sen, A., & Sinha, A. P. (2008). Data warehousing infusion and organizational effectiveness. Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, 38(4), 976–994.
Ranallo, P. A., Kilbourne, A. M., Whatley, A. S., & Pincus, H. A. (2016). Behavioral health information technology: from chaos to clarity. Health Affairs, 35(6), 1106–1113.
Rossi, M., Tuunainen, V. K., & Pesonen, M. (2007). Mobile technology in field customer service: big improvements with small changes. Business Process Management Journal, 13(6), 853–865.
Saeed, K. A., & Abdinnour-Helm, S. (2008). Examining the effects of information system characteristics and perceived usefulness on post adoption usage of information systems. Information and Management, 45(6), 376–386.
Safran, C., & Goldberg, H. (2000). Electronic patient records and the impact of the internet. International Journal of Medical Informatics, 60(2), 77–83.
Saga, V. L., & Zmud, R. W. (1994). The nature and determinants of IT acceptance, routinization and infusion. Diffusion Transfer and Implementation of Information Technology, 45(A-45), 67–86.
Sousa, R. D., & Goodhue, D. L. (2003). Understanding exploratory use of ERP systems. In AMCIS 2003 Proceedings. (Vol. Paper 62).
Strauss, A. L., & Corbin, J. (1990). The basics of qualitative analysis: Grounded theory procedures and techniques. Newbury Park: Sage Publications Inc., California.
Sundaram, S., Schwarz, A., Jones, E., & Chin, W. (2007). Technology use on the front line: how information technology enhances individual performance. Journal of the Academy of Marketing Science, 35(1), 101–112. doi:10.1007/s11747-006-0010-4.
Sundin, P., Callan, J., & Mehta, K. (2016). Why do entrepreneurial mHealth ventures in the developing world fail to scale? Journal of Medical Engineering & Technology, 1–14.
Tanoglu, I., & Basoglu, N. (2006). Information technology (IT) diffusion: An analysis of user behavior in the exploitation of IT. In Technology Management for the Global Future, 2006. PICMET 2006, 8–13 July 2006 (Vol. 4, pp. 1735–1741). doi:10.1109/picmet.2006.296747.
Taylor, S., & Todd, P. A. (1995). Understanding information technology usage: a test of competing models. Information Systems Research, 6(2), 144–176.
Tenenhaus, M., Vinzi, V. E., Chatelin, Y. M., & Lauro, C. (2005). PLS path modeling. Computational Statistics and Data Analysis, 48(1), 159–205.
Tennant, V., Mills, A., & Chin, W. (2011). Investigating information system infusion at the individual level: re-conceptualisation and operationalization paper presented at the PACIS 2011 Proceedings. Paper 189.
Thatcher, J. B., McKnight, D. H., Baker, E. W., Arsal, R. E., & Roberts, N. H. (2011). The role of Trust in Postadoption IT exploration: an empirical examination of knowledge management systems. Engineering Management, IEEE Transactions on, 58(1), 56–70.
Torkzadeh, G., Chang, J. C. J., & Hardin, A. M. (2011). Usage and impact of technology enabled job learning. European Journal of Information Systems, 20(1), 69–86.
Torkzadeh, G., & Doll, W. J. (1999). The development of a tool for measuring the perceived impact of information technology on work. Omega, 27(3), 327–339.
Trice, A. W., & Treacy, M. E. (1988). Utilization as a dependent variable in MIS research. SIGMIS Database, 19(3–4), 33–41. doi:10.1145/65766.65771.
Tu, H. (2015). Failed cases of mobile healthcare apps: why Kanchufang has failed. mHealth, 1(1).
Turner, T., Spruijt-Metz, D., Wen, C., & Hingle, M. (2015). Prevention and treatment of pediatric obesity using mobile and wireless technologies: a systematic review. Pediatric Obesity, 10(6), 403–409.
Urquhart, C. (2001). An encounter with grounded theory: tackling the practical and philosophical issues. Qualitative research in IS: Issues and trends, 104–140.
Venkatesh, V., Brown, S. A., Maruping, L. M., & Bala, H. (2008). Predicting different conceptualizations of system use: the competing roles of behavioral intention, facilitating conditions, and behavioral expectation. MIS Quarterly, 32(3), 483–502.
Weingart, S. N., Massagli, M., Cyrulik, A., Isaac, T., Morway, L., Sands, D. Z., et al. (2009). Assessing the value of electronic prescribing in ambulatory care: a focus group study. International Journal of Medical Informatics, 78(9), 571–578.
White, A., Allen, P., Goodwin, L., Breckinridge, D., Dowell, J., & Garvy, R. (2005). Infusing PDA technology into nursing education. Nurse Educator, 30(4), 150–154.
Yin, R. K. (1994). Case study research, design and methods. Newbury Park: Sage Publications.
Zhang, N., Guo, X., Wang, F., Chen, G., & Wei, Q. (2011).Task-Technology Fit in Mobile Work: Exploring the Links between Task Attributes and Technology Characteristics. In Mobile Business (ICMB), 2011 Tenth International Conference on, 20–21 June 2011 (pp. 268–274). doi:10.1109/icmb.2011.47.
Zmud, R. W., & Apple, L. E. (1992). Measuring technology incorporation/infusion. Journal of Product Innovation Management, 9(2), 148–155.
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O’ Connor, Y., O’ Reilly, P. Examining the infusion of mobile technology by healthcare practitioners in a hospital setting. Inf Syst Front 20, 1297–1317 (2018). https://doi.org/10.1007/s10796-016-9728-9
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DOI: https://doi.org/10.1007/s10796-016-9728-9