Essential Nurse Documentation: Studying EHR Burden during COVID-19 (ENDBurden)

PROJECT SUMMARY/ABSTRACT This mixed-methods informatics study employs a series of data science methods triangulating data from Interviews and EHR documentation, with the goal to identify essential documentation from the COVID-19 pandemic and reduce EHR burden. EHR burden for registered nurses has been demonstrated by increased documentation time, documentation amount, workload, and burnout and linkages to poor patient outcomes. Decreasing EHR burden is a national priority, yet, there is no clear evidence to differentiate which types of documentation are essential to support patient care. In recognizing the increased workload demands during the COVID-19 pandemic, New York issued orders that relaxed documentation requirements for clinicians, including nurses. Therefore, nurses' documentation during the pandemic in New York reflects the information deemed most essential by nurses - providing a unique and rare natural experiment to study documentation burden. On the contrary, Missouri ranked as the 18th highest state for COVID cases overall, and had no similar state orders. To advance the science, we will learn about nurses' documentation from a data science and informatics perspective, discover which documentation patterns (i.e., types, amount of data entry and viewing) are deemed essential by nurses, and examine documentation pattern changes overtime from before the pandemic through present day. We know that EHR burden exists, yet it is not understood which documentation patterns explain and influence the relationship between patient care activities and patient outcomes. We will use an EHR log-file time-based measure of patient care activities, operationalized as "total shift time" minus "time spent documenting patient care activities or viewing data". We will target respiratory care management for acute and critical care patients and also include delirium care management for critical care patients - applicable outcomes for both hospitalized COVID-19 and non-COVID-19 patients. The specific aims are to: Aim 1: Examine changes in the temporal trends of data entry and data viewing patterns of nursing documentation (e.g., types, amount) from 2019 through present day, inclusive of the COVID-19 pandemic timeline. Aim 2: Investigate how nurses define and decide what is essential to document for patient care and the impact of all-inclusive documentation (i.e., documentation that meets both clinical and regulatory demands) on EHR burden . Aim 3: Examine changes in data entry and data viewing patterns of nursing documentation and the impact of these changes on patient care activities and patient outcomes, while controlling for confounding factors related to workload, and nurse, patient, team, and organizational characteristics.