Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Accept all cookies Reject all non-essential cookies Find out more

Jeffrey Lienert

Year 3 Graduate Student Prize Winner

Prior to matriculating in the DPhil program at the Nuffield Department of Medicine, I completed a BA in biochemistry followed by an MS in epidemiology. This interdisciplinary background has benefited my doctoral work which seeks to understand, broadly, how human social interactions impact health through social networks. The aim of my dissertation is to use electronic medical records and administrative data from the NHS to understand the health effects of patients being simultaneously located (co-present) in a hospital ward or room. I am jointly supervised by Dr. Felix Reed-Tsochas at the Saïd Business School, Dr. Laura Koehly at the National Human Genome Research Institute (NHGRI) at the National Institutes of Health (NIH), and Dr. Christopher Steven Marcum also at the NHGRI. All three have expertise in social network analysis, but from different academic backgrounds, and I benefit from their interdisciplinary perspectives.

My first study examined social influence between patients in the chemotherapy ward. In sum, I found that co-presence matters. Importantly I used large observational datasets instead of standard methods such as surveys or ethnographic research to infer potential social interactions. Studies using standard methods would have likely featured 10s or 100s of patients and potentially had difficulty detecting an effect, whereas my study included all 4,791 chemotherapy patients over a 10-year period. Compared to isolation, being co-present with patients who were likely responding well to their chemotherapy (as evidenced by surviving at least 5 years following chemotherapy), increased a patient's own likelihood of surviving at least 5 years following chemotherapy. Also compared to isolation, being with those whose health was not improving decreased a patient's own likelihood of survival.

I am currently studying how co-presence impacts infectious disease spread in hospitals. Again, I leverage administrative data to make inferences about disease transmission that would normally require much more detailed and time-consuming collection methods. Standard methods would often precisely detail the hospital movements of a handful of patients, where I am able to precisely follow over one million patients over a fifteen-year time frame. The research questions here are twofold: 1) can the number of hours of co-presence be used as a prospective marker of the likelihood of infection, and 2) can the amount of co-presence combined with biomarker information be used to infer subclinical infection? This research has implications for the management of infectious diseases in the healthcare setting.

Methods development is also a strong focus of mine. In the chemotherapy study, I created a method for determining the amount of co-presence that could be considered significant based on patient profiles. I have also extended the triad census, which tallies each unique structural configuration of three actors in a network (e.g. all three interact with one another), to include patient characteristics. This helps me better understand co-presence patterns among patients, and how they relate to the possibility of infection. Both methods required not only properly specifying the method and underlying calculations, but also ensuring the calculations proceed efficiently with large datasets.

Following the conferring of my DPhil, I intend to begin either a faculty position or a Postdoc. I intend to continue research in this vein, bolstered by additional datasets from other healthcare systems. In addition to research, I will remain active in teaching, for which academia offers an ideal environment.

PUBLICATIONS

Jeffrey's Website: http://jlienert.github.io

Lienert J, Marcum CS, Finney J, Reed-Tsochas F, and Koehly L. 2017. Social influence on 5-year survival in chemotherapy co-presence network. Network Science.DOI: https://doi.org/10.1017/nws.2017.16.

Lienert J, Tarko L, Uchino M, Christen WG, Li JZ, and Schaumberg DA. 2016. Long-term natural history of dry eye disease from the patient's perspective. Ophthalmology 123:425-33.

Blackburn J, Cleveland J, Griffin R, Davis G, Lienert J, McGwin, G Jr. 2012. Tattoo frequency and types among homicides and other deaths, 2007-2008: a matched case-control study. Am J Forensic Med Pathol 33:202-5.

Lienert J, Griffin R, Blackburn J, McGwin G Jr. 2012. The epidemiology of lawn trimmer injuries in the United States, 2000-2009. J Safety Res 43:137-9.

McGwin G Jr, Lienert J, Kennedy JI Jr. 2010. Formaldehyde exposure and asthma in children: a systematic review. Environ Health Perspect 118:313-317.

In this section