Experimental development of IT decision support solution for accurate and consistent Clinical Practice Guidelines (CPGs) in Cancer Real-World Practice

Clinical Practice Guidelines’ (CPGs) adherence supports high-quality care. However, healthcare providers do not always comply with CPGs recommendations. Despite the availability of CPGs with different presentation formats, a constant production or updating process, their uptake, adherence, or compliance by healthcare providers is variable, and sometimes reported as suboptimal. For example, it has been estimated that only 50% of patients in the United States receive CPGs-compliant healthcare.1 On the other hand, the proof of a positive relationship of guideline adherence and survival seems to be more complex than understood so far.2

There is growing evidence that cancer care is not connected because currently, variability in cancer care exists at every level: country, region, and hospital.

Breast cancer survival has improved with significant progress in treatment and disease management. However, compliance with treatment varies. Treatment noncompliance was associated with worse overall survival for surgery, chemotherapy, radiotherapy, and endocrine therapy. Worse survival was similarly observed in older patients for whom guidelines generally do not apply. Results highlight the importance of following appropriate treatment as recommended by current guidelines.3

A substantial proportion of breast cancer patients appear not to be receiving CPGs-recommended care. Aligning healthcare provider’s decisions with breast cancer CPGs recommendations in European countries should be improved for almost all processes of care, especially for preventive therapies and follow-up. Knowing the reasons for non-compliance is essential to understand these deviations. The development and implementation of CPGs for breast cancer patients should address relevant patient-related factors to enhance the applicability of CPGs in clinical care.4

The development of IT decision support solution for accurate and CPGs in cancer real-world practice could empower healthcare professionals to provide the best available clinical care through CPGs, based on real world data analyses, performed by ML algorithms for data structuring.

As part of our core-engine Danny Platform, Sqilline has developed artificial intelligence (AI)-based Decision support Application (DSA) integrated with clinical practice guidelines (ESMO) in the treatment of breast and prostate cancer. The DSA will establish a CPG gap-filling mechanism for patient-individual care path optimization. The innovative application inferences in terms of edges (association between cancer therapy and clinical guidelines) and nodes (oncology knowledge) to explore new therapeutic approaches in breast and prostate cancer. The project “Experimental development for creation of decision support application (Danny DSA) for breast and prostate cancer care”, promoted by Sqilline, was approved for funding by Norwegian Financial Mechanism 2014-2021, Programme Business Development, Innovation and SMEs, Bulgaria.

The value chain supported by Danny DSA brings certain benefits, such as aiding clinicians’ adherence to CPGs for therapeutic decisions, which could positively impact clinical outcomes and healthcare costs. Additionally, it leverages evidence from real-world data (Electronic Health Records, EHRs) to bridge existing discrepancies and gaps in CPGs and to overcome any weaknesses in their content. Moreover, it addresses patients’ timely information needs at the point of care, which is crucial in the rapidly evolving, complex decision-making process in cancer treatment. Lastly, it offers insights into novel, effective, and safer potential drug treatments for cancer.

Danny DSA empowers key stakeholders in healthcare to turn medical real-world data into practical insights supporting decision making on different levels across the system.

The implementation of Danny DSA is expected to have a significant impact on each healthcare system. Our software solution enables the tracking of Clinical Practice Guidelines (CPGs), ensuring deeper analysis regarding adherence to guidelines approved by authorities and the outcomes of their implementation. This will streamline patient care pathways, ensuring personalized treatments for enhanced outcomes. Clinicians will gain from improved therapeutic decision-making, leading to improved patient care and cost savings.

Furthermore, the Decision Support Application will catalyze innovation in cancer drug development, providing invaluable insights for future treatments. Its adoption across European Government Healthcare Systems will lead to systemic improvements, benefiting patients and healthcare systems.


1 McGlynn EA, Asch SM, Adams J, Keesey J, Hicks J, DeCristofaro A, et al. The quality of health care delivered to adults in the United States. N Engl J Med. 2003;348(26):2635–2645.

2 Jacke et al. The adherence paradox: guideline deviations contribute to the increased 5-year survival of breast cancer patients. BMC Cancer (2015) 15:734

3 Ho, Peh Joo et al. “Impact of deviation from guideline recommended treatment on breast cancer survival in Asia.” Scientific reports vol. 10,1 1330. 28 Jan. 2020

4 Niño de Guzmán, E., Song, Y., Alonso-Coello, P. et al. Healthcare providers’ adherence to breast cancer guidelines in Europe: a systematic literature review. Breast Cancer Res Treat 181, 499–518 (2020).

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