scholarly journals Implementing Decision Coaching for Lung Cancer Screening in the Low-Dose Computed Tomography Setting

2020 ◽  
Vol 16 (8) ◽  
pp. e703-e725 ◽  
Author(s):  
Lisa M. Lowenstein ◽  
Myrna Cobos Barco Godoy ◽  
Jeremy J. Erasmus ◽  
Zineb Zirari ◽  
Alina Bennett ◽  
...  

PURPOSE: The uptake of shared decision making (SDM) for lung cancer screening (LCS) as required by the Centers for Medicare & Medicaid Services (CMS) is suboptimal. Alternative models for delivering SDM are needed, such as decision coaching in the low-dose computed tomography (LDCT) setting. METHODS AND MATERIALS: The Replicating Effective Programs framework guided our implementation of decision coaching, which included a patient-facilitated component before screening followed by in-person coaching that addressed the required elements for the SDM visit from CMS. We surveyed two LCS patient cohorts (pre-implementation and implementation of decision coaching) about their knowledge of LCS and perception of the SDM process. We conducted time-motion studies to assess the feasibility of implementing decision coaching and audio recorded clinical encounters from the implementation cohort to assess fidelity of the SDM conversation to the CMS requirements. RESULTS: Compared with the pre-implementation cohort (n = 51), the implementation cohort (n = 30) had greater knowledge of LCS ( P < .01) and reported a better SDM process ( P = .01). Coaching took 7.6 ± 4.1 minutes and did not increase visit time ( P = .72). Coaches addressed an average of 6.4 of 7 SDM elements required by CMS. CONCLUSION: Decision coaching in the LDCT setting provides an opportunity for patients to confirm their screening decision by ensuring that patients are truly informed about the potential harms and benefits of LCS. The decision coaching had excellent fidelity in addressing the required SDM elements from CMS and is feasible.

2019 ◽  
Vol 65 (2) ◽  
pp. 224-233
Author(s):  
Sergey Morozov ◽  
Viktor Gombolevskiy ◽  
Anton Vladzimirskiy ◽  
Albina Laypan ◽  
Pavel Kononets ◽  
...  

Study aim. To justify selective lung cancer screening via low-dose computed tomography and evaluate its effectiveness. Materials and methods. In 2017 we have concluded the baseline stage of “Lowdose computed tomography in Moscow for lung cancer screening (LDCT-MLCS)” trial. The trial included 10 outpatient clinics with 64-detector CT units (Toshiba Aquilion 64 and Toshiba CLX). Special low-dose protocols have been developed for each unit with maximum effective dose of 1 mSv (in accordance with the requirements of paragraph 2.2.1, Sanitary Regulations 2.6.1.1192-03). The study involved 5,310 patients (53% men, 47% women) aged 18-92 years (mean age 62 years). Diagnosis verification was carried out in the specialized medical organizations via consultations, additional instrumental, laboratory as well as pathohistological studies. The results were then entered into the “National Cancer Registry”. Results. 5310 patients (53% men, 47% women) aged 18 to 92 years (an average of 62 years) participated in the LDCT-MLCS. The final cohort was comprised of 4762 (89.6%) patients. We have detected 291 (6.1%) Lung-RADS 3 lesions, 228 (4.8%) Lung- RADS 4A lesions and 196 (4.1%) Lung-RADS 4B/4X lesions. All 4B and 4X lesions were routed in accordance with the project's methodology and legislative documents. Malignant neoplasms were verified in 84 cases (1.76% of the cohort). Stage I-II lung cancer was actively detected in 40.3% of these individuals. For the first time in the Russian Federation we have calculated the number needed to screen (NNS) to identify one lung cancer (NNS=57) and to detect one Stage I lung cancer (NNS=207). Conclusions. Based on the global experience and our own practices, we argue that selective LDCT is the most systematic solution to the problem of early-stage lung cancer screening.


2021 ◽  
Vol 16 (10) ◽  
pp. S1176
Author(s):  
L. Jungblut ◽  
J. Walter ◽  
C. Zellweger ◽  
M. Patella ◽  
D. Franzen ◽  
...  

2020 ◽  
Vol 135 ◽  
pp. 121-129 ◽  
Author(s):  
Yihui Du ◽  
Grigory Sidorenkov ◽  
Marjolein A. Heuvelmans ◽  
Harry J.M. Groen ◽  
Karin M. Vermeulen ◽  
...  

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