# Leadership Lessons From a Quality Improvement Project to Decrease the Avoidable Days in the Hospital Related to Decision-Making Capacity

## TL;DR

This study shows how implementing a structured decision-making capacity assessment tool and leadership changes can reduce avoidable hospital days.

## Contribution

The study introduces a multifaceted intervention combining the U-CARE tool and leadership strategies to reduce avoidable hospital days.

## Key findings

- The U-CARE tool and bundled intervention were associated with a reduction in avoidable days.
- Leadership changes significantly impacted the outcomes of the quality improvement project.
- Many physicians lacked awareness and use of standardized capacity assessment tools prior to the intervention.

## Abstract

Introduction: Extended hospital stays drive up costs for patients, payors, and health systems. For this reason, it is crucial to minimize “avoidable days” (ADs), or delays to discharge after a patient is medically stable. Delays in determining decision-making capacity are a significant contributor to ADs. The present study implemented the U-CARE tool - a structured, evidence-informed capacity assessment instrument that provides a standardized framework for evaluating understanding, choice, appreciation, and reasoning. The tool requires brief clinician training and has been used in prior hospital-based quality improvement initiatives to improve consistency in capacity evaluations. We introduced U-CARE as part of a multifaceted bundled intervention to decrease ADs at a community hospital in Lebanon, Pennsylvania.

Methods: A quasi-experimental pre-post intervention study was conducted, involving a review of trends in ADs in pre- and post-intervention periods. ADs in the pre-intervention period were compared with ADs in the post-intervention period. There were three components of the multifaceted intervention. First, the quality improvement team including the co-authors of this article educated all attending physicians and residents on the use of the U-CARE assessment tool. Second, case managers performed weekly audits of patient charts and sent reminders about ADs to the hospitalist physician. Third, multidisciplinary rounds (MDR) included a scripted inquiry about ADs to prompt physicians to use the U-CARE tool.

Results: The pre-intervention survey had a response rate of 100% (n=32). Of note, 87.5% of respondents indicated that they are challenged with decision-making capacity evaluation on a patient. 61.5% were not utilizing any capacity assessment tool and 42.3% were not aware of the U-CARE tool for capacity evaluation. In response to inquiry about common reasons for ADs in patients needing capacity assessment, 48.2% indicated delays in psych consults, whereas 44.8% attributed it to not having a standardized process in place. The data on ADs was analyzed using the Statistical Process Control (SPC) Chart with the software JMP Pro 16 (JMP Statistical Discovery LLC, Cary, NC, USA). One-way ANOVA was performed to detect statistically significant (p value<0.05) differences in ADs between the three phases. Pre-intervention phase showed an average of 220 ADs per month.

Conclusions: The phase analysis on the SPC chart shows that leadership change had a significant association with the outcomes. Further research is needed to assess the efficacy of U-CARE tool implementation in reducing ADs and to elucidate the impact of leadership presence on successful implementation.