[1] TRUE6 Consultation Analysis
This document presents the detailed analysis of intradepartmental consultations.
6.1 Anonymization Note
All analyses in this chapter use anonymized pathologist codes (P1, P2, …) derived from the mapping in data/config/name_mapping.csv; no raw names are displayed.
6.2 Network Analysis
Who consults whom? This section visualizes the flow of consultations between pathologists.
| Asker | Responder | Weight |
|---|---|---|
| P10 | P21 | 197 |
| P8 | P9 | 155 |
| P13 | P11 | 154 |
| P8 | P23 | 142 |
| P8 | P2 | 106 |
| P8 | P17 | 105 |
| P28 | P5 | 104 |
| P3 | P33 | 104 |
| P22 | P11 | 94 |
| P13 | P5 | 87 |
6.3 Temporal Trends
How has the volume of consultations changed over time? Tracking monthly volumes helps identify growth patterns, seasonal fluctuations, and the impact of departmental changes (e.g., new hires, digital pathology adoption).
6.4 Turnaround Time (TAT) Analysis
How long does it take to get a response? TAT is a key quality metric because delayed consultations can hold up final diagnoses and treatment decisions.
6.4.1 Distribution of Response Times
6.4.2 TAT by Responder
Which consultants respond the fastest?
6.5 Impact of Multiple Consultants
Does involving more consultants lead to longer response times?
6.5.1 Distribution of Consultants per Case
6.5.2 TAT vs Number of Consultants
Testing the assumption: “The more consultants, the longer the response time.”
6.6 Hourly Patterns
What time of day are consultations initiated and completed?
6.6.1 Consultation Initiation by Hour
6.6.2 Consultation Completion by Hour
6.6.3 TAT by Hour of Initiation
Do consultations initiated at certain times take longer?
6.7 Day of Week Analysis
How do consultation patterns vary by day of the week?
6.7.1 Volume by Day of Week
6.7.2 TAT by Day of Week
6.7.3 Weekend vs Weekday Comparison
| IsWeekend | Count | Median_TAT | Mean_TAT | SD_TAT |
|---|---|---|---|---|
| Weekday | 5081 | 2.70 | 9.04 | 14.86 |
| Weekend | 801 | 11.77 | 18.32 | 20.71 |
6.8 Seasonal Patterns
Are there monthly or seasonal trends in consultation activity? Seasonal variation may reflect vacation schedules, training cycles (new residents in July), or case-mix changes.
6.8.1 Monthly Volume with Trend
6.8.2 Monthly Median TAT
6.8.3 Seasonal Decomposition
Decomposing the time series into trend, seasonal, and irregular components:
6.8.4 By Calendar Month (Aggregated Across Years)
6.9 Time Series Forecasting Preview
Preview of consultation volume trend for forecasting:
6.10 Case Complexity: Multiple Consultations
Analysis of cases requiring multiple consultations:
6.10.1 Sequential vs Concurrent Consultations
| Type | Count | Percentage |
|---|---|---|
| Sequential | 162 | 12 |
| Concurrent (Parallel) | 1188 | 88 |
6.10.2 Consultation Chains
Cases with consultation sequences:
| Case_ID | n_consultants | Responders | Max_TAT_Hours |
|---|---|---|---|
| 54164-25 | 9 | P18 -> P8 -> P9 -> P4 -> P30 -> P28 -> P23 -> P11 -> P24 | 42.437500 |
| 63477-25 | 8 | P23 -> P24 -> P9 -> P18 -> P4 -> P11 -> P32 -> P30 | 25.444167 |
| 50945-25 | 8 | P8 -> P11 -> P23 -> P30 -> P18 -> P9 -> P4 -> P27 | 7.944444 |
| 10635-25 | 8 | P23 -> P27 -> P21 -> P2 -> P4 -> P28 -> P11 -> P9 | 7.751667 |
| 51203-25 | 7 | P18 -> P23 -> P30 -> P27 -> P11 -> P9 -> P28 | 77.898611 |
| 51972-24 | 7 | P2 -> P18 -> P21 -> P5 -> P4 -> P16 -> P23 | 37.213333 |
| 49732-25 | 7 | P11 -> P28 -> P4 -> P30 -> P18 -> P9 -> P23 | 30.102222 |
| 29241-23 | 7 | P11 -> P18 -> P5 -> P19 -> P2 -> P6 -> P9 | 25.453889 |
| 36989-22 | 7 | P1 -> P6 -> P13 -> P7 -> P33 -> P33 -> P3 -> P2 | 17.476111 |
| 29862-25 | 7 | P9 -> P23 -> P18 -> P5 -> P25 -> P28 -> P11 | 17.206944 |
6.10.3 Repeat Consultations: Same Responder Multiple Times
| Case_ID | Responder | n_times | First_Response | Last_Response |
|---|---|---|---|---|
| 40643-22 | P2 | 4 | 2022-11-07 18:50:50 | 2022-11-08 22:36:39 |
| 1135-23 | P5 | 3 | 2023-01-12 12:16:23 | 2023-01-17 14:11:34 |
| 36493-22 | P33 | 3 | 2022-10-10 12:30:57 | 2022-10-10 12:47:55 |
| 40542-22 | P2 | 3 | 2022-11-09 15:47:04 | 2022-11-14 17:19:11 |
| 42618-22 | P33 | 3 | 2022-11-24 14:52:56 | 2022-11-24 14:53:20 |
| 43465-23 | P17 | 3 | 2023-11-29 11:02:25 | 2023-12-05 11:31:12 |
| 44684-22 | P2 | 3 | 2022-12-05 14:21:01 | 2022-12-07 22:05:47 |
| 44684-22 | P6 | 3 | 2022-12-05 14:21:01 | 2022-12-07 23:08:19 |
| 46235-22 | P5 | 3 | 2022-12-19 09:26:28 | 2022-12-23 08:34:24 |
| 46300-22 | P5 | 3 | 2022-12-20 07:56:01 | 2022-12-21 12:32:24 |