Reducing Wait Time for Lung Cancer Diagnosis and Treatment: Impact of a Multidisciplinary, Centralized Referral Program

2018 ◽  
Vol 69 (3) ◽  
pp. 322-327 ◽  
Author(s):  
Jessica L. Common ◽  
Hensley H. Mariathas ◽  
Kaylah Parsons ◽  
Jonathan D. Greenland ◽  
Scott Harris ◽  
...  

Background A multidisciplinary, centralized referral program was established at our institution in 2014 to reduce delays in lung cancer diagnosis and treatment following diagnostic imaging observed with the traditional, primary care provider–led referral process. The main objectives of this retrospective cohort study were to determine if referral to a Thoracic Triage Panel (TTP): 1) expedites lung cancer diagnosis and treatment initiation; and 2) leads to more appropriate specialist consultation. Methods Patients with a diagnosis of lung cancer and initial diagnostic imaging between March 1, 2015, and February 29, 2016, at a Memorial University–affiliated tertiary care centre in St John's, Newfoundland, were identified and grouped according to whether they were referred to the TTP or managed through a traditional referral process. Wait times (in days) from first abnormal imaging to biopsy and treatment initiation were recorded. Statistical analysis was performed using the Wilcoxon rank-sum test. Results A total of 133 patients who met inclusion criteria were identified. Seventy-nine patients were referred to the TTP and 54 were managed by traditional means. There was a statistically significant reduction in median wait times for patients referred to the TTP. Wait time from first abnormal imaging to biopsy decreased from 61.5 to 36.0 days ( P < .0001). Wait time from first abnormal imaging to treatment initiation decreased from 118.0 to 80.0 days ( P < .001). The percentage of specialist consultations that led to treatment was also greater for patients referred to the TTP. Conclusions A collaborative, centralized intake and referral program helps to reduce wait time for diagnosis and treatment of lung cancer.

Lung Cancer ◽  
2021 ◽  
Vol 156 ◽  
pp. S48-S49
Author(s):  
Sarah Booth ◽  
Patrick Grove ◽  
Stephanie Davies ◽  
Shahul Leyakathali khan

Biochimie ◽  
2018 ◽  
Vol 151 ◽  
pp. 27-36 ◽  
Author(s):  
Christos Masaoutis ◽  
Chrysovalantou Mihailidou ◽  
Gerasimos Tsourouflis ◽  
Stamatios Theocharis

2006 ◽  
Vol 11 (1) ◽  
pp. 9-12 ◽  
Author(s):  
Tatsuo Ohira ◽  
Yasuhiro Suga ◽  
Yoshitaka Nagatsuka ◽  
Jitsuo Usuda ◽  
Masahiro Tsuboi ◽  
...  

2015 ◽  
Vol 66 (1) ◽  
pp. 53-57 ◽  
Author(s):  
Suzanne C. Byrne ◽  
Brendan Barrett ◽  
Rick Bhatia

Objective This study was performed to determine whether gaps in patient flow from initial lung imaging to computed tomography (CT) guided lung biopsy in patients with non–small cell lung cancer (NSCLC) was associated with a change in tumour size, stage, and thus prognosis. Methods All patients who had a CT-guided lung biopsy in 2009 (phase I) and in 2011 (phase II) with a pathologic diagnosis of primary lung cancer (NSCLC) at Eastern Health, Newfoundland, were identified. Dates of initial abnormal imaging, confirmatory CT (if performed), and CT-guided biopsy were recorded, along with tumour size and resulting T stage at each time point. In 2010, wait times for diagnostic imaging at Eastern Health were reduced. The stage and prognosis of NSCLC in 2009 was compared with 2011. Results In phase 1, there was a statistically significant increase in tumour size (mean difference, 0.67 cm; P < .0001) and stage ( P < .0001) from initial image to biopsy. There was a moderate correlation between the time (in days) between the images and change in size ( r = 0.33, P = .008) or stage ( r = 0.26, P = .036). In phase II, the median wait time from initial imaging to confirmatory CT was reduced to 7.5 days (from 19 days). At this reduced wait time, there was no statistically significant increase in tumour size (mean difference, 0.02; P > .05) or stage ( P > .05) from initial imaging to confirmatory CT. Conclusions Delays in patient flow through diagnostic imaging resulted in an increase in tumour size and stage, with a negative impact on prognosis of NSCLC. This information contributed to the hiring of additional CT technologists and extended CT hours to decrease the wait time for diagnostic imaging. With reduced wait times, the prognosis of NSCLC was not adversely impacted as patients navigated through diagnostic imaging.


2021 ◽  
Vol 16 (10) ◽  
pp. S1053
Author(s):  
G. Kasymjanova ◽  
A. Anwar ◽  
L. Sakr ◽  
V. Cohen ◽  
D. Small ◽  
...  

Author(s):  
Anna Fry ◽  
Isabella Careniro ◽  
David Kennedy ◽  
Abigail Bentley ◽  
Gemma Luck ◽  
...  

ABSTRACT ObjectivesTo link the Diagnostic Imaging Dataset (DID) to cancer registration records to allow investigation of imaging performed in patients diagnosed with cancer and its relation to patient pathways and outcomes for lung and ovarian cancer patients diagnosed in England in 2013. ApproachAll available DID data from April 2012 until July 2015 were joined with registry data for all patients diagnosed with lung cancer in 2013, extracted from Public Health England’s tumour-level cancer records. Records were joined on NHS number and date of birth for individuals aged 15-99, with a non-provisional tumour record and with only one lung cancer diagnosis. One tumour can be linked to many imaging records. Because DID data are not limited to cancer-associated imaging, variables were created to flag imaging records that are likely to be related to the lung cancer diagnosis. Lists of imaging procedure (SNOMED) codes considered to be related to the cancer diagnosis were created in consultation with clinicians. Imaging records that took place in the 3 months prior to diagnosis and were on the list of relevant procedure codes were flagged as relevant records. The same method was replicated for ovarian cancer. Results34,780 patients, each with only one lung tumour diagnosed in 2013, were joined with 502,600 DID records. The aforementioned flagging procedure resulted in 52,429 relevant DID records. 5,911 patients, each with only one ovarian tumour diagnosed in 2013, were joined with 74,425 DID records. The aforementioned flagging procedure resulted in 3,830 relevant DID records. The resulting linkage has highlighted issues with potential missing imaging data and this is being explored and will be reported upon. ConclusionThis is the first time linkage of DID and cancer registration data has taken place. The newly linked dataset will enable researchers to explore the imaging dataset further, with the potential to deepen understanding of issues such as imaging usage and intervals in imaging delivery. Funding sourcesCancer Research UK.


2017 ◽  
Vol 17 (1) ◽  
Author(s):  
Nicole Ezer ◽  
Asma Navasakulpong ◽  
Kevin Schwartzman ◽  
Linda Ofiara ◽  
Anne V. Gonzalez

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