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International Conference on Design Science Research in Information System and Technology

DESRIST 2016: Tackling Society's Grand Challenges with Design Science pp 158–174Cite as

Prototype Design of a Healthcare-Analytics Pre-adoption Readiness Assessment (HAPRA) Instrument

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Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9661))

Abstract

Healthcare organizations (HCO) adopt emerging technology solutions such as Healthcare Analytics (HA) to improve the quality and efficiency of their operations, patient care, and clinical decisions. While their intent is to adopt HA, many of them are unsure of their organizational readiness for that adoption. There is a paucity of research on HA pre-adoption readiness assessment techniques and tools, which can be leveraged by hospitals, to make well-informed decisions. In this paper, we fill this gap, by proposing a prototype design of an instrument based on the design science approach. We base the constructs used in our artifact on our findings from the multi-case study analysis of three hospitals, which we also discuss briefly. The key contribution of this research is the process that we followed in integrating the case study approach with DSRM in the area of HA adoption.

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References

  1. National Health Expenditure Projections 2014–2024. https://www.cms.gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/NationalHealthExpendData/NationalHealthAccountsProjected.html

  2. Prewitt, E.: Effective data analytics for a data-rich industry. The Promise of Healthcare Analytics (2012)

    Google Scholar 

  3. Raghupathi, W., Tan, J.: Information systems and healthcare XXX: charting a strategic path for health information technology. Commun. Assoc. Inf. Syst. 23, 501–522 (2008)

    Google Scholar 

  4. Cortada, J.W., Gordon, D., Lenihan, B.: The Value of Analytics in Healthcare. IBM Institute for Business Value, New York (2010)

    Google Scholar 

  5. Davenport, T.H., Harris, J.G.: Competing on Analytics: The New Science of Winning. Harvard Business School Press, Boston (2007)

    Google Scholar 

  6. Andreu-Perez, J., Poon, C.C.Y., Merrifield, R.D., Wong, S.T.C., Yang, G.Z.: Big data for health. IEEE J. Biomed. Heal. Inform. 19, 1193–1208 (2015)

    Article  Google Scholar 

  7. Ward, M.J., Marsolo, K.A., Froehle, C.M.: Applications of business analytics in healthcare. Bus. Horiz. 57, 571–582 (2014)

    Article  Google Scholar 

  8. Frost and Sullivan: Drowning in Big Data? Reducing Information Technology Complexities and Costs for Healthcare Organizations (2011)

    Google Scholar 

  9. Adler-Milstein, J., Jha, A.K.: Health information exchange among U.S. hospitals: who’s in, who’s out, and why? Healthcare 2, 26–32 (2014)

    Article  Google Scholar 

  10. Buntin, M.B., Jain, S.H., Blumenthal, D.: Health information technology: laying the infrastructure for national health reform (2010)

    Google Scholar 

  11. Sherer, S.A.: Advocating for action design research on IT value creation in healthcare. J. Assoc. Inf. Syst. 15, 860–878 (2014)

    Google Scholar 

  12. Angst, C.M., Agarwal, R.: Adoption of electronic health records in the presence of privacy concerns: the elaboration likelihood model and individual persuasion. MIS Q. 33, 339–370 (2009)

    Google Scholar 

  13. Bonney, W.: Applicability of business intelligence in electronic health record. Procedia - Soc. Behav. Sci. 73, 257–262 (2013)

    Article  Google Scholar 

  14. Venkatesh, V., Davis, F.D.: A theoretical extension of the technology acceptance model: four longitudinal field studies. Manag. Sci. 46, 186–204 (2000)

    Article  Google Scholar 

  15. Venkatesh, V., Morris, M.G., Davis, G.B., Davis, F.D.: User acceptance of information technology: toward a unified view. MIS Q. 27, 425–478 (2003)

    Google Scholar 

  16. Tornatzky, L.G., Fleischer, M., Chakrabarti, A.K.: The Processes of Technological Innovation. Lexington Books, Lexington (1990)

    Google Scholar 

  17. DeLone, W.H., McLean, E.R.: The DeLone and McLean model of information systems success: a ten-year update. J. Manag. Inf. Syst. 19, 9–30 (2003)

    Google Scholar 

  18. Bhattacherjee, A., Hikmet, N.: Reconceptualizing organizational support and its effect on information technology usage: evidence from the health care sector. J. Comput. Inf. Syst. 48, 69–76 (2008)

    Google Scholar 

  19. Lancry, P.J., Oconnor, R., Stempel, D., Raz, M.: Using health outcomes data to inform decision-making: healthcare payer perspective. Pharmacoeconomics 19(Suppl 2), 39–47 (2001)

    Article  Google Scholar 

  20. Van Der Meijden, M.J., Tange, H.J., Troost, J., Hasman, A.: Determinants of success of inpatient clinical information systems: a literature review. J. Am. Med. Inform. Assoc. 10, 235–243 (2003)

    Article  Google Scholar 

  21. Yu, P.: A multi-method approach to evaluate health information systems. Stud. Health Technol. Inf. 160, 1231–1235 (2010)

    Google Scholar 

  22. Malladi, S., Arbor, A.: Adoption of business intelligence and analytics in organizations – an empirical study of antecedents. pp. 1–11 (2013)

    Google Scholar 

  23. Venkatraman, S., Sundarraj, R.P., Seethamraju, R.: Healthcare analytics adoption-decision model: a case study. In: Proceedings of PACIS 2015 (2015)

    Google Scholar 

  24. Brooks, P., El-Gayar, O., Sarnikar, S.: A framework for developing a domain specific business intelligence maturity model: application to healthcare. Int. J. Inf. Manag. 35, 337–345 (2015)

    Article  Google Scholar 

  25. Yusof, M.M., Kuljis, J., Papazafeiropoulou, A., Stergioulas, L.K.: An evaluation framework for health information systems: human, organization and technology-fit factors (HOT-fit). Int. J. Med. Inform. 77, 386–398 (2008)

    Article  Google Scholar 

  26. Yusof, M.M., Papazafeiropoulou, A., Paul, R.J., Stergioulas, L.K.: Investigating evaluation frameworks for health information systems. Int. J. Med. Inform. 77, 377–385 (2008)

    Article  Google Scholar 

  27. Sanders, D., Burton, D., Protti, D.: The healthcare analytics adoption model: a framework and roadmap (2013). https://www.healthcatalyst.com/white-paper/healthcare-analytics-adoption-model

  28. Ghosh, B., Scott, J.E.: Antecedents and catalysts for developing a healthcare analytic capability. Commun. Assoc. Inf. Syst. 29, 1 (2011)

    Google Scholar 

  29. Peffers, K., Tuunanen, T., Rothenberger, M.A., Chatterjee, S.: A design science research methodology for information systems research. J. Manag. Inf. Syst. 24, 45–77 (2008)

    Article  Google Scholar 

  30. Hevner, A.R., March, S.T., Park, J., Ram, S.: Design science in information systems research. MIS Q. 28, 75–105 (2004)

    Google Scholar 

  31. Markus, M.L., Majchrzak, A., Les, G.: A design theory for systems that support emergent knowledge processes. MIS Q. 26, 179–212 (2002)

    Google Scholar 

  32. Zhang, N.J., Seblega, B., Wan, T., Unruh, L., Agiro, A., Miao, L.: Health information technology adoption in U.S. acute care hospitals. J. Med. Syst. 37, 1–9 (2013)

    Google Scholar 

  33. Yin, R.K.: Case Study Research. 4th edn. (2009)

    Google Scholar 

  34. Eisenhardt, K.M., Graebner, M.E.: Theory building from cases: opportunities and challenges. Acad. Manag. J. 50, 25–32 (2007)

    Article  Google Scholar 

  35. Creswell, J.W.: Qualitative Inquiry and Research Design - Choosing Among Five Approaches (2007)

    Google Scholar 

  36. Shneiderman, B., Plaisant, C., Hesse, B.W.: Improving healthcare with interactive visualization. Comput. IEEE Comput. Soc. 46, 58–66 (2013)

    Article  Google Scholar 

  37. Jourdan, Z., Rainer, R.K., Marshall, T.E.: Business intelligence: an analysis of the literature. Inf. Syst. Manag. 25, 121–131 (2008)

    Article  Google Scholar 

  38. Chasalow, L.C.: A model of organizational competencies for business intelligence success. ProQuest dissertations and thesis, pp. 191–276 (2009)

    Google Scholar 

  39. Shanks, G., Sharma, R., Seddon, P., Reynolds, P.: The impact of strategy and maturity on business analytics and firm performance : a review and research agenda. In: Proceedings of ACIS 2010, p. 51 (2010)

    Google Scholar 

  40. Lau, F.: Toward a conceptual knowledge management framework in health. Perspect. Health Inf. Manag. 1, 8 (2004)

    Google Scholar 

  41. Poston, R.S., Reynolds, R.B., Gillenson, M.L.: Technology solutions for improving accuracy and availability of healthcare records. Inf. Syst. Manag. 24, 59–71 (2006)

    Article  Google Scholar 

  42. Bell, G.B., Sethi, A.: Matching records in a national medical patient index. Commun. ACM 44, 83–88 (2001)

    Article  Google Scholar 

  43. McCoy, A.B., Wright, A., Kahn, M.G., Shapiro, J.S., Bernstam, E.V., Sittig, D.F.: Matching identifiers in electronic health records: implications for duplicate records and patient safety. BMJ Qual. Saf. 22, 219–224 (2013)

    Article  Google Scholar 

  44. Pipino, L.L., Lee, Y.W., Wang, R.Y.: Data quality assessment. Commun. ACM 45, 211 (2002)

    Article  Google Scholar 

  45. Batini, C., Cappiello, C., Francalanci, C., Maurino, A.: Methodologies for data quality assessment and improvement. ACM Comput. Surv. 41, 1–52 (2009)

    Article  Google Scholar 

  46. Jarvenpaa, S.L., Ives, B.: Executive involvement and participation in the management of information technology. MIS Q. 15, 205–227 (1991)

    Article  Google Scholar 

  47. Kearns, G.S., Lederer, A.L.: The effect of strategic alignment on the use of IS-based resources for competitive advantage. J. Strateg. Inf. Syst. 9, 265–293 (2000)

    Article  Google Scholar 

  48. Henderson, J.C., Venkatraman, H.: Strategic alignment: leveraging information systems and transforming organizations. IBM Syst. J. 32, 472–484 (1999)

    Article  Google Scholar 

  49. Bush, M., Lederer, A.L., Li, X., Palmisano, J., Rao, S.: The alignment of information systems with organizational objectives and strategies in health care. Int. J. Med. Inform. 78, 446–456 (2009)

    Article  Google Scholar 

  50. Zubrow, D., Hayes, W., Siegel, J., Goldesson, S.: Maturity Questionnaire - CMM - SEI (1994)

    Google Scholar 

  51. Saaty, T.L.: The Analytic Hierarchy Process. McGraw-Hill Inc., New York (1980)

    MATH  Google Scholar 

  52. Ramanathan, R.: Data envelopment analysis for weight derivation and aggregation in the analytic hierarchy process. Comput. Oper. Res. 33, 1289–1307 (2006)

    Article  MATH  Google Scholar 

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Author information

Authors and Affiliations

  1. Department of Management Studies, IIT Madras, Sardar Patel Road, Chennai, 600036, Tamil Nadu, India

    Sathyanarayanan Venkatraman, R. P. Sundarraj & Anik Mukherjee

Authors
  1. Sathyanarayanan Venkatraman
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  2. R. P. Sundarraj
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  3. Anik Mukherjee
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Corresponding author

Correspondence to Sathyanarayanan Venkatraman .

Editor information

Editors and Affiliations

  1. Memorial University of Newfoundland, St. Johns, Canada

    Jeffrey Parsons

  2. University of Jyväskylöä, Jyväskylä yliopisto, Finland

    Tuure Tuunanen

  3. Curtain University, Bentley, Australia

    John Venable

  4. Innovation Value Institute, Maynooth University, Maynooth, Co., Kildare, Ireland

    Brian Donnellan

  5. School of Computing, Dublin City University, Dublin 9, Ireland

    Markus Helfert

  6. Intel Labs Europe, Leixlip, Ireland

    Jim Kenneally

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© 2016 Springer International Publishing Switzerland

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Venkatraman, S., Sundarraj, R.P., Mukherjee, A. (2016). Prototype Design of a Healthcare-Analytics Pre-adoption Readiness Assessment (HAPRA) Instrument. In: Parsons, J., Tuunanen, T., Venable, J., Donnellan, B., Helfert, M., Kenneally, J. (eds) Tackling Society's Grand Challenges with Design Science. DESRIST 2016. Lecture Notes in Computer Science(), vol 9661. Springer, Cham. https://doi.org/10.1007/978-3-319-39294-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-39294-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-39293-6

  • Online ISBN: 978-3-319-39294-3

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