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Aimn Abdujawad and Collaegues: A Quality Improvement Project to Optimize IVC Filter Use and Retrieval and Other More Projects at the ASH
Aimn Abdujawad/LinkedIn
Dec 9, 2025, 13:34

Aimn Abdujawad and Collaegues: A Quality Improvement Project to Optimize IVC Filter Use and Retrieval and Other More Projects at the ASH

Aimn Abdujawad, Quality Improvement Specialist at Ministry of National Guard Health Affairs (MNGHA), posted on LinkedIn:

“Under the leadership of Dr. Abdulrahman Al Raizah and with the support of our colleague Saad Alotaibi, our team has made significant progress in advancing quality improvement and patient safety. In one year, we are proud to share that four of our projects have been accepted as abstracts by the American Society of Hematology (ASH) and will be presented at the upcoming conference starting today till December 9, 2025:

  1. A quality improvement project to optimize IVC filter use and retrieval: Translating guidelines into practice
  2. A quality improvement project to optimize VTE prophylaxis in surgical patients
  3. A triple threat to diagnostic safety in CTPA: Diagnostic uncertainty, sspe, and reporting discrepancies
  4. Overcoming surveillance gaps: Deep learning for accurate detection and chronicity classification of hospital-acquired pulmonary embolism

Summary of Achievements:

  1. IVC filter project: Appropriateness of insertion improved from 72.7% to 91.4%; retrieval rates increased from 76% to 92.3%; median retrieval time reduced from 35 to 22 days.
  2. VTE prophylaxis project: Across 11,246 surgical inpatients, guideline-concordant prophylaxis improved from 37.8% to 54.8% (p < 0.0001). Since the time of abstract submission, compliance has continued to rise reaching 70% in November 2025, showing sustained improvement.
  3. CTPA diagnostic safety project: Review of 1,800 CTPA studies revealed diagnostic uncertainty in 2.1%, SSPE in 16.8% of PE-positive cases, and reporting discrepancies in 3.1% highlighting key risks to patient safety.
  4. AI surveillance project: Using 2,679 curated CTPA reports, the deep learning model achieved 99.47% accuracy for PE detection and 96.48% accuracy for acute/chronic classification, with only 2 false negatives in detection.

All of this couldn’t have been accomplished without the guidance and vision of Dr. Abdulrahman Al Raizah. I’m truly glad that we became a team in January of this year and know that this is only the beginning.

Here you may find the full abstracts:
IVC Filter project

VTE prophylaxis project

A triple threat to diagnostic safety in CTPA

AI surveillance project”

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Aimn Abdujawad American Society of Hematology (ASH) ASH2025 ASH25 Dr. Abdulrahman Al Raizah Health Hematology Hemostasis Hemostasis Today Medicine Ministry of National Guard Health Affairs (MNGHA) Patient Safety quality improvement Saad Alotaibi
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