Using Complexity to Respond to Low Influenza Vaccination Rates among Health Care Professionals and Support Staff

By contributor, Angie (Metzger) Thomure

Have you or a loved one ever been hospitalized? The last thing on your mind, at a time like this, should be whether your care providers have received their annual influenza vaccination. Annually, the compliance rate of health care providers receiving the influenza vaccination varies from 2 to 36% (Couto, Pannuti, & Paz, 2012). However, health care workers are at a higher risk for exposure from patients with influenza and are also potential vectors for exposing otherwise uninfected patients to influenza. Houston, there is a problem. According to Lindley et al. (2009), while the overwhelming majority of hospitals surveys provided flu vaccinations to employees including medical and support staff, there was a marked disparity in the availability of the vaccine to medical students and residents. Among those hospitals surveys, half reported employees in their hospital network that refused vaccination in spite of hospital policy supporting it. Few studies have used complexity to analyze this infection control problem. This needs to change.
A system with complexity involves several large networks with no central control, simple rules of operation, complex collective behavior, sophisticated informational processing, and adaptions (Mitchell, 2009). A hierarchy can be used to describe complexity and the structure of a hospital system. Hospitals are beyond complicated. In a complex hospital system, boundaries can change and health care workers can belong to several systems at the same time. Health care professionals and support staff overlap or transfer wards, floors, and employee ranks. This adaptability, “on the edge of chaos”, must be accounted for in some systematic fashion. Enter social network analysis. First, systems are embedded within other systems and co-evolve and hospitals fit this bill (Plsek, 2001). For example, the evolution of one unit in a hospital may influence another unit to change because they are nested within other systems all evolving together and interacting. A decrease in employee vaccinations may lead to longer in-bed hospital stays by way of worsened patient outcomes, increasing strain on the resources of patients (and their support networks) and healthy personnel alike.
By definition, the behavior of a complex system is often nonlinear, changeable, sensitive to small changes, and is fundamentally unpredictable over time. While daunting, shouldn’t the “sensitivity to small changes” excite us if the tables can be turned in favor of a safer hospital environment. What leverage can the hospital try to manipulate? A logical way to know what a complex system will do is to observe the network based characteristics of the front line workers linked to this behavior of vaccinating (or not). However, it is possible to make generally true and useful statements about the behavior of a complex system, such as in a hospital, because there is an overall pattern that does not follow hardened physical laws. Complexity science has shown that it is often better to try multiple approaches and let direction arise by gradually shifting time, resources, and attention towards things that seem to be working best (Plsek, 2001). The study of complexity can advise hospital officials to use accept unpredictability and respond flexibly to emerging patterns. Overall, despite evidence that the vaccination of health care workers protects against seasonal and pandemic influenza, vaccination of health care workers in the United States remains at unacceptable levels. The use of complete social network analysis and complexity may help to locate ways to intervene in the system in real-time in order to increase the vaccination compliance rate among health care workers. First do no harm may begin with first bring no harm to the patients by improved compliance with vaccination requirements by health care workers.

Couto, C., Pannuti, C., Paz J. (2012) Fighting Misconceptions to Improve Compliance with
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Lindley, M., Yonek, J., Ahmed, F., Perz, J. & Williams Torres, G. (2009). Measurement of influenza vaccination coverage among healthcare personnel in US hospitals. Infection Control and Hospital Epidemiology. 30(12), 1150-7.
Mitchell, M. (2009). Defining and measuring complexity. In Complexity: A Guided Tour. New
York: Oxford.
Plsek, R. & Greenhalgh, T. (2001). The challenge of complexity in health care. BMJ, 323, 625-