Preface

Are you wondering why we chose this photo for the introduction to this book? Looking at this photo, we see complexity, diversity, and layers of visual information that come together to reveal something beautiful. This photo feels dynamic and ever-changing. As you go through this book, we ask that you keep this photo in mind. Using data to drive change in the health sector is not a linear process. It is complex, diverse, and layered. It is dynamic and ever-changing. What this means is that effectively driving change demands a strong understanding of data (Chapter 1: Data Literacy), the use of data as a tool for equity (Chapter 2: Data for Equity), how to drive change (Chapter 3: Implementing Change – Easier Said Than Done), how to translate research evidence into policy and practice (Chapter 4: Knowledge Translation and Exchange to Support Decision-Making), and finally, how to use data to inform decisions about resource allocation (Chapter 5: Using Health Economic Evidence to Inform Decisions About Resource Allocation). We hope that the diversity of chapters in this book will make one thing clear – it truly takes an integrated approach to drive change in the health sector.

Did you know that it takes approximately 17 years for evidence to be fully adopted in practice? Or that only 50% of new evidence-based strategies even make it into practice?

Why is this?

We spend a great deal of time and energy (not to mention money) on research to explore and understand new ways of providing health services. When research demonstrates positive outcomes for patients and/or the system, why does it not become adopted into practice right away across the system? If the evidence is there to support something new, why is it not happening?

That is truly the million-dollar question that motivates researchers in the field of implementation science. Eccles and Mittman (2006) define implementation science as “the scientific study of methods to promote the systematic uptake of research findings and other evidence-based practices into routine practice, and, hence, to improve the quality and effectiveness of health services and care”. Implementation scientists are those who are interested in the middle ground of how we take what we know works and make sure that this is realized in the practice setting. They focus on the factors that influence the uptake of new innovations in order to successfully drive change based on the latest evidence. We hope that this book, with its chapters on data literacy, data for equitable change, implementing change, knowledge translation and exchange, and health economics, will provide valuable information for students and practitioners to consider when exploring how to use evidence to drive change in the health sector.

The goal of this book is to be interesting, interactive, and engaging in the way that we provide  information that will hopefully shape your current or future role in the health sector. We aim to deliver the information in this book in a stimulating and thought-provoking manner through multimedia, case studies, and thought-provoking questions. We hope that you will reflect on your current knowledge and perceptions, challenge your assumptions, and advance your thinking and skills. As you move through this book, you will see that it has been written in a way that allows for a foundational understanding of the content but with “deeper dive” sections including additional resources in case you would like to expand your learning beyond the pages of this book. We hope that you enjoy this book and use the information that you learn to effectively drive change in the health sector as a change leader. Finally, we want to acknowledge all of the academic, community, and student partners who were involved in the development of this book – this would not have been possible without such an incredible collaborative team.

Dr. Madelyn P. Law and Caitlin Muhl