A leading oncology center in Poland partnered with Sqilline to tackle one of the most persistent challenges in lung cancer care: the time patients wait between diagnosis and immunotherapy. Using Sqilline’s Danny DataStruct & Danny Analytics tools, the center implemented a Patient Optimization Program (POP) that delivered measurable reductions across every stage of the NSCLC treatment pathway – from initial diagnostic workup through to first drug administration.

Key Summary

Objectives
  • Reduce waiting times across the full NSCLC care pathway for patients eligible for first-line immunotherapy treatment.
  • Accelerate the transition from diagnostic procedures to multidisciplinary team (MDT) decision-making.
  • Tighten the administrative gap between MDT decisions and treatment protocol assignment.
  • Shorten the interval between treatment protocol approval and actual drug administration.
  • Preserve or improve baseline patient performance status (ECOG) by initiating therapy earlier.
Challenges
  • In 2024, NSCLC patients at the center waited an average of 32 days from the start of diagnostic procedures to MDT decision – a window during which physical deterioration can compromise treatment eligibility and outcomes.
  • The average time from MDT decision to treatment protocol assignment, while shorter, still carried unnecessary administrative friction.
  • The longest bottleneck sat between treatment protocol approval and first drug administration, averaging 45 days in 2024 – meaning patients who had already been diagnosed and assigned a treatment plan still faced over six weeks before receiving their first dose administration.
  • These cumulative delays risked worsening patient ECOG performance status, reducing drug tolerance, increasing early toxicity-related drop-offs, and ultimately shortening overall therapy duration.
Solution

Sqilline deployed Danny Platform to provide the center with real-time visibility into patient flow across the entire treatment pathway. Through the Patient Optimization Program (POP), the clinical and administrative teams gained:

  • Continuous monitoring of waiting times at each stage of the pathway, broken down by quarter.
  • Data-driven identification of bottlenecks and process inefficiencies.
  • Actionable insights to streamline handoffs between diagnostic, MDT, protocol, and treatment administration stages.

Results

Stage 1: Diagnostic Procedures to MDT Decision

Average waiting time dropped from 32 days (2024) to 20 days (2025) – a 12-day reduction .

Quarterly breakdown:

The steepest improvement came in Q2 2025 (17.833 days), following the full rollout of the POP. While Q1 2025 still reflected transitional performance (26.75 days), the program delivered consistent sub 21-day averages from Q2 onward.

Stage 2: MDT Decision to Treatment Protocol

The POP program delivered a 2-day reduction in the time between MDT decision and drug prescription protocol.

Quarterly breakdown:

Stage2.1

This stage was already relatively lean, but the POP tightened administrative execution further, ensuring that expert clinical consensus translated into actionable patient care more rapidly. The Q4 2025 result of 5.259 days represents the best quarterly performance recorded.

Stage 3: Treatment Protocol to First Drug Administration

Average waiting time dropped from 45 days on average (2024) to 30 days on average (2025) – a 15-day reduction.

Quarterly breakdown:

This was the highest-impact reduction in the pathway. The 2024 data showed this segment consistently exceeding 40 days – and peaking at over 50 days in Q3 2024. Post-POP, no quarter in 2025 exceeded 30 days, with Q1 2025 delivering the best result at 26.125 days.

Benefits

  • Preserved patient performance status: A 12-day acceleration from diagnosis to MDT decision means patients begin therapy with a stronger baseline ECOG score, avoiding the physical deterioration that comes with prolonged diagnostic limbo.
  • Improved drug tolerance and therapy duration: Initiating immunotherapy earlier – while patients are in better physical condition – minimizes early toxicity-related drop-offs and extends the overall duration patients can remain on treatment.
  • Tighter administrative execution: The 2-day reduction in MDT-to-protocol time demonstrates that even well-functioning processes can be further optimized with the right data visibility.
  • Significant reduction in the longest bottleneck: Cutting 15 days from the protocol-to-administration gap directly addresses the most impactful delay in the pathway – the period where an approved treatment plan sits idle before the patient receives their first drug administration.
  • Ongoing optimization opportunity: While the results represent major progress, the remaining latency before first drug administration highlights continued opportunity for systemic improvement – a clear signal that data-driven pathway management is a continuous discipline, not a one-time fix.

This case study is based on real-world data from an active Sqilline deployment at a major oncology center in Poland, covering NSCLC patients treated with first-line immunotherapy. All data reflects quarterly averages from Q1 2024 through Q4 2025.