(CCSP005) IMPROVING CLINIC COORDINATION IN CARDIOLOGY: TACKLING INEFFICIENCIES OF RESOURCE ALLOCATION IN ONTARIO'S HEALTH CARE SYSTEM - A PILOT STUDY

Background: Sub-optimal resource allocation in the clinic setting can lead to prolonged wait times, physician burnout and inadequate patient outcomes. This quality improvement project, conducted at the Heart Function Clinic at Toronto General Hospital, aimed to identify contributors to inefficiencies in resource allocation and clinical coordination to foster greater understanding toward efficient and effective clinic workflow.

METHODS AND RESULTS: This mixed-methods study involved quantitative patient flow timing observations and qualitative semi-structured interviews. Observational data were collected by tracking patient journeys over 7 workdays, where each scheduled consultation indicated 1 journey. Collected time consumption data included scheduled appointment times and timings of patient activity, such as consultations and blood work. Unforeseen circumstances were documented to provide context. Semi-structured interviews were conducted with 5 types of stakeholders: physicians, nurses, administrative staff, clinic directors/managers, and patient advocates. Data saturation dictated the interview sample size. Statistical tests and graphical visualizations were used to analyze the quantitative data, and thematic analysis was used to better characterize patient journeys and problems from the qualitative data.

In total, we collected 180 patient journeys and 9 semi-structured interviews. Results of the combined data suggests that patient care consists of 7 main areas: referral triage, booking/scheduling, check-in/front-desk, physician consultation, general tests including blood work and electrocardiogram, check-out, and overall considerations. Time consumption revealed how trainee presence increased patient time while decreasing physician time, and graphed to check-in time, time consumption peaked around mid-clinic workday. Additionally, we identified specific challenges in the clinic, including delays in digital communication and staff feeling overwhelmed by excessive responsibilities due to unclear delegation. Finally, staff-to-physician ratio, use of digital technology, patient volume, physician availability, number of components within a visit, and appointment type such as new or follow-up were contextual variables found to influence the overall clinic flow and time consumption.

Conclusion: Integrated observational and interview data revealed complex relationships between time consumption, patient care variables, and contextual variables. These findings highlight the importance of data-informed decision-making for effective clinic coordination and prioritization. Enhanced understanding of time consumption and underlying causes improves decision-making, resulting in more efficiency and resource allocation, positively influencing staff workload, satisfaction, clinic flow, and patient experience.