Defense Date

7-17-2025

Graduation Date

Summer 8-31-2025

Submission Type

Dissertation/Thesis

Degree Name

Doctor of Nurse Anesthesia Practice

Department

Doctor of Nurse Anesthesia Practice (DNAP) Program

School

School of Nursing

Faculty Mentor

Michael W. Neft

Committee Member

Erica Coffin

Committee Member

Matthew Caldwell

Keywords

post-dural puncture headache, unintentional dural puncture, obstetric anesthesia, obstetric analgesia, quality improvement, tracking tool

Abstract

Post-dural puncture headache (PDPH) is a debilitating complication following labor analgesia, often resulting from unintentional dural puncture (UDP). While national incidence is approximately 1.5%, institutional rates may vary due to provider experience, documentation practices, and patient factors. This Doctor of Nurse Anesthesia Practice (DNAP) quality improvement project aimed to improve identification and monitoring of UDP and PDPH through a revised tracking tool, retrospective review of 2024 data, and planning for an electronic registry. A multidisciplinary team of anesthesiologists, Certified Registered Nurse Anesthetists (CRNAs), Student Registered Nurse Anesthetists (SRNAs), and IT and quality specialists revised an existing tracking tool to better capture procedural and patient variables. A retrospective chart review was conducted on obstetric patients in 2024 who received neuraxial anesthesia and experienced UDP or PDPH. Data collected included provider experience, number of attempts, and patient demographics. Thirty-six patients were reviewed. UDP occurred in 17 (47%), and 14 (39%) required an epidural blood patch. Most cases involved two or more attempts, with higher complication rates in less experienced providers. The revised tool improved documentation quality and revealed the need for real-time data capture and electronic integration. This project enhanced awareness, improved documentation, and enabled meaningful trend analysis. Multiple attempts, provider inexperience, and patient-specific factors such as BMI were identified as risks. Future directions include transition to an Epic-based registry to automate data collection, supporting long-term sustainability and patient safety in obstetric anesthesia.

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