Volume 21, Issue 74 (1-2019)
jha 2019, 21(74): 19-34 |
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Aalikhani R, Rasouli M R, Aliahmadi A R. The impact of key factors on an appropriate network governance model in health care systems: a structural equation modeling approach. jha 2019; 21 (74) :19-34
URL: http://jha.iums.ac.ir/article-1-2775-en.html
URL: http://jha.iums.ac.ir/article-1-2775-en.html
1- faculty of industrial engineering, Iran University of Science and Technology, Tehran, Iran
2- faculty of industrial engineering, Iran University of Science and Technology, Tehran, Iran; Corresponding Author (rasouli@iust.ac.ir) , rasouli@iust.ac.ir
2- faculty of industrial engineering, Iran University of Science and Technology, Tehran, Iran; Corresponding Author (rasouli@iust.ac.ir) , rasouli@iust.ac.ir
Abstract: (5504 Views)
Introduction: Due to the complexity of health services, which require the engagement of different parties for the provision of integrated services, inappropriate network governance models can lead to financial conflicts, lack of transparency of accountabilities for medical errors, and difficulties on multi-professional team working. Therefore, this study aimed to examine factors influencing the design of an appropriate network governance model in the healthcare system.
Methods: In this quantitative-correlational study, first factors influencing the domains of network governance were extracted from the literature. In the next step, a structural model was developed based on the hypotheses. To test the research hypotheses, structural equation modeling - partial least- squares method and Smart Pls2 software were used. The data were collected using a standard questionnaire which was distributed to two collaborative networks of diagnostic laboratories and one medical equipment supply network with 194 members. A total of 98 questionnires were collected.
Results: Opportunistic behavioral, trust, commitment, information sharing, knowledge sharing were used as key factors influencing governance model within the structural model of this research. The results showed that commitment and information sharing had the most direct impact on the network governance. Moreover, opportunistic behavior had a negative and severe effect on trust in the network, which in turn affected the governance of the network.
Conclusion: In order to design an appropriate network governance model in healthcare system, special attention should be paid to trust and commitment. These variables can also affect the governance of the network through improving information sharing. Furthermore, the governance model should be designed in such a way as to prevent the opportunistic behavior of the members.
Methods: In this quantitative-correlational study, first factors influencing the domains of network governance were extracted from the literature. In the next step, a structural model was developed based on the hypotheses. To test the research hypotheses, structural equation modeling - partial least- squares method and Smart Pls2 software were used. The data were collected using a standard questionnaire which was distributed to two collaborative networks of diagnostic laboratories and one medical equipment supply network with 194 members. A total of 98 questionnires were collected.
Results: Opportunistic behavioral, trust, commitment, information sharing, knowledge sharing were used as key factors influencing governance model within the structural model of this research. The results showed that commitment and information sharing had the most direct impact on the network governance. Moreover, opportunistic behavior had a negative and severe effect on trust in the network, which in turn affected the governance of the network.
Conclusion: In order to design an appropriate network governance model in healthcare system, special attention should be paid to trust and commitment. These variables can also affect the governance of the network through improving information sharing. Furthermore, the governance model should be designed in such a way as to prevent the opportunistic behavior of the members.
Keywords: Network Governance Model, Health Care Systems, Structural Equation Modeling, Medical diagnostic laboratory, Medical Equipment Supply Network
Type of Study: Research |
Received: 2018/07/26 | Accepted: 2019/01/23 | Published: 2019/01/23
Received: 2018/07/26 | Accepted: 2019/01/23 | Published: 2019/01/23
References
1. Pimentel D, Cooperstein S, Randell H, Filiberto D, Sorrentino S, Kaye B. Ecology of increasing diseases: Population growth and environmental degradation. Human Ecology. 2007;35(6):653–668. [DOI:10.1007/s10745-007-9128-3]
2. Basole RC, Rouse WB. Complexity of service value networks: Conceptualization and empirical investigation. IBM Systems Journal. 2008;47(1):53–70. [DOI:10.1147/sj.471.0053]
3. Karanikolos M, Mladovsky P, Cylus J, Thomson S, Basu S, Stuckler D, et al. Financial crisis, austerity, and health in Europe. The Lancet. 2013;381(5):1323–1331. [DOI:10.1016/S0140-6736(13)60102-6]
4. Brunson JC, Laubenbacher RC. Applications of network analysis to routinely collected health care data: A systematic review. Journal of the American Medical Informatics Association. 2018;25(2):210–21. [DOI:10.1093/jamia/ocx052]
5. Zwarenstein M, Goldman J, Reeves S. Interprofessional collaboration : effects of practice-based interventions on professional practice and healthcare outcomes (Review). Cochrane Database of Systematic Reviews. 2009;3(3):2–4.
6. Mays GP, Scutchfield FD. Improving public health system performance through multiorganizational partnerships. Preventing Chronic Disease. 2010;7(6):1-8.
7. Leurs M, Mur-Veeman IM, van der Sar R, Schaalma HP, De Vries NK. Diagnosis of sustainable collaboration in health promotion - A case study. BMC Public Health. 2008;328(8):145-160. [DOI:10.1186/1471-2458-8-382]
8. Arya B, Lin Z (John). Understanding collaboration outcomes from an extended resource-based view perspective: The roles of organizational characteristics, partner attributes, and network structures. Journal of Management. 2007;33(5):697–723. [DOI:10.1177/0149206307305561]
9. Van Eyk H, Baum F. Learning About Interagency Collaboration: Trialing Collaborative Projects Between Hospitals and Community Health Services. Health and Social Care in the Community. 2002;10(4): 262-269. [DOI:10.1046/j.1365-2524.2002.00369.x]
10. Provan KG, Beagles JE, Leischow SJ. Network formation, governance, and evolution in public health: The North American Quitline Consortium case. Health Care Management Review. 2011;36(4): 315–326. [DOI:10.1097/HMR.0b013e31820e1124]
11. Shortell SM. Increasing value: A research agenda for addressing the managerial and organizational challenges facing health care delivery in the United States. Medical Care Research and Review. 2004;61(3):12–30. [DOI:10.1177/1077558704266768]
12. Wiktorowicz ME, Fleury MJ, Adair CE, Lesage A, Goldner E, Peters S. Mental health network governance: comparative analysis across Canadian regions. International Journal of Integrated Care. 2010;14(10):1-17. [DOI:10.5334/ijic.525]
13. Provan KG, Kenis P. Modes of network governance: Structure, management, and effectiveness. Journal of Public Administration Research and Theory. 2007;18(2):229–252. [DOI:10.1093/jopart/mum015]
14. Provan KG, Fish A, Sydow J. Interorganizational Networks at the Network Level: A Review of the Empirical Literature on Whole Networks. Journal of Management. 2007;33(3):479–516. [DOI:10.1177/0149206307302554]
15. Willem A, Gemmel P. Do governance choices matter in health care networks?: an exploratory configuration study of health care networks. BMC Health Services Research. 2013;13(1):229-329. [DOI:10.1186/1472-6963-13-229]
16. Patru D, Lauche K, Van Kranenburg H, Ziggers GW. Multilateral Boundary Spanners. Medical Care Research and Review. 2015;72(6):665–686. [DOI:10.1177/1077558715590233]
17. Moynihan DP. The network governance of crisis response: Case studies of incident command systems. Journal of Public Administration Research and Theory. 2009;19(4):895–915. [DOI:10.1093/jopart/mun033]
18. Junior NB, Shimizu HE. Theoretical reflections on governance in health regions. Cien Saude Colet. 2017;22(4):1085–95.
19. Poochaoren O, Ting B. Collaboration , Coproduction , Networks – Convergence of Theories. Lee Kuan Yew School of Public Policy Research Paper. 2014; 14-13(65):587–614.
20. Brito RP, Miguel PLS, Abdullah E, Idris A, Saparon A. Power, Governance, and Value in Collaboration: Differences between Buyer and Supplier Perspectives. Journal of Supply Chain Management. 2017;53(2):61–87. [DOI:10.1111/jscm.12134]
21. Xia J, Rutherford S, Ma Y, Wu L, Gao S, Chen T, et al. Obstacles to the coordination of delivering integrated prenatal HIV, syphilis and hepatitis B testing services in Guangdong: using a needs assessment approach. BMC Health Services Research. 2015;15(1):117-126. [DOI:10.1186/s12913-015-0760-0]
22. Vargas I, Susana Mogollon-Perez A, De Paepe P, da Silva MR, Unger J-P, Vazquez M-L. Barriers to healthcare coordination in market-based and decentralized public health systems: a qualitative study in healthcare networks of Colombia and Brazil. Health Policy Planing. 2016;31(6):736–748. [DOI:10.1093/heapol/czv126]
23. Altalib HH, Fenton BT, Cheung K-H, Pugh MJ V, Bates J, Valente TW. Care coordination in epilepsy: Measuring neurologists' connectivity using social network analysis. Epilepsy & Behavior. 2017;73(1):31–35. [DOI:10.1016/j.yebeh.2017.05.026]
24. Harris JK, Provan KG, Johnson KJ, Leischow SJ. Drawbacks and benefits associated with inter-organizational collaboration along the discovery-development-delivery continuum: a cancer research network case study. Implementation Science. 2012;69(7);1-12. [DOI:10.1186/1748-5908-7-69]
25. Retrum JH, Chapman CL, Varda DM. Implications of Network Structure on Public Health Collaboratives. Health Education & Behavior. 2013;40(1):13–23. [DOI:10.1177/1090198113492759]
26. Aldrich R, Committee W, Fe S, Community C, Division S, Fe S, et al. Trust is key to collaboration in managed care health service delivery networks. Public Administration Review. 2014;74(5):599–600. [DOI:10.1111/puar.12232]
27. Wu IL, Chuang CH, Hsu CH. Information sharing and collaborative behaviors in enabling supply chain performance: A social exchange perspective. International Journal of Production Economics. 2014;148(8):122–132. [DOI:10.1016/j.ijpe.2013.09.016]
28. Rasouli MR, Trienekens JJM, Kusters RJ, Grefen PWPJ. Information governance requirements in dynamic business networking. Industrial Management & Data Systems. 2016;116(7):1356–1379. [DOI:10.1108/IMDS-06-2015-0260]
29. Yong AG, Pearce S. A beginner's guide to factor analysis: Focusing on exploratory factor analysis. Tutorials in Quantitative Methods for Psychology. 2013;9(2):79–94. [DOI:10.20982/tqmp.09.2.p079]
30. Cheng JH, Fu YC. Inter-organizational relationships and knowledge sharing through the relationship and institutional orientations in supply chains. International Journal of Information Management.2013;33(3):473-485. [DOI:10.1016/j.ijinfomgt.2013.01.002]
31. Cheng J-H, Yeh C-H, Tu C. Trust and knowledge sharing in green supply chains. Supply Chain Management: An International Journal. 2008;13(4):283–295. [DOI:10.1108/13598540810882170]
32. Kwon I, Suh T. Factors affecting the level of trust and commitment in supply chain relationships. Journal of Supply Chain Management. 2004;40(1):4-14. [DOI:10.1111/j.1745-493X.2004.tb00165.x]
33. Li S, Lin B. Accessing information sharing and information quality in supply chain management. Decision Support Systems. 2006;42(3):1641–1656. [DOI:10.1016/j.dss.2006.02.011]
34. Sanders NR, Premus R. Modeling the relationship between firm IT capability, collaboration, and performance. Journal of Business Logisttics. 2005;26(1):1–23. [DOI:10.1002/j.2158-1592.2005.tb00192.x]
35. Rampersad G, Quester P, Troshani I. Examining network factors: commitment, trust, coordination and harmony. Journal of Business & Industrial Marketing. 2010;25(7):487–500. [DOI:10.1108/08858621011077727]
36. Long JS. Confirmatory factor analysis: A preface to LISREL. Sage Publications; 1983. Hair JF, Hult GTM, Ringle C, Sarstedt M. A primer on partial least squares structural equation modeling (PLS-SEM). Sage Publications; 2016.
37. Fornell C, Larcker DF. Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research. 1981;18(1):39–50. [DOI:10.1177/002224378101800104]
38. Hulland J. Use of partial least squares (PLS) in strategic management research a review of four recent studies. Strategic Management Journal. 1999;20(2):195–204.
https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7 [DOI:10.1002/(SICI)1097-0266(199902)20:23.0.CO;2-7]
39. https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7
https://doi.org/10.1002/(SICI)1097-0266(199902)20:2<195::AID-SMJ13>3.0.CO;2-7 [DOI:10.1002/(SICI)1097-0266(199902)20:23.0.CO;2-7]
40. Henseler J, Sarstedt M. Goodness-of-fit indices for partial least squares path modeling. Computational Statistics. 2013;28(2):565–580. [DOI:10.1007/s00180-012-0317-1]
41. Bunger AC. Administrative Coordination in Non-Profit Human Service Delivery Networks: The Role of Competition and Trust. Nonprofit and Voluntary Sector Quarterly. 2012;42(6):265–275.
42. Vázquez ML, Vargas I, Garcia-Subirats I, Unger J-PP, De Paepe P, Mogollón-Pérez AS, et al. Doctors' experience of coordination across care levels and associated factors. A cross-sectional study in public healthcare networks of six Latin American countries. BMC Health Services Research. 2017;182(4):10-19.
43. Sheaff R, Windle K, Wistow G, Ashby S, Beech R, Dickinson A, et al. Reducing emergency bed-days for older people? Network governance lessons from the `Improving the Future for Older People' programme. Social Science Medical. 2014;106(10):59–66. [DOI:10.1016/j.socscimed.2014.01.033]
44. White S, Siu-Yun Lui S. Distinguishing costs of cooperation and control in alliances. Strategic Management Journal. 2005;26(10):913–932. [DOI:10.1002/smj.490]
45. Kartseva V, Hulstijn J, Gordijn J, Tan Y-H. Control patterns in a health-care network. European Journal Of Information Systems. 2010;19(3):320–243. [DOI:10.1057/ejis.2010.13]
46. Kembro J, Selviaridis K, Näslund D. Theoretical perspectives on information sharing in supply chains: a systematic literature review and conceptual framework. Supply Chain Management An International Journal. 2014;19(5):609–625. [DOI:10.1108/SCM-12-2013-0460]
47. Koçoǧlu I, Imamoǧlu SZ, Ince H, Keskin H. The effect of supply chain integration on information sharing: Enhancing the supply chain performance. Procedia - Social and Behavioral Sciences. 2011;24(1):1630–1649. [DOI:10.1016/j.sbspro.2011.09.016]
48. Cheng J-H, Yeh C-H, Tu C. Trust and knowledge sharing in green supply chains. Supply Chain Management: An International Journal. 2008;13(4):283–295. [DOI:10.1108/13598540810882170]
49. Addicott R, McGivern G, Ferlie E. Networks, organizational learning and knowledge management: NHS cancer networks. Public Money and Management. 2006;26(2):87–94. [DOI:10.1111/j.1467-9302.2006.00506.x]
50. Blomqvist K, Levy J. Collaboration capability a focal concept in knowledge creation and collaborative innovation in networks. International Journal of Management Concepts and Philosophy. 2006;2(1):31-48. [DOI:10.1504/IJMCP.2006.009645]
51. Emerson K, Nabatchi T, Balogh S. An integrative framework for collaborative governance. Journal of Public Administarion Reseach Theory. 2012;22(1):1–29. [DOI:10.1093/jopart/mur011]
52. Beers LS, Godoy L, Biel MG. Using Effective Public Private Collaboration to Advance Integrated Care. Child and Adolescent Psychiatric Clinics of North America. 2017;26(4):665-675. [DOI:10.1016/j.chc.2017.06.003]
53. Menger LM, Stallones L, Cross JE, Henry KL, Chen PY. Strengthening suicide prevention networks: Interorganizational collaboration and tie strength. Psychosocial Intervention. 2015;24(3):155–165. [DOI:10.1016/j.psi.2015.07.005]
54. Chen YH, Lin TP, Yen DC. How to facilitate inter-organizational knowledge sharing: The impact of trust. Information Management. 2014;51(5):568–778. [DOI:10.1016/j.im.2014.03.007]
55. Loebbecke C, van Fenema PC, Powell P. Managing inter-organizational knowledge sharing. Journal of Strategic Information Systems. 2016;25(1):4–14. [DOI:10.1016/j.jsis.2015.12.002]
56. Gupta S, Polonsky M. Inter-firm learning and knowledge-sharing in multinational networks: An outsourced organization's perspective. Journal of Business Research. 2014;67(4):615–622. [DOI:10.1016/j.jbusres.2013.02.043]
57. Tuohy CH. Agency, contract, and governance: Shifting shapes of accountability in the health care arena. Journal of Health Politics Policy and Law. 2003;28(2–3):195–215. [DOI:10.1215/03616878-28-2-3-195]
58. Beatty KE, Wilson KD, Ciecior A, Stringer L. Collaboration among missouri nonprofit hospitals and local health departments: Content analysis of community health needs assessments. American Journal of Public Health. 2015;105(2): 337–344. [DOI:10.2105/AJPH.2014.302488]
59. Wang ETG, Wei HL. Interorganizational governance value creation: Coordinating for information visibility and flexibility in supply chains. Decision Sciences. 2007;38(4):647–674. [DOI:10.1111/j.1540-5915.2007.00173.x]
60. Alrajeh NA, Elmir B, Bounabat B, El Hami N. Interoperability optimization in healthcare collaboration networks. Biomedical Engineering / Biomedizinische Technik. 2012;57(5):403–411. [DOI:10.1515/bmt-2011-0118]
61. Nembhard IM, Tucker AL. Applying Organizational Learning Research to Accountable Care Organizations. Medical Care Research and Review. 2016;73(6):673–684. [DOI:10.1177/1077558716640415]
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