Date of Award

Winter 2024

Project Type

Clinical Doctorate

Department

Nursing

Program or Major

DNP

First Advisor

Cathleen Colleran

Second Advisor

Courtney Coffey

Abstract

BACKGROUND: A rural academic medical center child development clinic in New Hampshire experienced high volumes and inefficient workflows, causing delays in care. With a referral rate at 5-fold capacity, the need to create an efficient intake process that allowed for triage and data collection was apparent.

PURPOSE: Institute an integrated electronic new patient intake questionnaire (e-NPIQ) to improve work efficiency.

METHODS: A literature review on barriers and enablers for patient uptake of electronic questionnaires guided best practices for workflow redesign. The project instituted an integrated e-NPIQ while simultaneously creating a standardized new patient intake process. A mixed methods approach analyzed pre- and post-intervention cycle times and completion rates, and themes from clinician and staff interviews over a 6-month period.

RESULTS: While having inadequate data for statistical power, data sets suggest a clear difference between pre- and post-intervention cycle times and completion rates. The average completion rate more than doubled (22.78% to 47.7%), while the interval between referral and scheduling decreased by 40% (52.66 days before and 31.55 days after), representing a promising trend. Themes from semi-structured interviews revealed supportive themes around improved workflow and communication and disruptive themes around feelings of burnout and the process still being overly complicated.

CONCLUSIONS: There was improved clinic efficiency with a shortened duration between time of referral to time of scheduling, and an increased completion rate during the 2-month study period. The intervention likely contributed to these improvements, but ongoing data collection is necessary to see if the trend is sustained. Additional studies that evaluate project effectiveness over time to account for technological advancements, workforce changes, seasonal variability, patient demographics, and the impact of workflow changes on staff burnout are indicated.

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