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Volume 79, Issue 6, Pages e116-e125 (June 2010)


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Social network analysis of medication advice-seeking interactions among staff in an Australian hospital

Nerida CreswickCorresponding Author Informationemail address, Johanna I. Westbrook

Received 25 February 2008; received in revised form 1 August 2008; accepted 18 August 2008. published online 30 January 2009.

Abstract 

Purpose

To examine the medication advice-seeking network of staff in a hospital ward.

Methods

Social network analysis was carried out in a renal ward of an Australian metropolitan teaching hospital. The medication advice-seeking interactions of doctors, nurses, allied health professionals (including a pharmacist) and a ward clerk were examined using data from questionnaires administered to staff. The questionnaire listed all staff who worked in the ward and sought information from respondents regarding their interactions with each staff member. Data were analysed using social network software, UCINET. Analyses performed included geodesic distance, network density, strength of ties, reciprocation of relations, and centrality of individuals. NetDraw was used to produce social network diagrams.

Results

A very high response rate of 96% was achieved with 45 of 47 staff returning the questionnaire. On average, there is little interaction between each of the staff members in the medication advice-seeking network, with even less interaction between staff from different professional groups. Nurses are mainly located on one side of the network and doctors on the other. However, the pharmacist is quite central in the medication advice-seeking network as are some senior nurses and a junior doctor.

Conclusions

When hospital clinical staff seek medication advice from other members of a ward it tends to be sought from those in their profession. However key individuals in the ward are relied upon for the provision of medication advice by staff from all professions. Social network analysis can be used to examine the complex medication advice-seeking interactions amongst staff in a hospital ward, providing useful quantitative baseline data against which to compare the effect of interventions, such as an electronic medication system, on interactions.

Health Informatics Research & Evaluation Unit, Faculty of Health Sciences, The University of Sydney, PO Box 170, Lidcombe, NSW 1825, Australia

Corresponding Author InformationCorresponding author. Tel.: +61 2 9351 9987.

PII: S1386-5056(08)00151-2

doi:10.1016/j.ijmedinf.2008.08.005


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