"When the Time Comes": Exploring Temporal Differences in the Adoption of Medical Innovation

Titolo Rivista STUDI ORGANIZZATIVI
Autori/Curatori Daniele Mascia, Valentina Iacopino, Americo Cicchetti
Anno di pubblicazione 2019 Fascicolo 2018/2 Lingua Inglese
Numero pagine 26 P. 62-87 Dimensione file 581 KB
DOI 10.3280/SO2018-002003
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The effects of institutional, organizational, and professional factors on the adoption of medical innovations are widely recognized, but scant empirical evidence for how they jointly affect adoption behaviors over time is available. This study aimed to shed new light on the impact of these factors on the timing of organizations’ decisions to adopt an innovative technology. We collected data on temporal patterns of diffusion of a robotic surgical system among Italian hospital organizations. We adopted a dyadic approach to examine the time elapsed between paired hospitals’ adoption decisions. Negative binomial regression analysis was then performed to test our research hypotheses. The results indicate that professional factors, as well as regional governance and technological policies, significantly predicted the temporal lag in adoption decisions. Our study provides empirical support for the strong effects of professional and institutional characteristics on the temporal aspects of medical innovation diffusion.

Il processo di adozione delle tecnologie sanitarie è al centro del dibattito scientifico ed istituzionale nei contesti odierni. Il costo delle soluzioni tecnologiche, e il loro progressivo utilizzo nell’ambito dei processi di cura, rendono essenziale un’attività di selezione di quelle tecnologie realmente capaci di generare valore. Comprendere i fattori in grado di accelerare o rallentare il processo innovativo è quindi attività estremamente utile ad adottare soluzioni organizzative idonee al contesto odierno e ad implementare tecnologie capaci di generare un impatto positivo sulla salute. Questo studio analizza, in particolare, gli effetti dei fattori istituzionali, organizzativi e professionali sull'adozione delle innovazioni sanitarie, ed è volto nello specifico a comprendere come tali dimensioni influenzino congiuntamente le scelte temporali di adozione. Selezionando una specifica tipologia di robot chirurgico quale oggetto dello studio, sono state raccolte informazioni sul relativo processo di diffusione all’interno del Servizio Sanitario Nazionale italiano e sono state investigate le decisioni di adozione degli ospedali, con riferimento alla temporalità di tali scelte. I risultati della ricerca indicano che i fattori professionali, così come la governance regionale e le politiche tecnologiche, incidono sulla temporalità delle decisioni di adozione da parte delle organizzazioni.

Keywords:Organizzazioni sanitarie, tecnologie sanitarie, innovazione, diffusione, progettazione organizzativa, prossimità sociale, reti professionali.

  1. Achillaidelis, B., Antonakis, N. (2001), “The Dynamics of Technological Innovation: the Case of the Pharmaceutical Industry”, Research Policy, 30: 535-588,
  2. Abraham, J., Jerome-D’Emilia, B., Begun, J.W. (2011), “The diffusion of Magnet hospital recognition”, Health Care Management Review, 36(4): 306-314,
  3. Abrahamson, E. (1991), “Managerial Fads and Fashions: The Diffusion and Rejection of Innovations”, Academy of Management Review, 16(3): 586-612, DOI: 10.2307/258919.
  4. Anderson, J.G. (2002), “Evaluation in Health Informatics: Social Network Analysis”, Computers in Biology and Medicine, 32: 179-193, DOI: 10.1016/S0010-4825(02)00014-8.
  5. Angst, C.M., Agarwal, R., Sambamurthy, V., Kelley, K. (2010), “Social Contagion and Information Technology Diffusion: The Adoption of Electronic Medical Records in U.S. Hospitals”, Management Science, 56(8): 1219-1241,
  6. Afuah, A. (2004), “Does a Focal Firm’s Technology Entry Timing depend on the Impact of the Technology on co-opetitors?”, Research Policy, 33: 1231-1246,
  7. Anagnostopoulos, A., Kumar, R., Mahdian, M. (2008), “Influence and correlation in social networks”. 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (ACM, New York) 2008; 7–15, DOI: 10.1145/1401890.1401897.
  8. Aral, S., Muchnik, L., Sundararajan, A. (2009), “Distinguishing Influence Based Contagion from Homophily-Driven Diffusion in Dynamic Networks”. Proceedings of the National Academy of Science of The United States of America, 106(51): 21544–21549,
  9. Baldwin, J., Lin, Z. (2002), “Impediments to advanced technology adoption for Canadian manufacturers”, Research Policy, 31: 1-18, DOI: 10.1016/S0048-7333(01)00110-X.
  10. Battista, R.N. (2006), “Expanding the scientific basis of health technology assessment: A research agenda for the next decade”, International Journal of Technology Assessment in Health Care, 22(3): 275–282, DOI: 10.1017/S0266462306051130
  11. Battisti, G., Iona, A. (2009), “The Intra-firm Diffusion of Complementary Innovations: Evidence from the Adoption of Management Practices by British Establishments”, Research Policy, 38: 1326-1339,
  12. Battisti, G., Stoneman, P. (2003), “Inter- and Intra-firm Effects in the Diffusion of New Process Technology”, Research Policy, 32: 1641-1655, DOI: 10.1016/S0048-7333(03)00055-6.
  13. Baum, J.A.C., Mezias, S.J. (1992), “Localized competition and organizational failure in the Manhattan hotel industry, 1898–1990”, Administrative Science Quarterly, 36: 187–218, DOI: 10.2307/2393473.
  14. Beane, M. (2018). “Shadow Learning: Building Robotic Surgical Skill When Approved Means Fail”. Administrative Science Quarterly, DOI: 10.1177/0001839217751692.
  15. Becker, M.H. (1970), “Factors affecting diffusion of innovations among health professionals”, American Journal of Public Health, 60(2): 294-303,
  16. Bodas Freitas, I.M. (2008), “Sources of Differences in the Pattern of Adoption of Organizational and Managerial Innovations from Early to late 1990s, in the UK”, Research Policy, 37: 131-148,
  17. Boni, S. (2007), I Sistemi di Governance dei Servizi Sanitari Regionali. I Quaderni del Formez, -- disponibile al sito: http://sanita.formez.it/sites/all/files/pdf_quaderno_57.pdf.
  18. Boothby, D., Doufour, A., Tang J. (2010), “Technology Adoption, Training and Productivity Performance”, Research Policy, 39: 650-661,
  19. Borgatti, S.P., Everett, M.G., Freeman, L.G. (2002), UCINET 6 for Windows: Software for Social Network Analysis. Harvard: Analytic Technologies.
  20. Burns, L.R., Wholey, D.R. (1993), “Adoption and Abandonment of Matrix Management Programs: Effects of Organizational Characteristics and Interorganizational Networks”, Academy of Management Journal, 36(1): 106-138, DOI: 10.2307/256514.
  21. Burt, R. (1987), “Social Contagion and Innovation: Cohesion Versus Structural Equivalence”, American Journal of Sociology, 92(6): 1287-1335, 10.1086/228667.
  22. Brumana, M., Decastri, M., Scarozza, D., Za, D. (2014), “Innovazione tecnologica e organizzazione: trend, aree di ricerca e prospettive”, Studi Organizzativi, 2: 42-75, DOI: 10.3280/SO2014-002002.
  23. Cappellaro, G., Ghislandi, S., Anessi-Pessina, E. (2011), “Diffusion of Medical Technology: The Role of Financing”, Health Policy, 100: 51-59,
  24. Carrosio, G. (2012), “La diffusione degli impianti per la produzione di energia da biogas agricolo in Italia: una storia di isomorfismo istituzionale”. Studi Organizzativi, 2:9-25, DOI: 10.3280/SO2012-002001.
  25. Casper, S., Matraves, C. (2003), “Institutional Frameworks and Innovation in the German and UK Pharmaceutical Industry”, Research Policy, 32: 1865-1879, DOI: 10.1016/S0048-7333(03)00082-9.
  26. Centola, D., Macy, M. (2007), “Complex Contagions and the Weakness of Long Ties”, American Journal of Sociology, 113: 702-734, DOI: 10.1086/521848.
  27. Coleman, J., Katz, E., Menzel, H. (1957), “The Diffusion of an Innovation Among Physicians”, Sociometry, 20(4): 253-270, DOI: 10.2307/2785979.
  28. Compagni, A., Mele, V., Ravasi, D. (2015), “How Early Implementations Influence Later Adoptions of Innovations: Social Positioning and Skill Reproduction in the Diffusion of Robotic Surgery”, Academy of Management Journal, 58(1): 242-278,
  29. Damanpour, F. (1991), “Organizational Innovation: A Meta-Analysis and Moderators”, Academy of Management Journal, 34(3): 555-590, DOI: 10.2307/256406.
  30. Di Maggio, P.J., Powell, W.W. (1983), “The Iron Cage Revisited: Institutional and Collective Rationality in Organizational Fields”, American Sociological Review, 48(2): 147-160, DOI: 10.2307/2095101.
  31. Dirksen, C.D., Ament, A.J.H., Go, P.M.N. (1996), “Diffusion of six surgical endoscopic procedures in the Netherlands. Stimulating and restraining factors”, Health Policy, 37: 91-104, DOI: 10.1016/S0168-8510(96)90054-8.
  32. Dopson, S., Fitzgerald, L., Ferlie, E., Gabbay, J., Locock, L. (2002), “No magic targets! Changing clinical practice to become more evidence based”, Health Care Management Review, 35(1): 2-12,
  33. Evangelista, R., Vezzani, A. (2010), “The Economic Impact of Technological and Organizational Innovations. A Firm-level Analysis”, Research Policy, 39: 1253-1263,
  34. Fabrizio, K.R., Hawn, O. (2013), “Enabling Diffusion: How Complementary Inputs Moderate the Response to Environmental Policy”, Research Policy, 42: 1099-1111,
  35. Ferlie, E., Fitzgerald, L., Wood, M., Hawkins, C. (2005), “The Non-Spread of Innovations: The Mediating Role of Professional”, Academy of Management Journal, 48(1): 117-113, DOI: 10.5465/AMJ.2005.15993150.
  36. Fuentelsaz, L., Gomez, J., Polo, Y. (2003), “Intrafirm Diffusion of New Technologies: an empirical application”, Research Policy, 32: 533-551, DOI: 10.1016/S0048-7333(02)00081-1.
  37. Galende, J., de la Fuente, J.M. (2003), “Internal Factors determining a Firm’s Innovative Behaviour”, Research Policy, 32: 715-736, DOI: 10.1016/S0048-7333(02)00081-1
  38. Geroski, P.A. (2000), “Models of Technology Diffusion”, Research Policy, 29: 603-625, DOI: 10.1016/S0048-7333(99)00092-X.
  39. Gallaud, D., Torre, A., (2005), “Geographical Proximity and the Diffusion of Knowledge”. In: Fuchs, G., Shapira, P., Koch A. (eds), Rethinking Regional Innovation and Change. Path Dependency or Regional Breakthrough?, Springer Verlag, Dordrecht, 127-146, DOI: 10.1007/0-387-23002-5_7.
  40. Gooty, J., Yammarino, F.J. (2011), “Dyads in Organizational Research: Conceptual Issues and Multilevel Analyses”, Organizational Research Methods, 14(3): 456-483, DOI: 10.1177/1094428109358271.
  41. Gómez, J., Vargas, P. (2012), “Intangible Resources and Technology Adoption in Manufacturing Firms”, Research Policy, 41: 1607-1619,
  42. Gómez, J., Vargas, P. (2009), “The Effect of Financial Constraints, Absorptive Capacity and Complementarities on the Adoption of Multiple Process Technologies”, Research Policy, 38: 106-119,
  43. Greenhalgh, T., Robert, G., MacFarlane, F., Bate, P., Kyriakidou, O. (2004), “Diffusion of Innovations in Service Organizations: Systematic Review and Recommendations”, The Mildbank Quarterly, 82(4): 581-629,
  44. Greer, A.L. (1985), “Adoption of Medical Technology: the Hospital’s three decision system”, International Journal of Technology Assessment in Health Care, 1: 669-680, DOI: 10.1017/S0266462300001562.
  45. Hashimoto, H., Noguchi, H., Heidenreich, P., Saynina, O., Moreland, A., Miyazaki, S., Ikeda, S., Kaneko, Y., Ikegami, N. (2006), “The diffusion of medical technology local conditions, and technology re-invention: A Comparative Case Study on Coronary Stenting”, Health Policy, 79: 221-230,
  46. Haunschild, P.R., Miner, A.S. (1997), “Modes of Interorganizational Imitation: The Effects of Outcome Salience and Uncertainty”, Administrative Science Quarterly, 42: 472-500, DOI: 10.2307/2393735.
  47. Hemmert, M. (2004), “The Influence of Institutional Factors on the Technology Acquisition Performance of High-Tech Firms: Survey Results for Germany and Japan”, Research Policy, 33: 1019-1039,
  48. Hockstein, N.G., Gourin, C.G., Faust R.A., Terries D.J. (2007), “A History of robots from science function to surgical robots”, Journal of Robotic Surgery, 1: 113-118,
  49. Hollenstein, H., Woerter, M. (2008), “Inter-firm and Intra-firm Diffusion of Technology: The Example of E-commerce. An analysis based on Swiss Firm-level data”, Research Policy, 37: 545-564,
  50. Hovav, A., Hemmert, M., Kim, Y.J. (2011), “Determinants of Internet Standards Adoption: The Case of South Korea”, Research Policy, 40: 253-262,
  51. Iacopino, V., Mascia, D., Cicchetti, A. (2018a), “Professional Networks and the Alignment of Individual Perceptions about Medical Innovation”, Health Care Management Review, 43(2): 92-103, DOI: 10.1097/HMR.0000000000000132
  52. Iacopino, V., Mascia, D., Monti, A., & Cicchetti A. (2018b). “Professional Networks and the Diffusion of Medical Technologies: An Empirical Study on Robotic Surgery”. In Boccardelli, P., Magnusson, M., Annosi, M.C., Brunetta, F. (eds.). Learning and Innovation in hybrids and “new” organizations. Palgrave Macmillan Publisher, Isbn: 978-3-319-62467-9.
  53. Jacobs, B.L., Zhang, Y., Skolarus, T.A., Wei, J.T., Montie, J.E., Schroeck, F.R., Hollenbeck, BK. (2013), “Certificate of need legislation and the dissemination of robotic surgery for prostate cancer”, Journal of Urology, 289(1): 80-85,
  54. Kaissi, A.A., Begun, J.W. (2008), “Fads, Fashions and Bandwagons in Health Care Strategy”, Health Care Management Review, 33(2): 94-102, DOI: 10.1097/01.HMR.0000304498.97308.40
  55. Kimberly, J.R., Evanisko, M.J. (1981), “Organizational Innovation: The Influence of Individual, Organizational and Contextual Factors on Hospital Adoption of Technological and Administrative Innovations”, Academy of Management Journal, 24(4): 689-713, DOI: 10.2307/256170.
  56. Leonard-Barton, D., Deschamps, I., (1988), “Managerial Influence in the Implementation of the New Technology”, Management Science, 34(10): 1252-1265,
  57. Lal, K. (1999), “Determinants of the adoption of Information Technology: a case study of electrical and electronic goods manufacturing firms in India”, Research Policy, 28: 667-680 DOI: 10.1016/S0048-7333(99)00014-1.
  58. Lindner, R.K., Pardey, P.G., Jarrett, F.G. (1982), “Distance to Information Source and the Time Lag to Early Adoption of Trace Elements Fertilisers”, Australian Journal of Agricultural Economics, 26(2): 98-113,
  59. Lo Scalzo, A., Donatini, A., Orzella, L., Cicchetti, A., Profili, S., Maresso, A. Italy (2009), “Health System Review. European Observatory of Health Systems and Policies”, Health System in Transition, 11(6).
  60. Majumdar, S.K. (1995), “Does New Technology Adoption Pay? Electronic Switching Patterns and Firm-Level Performance in US Telecommunications”, Research Policy, 24: 803-822, DOI: 10.1016/0048-7333(94)00809-L.
  61. Makarov, D.V., Yu, J.B., Desai, R.A., Penson, D.F., Gross, C.P. (2011), “The Association Between Diffusion of the Surgical Robot and Radical Prostatectomy Rates”, Medical Care, 49: 333-339,
  62. Marsden, P.V. (1988), “Homogeneity in confiding relations”, Social Networks, 10: 57-76, DOI: 10.1016/0378-8733(88)90010-X.
  63. Mascia, D., Di Vincenzo, F. (2011), “Co-opetition e performance organizzativa: un’analisi empirica nel settore sanitario”, Studi Organizzativi, 1: 56-86, DOI: 10.3280/SO2011-001003
  64. Mascia, D., Pallotti, F., Cicchetti, A., Lomi, A. (2009), “Cooperazione, competizione o co-opetizione? Evidenze empiriche nel settore della sanità”, Studi Organizzativi, 1:5-29, DOI: 10.3280/SO2009-001001
  65. McPherson, W., Smith-Lovin, L., Cook M. (2001), “Birds of a Feather: Homophily in Social Networks”, Annual Review of Sociology, 27: 415-444,
  66. Mendivil, A., Hollowayb, R.W., Boggessa, J.F. (2009), “Emergence of robotic assisted surgery in gynecologic oncology: American perspective”, Gynecologic Oncology, 114(2): S24–S31,
  67. Metcalfe, S., (1981), “Impulse and diffusion in the process of technological change”, Futures, B: 347-359, DOI: 10.1016/0016-3287(81)90120-8.
  68. Metcalfe, S., (1988), The diffusion of innovation: an interpretative survey. In Dosi G., Pavitt, K., Soete L. (eds.), Technical Change and Economic Theory. London, Frances Pinter.
  69. National Agency for Regional Healthcare Services, (2010), “Programma Strategico Strumenti e Metodi per il Governo dei Processi di Innovazione Tecnologica, Clinica ed Organizzativa nel Servizio Sanitario Nazionale - Un Sistema Integrato di Ricerca”. Final Report of the Strategic Project PS1”, internal document.
  70. Nugroho, Y. (2011), “Opening the Black Box: The Adoption of Innovations in the Voluntary Sector – The Case of Indonesian Civil Society Organisations”, Research Policy, 40: 761-777,
  71. Owen-Smith, J., Powell, W. (2002), “Knowledge Networks as Channels and conduits: The Effects of Spillover in the Boston Biotechnology Community”, Organisation Science, 15: 5-21,
  72. Orlikowski, W.J. (2007), “Sociomaterial Practices: Exploring Technology at Work”. Organization Studies, 28 (9):1435–1448, DOI: 10.1177/0170840607081138
  73. Pache, A. C., Santos, F. (2010). “When worlds collide: The internal dynamics of organizational responses to conflicting institutional demands”. Academy of management review, 35(3):455-476.
  74. Pal, B. (2012), “Robot-assisted laparoscopic surgery: Just another toy?”, Apollo Medicine, 9(3): 239–241,
  75. Reagans, R., & McEvily, B. (2003), “Network Structure and Knowledge Transfer: The Effects of Cohesion and Range”, Administrative Science Quarterly, 28: 240-267, DOI: 10.2307/3556658.
  76. Ricciardi, W., Agostinelli, A., La Torre, G., Cicchetti, A., Derrico, P., Patarnello, F., (2010), ViHTA Project Team. Primo Libro Bianco sull’Health Technology Assessment in Italia. Progetto VIHTA. Valore in Health Technology Assessment, -- retrieved from: http://www.panoramasanita.it/docs/Primo_Libro_Bianco_HTA.pdf.
  77. Robertson, M., Swan, J., Newell, S. (1996), “The Role of Networks in the Diffusion of Technological Innovation”, Journal of Management Studies, 33(3): 333-359,
  78. Rogers, E.M. (1962), Diffusion of Innovations. New York, Free Press, Isbn: 0-02-926650-5.
  79. Rowley, T. J. (1997). “Moving beyond dyadic ties: A network theory of stakeholder influences”. Academy of management Review, 22(4):887-910, DOI: 10.2307/259248.
  80. Rye, B.C., Kimberly, J.R. (2007), “The adoption of Innovations by Provider Organizations in Health Care”, Medical Care Research and Review, 64(3): 235-278, DOI: 10.1177/1077558707299865.
  81. Scott, W.R., Meyer, J.W. (1991), “The rise of training programs in firms and agencies: An institutional perspective”, Research in Organizational Behavior, 13: 297–326.
  82. Scott, W.R., Ruef, M., Mendel, P. J., & Caronna, C. A. (2000). Institutional change and healthcare organizations: From professional dominance to managed care. Chicago, University of Chicago Press, Isbn: 9780226743103.
  83. Scott Long, J., Freese, J. (2001), Regression Models for Categorical Dependent Variable Using Stata, Stata Press, Isbn-13: 978-1-59718-111-2.
  84. Spanos, Y.E., Voudouris, I. (2009), “Antecedents and Trajectories of AMT Adoption: The Case of Greek Manufacturing SMEs”, Research Policy, 38: 144-155,
  85. Swamidass, P.M. (2003), “Modeling the Adoption Rates of Manufacturing Technology Innovations by Small US Manufacturers: a Longitudinal Investigation”, Research Policy, 32: 351-366,
  86. Tediosi, F., Gabriele, S., Longo, F. (2009), “Governing Decentralization in Health Care under tough budget constraint: What can we learn from the Italian experience?”, Health Policy, 90: 303-312,
  87. Traore, N., Rose, A. (2003), “Determinants of biotechnology utilization by the Canadian industry”, Research Policy, 32: 1719-1735, DOI: 10.1016/S0048-7333(03)00081-7.
  88. van Dam, P., Hauspy, J., Verkinderen, L., Trinh, B., Van Looy, L., Dirix, L. (2011), “Do Costs of Robotic Surgery Matter?” In: Darwish, A. (eds), Advanced Gynecologic Endoscopy, DOI: 10.5772/20189.
  89. Weterings, A., Boschma, R. (2009), “Does Spatial Proximity to Customers Matter for Innovative Performance? Evidence from the Dutch Software Sector”, Research Policy, 38: 746-755,
  90. White, K. R. (2000). “Hospitals sponsored by the Roman Catholic Church: separate, equal, and distinct?”, The Milbank Quarterly, 78(2): 213-239, DOI: 10.1111/1468-0009.00169.
  91. Winick, C. (1961), “The Diffusion of an Innovation among Physicians in a Large City”, Sociometry, 24(9): 384-396, DOI: 10.2307/2785920.
  92. Wuyts, S., Colombo, M.G., Dutta, S., Nooteboom, B. (2005), “Empirical tests of optimal cognitive distance”, Journal of Economic Behavior & Organization, 58(2): 277–302,
  93. Zheng, K., Padman, R., Krackhartd, D., Johnson, M.P., Diamond, H.S. (2010), “Social Networks and Physician Adoption of Electronic Health Records: Insights from an Empirical Study”, Journal of the American Medical Informatics Association, 17: 328-336,

Daniele Mascia, Valentina Iacopino, Americo Cicchetti, "When the Time Comes": Exploring Temporal Differences in the Adoption of Medical Innovation in "STUDI ORGANIZZATIVI " 2/2018, pp 62-87, DOI: 10.3280/SO2018-002003