Abstract
Socio-technical values, principles, and theories are foundational knowledge for health information professionals. These emphasise that people who work with technology are augmented by it, not subordinate to it. Applying them can contribute to more effective design, development, implementation, management, and use of digital health and information systems. This chapter briefly describes the origins and underlying values of the socio-technical approach. It then discusses theories and key concepts. The second section demonstrates the relevance of socio-technical design to the health services in general and health information professionals, in particular. Examples from research and case studies are used to demonstrate how this workforce can apply socio-technical values and principles.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Adaba GB, Kebebew Y. Improving a health information system for real-time data entries: an action research project using socio-technical systems theory. Inform Health Social Care. 2018;43(2):159–71.
Agarwal R, Prasad J. The role of innovation characteristics and perceived voluntariness in the acceptance of information technologies. Decis Sci. 1997;28(3):557–82.
Ahmad MI. Unified theory of acceptance and use of technology (UTAUT): a decade of validation and development. Proceedings of the 4th International Conference on ICT in our Lives (ISSN 2314–8942). Egypt: Alexandria University; 2014.
Australian Digital Health Agency. Australia’s National Digital Health strategy: safe, seamless and secure: evolving health and care to meet the needs of modern Australia. Australian Government and Australian Digital Health Agency: Sydney; 2018.
Ayaz A, Yanartaş M. An analysis on the unified theory of acceptance and use of technology theory (UTAUT): acceptance of electronic document management system (EDMS). Comput Human Behav Rep. 2020;2:100032.
Azzopardi-Muscat N, Sørensen K. Towards an equitable digital public health era: promoting equity through a health literacy perspective. Eur J Public Health. 2019;29(Suppl 3):13–7.
Baker KM, Magee MF, Smith KM. Understanding nursing workflow for inpatient education delivery: time and motion study. JMIR Nurs. 2019;2(1):e15658.
Baxter G, Sommerville I. Socio-technical systems: from design methods to systems engineering. Interact Comput. 2011;23(1):4–17.
Borycki E, Kushniruk A. Towards an integrative cognitive-socio-technical approach in health informatics: analyzing technology-induced error involving health information systems to improve patient safety. Open Med Inform J. 2010;4:181.
Callon M. The sociology of an actor-network: the case of the electric vehicle. In: Callon M, Law J, Rip A, editors. Mapping the dynamics of science and technology. London: Springer; 1986. p. 19–34.
Cresswell KM, Worth A, Sheikh A. Actor-network theory and its role in understanding the implementation of information technology developments in healthcare. BMC Medical Inform Decis Making. 2010;10(1):1–11.
Cusumano MA, Selby RW. How Microsoft builds software. Commun ACM. 1997;40(6):53–61.
Deluca JM, Enmark R. E-health: the changing model of healthcare. Front Health Serv Manag. 2000;17(1):3.
Driscoll CAH, Gurmu S, Azeem A, El Metwally D. Implementation of smart phones to facilitate in-hospital telephone communication: challenges, successes and lessons from a neonatal intensive care unit. Healthcare; 2019:100331.
Huckvale K, Wang CJ, Majeed A, Car J. Digital health at fifteen: more human (more needed). BMC Med. 2019;17(1):1–4.
Hughes HP, Clegg CW, Bolton LE, Machon LC. Systems scenarios: a tool for facilitating the socio-technical design of work systems. Ergonomics. 2017;60(10):1319–35.
Jensen S. Use of clinical simulation in development of clinical systems. Department of Planning and Development. Denmark: Aalborg University; 2014.
Jensen S. Patient safety and quality of care: how may clinical simulation contribute? Knowl Manag E-Learn. 2015;7(3):412–24.
Jensen S, Kushniruk A. Boundary objects in clinical simulation and design of eHealth. Health Inform J. 2016;22(2):248–64.
Katz D, Kahn RL. The social psychology of organizations. New York: Auflage Wiley; 1966.
Kennedy S, Yaldren J. A look at digital literacy in health and social care. Br J Cardiac Nurs. 2017;12(9):428–32.
Kim S, Lee K-H, Hwang H, Yoo S. 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 Medical Inform Decis Making. 2015;16(1):1–12.
Land F, Mumford E, Hawgood J. Training the systems analyst for the 1980s: four new design tools to assist the design process. The Information Systems Environment. North Holland; 1979.
Lee Y, Kozar KA, Larsen KR. The technology acceptance model: past, present, and future. Commun Assoc Inf Syst. 2003;12(1):752–80.
Leitch S, Warren MJ. ETHICS: the past, present and future of socio-technical systems design. IFIP International Conference on the History of Computing. 2010:189–97.
Leonardi PM. Theoretical foundations for the study of sociomateriality. Inf Organ. 2013;23(2):59–76.
MacLeod A, Cameron P, Ajjawi R, Kits O, Tummons J. Actor-network theory and ethnography: sociomaterial approaches to researching medical education. Perspect Medical Educ. 2019;8(3):177–86.
Mather C. Case Study: An interdisciplinary evaluation of an e-portfolio: WIL at the University of Tasmania Workready: E-portfolios to support professional placements in Nursing and Construction Management degrees in Australia. Print National: NSW; 2012.
Mather C, Cummings E. Modelling digital knowledge transfer: nurse supervisors transforming learning at point of care to advance nursing practice. Informatics; 2017:12.
Mather CA, Cummings E. Developing and sustaining digital professionalism: a model for assessing readiness of healthcare environments and capability of nurses. BMJ Health Care Inform. 2019;26(1):1–5.
Mather C, Jensen S, Cummings E. Clinical simulation: a protocol for evaluation of mobile technology. Stud Health Technol Inform. 2017a;241:179–84.
Mather CA, Gale F, Cummings EA. Governing mobile technology use for continuing professional development in the Australian nursing profession. BMC Nurs. 2017b;16(1):1–11.
Mumford E. The story of socio-technical design: reflections on its successes, failures and potential. Inf Syst J. 2006;16(4):317–42.
Orlikowski WJ, Baroudi JJ. Studying information technology in organizations: research approaches and assumptions. Inf Syst Res. 1991;2(1):1–28.
Orlikowski WJ, Scott SV. Digital work: a research agenda. A research agenda for management and organization studies. Edward Elgar; 2016.
Sahay S. Implementation of information technology: a time-space perspective. Organ Stud. 1997;18(2):229–60.
Sawyer S, Jarrahi M. Computing handbook: information systems and information technology. Florida: CRC Press; 2014.
Showell C, Cummings E, Turner P. The invisibility of disadvantage: why do we not notice? Stud Health Technol Inform. 2017;235:388–92.
Sittig DF, Singh H. Defining health information technology–related errors: new developments since to err is human. Arch Intern Med. 2011;171(14):1281–4.
Thomassen OJ, Heggen K, Strand R. Applying principles of sociotechnical systems onto working environment research. 2017.
Venkatesh V, Morris MG, Davis GB, Davis FD. User acceptance of information technology: toward a unified view. MIS Q. 2003:425–78.
Venkatesh V, Zhang X, Sykes TA. “Doctors do too little technology”: a longitudinal field study of an electronic healthcare system implementation. Inf Syst Res. 2011;22(3):523–46.
Venkatesh V, Brown SA, Bala H. Bridging the qualitative-quantitative divide: guidelines for conducting mixed methods research in information systems. MIS Q. 2013:21–54.
von Bertalanffy L. An outline of general system theory. Br J Philos Sci. 1950;1:134–65.
Walter SR, Dunsmuir WT, Raban MZ, Westbrook JI. Understanding clinical workflow through direct continuous observation: addressing the unique statistical challenges. Cogn Inform. 2019:191–210.
Westbrook JI, Duffield C, Li L, Creswick NJ. How much time do nurses have for patients? A longitudinal study quantifying hospital nurses’ patterns of task time distribution and interactions with health professionals. BMC Health Serv Res. 2011;11(1):319.
Whetton S. Health informatics: a socio-technical perspective. South Melbourne: Oxford University Press; 2005.
Yurtseven MK, Buchanan WW. Socio-technical system design: a general systems theory perspective. Proceedings of the International Conference on Engineering and Computer Education-ICECE’2013; 2013.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Mather, C.A., Whetton, S. (2021). The Socio-technical Foundations of Health Information Work. In: Butler-Henderson, K., Day, K., Gray, K. (eds) The Health Information Workforce . Health Informatics. Springer, Cham. https://doi.org/10.1007/978-3-030-81850-0_3
Download citation
DOI: https://doi.org/10.1007/978-3-030-81850-0_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-81849-4
Online ISBN: 978-3-030-81850-0
eBook Packages: MedicineMedicine (R0)