CANDIDATE: Dr. Edward R. Melnick is an Assistant Professor in the Department of Emergency and currently a student in the Master of Health Science Degree program with Clinical Informatics Track at the Yale University School of Medicine. His research focuses on improving clinical practice guideline implementation using computerized Clinical Decision Support (CDS). Traditional CDS consists of alerts or reminders presented to the clinician regarding patient-specific recommendations. Dr. Melnick has a track record for scholarly productivity with 13 peer-reviewed publications over the last five years. He is also an active member of the national clinical practice guideline development group for emergency medicine. The long-term goal of Dr. Melnick's research program is to become an independent investigator whose research program is aimed at changing the acute care clinical encounter paradigm by developing systematic patient-centered methods that promote transparent, shared, informed decision-making to safely reduce resource utilization. He plans to devote his career to overcoming the design challenges to effective CDS thus incorporating CDS that is useful, usable, promotes shared decision-making, and is seamlessly integrated into clinical workflow. Dr. Melnick's design innovations will change the way that health care is delivered and, subsequently, achieve a significant impact on patient outcomes, health care quality, safety, efficiency, costs, and effectiveness for all Americans. ENVIRONMENT &MENTOR: The Department of Emergency Medicine at the Yale University School of Medicine offers a fertile environment for physician-scientists committed to clinical research. The Department and University offer abundant research support and resources for professional development and research excellence. During the proposed award, Dr. Melnick will develop his skills by completing: (1) his ongoing master's of health science degree program with clinical informatics track, (2) formal coursework in human- computer interaction, medical decision-making, databases, and clinical information systems, and (3) goal- directed training activities in CDS, cognitive task analysis, human factors engineering, qualitative research methods, and implementation science under the mentorship of Drs. Shiffman and Post. Dr. Shiffman, Professor and Associate Director for the Yale Center for Medical Informatics, is a well-established researcher whose work focuses on defining systematic and replicable processes by which guideline knowledge can be translated into CDS. Dr. Post, Associate Professor and Research Director of Emergency Medicine at Yale, is an expert in Health Information Technology research using qualitative and mixed methods including experiences with focus groups, survey research, and usability testing. RESEARCH PROJECT: The objective of this project is to pilot an innovative CDS design process that produces patient-centered, useful, and usable CDS for the management of minor head injury in the emergency department (ED). The ED is the ideal setting to study overuse of diagnostic imaging as imaging rates of injured patients have tripled over ten years without a measurable improvement in patient outcomes, despite implementation of highly sensitive and specific clinical decision rules for detecting clinically important brain injury in minor head injury patients. Evidence-based best practices face barriers to implementation including: lack of awareness, agreement, and adherence. CDS offers a promising strategy to improve guideline implementation. Despite forty years of implementation attempts, CDS has not been universally adopted nor have its benefits been fully realized. Several adoption barriers have been identified with the primary challenge being the """"""""usefulness"""""""" (whether it accomplishes its objective) and """"""""usability"""""""" (ease-of-use) of the CDS due to poor integration into clinical workflow. This investigation will rely on qualitative methods to identify factors that promote or inhibit the appropriate use of computed tomography (CT) in patients presenting to the ED with minor head injury. Qualitative factors identified in this analysis will b integrated into the design of a patient- centered decision support tool prototype for use by patients and their provider at the bedside. This tool will undergo iterative refinement via rigorou usability testing in the usability lab and the ED in order to maximize its usefulness, efficiency, ease-of-use, user satisfaction, integration into clinical workflow, and ability to promote shared decision-making regarding the appropriate use of CT. The feasibility of implementing this patient- centered decision support at the bedside in a high-volume ED will be provide data for the subsequent clinical trial. The data generated from this pilot is critical to take my research program to the next level-an effectiveness study of the patient-centered decision support tool to safely reduce CT use. This proposal fulfills the Agency for Healthcare Research and Quality (AHRQ) research priority of training investigators in health information technology to improve health care decision-making and support patient-centered care. It will be piloted in the Yale-New Haven ED whose patients include an inner-city population with large minority and low- income groups-two AHRQ priority populations. The tool will include special provisions for shared decision- making with the elderly, another AHRQ priority population.
Overuse of advanced diagnostic imaging in injured patients in the emergency department has increased dramatically correlating to increased health care costs, exposure to ionizing radiation, and length of stay without a measurable improvement in patient outcomes. Validated, evidence-based guidelines and computerized clinical decision support are promising;however, there are many challenges to implementation including awareness and adherence to guidelines and usefulness, usability, and integration of decision support into clinical workflow. This study aims to pilot an innovative clinical decision support design process that produces decision support for patients and their providers that is patient-centered, useful, usable, and promotes shared decision-making for the management of minor head injury in the emergency department.
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