Use patterns of health information exchange systems and admission decisions: Reductionistic and configurational approaches

Abstract

BackgroundResearch that endeavors to identify the value of electronic health information exchange (HIE) systems to the healthcare industry and, specifically, to clinical decision making is often inconclusive or theory-based. Studies seeking to identify how clinical decisions relate to patterns of actual HIE use, often by analyzing system log files, generally rely on dichotomous distinctions between system use and no-use, disregard the availability of information in the system, and control for few user characteristics. ObjectiveWe aim at empirically exploring the associations between use patterns of HIE systems and subsequent clinical decisions on the basis of broad definitions of use patterns, available information, and control variables. MethodsWe examine the decision to admit critically-ill patients either to the intensive care unit (ICU) or to another ward at a busy emergency department in the period 2010–2012. Using HIE log files, use patterns are characterized by the variables of number of users, volume, diversity, granularity, duration, and content. We test the association between HIE use patterns and the admission decision, after controlling for multiple demographic, clinical, physician, and situational variables and for available HIE information. This association is examined by taking a reductionistic approach that focuses on independent use variables and a configurational approach that focuses on use profiles. ResultsFive use profiles were identified, the largest of which (46.95% of encounters) described basic HIE access. ICU admission is more probable when the HIE system is perused by multiple users (odds increase by 31%) and when use profiles include prolonged screen viewing (odds increase by 159%) or access to diverse and multiple types of information, specifically on test results, procedures, and previous encounters. DiscussionReductionistic and configurational approaches yield complementary insights, which advance the understanding of how actual HIE use is associated with clinical decision making. The study shows that congruent profiles of HIE use enhance the predictability of the admission decision beyond what can be explained by independent variables of HIE use.