Learning Tag

Introduction

Interprofessional learning (IPL) and Quality Improvement Education (QIE) are increasingly recognized as important tools to improve performance of U.S. healthcare teams and address the changes the U.S. healthcare system and the Continuing Professional Development (CPD) system are undergoing (Hager, Russell, Fletcher, & Macy Jr, 2008; IoM, 2010; Macy, 2013; WHO, 2010). The need for change is clear: Healthcare is increasingly delivered by teams, yet healthcare teams are not trained as teams or familiar with team-based quality improvement (QI) methodology – and therefore their ability to address the need for quality improvement is limited.

Figure 1. Rising interest in IPL. Source: CIHC (2008)

To address that gap, the Institute of Medicine concluded that professional development of the healthcare workforce and healthcare system should be analyzed together. To improve our healthcare outcomes, it is important to better align the transformation of healthcare workforce CPD with the massive reform of the U.S. healthcare system, and ensure widespread adoption of IPL (IoM, 2015).

This research aims to contribute to that goal by finding how QIE and IPL are perceived by four professions participating in the perioperative team (physician anesthesiologists, surgeons, nurse anesthetists and anesthesiologist assistants), and which QIE- and IPL-related technologies and practices each profession involved in the research have available or plan to implement soon. Results of this research will help healthcare leaders better plan implementation of technology-enhanced QIE and IPL in the context of the perioperative team. In addition, although the perioperative context is specific, a significant part of the findings will be applicable to other interprofessional healthcare teams.
I believe that the research will show that technology-enhanced QIE and IPL are in many ways related to networked learning, and that their successful implementation will require creation of networked learning communities.

Data analysis

Data analysis will rely on three segments (Figure 5):

1. Phenomenographic research will draw a picture of how QIE/IPL is perceived. My goal is to make the process as collaborative, iterative and transparent as possible/approved. Therefore, in addition to the standard phenomenographic method illustrated below, to evaluate the findings I will 1) organize a follow-up interview with selected participants and 2) share findings with a few leaders and the public (if approved) and ask for feedback. If there are moderate differences between groups, I will reflect on them. If those differences are significant, it may be possible to create separate outcome spaces for each group.
2. A case study of each professional organization involved in the research will be focused on QIE/IPL-related practices and technology, and the official policy used in the organization. That can help us better interpret data from phenomenographic research and get insight into what is possible in reality. For example, in my most recent research (Hlede, 2015) I found that in the ASA all research participants indicated that IPL is the preferred way to go. However, the official policy of the organization doesn’t reflect that.
3. Interaction between groups and existing and potential QIE/IPL projects will be analyzed through activity theory, so we can get a better picture of interprofessional activities that at this moment shape perceptions of each profession.

Figure 5. Data analysis.

Reference

Hlede, V. (2015). Interprofessional Learning: Anesthesiologists’ Perspectives. Assignment, Doctoral Programme in E-Research and Technology Enhanced Learning. Department of Educational Research. Lancaster University.