M Sriram Iyengar1, Deevakar Rogith2, Jose F Florez-Arango1,3. 1. Center for Biomedical Informatics, College of Medicine, Texas A&M Health Science Center, Houston, TX, USA. 2. The University of Texas Health Science Center at Houston (UTHealth) School of Biomedical Informatics, Houston, TX, USA. 3. Escuela de Ciencias de la Salud, Universidad Pontificia Bolivariana, Medellin, Colombia.
Abstract
Introduction: The increasing use of Health Information Technology (HIT) can add substantially to workload on clinical providers. Current methods for assessing workload do not take into account the nature of clinical cases and the use of HIT tools while solving them. Methods: The Clinical Case Demand Index (CCDI), consisting of a summary score and visual representation, was developed to meet this need. Consistency with current perceived workload measures was evaluated in a Randomized Control Trial of a mobile health system. Results: CCDI is significantly correlated with existing workload measures and inversely related to provider performance. Discussion: CCDI combines subjective and objective characteristics of clinical cases along with cognitive and clinical dimensions. Applications include evaluation of HIT tools, clinician scheduling, medical education. Conclusion: CCDI supports comparative effectiveness research of HIT tools. In addition, CCDI could have numerous applications including training, clinical trials, design of clinical workflows, and others.
Introduction: The increasing use of Health Information Technology (HIT) can add substantially to workload on clinical providers. Current methods for assessing workload do not take into account the nature of clinical cases and the use of HIT tools while solving them. Methods: The Clinical Case Demand Index (CCDI), consisting of a summary score and visual representation, was developed to meet this need. Consistency with current perceived workload measures was evaluated in a Randomized Control Trial of a mobile health system. Results: CCDI is significantly correlated with existing workload measures and inversely related to provider performance. Discussion: CCDI combines subjective and objective characteristics of clinical cases along with cognitive and clinical dimensions. Applications include evaluation of HIT tools, clinician scheduling, medical education. Conclusion: CCDI supports comparative effectiveness research of HIT tools. In addition, CCDI could have numerous applications including training, clinical trials, design of clinical workflows, and others.
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