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Capturing Pathology Workload Required for a Precision Oncology Molecular Test (POMT)
Background
Precision oncology has made nextgeneration sequencing a part of daily practice. With indications for comprehensive genomic profiling expanding, there will be further attendant increases in pathology workload. The pathology workforce shortage is one of the greatest barriers to precision oncology and an understanding of pathology workload associated with POMTs is necessary to address this barrier and plan for the future.
Methods
In this presentation we aim to provide, or at least contribute to, such an understanding through a review of the process at our site and measurement of associated time for each step. We began by conceptualizing the process in order to develop a process map. We then measured the average time for each step. We reviewed our anatomic pathology records for 2021 to determine the number of POMTs then calculated cumulative time investment on POMTs. A theoretical number of relative value units (RVUs) for POMTs was calculated using the new pathology clinical consultation CPT codes (80503-80506), and this was compared to the total anatomic pathology RVUs actually generated in 2021.
Results
Of the 7007 anatomic pathology cases, there were 706 cancers and 446 that required POMTs. At our institution, it was determined that on average 1.5 hours – about 50 minutes of pathologist time and 40 minutes of technician time – was needed to complete the tasks necessary to fulfillment of requests for POMTs. For all of 2021, 669 hours of pathology staff time were dedicated to POMTs. With the ability to bill for this time, we would have generated 13.2% (1142/8640) more anatomic pathology RVUs.
Conculsions
In light of this, we have implemented measures to bill for these formerly uncaptured activities such that our documented productivity more accurately reflects our workload. This will hopefully result in more appropriate resource allocation such that the barrier created by pathology understaffing is recast as a buttress in support of precision oncology practice.
Background
Precision oncology has made nextgeneration sequencing a part of daily practice. With indications for comprehensive genomic profiling expanding, there will be further attendant increases in pathology workload. The pathology workforce shortage is one of the greatest barriers to precision oncology and an understanding of pathology workload associated with POMTs is necessary to address this barrier and plan for the future.
Methods
In this presentation we aim to provide, or at least contribute to, such an understanding through a review of the process at our site and measurement of associated time for each step. We began by conceptualizing the process in order to develop a process map. We then measured the average time for each step. We reviewed our anatomic pathology records for 2021 to determine the number of POMTs then calculated cumulative time investment on POMTs. A theoretical number of relative value units (RVUs) for POMTs was calculated using the new pathology clinical consultation CPT codes (80503-80506), and this was compared to the total anatomic pathology RVUs actually generated in 2021.
Results
Of the 7007 anatomic pathology cases, there were 706 cancers and 446 that required POMTs. At our institution, it was determined that on average 1.5 hours – about 50 minutes of pathologist time and 40 minutes of technician time – was needed to complete the tasks necessary to fulfillment of requests for POMTs. For all of 2021, 669 hours of pathology staff time were dedicated to POMTs. With the ability to bill for this time, we would have generated 13.2% (1142/8640) more anatomic pathology RVUs.
Conculsions
In light of this, we have implemented measures to bill for these formerly uncaptured activities such that our documented productivity more accurately reflects our workload. This will hopefully result in more appropriate resource allocation such that the barrier created by pathology understaffing is recast as a buttress in support of precision oncology practice.
Background
Precision oncology has made nextgeneration sequencing a part of daily practice. With indications for comprehensive genomic profiling expanding, there will be further attendant increases in pathology workload. The pathology workforce shortage is one of the greatest barriers to precision oncology and an understanding of pathology workload associated with POMTs is necessary to address this barrier and plan for the future.
Methods
In this presentation we aim to provide, or at least contribute to, such an understanding through a review of the process at our site and measurement of associated time for each step. We began by conceptualizing the process in order to develop a process map. We then measured the average time for each step. We reviewed our anatomic pathology records for 2021 to determine the number of POMTs then calculated cumulative time investment on POMTs. A theoretical number of relative value units (RVUs) for POMTs was calculated using the new pathology clinical consultation CPT codes (80503-80506), and this was compared to the total anatomic pathology RVUs actually generated in 2021.
Results
Of the 7007 anatomic pathology cases, there were 706 cancers and 446 that required POMTs. At our institution, it was determined that on average 1.5 hours – about 50 minutes of pathologist time and 40 minutes of technician time – was needed to complete the tasks necessary to fulfillment of requests for POMTs. For all of 2021, 669 hours of pathology staff time were dedicated to POMTs. With the ability to bill for this time, we would have generated 13.2% (1142/8640) more anatomic pathology RVUs.
Conculsions
In light of this, we have implemented measures to bill for these formerly uncaptured activities such that our documented productivity more accurately reflects our workload. This will hopefully result in more appropriate resource allocation such that the barrier created by pathology understaffing is recast as a buttress in support of precision oncology practice.
Identification of Clinically Actionable Genomic Alterations in Colorectal Cancer Patients From the VA National Precision Oncology Program (NPOP)
Purpose
Colorectal cancer (CRC) is the fourth most common cancer at VA and the third leading cause of cancer-related death in the USA. The VA National Precision Oncology Program (NPOP) was established in 2016 with the goal of implementing standardized, streamlined methods for molecular testing of veterans with cancer and has enabled comprehensive genomic profiling (CGP) and precision medicine as part of routine cancer care. Obtaining CGP of predictive biomarkers in cancer tissue, including mutations in genes (e.g., KRAS, NRAS and BRAF), tumor mutation burden (TMB) and microsatellite instability status (MSI) can be used to support treatment decisions with targeted and immunotherapies.
Methods
In this study we describe the frequencies of these clinical biomarkers in colon adenocarcinoma (COAD), rectal adenocarcinoma (READ), and other colon or rectum histologies (CROT); and compare these frequencies to a published cohort of metastatic CRC using Chi-square test (Yaeger et al., 2018).
Results
A total of 1802 patients with CRC were included in this study. COAD was the most frequent disease site (76.9%) followed by READ (19.1%). Approximately 52.9% of COAD patients harbored at least one highly actionable biomarker (defined as having an FDA-approved indication) including NRAS/ KRAS/BRAF wildtype (38.0%), TMB-H (12.9%), BRAF V600E (9.7%), MSI-H (8.9%), and NTRK fusion or rearrangement (0.3%). About 52.0% of patients with READ had these biomarkers, while this rate was (16.4%) in CROT. Among patients with COAD and READ, those with BRAF V600E mutations were more likely to be older, White, not Hispanic or Latino, and lived in urban areas compared to those without BRAF V600E. Relative to those with NRAS/KRAS/BRAF mutations, patients with NRAS/KRAS/BRAF wildtype were frequently younger. Relative to the frequency of biomarkers from a cBioPortal cohort of metastatic CRC, the frequency of NRAS wildtype was significantly lower in patients with COAD and READ tested through NPOP.
Consulsions
In this cohort, ~53 % of patients with COAD and 52% of patients with READ have highly actionable biomarkers and are potentially eligible for FDAapproved targeted therapies. Future studies examining cancer outcomes with regard to the use of targeted therapies in the setting of actionable gene alterations, TMB, and MSI are warranted.
Purpose
Colorectal cancer (CRC) is the fourth most common cancer at VA and the third leading cause of cancer-related death in the USA. The VA National Precision Oncology Program (NPOP) was established in 2016 with the goal of implementing standardized, streamlined methods for molecular testing of veterans with cancer and has enabled comprehensive genomic profiling (CGP) and precision medicine as part of routine cancer care. Obtaining CGP of predictive biomarkers in cancer tissue, including mutations in genes (e.g., KRAS, NRAS and BRAF), tumor mutation burden (TMB) and microsatellite instability status (MSI) can be used to support treatment decisions with targeted and immunotherapies.
Methods
In this study we describe the frequencies of these clinical biomarkers in colon adenocarcinoma (COAD), rectal adenocarcinoma (READ), and other colon or rectum histologies (CROT); and compare these frequencies to a published cohort of metastatic CRC using Chi-square test (Yaeger et al., 2018).
Results
A total of 1802 patients with CRC were included in this study. COAD was the most frequent disease site (76.9%) followed by READ (19.1%). Approximately 52.9% of COAD patients harbored at least one highly actionable biomarker (defined as having an FDA-approved indication) including NRAS/ KRAS/BRAF wildtype (38.0%), TMB-H (12.9%), BRAF V600E (9.7%), MSI-H (8.9%), and NTRK fusion or rearrangement (0.3%). About 52.0% of patients with READ had these biomarkers, while this rate was (16.4%) in CROT. Among patients with COAD and READ, those with BRAF V600E mutations were more likely to be older, White, not Hispanic or Latino, and lived in urban areas compared to those without BRAF V600E. Relative to those with NRAS/KRAS/BRAF mutations, patients with NRAS/KRAS/BRAF wildtype were frequently younger. Relative to the frequency of biomarkers from a cBioPortal cohort of metastatic CRC, the frequency of NRAS wildtype was significantly lower in patients with COAD and READ tested through NPOP.
Consulsions
In this cohort, ~53 % of patients with COAD and 52% of patients with READ have highly actionable biomarkers and are potentially eligible for FDAapproved targeted therapies. Future studies examining cancer outcomes with regard to the use of targeted therapies in the setting of actionable gene alterations, TMB, and MSI are warranted.
Purpose
Colorectal cancer (CRC) is the fourth most common cancer at VA and the third leading cause of cancer-related death in the USA. The VA National Precision Oncology Program (NPOP) was established in 2016 with the goal of implementing standardized, streamlined methods for molecular testing of veterans with cancer and has enabled comprehensive genomic profiling (CGP) and precision medicine as part of routine cancer care. Obtaining CGP of predictive biomarkers in cancer tissue, including mutations in genes (e.g., KRAS, NRAS and BRAF), tumor mutation burden (TMB) and microsatellite instability status (MSI) can be used to support treatment decisions with targeted and immunotherapies.
Methods
In this study we describe the frequencies of these clinical biomarkers in colon adenocarcinoma (COAD), rectal adenocarcinoma (READ), and other colon or rectum histologies (CROT); and compare these frequencies to a published cohort of metastatic CRC using Chi-square test (Yaeger et al., 2018).
Results
A total of 1802 patients with CRC were included in this study. COAD was the most frequent disease site (76.9%) followed by READ (19.1%). Approximately 52.9% of COAD patients harbored at least one highly actionable biomarker (defined as having an FDA-approved indication) including NRAS/ KRAS/BRAF wildtype (38.0%), TMB-H (12.9%), BRAF V600E (9.7%), MSI-H (8.9%), and NTRK fusion or rearrangement (0.3%). About 52.0% of patients with READ had these biomarkers, while this rate was (16.4%) in CROT. Among patients with COAD and READ, those with BRAF V600E mutations were more likely to be older, White, not Hispanic or Latino, and lived in urban areas compared to those without BRAF V600E. Relative to those with NRAS/KRAS/BRAF mutations, patients with NRAS/KRAS/BRAF wildtype were frequently younger. Relative to the frequency of biomarkers from a cBioPortal cohort of metastatic CRC, the frequency of NRAS wildtype was significantly lower in patients with COAD and READ tested through NPOP.
Consulsions
In this cohort, ~53 % of patients with COAD and 52% of patients with READ have highly actionable biomarkers and are potentially eligible for FDAapproved targeted therapies. Future studies examining cancer outcomes with regard to the use of targeted therapies in the setting of actionable gene alterations, TMB, and MSI are warranted.