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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 6 of 6 Research Studies DisplayedDesai S, Kapoor N, Hammer MM
RADAR: a closed-loop quality improvement initiative leveraging a safety net model for incidental pulmonary nodule management.
This study was conducted to assess whether patients with incidental pulmonary nodules (IPNs) received timely follow-up care after implementation of a quality improvement (QI) initiative between radiologists and primary care providers. A QI initiative, RADAR (Radiology Result Alert and Development of Automated Resolution), was implemented. Findings showed that the RADAR QI initiative was associated with increased timely IPN follow-up.
AHRQ-funded; HS024722.
Citation: Desai S, Kapoor N, Hammer MM .
RADAR: a closed-loop quality improvement initiative leveraging a safety net model for incidental pulmonary nodule management.
Jt Comm J Qual Patient Saf 2021 May;47(5):275-81. doi: 10.1016/j.jcjq.2020.12.006..
Keywords: Quality Improvement, Quality of Care, Diagnostic Safety and Quality, Imaging
Ray X, Bojechko C, Moore KL
Evaluating the sensitivity of Halcyon's automatic transit image acquisition for treatment error detection: a phantom study using static IMRT.
The Varian Halcyon electronic portal imaging detector is always in-line with the beam and automatically acquires transit images for every patient with full-field coverage. These images could be used for "every patient, every monitor unit" quality assurance (QA) and eventually adaptive radiotherapy. This study evaluated the imager's sensitivity to potential clinical errors and day-to-day variations from clinical exit images.
AHRQ-funded; HS025440.
Citation: Ray X, Bojechko C, Moore KL .
Evaluating the sensitivity of Halcyon's automatic transit image acquisition for treatment error detection: a phantom study using static IMRT.
J Appl Clin Med Phys 2019 Nov;20(11):131-43. doi: 10.1002/acm2.12749..
Keywords: Imaging, Quality of Care
Kang SK, Garry K, Chung R
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
The authors developed natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations using the electronic health records for patients who underwent chest CT before and after implementation of a department-wide dictation macro of the Fleischner Society recommendations. They concluded that NLP reliably automates identification of ILNs in unstructured reports, pertinent to quality improvement efforts for ILN management.
AHRQ-funded; HS024376.
Citation: Kang SK, Garry K, Chung R .
Natural language processing for identification of incidental pulmonary nodules in radiology reports.
J Am Coll Radiol 2019 Nov;16(11):1587-94. doi: 10.1016/j.jacr.2019.04.026..
Keywords: Imaging, Diagnostic Safety and Quality, Health Information Technology (HIT), Electronic Health Records (EHRs), Quality Improvement, Quality of Care
Cochon LR, Kapoor N, Carrodeguas E
Variation in follow-up imaging recommendations in radiology reports: patient, modality, and radiologist predictors.
The purpose of this study was to determine the incidence and to identify factors associated with follow-up recommendations in radiology reports from multiple modalities, patient care settings, and imaging divisions. A trained algorithm classified 318,366 report; the findings indicate that substantial interradiologist variation exists in the probability of recommending a follow-up examination in a radiology report.
AHRQ-funded; HS024722.
Citation: Cochon LR, Kapoor N, Carrodeguas E .
Variation in follow-up imaging recommendations in radiology reports: patient, modality, and radiologist predictors.
Radiology 2019 Jun;291(3):700-07. doi: 10.1148/radiol.2019182826..
Keywords: Shared Decision Making, Diagnostic Safety and Quality, Imaging, Patient Safety, Quality of Care, Quality Improvement
Kanzaria HK, Hall MK, Moore CL
Emergency department diagnostic imaging: the journey to quality.
The authors examine the current state of quality measurement as it pertains to ED imaging. They also review relevant policies and discuss both the associated challenges and the facilitators of using quality measures to help optimize ED imaging. Understanding such factors will help ensure the delivery of diagnostic imaging that is appropriate, high-quality, and patient-centered.
AHRQ-funded; HS023498.
Citation: Kanzaria HK, Hall MK, Moore CL .
Emergency department diagnostic imaging: the journey to quality.
Acad Emerg Med 2015 Dec;22(12):1380-4. doi: 10.1111/acem.12817.
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Keywords: Emergency Department, Imaging, Quality Indicators (QIs), Quality of Care
Ford E, Phillips M, Bojechko C
TU-G-BRD-08: in-vivo EPID dosimetry: quantifying the detectability of four classes of errors.
The researchers analyzed 17 patients; EPID images of the exit dose were acquired and used to reconstruct the planar dose at isocenter. Their data demonstrate the ability of EPID-based in-vivo dosimetry in detecting variations in patient habitus and errors related to machine parameters such as systematic multi-leaf collimator misalignments and machine output changes.
AHRQ-funded; HS022244.
Citation: Ford E, Phillips M, Bojechko C .
TU-G-BRD-08: in-vivo EPID dosimetry: quantifying the detectability of four classes of errors.
Med Phys 2015 Jun;42(6 Part 35):3629. doi: 10.1118/1.4925743..
Keywords: Patient Safety, Imaging, Quality of Care