General Practitioners (GPs) provide first contact and continuity with the medical system in many countries, and the way they manage clinical decision-making has a significant impact on both health outcomes and cost effectiveness. Evidence-based medicine (EBM) is currently promoted as the best approach to facilitate the transfer of results from medical research to clinical practice . Use of this evidence has been supported by the development of computerized information retrieval systems and evidence-based resource databases such as Medline and the Cochrane Library [2, 3]. Access to medical evidence has been revolutionised by the increasing speed and sophistication of Internet search engines such as Google and Google Scholar [4, 5].
General practitioners have supported the promotion of EBM [6, 7], but have identified the challenges inherent in applying EBM approaches within the constraints of everyday practice. The primary barriers preventing physicians from answering clinical question were identified in several studies as "lack of time" and "information overload" [8, 9].
Understanding information management approaches and constraints in primary care settings is important given the pivotal role of GPs in healthcare. This paper describes a model for understanding GP information searching using Optimal Foraging Theory (OFT), developed to study patterns and strategies of animal foraging [10, 11]. Under OFT, the behaviour of an individual forager is broken down into a sequence of discrete behavioural steps (e.g. where to forage, which prey to pursue). At each step, the forager can choose between alternative decisions, and choices may be limited by intrinsic constraints (e.g. foraging skills) and/or extrinsic constraints (e.g. time available, resource distribution). Costs and benefits of alternative foraging decisions are measured using one or a set of currencies (e.g. energy gained per unit time). Central to deriving optimal decisions is the principle of lost opportunity, whereby choosing one activity precludes engaging in an alternative activity which may be more profitable under a given currency and set of constraints.
The two conventional models of OFT are the prey and patch models. Prey models predict that prey types are ranked by profitability (ratio of energy gained to energy spent), and that inclusion of a prey type depends on profitability and encounter rate relative to those of other prey types. Patch models deal with foraging in an environment where resources are clumped (e.g. fruiting trees, schools of fish) and a forager has to allocate its time between foraging within a patch versus searching for a new patch. Patch models generally assume that a forager assesses the quality of a patch by means of the net rate of energy gain. The main prediction of patch models is that a forager should leave a patch when the instantaneous intake rate drops below the average rate in all patches .
OFT has been applied in an information-seeking context, whereby information searchers become the foragers, and information items their "preys" [13–15]. Like animal foragers, information seekers have to navigate in a patchy environment in which information items are clumped within discrete patches (e.g. professional colleagues, journals, books, websites, temporary collections constructed by a retrieval programme or search engine). Information foraging analyzes trade-offs in the value of information gained against the costs of performing the activity of human information searching.
Sandstrom  argues that because OFT integrates deductive models of evolutionary biology and microeconomics, it lays the groundwork for cost-benefit analyses that can be successfully applied to all human choice-making phenomena, including decisions associated with information behaviour. Pirolli and Card  argue that in an information-rich world, the problem is not so much how to collect more information but rather how to optimize the user's time in an attempt to increase relevant information gained per unit time spent. Despite some application to clinical practice, for example the analysis of risky choices made by heroin addicts  there has been no published research which applies foraging theory to information management in general practice
The aim of this study was to explore OFT as a tool to understand and model the information seeking behaviour of GPs, and apply it to measure costs (time spent) and benefits of information seeking decisions (finding a satisfactory answer) by GPs.