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RADAR: A Closed-Loop Quality Improvement Initiative Leveraging A Safety Net Model for Incidental Pulmonary Nodule
The RADAR quality improvement initiative significantly improved timely follow-up for incidental pulmonary nodules (IPNs). This electronic alert and care coordination system enhanced patient care pathways for lung nodule management.
Area of Science:
- Medical Informatics
- Radiology
- Quality Improvement in Healthcare
Background:
- Incidental pulmonary nodules (IPNs) require timely follow-up to ensure appropriate patient management.
- Variability in follow-up care for IPNs can lead to delayed diagnosis and treatment.
- A quality improvement (QI) initiative was implemented to address challenges in IPN follow-up.
Purpose of the Study:
- To evaluate the effectiveness of the RADAR (Radiology Result Alert and Development of Automated Resolution) QI initiative.
- To assess whether patients with IPNs received timely follow-up care post-QI implementation.
- To compare the rates of timely IPN follow-up before and after the QI intervention.
Main Methods:
- A QI study was conducted at an academic medical center, analyzing IPNs identified on chest imaging between February 2017 and March 2019.
- The RADAR initiative, implemented in March 2018, included an electronic alert system for radiologists and a care coordination team.
- Pre- and post-intervention cohorts were established using natural language processing and manual chart review to determine timely follow-up rates.
Main Results:
- Timely follow-up for IPNs increased significantly from 64.5% in the pre-intervention cohort to 84.3% in the post-intervention cohort (p=0.001).
- The study assessed 110 IPN alerts pre-intervention and 108 post-intervention.
- Post-intervention, agreement between primary care providers (PCPs) and radiologists on the follow-up plan was high at 87.0%.
Conclusions:
- The RADAR QI initiative demonstrated a positive impact on increasing timely follow-up for incidental pulmonary nodules.
- The safety net model employed by RADAR shows potential for broader application to other radiology findings.
- This approach can be scaled to various clinical settings to improve care coordination and patient outcomes.
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