Lawrence N

Purpose: To evaluate data extraction methods for identifying cytogenetic and fluorescence in situ hybridization (FISH) testing among chronic lymphoblastic leukemia (CLL) patients in the Veterans Health Administration (VHA).

Background: Cytogenetic/FISH testing are increasingly important for assessing risk and guiding therapy in patients with CLL. Administrative health data are frequently used to study testing practices; however, they are limited in their sensitivity and reliability. Increasing adoption of electronic health records (EHR) presents an opportunity to describe clinical practices in large patient populations. We compare three different EHR extraction methods to identify cytogenetic/ FISH testing in a cohort of CLL patients treated within the VHA.

Methods: CLL patients were identified using the VA Clinical Cancer Registry. Testing information was extracted from time of diagnosis to time of first treatment using three methods: (1) Current Procedural Terminology (CPT) codes; (2) Text mining of healthcare provider orders (HPO); (3) Clinical Lab Information Retrieval (CLIR), a previously validated conceptual framework that incorporates LOINC codes and test names that are then validated using test result information.

Results: 1,363 CLL patients were diagnosed and followed until their first line of therapy at VHA between 2008 and 2016: 635 (47%) had evidence of testing by text mining of HPO, 554 (41%) by CPT, and 399 (29%) by CLIR. Comparing CPT vs combined CLIR+HPO, CPT extraction had
a sensitivity of 52.8%, a precision of 73.1% and an F-measure of 0.613. Cytogenetic/FISH testing increased by nearly two-fold from 2008 to 2016, regardless of extraction method: HPO text mining (25% to 51%), CPT (20% to 54%), or CLIR (19% to 32%).

Conclusions: Advanced EHR extraction methods offer a more granular description of testing practices than administrative data alone as they examine multiple components of the EHR including the ordering, processing, and results of testing occurrences. Results suggest that there has been a slow increase in the number of CLL patients undergoing cytogenetic/FISH testing during the past decade, which is comparable to similar reports of testing practices outside the VHA, although approximately half of all CLL patients are not undergoing testing despite established clinical guideline recommendations.

Purpose: To evaluate data extraction methods for identifying cytogenetic and fluorescence in situ hybridization (FISH) testing among chronic lymphoblastic leukemia (CLL) patients in the Veterans Health Administration (VHA).

Background: Cytogenetic/FISH testing are increasingly important for assessing risk and guiding therapy in patients with CLL. Administrative health data are frequently used to study testing practices; however, they are limited in their sensitivity and reliability. Increasing adoption of electronic health records (EHR) presents an opportunity to describe clinical practices in large patient populations. We compare three different EHR extraction methods to identify cytogenetic/ FISH testing in a cohort of CLL patients treated within the VHA.

Methods: CLL patients were identified using the VA Clinical Cancer Registry. Testing information was extracted from time of diagnosis to time of first treatment using three methods: (1) Current Procedural Terminology (CPT) codes; (2) Text mining of healthcare provider orders (HPO); (3) Clinical Lab Information Retrieval (CLIR), a previously validated conceptual framework that incorporates LOINC codes and test names that are then validated using test result information.

Results: 1,363 CLL patients were diagnosed and followed until their first line of therapy at VHA between 2008 and 2016: 635 (47%) had evidence of testing by text mining of HPO, 554 (41%) by CPT, and 399 (29%) by CLIR. Comparing CPT vs combined CLIR+HPO, CPT extraction had
a sensitivity of 52.8%, a precision of 73.1% and an F-measure of 0.613. Cytogenetic/FISH testing increased by nearly two-fold from 2008 to 2016, regardless of extraction method: HPO text mining (25% to 51%), CPT (20% to 54%), or CLIR (19% to 32%).

Conclusions: Advanced EHR extraction methods offer a more granular description of testing practices than administrative data alone as they examine multiple components of the EHR including the ordering, processing, and results of testing occurrences. Results suggest that there has been a slow increase in the number of CLL patients undergoing cytogenetic/FISH testing during the past decade, which is comparable to similar reports of testing practices outside the VHA, although approximately half of all CLL patients are not undergoing testing despite established clinical guideline recommendations.

Purpose: To evaluate data extraction methods for identifying cytogenetic and fluorescence in situ hybridization (FISH) testing among chronic lymphoblastic leukemia (CLL) patients in the Veterans Health Administration (VHA).

Background: Cytogenetic/FISH testing are increasingly important for assessing risk and guiding therapy in patients with CLL. Administrative health data are frequently used to study testing practices; however, they are limited in their sensitivity and reliability. Increasing adoption of electronic health records (EHR) presents an opportunity to describe clinical practices in large patient populations. We compare three different EHR extraction methods to identify cytogenetic/ FISH testing in a cohort of CLL patients treated within the VHA.

Methods: CLL patients were identified using the VA Clinical Cancer Registry. Testing information was extracted from time of diagnosis to time of first treatment using three methods: (1) Current Procedural Terminology (CPT) codes; (2) Text mining of healthcare provider orders (HPO); (3) Clinical Lab Information Retrieval (CLIR), a previously validated conceptual framework that incorporates LOINC codes and test names that are then validated using test result information.

Results: 1,363 CLL patients were diagnosed and followed until their first line of therapy at VHA between 2008 and 2016: 635 (47%) had evidence of testing by text mining of HPO, 554 (41%) by CPT, and 399 (29%) by CLIR. Comparing CPT vs combined CLIR+HPO, CPT extraction had
a sensitivity of 52.8%, a precision of 73.1% and an F-measure of 0.613. Cytogenetic/FISH testing increased by nearly two-fold from 2008 to 2016, regardless of extraction method: HPO text mining (25% to 51%), CPT (20% to 54%), or CLIR (19% to 32%).

Conclusions: Advanced EHR extraction methods offer a more granular description of testing practices than administrative data alone as they examine multiple components of the EHR including the ordering, processing, and results of testing occurrences. Results suggest that there has been a slow increase in the number of CLL patients undergoing cytogenetic/FISH testing during the past decade, which is comparable to similar reports of testing practices outside the VHA, although approximately half of all CLL patients are not undergoing testing despite established clinical guideline recommendations.