Work

Collaborative Solutions to Identify Scheduling Barriers for Timely Post-Hospital Discharge Primary Care Follow-Up: A Quality Improvement Initiative

Year: 2026

Type: article

Abstract: Background: Post-hospital discharge primary care follow-up visits are associated with lower readmissions but may be underutilized. Limited structured data exist on clinic-, PCP-, and patient-level barriers encountered during scheduling. Methods: We implemented a quality improvement (QI) initiative with hospital operations and scheduling teams. Schedulers used a new in-house Epic SmartForm to document real-time barriers when scheduling post-discharge PCP follow-up. The SmartForm was refined through Plan-Do-Study-Act (PDSA) cycles to improve usability, barrier classification, and data reliability. SmartForm data were reviewed with interdisciplinary teams to guide scheduling interventions. Results: From August 2022 through October 2024, schedulers documented 13,823 SmartForm notes for 13,420 patients. Barriers were documented in 4,024 notes (29%), with 2,896 barrier notations after excluding "reason not listed." The most common barriers were PCP availability constraints (46%), namely accommodation requests (30%); and patient-related reasons (42%), namely patients feeling the appointment was not needed (12%). These findings informed education on protected post-hospital follow-up slots and targeted outreach to clinic directors and staff. Discussion: Barrier identification gave leadership clearer visibility into why timely post-discharge PCP follow-up was not being scheduled. PCP availability barriers directly informed education on protected follow-up slots and clinic outreach when accommodations were needed. Patient-related barriers suggested a need for stronger communication during discharge planning. Conclusions: Embedding an in-house SmartForm within scheduler workflows and refining it through PDSA cycles enabled structured, real-time capture of scheduling barriers. Schedulers are key contributors to care transitions and systematic monitoring of barriers can support data-driven QI efforts to improve timely post-discharge PCP follow-up.

Source: Journal of Brown Hospital Medicine

DOI: 10.56305/001c.170605

Authors: Brian Le, Wendy Simon, Jessica Zhang, Jeri Robertson, Erin Dowling

Institution: UCLA Health

Language: English

Topic: Healthcare Operations and Scheduling Optimization

Subfield: Management Science and Operations Research

Field: Decision Sciences

Domain: Social Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W7225104863