Abstract
Perinatal optimality means achieving maximal perinatal outcomes with minimal interventions considering women's past and present histories. The Optimality Index-US (OI-US) is a research tool designed to measure potential associations between evidence-based perinatal care processes and outcomes in aggregate groups of women against an optimal standard. This article describes how the Shenandoah University Nurse-Midwifery Program uses the OI-US to teach students to recognize evidence-based care, reflect on the influences that care processes may have on outcomes, and consider the value of measuring the relationship between interventions and outcomes. Case studies and individual presentations apply the optimality concept by illustrating different care processes, identifying evidence-based care, and evaluating management through the optimality lens. A pilot study was performed in which a 10-question interview was administered to 9 midwifery students before graduation. Two research questions were addressed: "Is the OI-US an effective teaching tool?" and "How can the program improve this strategy?" Narrative analysis was used to interpret students' understandings of the tool, how it affected their clinical learning, and its potential to use in future practices. Four themes were identified: 1) students felt the OI-US gave them a foundation to assess their management and the confidence to plan future management, 2) students used the OI-US as a teaching tool to help women prevent nonoptimal events from occurring, 3) students thought the OI-US would be feasible to use in their future practices, and 4) lack of accessibility to a printed version of the tool while providing care was an obstacle for efficient use. Students suggested increasing the tool's accessibility and using it in other learning activities. The use of the OI-US should be explored further to teach evidence-based care, to generate reflection concerning potential associations between perinatal care processes and outcomes, and to challenge students to question non-evidence-based practices.
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