SHM Converge Scientific Abstract ePoster Gallery-The Ai Rx for Documentation Dilemmas: A Prescription to Unlocking Productivity and Provider Satisfaction

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Northwell Health is New York State’s largest health care provider and private employer, serving communities through 23 hospitals and more than 700 outpatient facilities. Its mission is to improve community health by delivering high-quality care, educating health professionals, advancing biomedical research, promoting health education, and caring for all people regardless of ability to pay. Northwell also supports innovation through the Feinstein Institute for Medical Research, the Zucker School of Medicine, and Northwell Ventures.

The document describes a hospital medicine project titled <strong>“The AI Rx for Documentation Dilemmas: A Prescription to Unlocking Productivity and Provider Satisfaction.”</strong> The initiative used Northwell’s PHI-encrypted AI tool to generate discharge summaries quickly, improve documentation of diagnoses present on admission, and support more accurate coding within about a minute.

The project aimed to:
- reduce time spent on discharge paperwork,
- standardize discharge documentation,
- and improve capture of comorbidities and complications, including CCs and MCCs, to better reflect case mix index.

The rationale was that missed diagnoses in clinical documentation can lead to coding queries, inaccurate quality metrics, and financial and reputational harm. The team saw AI as a way to improve efficiency, reduce burnout, and enhance documentation quality, while still maintaining human review for accuracy.

Results showed strong provider satisfaction. Pre-implementation surveys found discharge paperwork was time consuming and limited patient care time. After implementation, nearly all respondents said the AI tool reduced documentation time. About 84% of providers used it for 75–100% of discharge notes. Nearly half reported fewer coder queries, while the other half saw no change. Capture of electrolyte abnormalities in documentation increased by 66% to 101% after rollout.

Next steps include expanding the tool to other departments and continuing to monitor outcomes.

Asset Subtitle

Lily L. Yung

Meta Tag

Author List Andre Reyes, Derek Lieberman, Lily L. Yung, Linda M. Kurian, Liron Sinvani, Michelle Loftus, Sri Nuvvula

Category Innovations

Concept AI-assisted Discharge Documentation Tool

Concept Human Oversight

Concept Diagnosis

Concept Comorbidity

Concept Complication

Distinguished Non-Finalist

Presenter Organization North Shore University Hospital, Northwell Health

Presenting Author Lily L. Yung

Track Technology in Hospital Medicine

Keywords

Northwell Health

AI documentation

discharge summaries

provider satisfaction

clinical coding

documentation efficiency

case mix index

coder queries

electronic health records

hospital medicine

AI-assisted Discharge Documentation Tool

Human Oversight

Diagnosis

Comorbidity

Complication