Mary Beth Flynn Makic1, Kathleen R Stevens2, R Mark Gritz3, Heidi Wald4, Judith Ouellet3, Cynthia Drake Morrow5, David Rodrick6, Blaine Reeder7. 1. University of Colorado, College of Nursing, Aurora, Colorado, United States. 2. School of Nursing, University of Texas Health Science Center San Antonio, San Antonio, Texas, United States. 3. Division of Health Care Policy and Research, School of Medicine, University of Colorado Denver, Aurora, Colorado, United States. 4. SCL Health, Denver, Colorado, United States. 5. Health Systems, Management and Policy, Colorado School of Public Health, Aurora, Colorado, United States. 6. Center for Quality Improvement and Patient Safety, Agency for Healthcare Research and Quality, Rockville, Maryland, United States. 7. University of Missouri Health, Sinclair School of Nursing and MU Institute for Data Science and Informatics, School of Nursing, Columbia, Missouri, United States.
Abstract
BACKGROUND: Hospital-acquired conditions (HACs) are common, costly, and national patient safety priority. Catheter-associated urinary tract infections (CAUTIs), hospital-acquired pressure injury (HAPI), and falls are common HACs. Clinicians assess each HAC risk independent of other conditions. Prevention strategies often focus on the reduction of a single HAC rather than considering how actions to prevent one condition could have unintended consequences for another HAC. OBJECTIVES: The objective of this study is to design an empirical framework to identify, assess, and quantify the risks of multiple HACs (MHACs) related to competing single-HAC interventions. METHODS: This study was an Institutional Review Board approved, and the proof of concept study evaluated MHAC Competing Risk Dashboard to enhance clinicians' management combining the risks of CAUTI, HAPI, and falls. The empirical model informing this study focused on the removal of an indwelling urinary catheter to reduce CAUTI, which may impact HAPI and falls. A multisite database was developed to understand and quantify competing risks of HACs; a predictive model dashboard was designed and clinical utility of a high-fidelity dashboard was qualitatively tested. Five hospital systems provided data for the predictive model prototype; three served as sites for testing and feedback on the dashboard design and usefulness. The participatory study design involved think-aloud methods as the clinician explored the dashboard. Individual interviews provided an understanding of clinician's perspective regarding ease of use and utility. RESULTS: Twenty-five clinicians were interviewed. Clinicians favored a dashboard gauge design composed of green, yellow, and red segments to depict MHAC risk associated with the removal of an indwelling urinary catheter to reduce CAUTI and possible adverse effects on HAPI and falls. CONCLUSION: Participants endorsed the utility of a visual dashboard guiding clinical decisions for MHAC risks preferring common stoplight color understanding. Clinicians did not want mandatory alerts for tool integration into the electronic health record. More research is needed to understand MHAC and tools to guide clinician decisions. Thieme. All rights reserved.
BACKGROUND: Hospital-acquired conditions (HACs) are common, costly, and national patient safety priority. Catheter-associated urinary tract infections (CAUTIs), hospital-acquired pressure injury (HAPI), and falls are common HACs. Clinicians assess each HAC risk independent of other conditions. Prevention strategies often focus on the reduction of a single HAC rather than considering how actions to prevent one condition could have unintended consequences for another HAC. OBJECTIVES: The objective of this study is to design an empirical framework to identify, assess, and quantify the risks of multiple HACs (MHACs) related to competing single-HAC interventions. METHODS: This study was an Institutional Review Board approved, and the proof of concept study evaluated MHAC Competing Risk Dashboard to enhance clinicians' management combining the risks of CAUTI, HAPI, and falls. The empirical model informing this study focused on the removal of an indwelling urinary catheter to reduce CAUTI, which may impact HAPI and falls. A multisite database was developed to understand and quantify competing risks of HACs; a predictive model dashboard was designed and clinical utility of a high-fidelity dashboard was qualitatively tested. Five hospital systems provided data for the predictive model prototype; three served as sites for testing and feedback on the dashboard design and usefulness. The participatory study design involved think-aloud methods as the clinician explored the dashboard. Individual interviews provided an understanding of clinician's perspective regarding ease of use and utility. RESULTS: Twenty-five clinicians were interviewed. Clinicians favored a dashboard gauge design composed of green, yellow, and red segments to depict MHAC risk associated with the removal of an indwelling urinary catheter to reduce CAUTI and possible adverse effects on HAPI and falls. CONCLUSION: Participants endorsed the utility of a visual dashboard guiding clinical decisions for MHAC risks preferring common stoplight color understanding. Clinicians did not want mandatory alerts for tool integration into the electronic health record. More research is needed to understand MHAC and tools to guide clinician decisions. Thieme. All rights reserved.
Authors: Alvin D Jeffery; Laurie L Novak; Betsy Kennedy; Mary S Dietrich; Lorraine C Mion Journal: J Am Med Inform Assoc Date: 2017-11-01 Impact factor: 4.497
Authors: Zachary Burningham; Regina Richter Lagha; Brittany Duford-Hutchinson; Carol Callaway-Lane; Brian C Sauer; Ahmad S Halwani; Jamie Bell; Tina Huynh; Joseph R Douglas; B Josea Kramer Journal: Appl Clin Inform Date: 2022-10-12 Impact factor: 2.762