| Autor: |
Collins S; Columbia University, Department of Biomedical Informatics, New York, NY.; Columbia University, School of Nursing, New York, NY., Couture B; Brigham and Women's Hospital, Boston, MA., Kang MJ; Brigham and Women's Hospital, Boston, MA.; Harvard Medical School, Boston, MA., Dykes P; Brigham and Women's Hospital, Boston, MA.; Harvard Medical School, Boston, MA., Schnock K; Brigham and Women's Hospital, Boston, MA.; Harvard Medical School, Boston, MA., Knaplund C; Columbia University, School of Nursing, New York, NY., Chang F; Brigham and Women's Hospital, Boston, MA., Cato K; Columbia University, School of Nursing, New York, NY. |
| Abstrakt: |
Documentation burden is a well-documented problem within healthcare, and improvement requires understanding of the scope and depth of the problem across domains. In this study we quantified documentation burden within EHR flowsheets, which are primarily used by nurses to document assessments and interventions. We found mean rates of 633-689 manual flowsheet data entries per 12-hour shift in the ICU and 631-875 manual flowsheet data entries per 12-hour shift in acute care, excluding device data. Automated streaming of device data only accounted for 5-20% of flowsheet data entries across our sample. Reported rates averaged to a nurse documenting 1 data point every 0.82-1.14 minutes, despite only a minimum data-set of required documentation. Increased automated device integration and novel approaches to decrease data capture burden (e.g., voice recognition), may increase nurses' available time for interpretation, annotation, and synthesis of patient data while also further advancing the richness of information within patient records. |
