Full Description
Governments and clinical providers are investing billions of dollars in health information technologies (HIT). This is being done with the expectation that HIT adoption will translate into healthier patients experiencing better care at lower cost. In the initial push to roll out HIT, the reliability of these claims was often not substantiated by systematic evaluation and testing. As the first wave of widespread adoption of HIT comes to an end and the next wave begins, it is more important than ever that stakeholders evaluate the results of their investment, evaluate their success (or failure), and make decisions about future directions.
Structured evaluations of a project's impact are an essential element of the justification for investment in HIT. A systematic approach to evaluation and testing should allow for comparison between different HIT interventions with the goal of identifying and promoting those which improve clinical care or other outcomes of interest. The question of the day is no longer "why perform evaluations," but "how to perform evaluations."
This updated book provides an easy-to-read reference outlining the basic concepts, theory, and methods required to perform a systematic evaluation of HIT. Chapters cover key domains of HIT evaluation: study structure and design, measurement fundamentals, results analysis, communicating results, guidelines development, and reference standards. Updated case studies and examples are included demonstrating the successes or failures of these investments. The authors also include new initiatives put in place by the government and discuss how they are being adopted and used by health systems.
Contents
Foreword. Preface. Acknowledgments. Authors. 1 The Foundation and Pragmatics of HIT Evaluation. 2 Structure and Design of Evaluation Studies. 3 Study Design and Measurements Fundamentals. 4 Analyzing the Results of Evaluation. 5 Proposing and Communicating the Results of Evaluation Studies. 6 Safety Evaluation. 7 Cost Evaluation. 8 Efficacy and Effectiveness Evaluation. 9 Usability Evaluation. 10 Case Studies. 11 Healthcare Artificial Intelligence Tools Evaluation. Index.
