Spread of Pathogens in the Patient Transfer Network of US Hospitals
Antibiotic-resistant organisms, an increasing source of morbidity and mortality, have a natural reservoir in hospitals, and recent estimates suggest that almost 2 million people develop hospital-acquired infections each year in the US alone. We investigate the temporal network of transfers of Medicare patients across US hospitals over a 2-year period to learn about the possible role of hospital-to-hospital transfers of patients in the spread of infections. We analyze temporal, geographical, and topological properties of the transfer network and show that this network may serve as a substrate for the spread of infections. Finally, we study different strategies for the early detection of incipient epidemics on the temporal transfer network as a function of activation time of a subset of sensor hospitals. We find that using approximately 2% of hospitals as sensors, chosen based on their network in-degree, with an activation time of 7 days results in optimal performance for this early warning system, enabling the early detection of 80% of the C. difficile. cases with the hospitals in the sensor set activated for only a fraction of 40% of the time.
KeywordsNosocomial Infection Medicare Patient Temporal Network Patient Transfer Network Neighbor
We thank Laurie Meneades for the expert assistance required to build the dataset. JFG and JPO are joint first authors of this article.
- 2.Threat Report 2013-Antimicrobial Resistance - CDC. http://www.cdc.gov/drugresistance/threat-report-2013/
- 4.Infectious Diseases Society of America (IDSA): Combating antimicrobial resistance: policy recommendations to save lives. Clin. Infect. Dis. 52(S5) (2011)Google Scholar
- 11.Unnikrishnan, K.P., Patnaik, D., Iwashyna, T.J.: Spatio-temporal structure of US critical care transfer network. AMIA Summits Transl. Sci. Proc. 2011, 74–78 (2011)Google Scholar
- 16.Isella, L., Romano, M., Barrat, A., Cattuto, C., Colizza, V., Van den Broeck, W., Gesualdo, F., Pandolfi, E., Rav, L., Rizzo, C., Tozzi, A.E.: Close encounters in a pediatric ward: measuring face-to-face proximity and mixing patterns with wearable sensors. PLoS ONE 6(2), e17144 (2011)CrossRefGoogle Scholar
- 17.Medicare beneficiaries as a percent of total population. http://kff.org/medicare/state-indicator/medicare-beneficiaries-as-of-total-pop/
- 18.Overview of hospital stays in the United States (2010). http://www.hcup-us.ahrq.gov/reports/statbriefs/sb144.jsp
- 19.American Hospital Association. http://www.aha.org/
- 20.Gerding, D.N., Johnson, S.: Harrisons principles of internal medicine. In: Fauci, A.S., Braunwald, E., Kasper, D.L., et al. (eds.) 17th Editi. McGraw-Hill, New York (2008)Google Scholar
- 22.Schmiedeskamp, M., Harpe, S., Polk, R., Oinonen, M., Pakyz, A.: Use of international classification of diseases, ninth revision, clinical modification codes and medication use data to identify nosocomial clostridium difficile infection. Infect. Control Hosp. Epidemiol. 30(11), 1070–1076 (2009)CrossRefGoogle Scholar
- 25.Fisher, R.A.: Frequency distribution of the values of the correlation coefficient in samples from an indefinitely large population. Biometrika 10(4), 507–521 (1915)Google Scholar
- 30.Kirkpatrick, S., Gelatt, C.D., Vecchi, M.P.: Science 220, 671–680 (1983)Google Scholar