Abstract
Health organizations have the opportunity to incorporate purposeful data analytics to improve decision making related to healthcare. Yet, adoption of analytics techniques in healthcare lags behind other industries. Patient activation refers to patients playing an active role in managing their own health and health care, and their perceived confidence in their ability to manage their own health. Yet, little search exists to guide the design of big data analytics that identify, monitor and improve the healthcare organization’s efforts in patient activation. The overall goal of the research is to fill this important gap. The focus is to collect and analyze data and develop our case-research based framework and its application in the development of Health Analytics Design Artifact for Improved Patient Activation.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Buntin, M.B., Burke, M.F., Hoaglin, M.C., Blumenthal, D.: The Benefits of Health Information Technology: A Review of the Recent Literature Shows Predominantly Positive Results. Health Affairs 30(3), 464–471 (2011)
Payton, F.C., Pare, G., Le Rouge, C.M., Reddy, M.: Health Care It: Process, People, Patients and Interdisciplinary Considerations. Journal of the Association for Information Systems 12(2), 3 (2011)
Nguyen, L., Bellucci, E., Nguyen, L.T.: Electronic Health Records Implementation: An Evaluation of Information System Impact and Contingency Factors. International Journal of Medical Informatics 83(11), 779–796 (2014)
Lluch, M.: Healthcare Professionals’ Organisational Barriers to Health Information Technologies—a Literature Review. International Journal of Medical Informatics 80(12), 849–862 (2011)
Jha, A.K., DesRoches, C.M., Campbell, E.G., Donelan, K., Rao, S.R., Ferris, T.G., Shields, A., Rosenbaum, S., Blumenthal, D.: Use of Electronic Health Records in Us Hospitals. New England Journal of Medicine 360(16), 1628–1638 (2009)
Roski, J., Bo-Linn, G.W., Andrews, T.A.: Creating Value in Health Care through Big Data: Opportunities and Policy Implications. Health Affairs 33(7), 1115–1122 (2014)
Kambatla, K., Kollias, G., Kumar, V., Grama, A.: Trends in Big Data Analytics. Journal of Parallel and Distributed Computing 74(7), 2561–2573 (2014)
Post, A.R., Kurc, T., Cholleti, S., Gao, J., Lin, X., Bornstein, W., Cantrell, D., Levine, D., Hohmann, S., Saltz, J.H.: The Analytic Information Warehouse (Aiw): A Platform for Analytics Using Electronic Health Record Data. Journal of Biomedical Informatics 46(3), 410–424 (2013)
Ward, M.J., Marsolo, K.A., Froehle, C.M.: Applications of Business Analytics in Healthcare. Business Horizons 57(5), 571–582 (2014)
Miller, K.: Big Data Analytics in Biomedical Research. Biomedical Computation Review, 14–21 (2012)
Straub, D.W.: Validating Instruments in Mis Research. MIS Quarterly, 147–169 (1989)
Hevner, A.R.: A Three Cycle View of Design Science Research. Scandinavian Journal of Information Systems 19(2), 4 (2007)
Hevner, A.R., March, S.T., Jinsoo, P., Sudha, R.: Design Science in Information Systems Research. MIS Quarterly 28(1), 75–105 (2004)
Hibbard, J.H., Mahoney, E.R., Stockard, J., Tusler, M.: Development and testing of a short form of the patient activation measure. Health Serv. Res. 40, 1918–1930 (2005)
Hibbard, J.H., Mahoney, E., Stock, R., Tusler, M.: Do increases in patient activation result in improved self-management behaviors? Health Services Research 42, 1443–1463 (2007)
Groves, P., Kayyali, B., Knott, D., Van Kuiken, S.: The ‘Big Data’ revolution in Healthcare. McKinsey Quarterly (2013)
Chen, H., Chiang, R.H.L., Storey, V.C.: Business Intelligence and Analytics: From Big Data to Big Impact. MIS Quarterly 36(4), 1165–1188 (2012)
Delen, D., Oztekin, A., Tomak, L.: An Analytic Approach to Better Understanding and Management of Coronary Surgeries. Decision Support Systems 52(3), 698–705 (2012)
Davenport, T.H.: Enterprise Analytics: Optimize Performance, Process, and Decisions through Big Data. Pearson Education (2013)
Yin, R.K.: Case Study Research: Design and Methods (S. Conneley, ed.), 4th edn. SAGE Publications, Thousand Oaks (2009)
Baskerville, R., Pries-Heje, J., Venable, J.: Soft Design Research: Extending the Boundaries of Evaluation in Design Research. In: Proceedings of the 2nd DESRIST Conference, Pasadena, CA, May 13-15, pp. 19–38 (2007)
March, S., Hevner, A., Ram, S.: Research Commentary An Agenda for Information Technology Research in Heterogeneous and Distributed Environments. Information Systems Research 11(4), 327–341 (2000)
March, S.T., Smith, G.: Design and Natural Science Research on Information Technology. Decision Support Systems 15(4), 251–266 (1995)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Kakhki, M.D., Singh, R., Loyd, K.W. (2015). Developing Health Analytics Design Artifact for Improved Patient Activation: An On-going Case Study. In: Rocha, A., Correia, A., Costanzo, S., Reis, L. (eds) New Contributions in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 353. Springer, Cham. https://doi.org/10.1007/978-3-319-16486-1_72
Download citation
DOI: https://doi.org/10.1007/978-3-319-16486-1_72
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-16485-4
Online ISBN: 978-3-319-16486-1
eBook Packages: Computer ScienceComputer Science (R0)