Emma Nodine

Daily Summaries 

Tuesday – 4/21/2026

On this day, I sorted through the Impression appointment outliers for both Dr. Zaleski and Dr. Leffert. For each outlier identified, I reviewed patient check-in times, appointment notes, and the schedule surrounding the appointment to assess whether late-running adjacent appointments, double-booking, or patient arrival lateness contributed to the extended duration. I also examined whether any additional procedures were completed that may have affected the timing. I organized the outlier appointments into 60-minute, 90-minute, and 120-minute duration categories to begin identifying which specific treatments within the Impression appointment type consistently require each length of time.

Thursday – 4/23/26

On this day, I continued the outlier analysis by sorting through the Restorative appointment category for both providers. I applied the same systematic review process, examining patient arrival times, appointment notes, and schedule context around each outlier to determine the cause of the extended appointment time. I organized the Restorative appointment outliers into the 60-minute, 90-minute, and 120-minute duration categories, as I had done for Impressions, to identify which specific treatments within the Restorative appointment type are associated with each time block. This categorization is helping to build a clearer and more detailed picture of how appointment time is actually being utilized across different procedure types and complexity levels.

Summary of Week 14 with Competencies 

• 4.3 Manage the collection and analysis of evaluation and/or research data using appropriate technology
  • 4.3.5 Prepare data for analysis
  • 4.3.6 Analyze data
  • This week, I continued systematically preparing and analyzing appointment timing data, focusing on the Impression and Restorative appointment categories. A key addition to the analytical framework this week was the organization of outlier appointments into 60-minute, 90-minute, and 120-minute duration categories. This additional layer of classification allowed for more granular analysis of how appointment time is being utilized within each procedure type and began revealing which specific treatments are driving longer appointment durations.
• 4.4 Interpret data
  • 4.4.1 Explain how findings address the questions and/or hypotheses
  • 4.4.4 Draw conclusions based on findings
  • 4.4.5 Identify implications for practice
  • By sorting outlier appointments into duration categories and connecting each to its contributing factors, I moved further into meaningful interpretation of the timing data. This process is beginning to generate actionable findings about which treatments within the Restorative and Impression categories require longer scheduling windows, directly addressing the project’s goal of improving appointment time allocation. These early conclusions have clear implications for how the clinic schedules specific procedure types going forward.
• 1.4 Synthesize assessment findings to inform the planning process
  • 1.4.4 Develop recommendations based on findings
  • The duration categorization work completed this week represents a significant step toward synthesizing the collected data into concrete scheduling recommendations. By identifying which treatments within each appointment category consistently require 60, 90, or 120 minutes, I am developing an evidence-based framework that can be translated directly into updated scheduling guidelines for the clinic’s providers.
• 2.4 Develop plans and materials for implementation and evaluation
  • 2.4.3 Address factors that influence implementation
  • As with previous weeks, the outlier analysis this week continued to surface the specific factors, including patient arrival lateness, schedule congestion, and procedural complexity, that influence how long appointments actually take. Documenting these factors across the Impression and Restorative categories adds to the growing body of evidence that will inform realistic and clinically grounded scheduling improvement recommendations.

Week 14 Reflection 

During my fourteenth week with the UGA UHC Dental Clinic, I worked through the Impression and Restorative appointment outliers for both providers, introducing a new layer of analysis by organizing outlier appointments into 60-minute, 90-minute, and 120-minute duration categories. Through this process, I learned that even within a single appointment type, the range of time required can vary significantly depending on the specific treatment being performed. Not all Restorative appointments, for example, are equal in complexity or time demand, and the current scheduling system does not always reflect those differences. Learning to differentiate within appointment categories, rather than treating them as uniform blocks, felt like an important methodological shift that will make the final recommendations more precise and effective.

This matters because vague scheduling recommendations are difficult to implement. Telling a clinic to “schedule more time for Restorative appointments” is far less actionable than being able to say which specific treatments within that category consistently require 90 minutes versus 60 minutes. The duration-category framework I developed this week moves the project toward that level of specificity, which is ultimately what will make the findings meaningful to providers and schedulers. It is also a reminder that in health promotion and public health work more broadly, the depth of your analysis directly shapes the quality of your recommendations. Surface-level findings lead to surface-level interventions, and this project is pushing me to think carefully about how to make data genuinely actionable.

I am completed with outlier analysis across all appointment categories, so I then synthesized all of the data I found (across all providers, appointment types, and contributing factors) into a cohesive set of scheduling recommendations. The recommendations were then communicated to clinical staff, Kristen, who is responsible for administrative leadership.