Real Impact in Oncology Care
See how leading oncology departments use Dashamlav to improve clinical efficiency, patient outcomes, and care delivery through intelligent automation
Reducing DIBH Assessment from 3 Days to 1 with Machine Learning
Predictive analytics streamline breast cancer treatment eligibility
The Challenge
Deep Inspiration Breath Hold (DIBH) reduces cardiac radiation exposure in left-sided breast cancer patients. However, traditional eligibility assessment required three consecutive days of coaching and testing—creating patient burden and capacity constraints.
Patients traveling from rural areas made multiple trips before treatment could begin. Clinical resources were tied up in assessments, and eligible candidates faced delays or were turned away due to scheduling constraints.
The Solution
The department had prospectively captured respiratory parameters in OncFlow for years. Using this structured dataset, they developed a machine learning model that predicts DIBH eligibility from a single coaching session.
New workflow:
- Single DIBH coaching session captures respiratory data
- OncFlow model predicts eligibility likelihood
- Clinicians review prediction alongside clinical judgment
- Immediate decision: proceed with DIBH or provide additional coaching
Day 1 eligibility decisions eliminate two assessment visits
Lower travel costs and less time away from family during treatment
Freed resources allow more DIBH-eligible patients to be treated
Key Takeaway
Prospective data collection in OncFlow enabled machine learning innovation. The model seamlessly integrates into clinical workflow—clinicians don’t need new systems or added administrative burden. This same methodology scales to other treatment selection challenges across oncology subspecialties.
Transforming Practice Analytics: From Hours to Minutes
Instant clinical insights enable quality improvement, research, and benchmarking
The Challenge
Oncology departments regularly need to analyze practice patterns for conference presentations, quality improvement initiatives, regulatory reporting, institutional benchmarking, and research protocols.
Traditional approaches created significant friction. Physicians manually reviewed charts or navigated disconnected EMR screens to extract data. A single query—”How many left-sided breast cancer patients received internal mammary chain radiation last year?”—could require hours of chart review.
Staff time spent on retrospective data extraction was time taken away from patient care. The burden discouraged physicians from asking questions that could improve clinical practice, simply because retrieving answers was too time-consuming.
The Solution
Instead of documenting in fragmented systems, the department systematically captured structured data in OncFlow during routine workflows. Clinical data became queryable, structured information from the moment it was entered.
OncFlow’s analytics module enables direct queries without IT support:
When preparing a conference presentation on breast cancer radiotherapy, a physician needed patient counts, technique distributions, treatment volumes, and IMC field percentages. The analytics module generated comprehensive answers in 25-30 minutes—including presentation-ready visualizations.
This same capability serves multiple recurring needs: quality improvement tracking, research cohort identification, regulatory reporting, peer benchmarking, and educational presentations.
Complex practice queries that required 4-8 hours of manual review now resolve in 20-30 minutes
When answering questions becomes effortless, physicians ask more—driving continuous quality improvement
Conference deadlines, audits, and benchmarking requests that took days now receive responses within hours
Key Takeaway
Prospective structured data capture transforms documentation from administrative burden to strategic asset. When physicians document care in structured formats during routine workflows, they build a continuously growing clinical database they can interrogate on demand. This fundamentally changes the relationship between documentation and insight—instead of data extraction being a barrier to clinical inquiry, it becomes instantaneous, enabling the continuous practice examination that drives quality improvement.
Transform Your Oncology Workflows
See how Dashamlav can help your department achieve similar results