The following article is the winning 2025 Richard Hader Visionary Leader Award entry submitted to Nursing Management in recognition of Ellie Jun, DNP, RN, CCRN, Director of Nursing at NewYork-Presbyterian Hospital in New York, NY.
The following article is the winning 2025 Richard Hader Visionary Leader Award entry submitted to Nursing Management in recognition of Ellie Jun, DNP, RN, CCRN, Director of Nursing at NewYork-Presbyterian Hospital in New York, NY.
The following article is the winning 2025 Richard Hader Visionary Leader Award entry submitted to Nursing Management in recognition of Ellie Jun, DNP, RN, CCRN, Director of Nursing at NewYork-Presbyterian Hospital in New York, NY.
Abstract: Telehealth is now integral to health care; however, billing and reimbursement remain inconsistent and inequitable for nurse practitioners and registered nurses. This article examines key challenges and highlights nurse managers' leadership in addressing coding confusion, regulatory risks, and reimbursement gaps through education, artificial intelligence integration, and policy advocacy to support care quality and revenue.
Background: Implementation research is focused on identifying barriers and facilitators to adopting evidence-based practices. Measuring pupil activity with a quantitative pupillometer (QP) has been repeatedly demonstrated to be a more evidence-based than subjective assessment of pupil reactivity. Yet, despite global availability, QP adoption is inconsistent. A possible influencing variable is documentation burden.
Purpose: The purpose of this study is to explore whether technology that provides for automated documentation is a facilitator for implementing QP.
Methods: This institutional review board-approved study explored data that were documented manually (manual cohort) and data that were directly uploaded into the electronic health record (automated-upload cohort). Compliance with the unit-based policy for pupil assessment was determined for each 4-hour period of time during the patient's stay in the intensive care unit.
Results: There were no significant demographic differences between the 122 manual-entry cohort and 229 automated-entry cohort patients. The mean compliance in the automated-entry cohort of 65.0% (95% CI: 61.6-68.4%) was significantly higher than the mean compliance in the manual-entry cohort (47.7% [95% CI: 43.7-51.8%]; t = -6.42, P < 0.0001).
Implications: A reduced documentation burden is associated with increased adoption of an evidence-based practice.

