We examine the dynamics of patient-sharing relations within an Italian regional community of 35 hospitals serving approximately 1,300,000 people. We test whether interorganizational relations provide individual patients access to higher quality providers of care.
We reconstruct the complete temporal sequence of the 3461 consecutive interhospital patient-sharing events observed between each pair of hospitals in the community during 2005–2008. We distinguish between transfers occurring between and within different medical specialties. We estimate newly derived models for relational event sequences that allow us to control for the most common forms of network-like dependencies that are known to characterize collaborative relations between hospitals. We use 45-day risk-adjusted readmission rate as a proxy for hospital quality.
After controls (eg, geographical distance, size, and the existence of prior collaborative relations), we find that patients flow from less to more capable hospitals. We show that this result holds for patient being shared both between as well as within medical specialties. Nonetheless there are strong and persistent other organizational and relational effects driving transfers.
Decentralized patient-sharing decisions taken by the 35 hospitals give rise to a system of collaborative interorganizational arrangements that allow the patient to access hospitals delivering a higher quality of care. This result is relevant for health care policy because it suggests that collaborative relations between hospitals may produce desirable outcomes both for individual patients, and for regional health care systems.
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*Faculty of Economics, University of Italian Switzerland, Lugano, Switzerland
†Department of Management, Catholic University of the Sacred Heart, Rome, Italy
‡Department of Mathematics and Statistics, University of Melbourne, Vic., Australia
§Department of International Business and Economics, Centre for Business Network Analysis, University of Greenwich, Old Royal Naval College, London, UK
∥Department of Internal Medicine, University of Michigan, Ann Arbor, MI
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Supported in part by the European Science Foundation, European Collaborative Research Project in the Social Sciences Program (ECRP VI), by the Swiss National Science Foundation (grant number 133273: Social Influence in Dynamic Networks) and by the NIH (NHLBI K08: HL091249).
The authors declare no conflict of interest.
Reprints: Theodore J. Iwashyna, MD, PhD, University of Michigan, 2800 Plymouth Road, Bldg 16, Room 332W, Ann Arbor, 41809, MI. E-Mail: email@example.com.