Precision medicine brings forth precision education Precision medicine was introduced in the US in 2015 and represents flexible approaches for the development of personal treatment plans that take into account genetic, environmental and patient factors, including informed choice. Using a similar dynamic model, precision education was introduced over the last few years by several medical schools including Johns Hopkins, Stanford and National University, and is built on the key fundamentals of personalised learning.

Precision education model Precision education involves harnessing the power of information technology to provide learners with an objective analysis of their progress and skills. In this approach, learner data is used to shape the curriculum so that learners can progress at their own pace, get individual remediation in an area that presents a challenge and even learn in their preferred modality.

Using big data to drive educational remediation The National University has developed micro-competencies for their courses. For example, if a course has eight key concepts, each will be divided into 5–6 micro-competencies. A range of educational resources, multimedia content and quizzes are then developed for each micro-competency. When students show a weakness in a micro-competency, they are prompted to remediate. Student learning data is being collected to identify which student profiles match which material type. Once these patterns are established, they enable specific recommendations to be made to students on how best to learn and remediate.

Helping students determine their best learning solutions At Stanford Medicine, options for outside-of-class learning are being improved by enhancing student access to quality multimedia learning tools.  This includes app-driven, case-based learning (with built-in knowledge checks) and provision of online medical education videos.  The university is attempting to generate a recommendation engine (like Netflix) to help students make good decisions about self-directed study.

Digital scorecards and coaching are improving patient outcomes At John Hopkins, individualised feedback is provided to surgery residents on how often they prescribed appropriate prophylaxis to prevent venous thromboembolism based on the patient’s profile and risk factors. Clinical and health informatics experts provide residents with an electronic scorecard detailing their performance and how it compared with that of other residents. Low performers also got one-on-one coaching. In the wake of the intervention, the level of preventable complications among patients has reduced and the number of patients getting appropriate interventions increased significantly. Venous thromboembolism (VTE) occurs when a blood clot forms in a deep vein; and is a common, life-threatening complication following surgery. Depending on a patient’s risk factors, varying degrees of precaution are taken, ordering anything from compression stockings to blood-thinning drugs.