The Impact of SOA for Achieving Healthcare Interoperability

Summary

Objectives: The evaluation of a service-oriented prototype implementation for healthcare interoperability.

Methods: A prototype framework was developed, aiming to exploit the use of service-oriented architecture (SOA) concepts for achieving healthcare interoperability and to move towards a virtual patient record (VPR) paradigm. The prototype implementation was evaluated for its hypothetical adoption. The evaluation strategy was based on the initial proposition of the DeLone and McLean model of information systems (IS) success [1], as modeled by Iivari [2]. A set of SOA and VPR characteristics were empirically encapsulated within the dimensions of IS success model, combined with measures from previous research works. The data gathered was analyzed using partial least squares (PLS).

Results: The results highlighted that system quality is a partial predictor of system use but not of user satisfaction. On the contrary, information quality proved to be a significant predictor of user satisfaction and partially a strong significant predictor of system use. Moreover, system use did not prove to be a significant predictor of individual impact whereas the bi-directional relation between use and user satisfaction did not confirm. Additionally, user satisfaction was found to be a strong significant predictor of individual impact. Finally, individual impact proved to be a strong significant predictor of organizational impact.

Conclusions: The empirical study attempted to obtain hypothetical, but still useful beliefs and perceptions regarding the SOA prototype implementation. The deduced observations can form the basis for further investigation regarding the adaptability of SOA implementations with VPR characteristics in the health-care domain.

Keywords

Interoperability - process - assessment-evaluation - IS success model - DeLone and McLean - partial least squares

• References

• 1 DeLone WH, McLean ER. Information systems success: the quest for the dependent variable. Inform Systems Res 1992; 3: 60-95.
• 2 Iivari J. An empirical test of the DeLone-McLean model of information system success. Data Base Adv Inf Sy 2005; 36 (02) 8-27.
• 3 Papazoglou MP. Service-oriented computing: concepts, characteristics and directions. In: Proceedings of the 4th International Conference on Web Information Systems Engineering; Dec 10-12, 2003 Rome, Italy. Washington, DC, USA: IEEE Computer Society; 2003. pp 3-10.
• 4 Papazoglou MP, Georgakopoulos D. Service-oriented computing. Communications of the ACM 2003; 46 (10) 25-28.
• 5 Komoda N. Service oriented architecture (SOA) in industrial systems. In: INDIN’06 Proceedings of the 4th International IEEE Conference on Industrial Informatics, Aug 16-18, 2006, Singapore. Washington, DC: IEEE Computer Society; 2006. pp 1-5.
• 6 Daskalakis S, Mantas J. A SOA framework for healthcare interoperability using BPEL: design and implementation. In: ICICTH’06 Proceedings of the 4th International Conference on Information and Communication Technologies in Healthcare, July 13-15, 2006, Samos, Greece. Athens: University of Athens; 2006. pp 247-254.
• 7 Henkel M, Zdravkovic J, Johannesson P. Service-based processes-design for business and technology. In: ICSOC ’04 Proceedings of the 2nd international conference on service oriented computing, Nov 15-19, 2004, New York. New York: Association for Computing Machinery; 2004. pp 21-29.
• 8 Pasley J. How BPEL and SOA are changing web services development. IEEE Internet computing 2005: 60-67.
• 9 Zou Z, Duan Z. Building business processes or assembling service components: reuse services with BPEL4WS and SCA. In: ECOWS’06 Proceedings of the 4th European Conference on Web Services, Dec 4-6, 2006, Zurich, Switzerland. Washington, DC: IEEE Computer Society; 2006. pp 138-147.
• 10 Malamateniou F, Vassilacopoulos G. Developing a virtual patient record using XML and web-based workflow technologies. Int J Med Inform 2003; 70: 131-139.
• 11 Berler A, Pavlopoulos S, Karkalis G, Sakka E, Konnis G, Koutsouris D. Implementation of a novel virtual patient record architecture. In: Proceedings of the 24th Annual International Conference of the IEEE in Medicine and Biology, 2002, Houston, Texas. Washington, DC: IEEE Computer Society; 2002. pp 1936-1937.
• 12 Raghupathi W, Kesh S. Interoperable electronic health records design: towards a service-oriented architecture. E-serv j 2007; 5 (03) 39-57.
• 13 Forslund DW, George JE, Koenig S, Staab T, Kratz M, Carter R. The importance of distributed, component based healthcare information systems: the role of a service-based architecture. In: CBMS ’01 Proceedings of the 14th IEEE Symposium on Computer-Based Medical Systems, Mar 26-27, 2001, Bethesda, Maryland, USA. Washington, DC: IEEE Computer Society; 2001. pp 79-82.
• 14 Wang W, Wang M, Zhu S. Healthcare information system integration: a service oriented approach. In: ICSSSM ’05 Proceedings of the 2005 International Conference on Services Systems and Services Management, June 13-15, 2005, Chongqing, China. Washington, DC: IEEE Computer Society; 2005. pp 1475-1480.
• 15 Chu S. From component-based to service oriented software architecture for healthcare. JITH 2006; 4 (01) 5-14.
• 16 Lenz R, Beyer M, Kuhn KA. Semantic integration in healthcare networks. Int J Med Inform 2007; 76: 201-207.
• 17 Ammenwerth E, Brender J, Nykänen P, Prokosch H-U, Rigby M, Talmon J. Visions and strategies to improve evaluation of health information systems: reflections and lessons based on the HIS-EVAL workshop in Innsbruck. Int J Med Inform 2004; 73: 479-491.
• 18 Raitoharju R. When acceptance is not enough – taking TAM-model into healthcare. In: HICSS ’05 Proceedings of the 38th Hawaii International Conference on System Sciences, Jan 3-6, 2005, Hawaii. New York: Association for Computing Machinery; 2005. pp 57-60.
• 19 Turunen P. Selecting evaluation methods for healthcare information systems – a stakeholder view. (PhD Dissertation). Turku: Turku School of Economics and Business Administration; 2001
• 20 Moore MB. Acceptance of information technology by health care professionals. In: Proceedings of the symposium on Computers and the quality of life, Feb 14-15, 1996, Philadelpia, Pennsylvania, USA. New York: Association for Computing Machinery; 1996. pp 57-60.
• 21 Yusof MM, Paul RJ, Stergioulas LK. Towards a framework for health information systems evaluation. In: HICSS’06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences, Jan 4-7, 2006, Big Island, Hawaii, USA. Washington, DC: IEEE Computer Society; 2006. p. 95.1.
• 22 Hu J-HH. Evaluating telemedicine systems success: a revised model. In: HICSS’03 Proceedings of the 36th Annual Hawaii International Conference on System Sciences, Jan 6-9, 2003, Big Island, Hawaii, USA. Washington, DC, USA: IEEE Computer Society; 2003. p 174.
• 23 Palm JM, Colombet I, Sicotte C, Degoulet P. Determinants of user satisfaction with a clinical information system. AMIA Annu Symp Proc 2006 pp 614-618.
• 24 Jen WY, Chao CC. Measuring mobile patient safety information system success: an empirical study. Int J Med Inform 2008; 77 (10) 689-697.
• 25 Golob Jr JF, Fadlalla AM, Kan JA, Patel NP, Yowler CJ, Claridge JA. Validation of surgical intensive care-infection registry: a medical informatics system for intensive care unit research, quality of care improvement, and daily patient care. J Am Coll Surg 2008; 207 (02) 164-173.
• 26 Morin D, Tourigny A, Pelletier D, Robichaud L, Mathieu L, Vézina A, Bonin L, Buteau M. Seniors’ views on the use of electronic health records. Inform Prim Care 2005; 13 (02) 125-133.
• 27 Roldán JL, Leal A. A validation test of an adaptation of the DeLone and McLean’s model in the Spanish EIS field. In: Cano JJ. editor. Critical reflections on information systems: a systemic approach. Hershey, PA, USA: IGI Publishing; 2003. pp 66-84.
• 28 Molla A, Licker PS. E-commerce systems success: an attempt to extend and respecify the DeLone and McLean model of IS success. JECR 2001; 2: 131-141.
• 29 Broy M, Deissenboeck F, Pizka M. Demystifying maintainability. In: Proceedings of the 2006 International workshop on Software Quality; 2006 May 2; Shangai, China. New York: Association for Computing Machinery; 2006. pp 21-26.
• 30 Gefen D, Straub DW, Boudreau M. Structural equation modeling techniques and regression: guidelines for research practice. Communications of AIS 2000; 7 (07) 1-78.
• 31 Chea S, Luo MM. Cognition, emotion, satisfaction and post-adoption behaviors of e-service customers. In: HICSS ’07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences, Jan 4-6, 2007, Big Island, Hawaii, USA. Washington, DC, USA: IEEE Computer Society; 2007. p 54b.
• 32 Shepherd MM, Tesch DB, Hsu JSC. Environmental traits that support a learning organization: the impact on information system development projects. Comparative Technology Transfer and Society 2006; 4 (02) 196-218.
• 33 Yigitbasioglu O. Information sharing with key suppliers: a contingency approach. In: Proceedings of the 10th European Conference on Accounting Information Systems, Apr 24, 2007, Lisbon, Portugal.:
• 34 Ringle CM, Wende S, Will A. SmartPLS 2.0 (M3), Hamburg 2005 [Online]. Available from: URL: http://www.smartpls.de.
• 35 Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. J Marketing Res 1981; 18: 39-50.
• 36 Bagozzi RP, Yi Y, Phillips L. W. Assessing construct validity in organizational research. Administrative Science Quarterly 1991; 36 (03) 421-458.
• 37 Daskalakis S. Application integration and inter-operability of healthcare information systems (PhD Dissertation). Athens: National and Kapodistrian University of Athens; 2007