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Background
The Veterans Affairs Central Cancer Registry (VACCR) is an information system, which collects and organizes data on Veterans with cancer for use in cancer surveillance activities, such as epidemiologic based efforts to reduce the overall cancer burden. Unfortunately, there was no structured standardized data acquisition method in place to ensure accurate or timely data entry of Lexington VA Healthcare System (LVAHCS) statistics. This quality improvement study evaluated the implementation of a Structured Query Language (SQL) code to identify specific documents in the Computerized Patient Records System (CPRS) electronic medical record with associated ICD-10 codes matching the reportable cancer cases in the Surveillance, Epidemiology, and End Results (SEER) program.
Methods
Outcomes Studied: Accuracy of the SQL code, rates of data entry into the VACCR pre- and postintervention. Cancer Program leadership collaborated with the VISN 9 Program Analyst to write a SQL code identifying the Veteran’s name; social security number; location by city, state, and county; and visit associated data such as visit location, ICD-10 code documented by the provider, and visit year. This code can be run manually or at a pre-determined cadence.
Results
A total of 3,099 incidences of cancer were entered into the VACCR by local Oncology Data Specialists (ODSs) for calendar years 2015 to 2022. This is approximately 238 cases yearly. After the intervention, 1692 patients were entered into the VACCR in 2023. This is an increased rate of data entry of 611%.
Conclusions
This study demonstrated the feasibility of implementing a SQL code to accurately identify Veterans with diagnoses matching the SEER list. Increasing accuracy of identification has led to increased data entry efficiency into the VACCR by local ODS staff. After proving the feasibility of this intervention, we are partnering with the VISN 9 Program Analyst to create a static, daily recurring report provided to the ODS staff. Future application of this intervention could also include expansion into other VHA sites, increasing their accuracy and timeliness of data entry. Overall, improving the timeliness and accuracy of the VACCR would subsequently improve the ability of the VHA to target interventions aimed at reducing the overall cancer burden.
Background
The Veterans Affairs Central Cancer Registry (VACCR) is an information system, which collects and organizes data on Veterans with cancer for use in cancer surveillance activities, such as epidemiologic based efforts to reduce the overall cancer burden. Unfortunately, there was no structured standardized data acquisition method in place to ensure accurate or timely data entry of Lexington VA Healthcare System (LVAHCS) statistics. This quality improvement study evaluated the implementation of a Structured Query Language (SQL) code to identify specific documents in the Computerized Patient Records System (CPRS) electronic medical record with associated ICD-10 codes matching the reportable cancer cases in the Surveillance, Epidemiology, and End Results (SEER) program.
Methods
Outcomes Studied: Accuracy of the SQL code, rates of data entry into the VACCR pre- and postintervention. Cancer Program leadership collaborated with the VISN 9 Program Analyst to write a SQL code identifying the Veteran’s name; social security number; location by city, state, and county; and visit associated data such as visit location, ICD-10 code documented by the provider, and visit year. This code can be run manually or at a pre-determined cadence.
Results
A total of 3,099 incidences of cancer were entered into the VACCR by local Oncology Data Specialists (ODSs) for calendar years 2015 to 2022. This is approximately 238 cases yearly. After the intervention, 1692 patients were entered into the VACCR in 2023. This is an increased rate of data entry of 611%.
Conclusions
This study demonstrated the feasibility of implementing a SQL code to accurately identify Veterans with diagnoses matching the SEER list. Increasing accuracy of identification has led to increased data entry efficiency into the VACCR by local ODS staff. After proving the feasibility of this intervention, we are partnering with the VISN 9 Program Analyst to create a static, daily recurring report provided to the ODS staff. Future application of this intervention could also include expansion into other VHA sites, increasing their accuracy and timeliness of data entry. Overall, improving the timeliness and accuracy of the VACCR would subsequently improve the ability of the VHA to target interventions aimed at reducing the overall cancer burden.
Background
The Veterans Affairs Central Cancer Registry (VACCR) is an information system, which collects and organizes data on Veterans with cancer for use in cancer surveillance activities, such as epidemiologic based efforts to reduce the overall cancer burden. Unfortunately, there was no structured standardized data acquisition method in place to ensure accurate or timely data entry of Lexington VA Healthcare System (LVAHCS) statistics. This quality improvement study evaluated the implementation of a Structured Query Language (SQL) code to identify specific documents in the Computerized Patient Records System (CPRS) electronic medical record with associated ICD-10 codes matching the reportable cancer cases in the Surveillance, Epidemiology, and End Results (SEER) program.
Methods
Outcomes Studied: Accuracy of the SQL code, rates of data entry into the VACCR pre- and postintervention. Cancer Program leadership collaborated with the VISN 9 Program Analyst to write a SQL code identifying the Veteran’s name; social security number; location by city, state, and county; and visit associated data such as visit location, ICD-10 code documented by the provider, and visit year. This code can be run manually or at a pre-determined cadence.
Results
A total of 3,099 incidences of cancer were entered into the VACCR by local Oncology Data Specialists (ODSs) for calendar years 2015 to 2022. This is approximately 238 cases yearly. After the intervention, 1692 patients were entered into the VACCR in 2023. This is an increased rate of data entry of 611%.
Conclusions
This study demonstrated the feasibility of implementing a SQL code to accurately identify Veterans with diagnoses matching the SEER list. Increasing accuracy of identification has led to increased data entry efficiency into the VACCR by local ODS staff. After proving the feasibility of this intervention, we are partnering with the VISN 9 Program Analyst to create a static, daily recurring report provided to the ODS staff. Future application of this intervention could also include expansion into other VHA sites, increasing their accuracy and timeliness of data entry. Overall, improving the timeliness and accuracy of the VACCR would subsequently improve the ability of the VHA to target interventions aimed at reducing the overall cancer burden.