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Enhancing Coding Accuracy at the Hematology/Oncology Clinic: Is It Time to Hire a Dedicated Coder?
Background
Accurate clinical coding that reflects all diagnoses and problems addressed during a patient encounter is essential for the cancer program’s data quality, research initiatives, and securing VERA (Veterans Equitable Resource Allocation) funding. However, providers often face barriers such as limited time during patient visits and difficulty navigating Electronic health record (EHR) systems. These challenges lead to inaccurate coding, which undermines downstream data integrity. This quality improvement (QI) study aimed to identify these barriers and implement an intervention to improve coding accuracy, while also assessing the financial implications of improved documentation.
Methods
This QI study was conducted at the Albany Stratton VA Medical Center, focusing on hematology/ oncology outpatient encounters. A baseline chart audit of diagnosis codes from June 2023 revealed an accuracy rate of 69.8%. To address this, an intervention was implemented in which dedicated coders were assigned to support attending physicians in coding for over a two-week period. These coders reviewed and corrected diagnosis codes in real-time. A follow-up audit conducted after the intervention showed an improved coding accuracy of 82%.
Discussion/Implications
Coding remains a timeconsuming task for providers, made more difficult by EHR systems that are not user-friendly. This study demonstrated that involving dedicated coders significantly improves documentation accuracy—from 69% to 82%. In addition to data quality, the financial benefits are notable. A projected annual return on investment of $216,094 was calculated, based on an internal analysis showing that in a sample of 124 patients, 10% could have qualified for higher VERA funding based on accurate coding, generating an estimated $17,427 in additional reimbursement per patient. This cost-benefit ratio supports the recommendation to staff dedicated coders. Other interventions were also utilised, such as updating the national encounter form and auto-populating documentation in Dragon software, but had limited impact and did not directly address diagnosis accuracy respectively.
Conclusions
Targeted interventions improved coding accuracy, but sustainability remains a challenge due to time and system limitations. Future efforts should focus on hiring full-time coders. These steps can further enhance coding quality and potentially increase hospital revenue.
Background
Accurate clinical coding that reflects all diagnoses and problems addressed during a patient encounter is essential for the cancer program’s data quality, research initiatives, and securing VERA (Veterans Equitable Resource Allocation) funding. However, providers often face barriers such as limited time during patient visits and difficulty navigating Electronic health record (EHR) systems. These challenges lead to inaccurate coding, which undermines downstream data integrity. This quality improvement (QI) study aimed to identify these barriers and implement an intervention to improve coding accuracy, while also assessing the financial implications of improved documentation.
Methods
This QI study was conducted at the Albany Stratton VA Medical Center, focusing on hematology/ oncology outpatient encounters. A baseline chart audit of diagnosis codes from June 2023 revealed an accuracy rate of 69.8%. To address this, an intervention was implemented in which dedicated coders were assigned to support attending physicians in coding for over a two-week period. These coders reviewed and corrected diagnosis codes in real-time. A follow-up audit conducted after the intervention showed an improved coding accuracy of 82%.
Discussion/Implications
Coding remains a timeconsuming task for providers, made more difficult by EHR systems that are not user-friendly. This study demonstrated that involving dedicated coders significantly improves documentation accuracy—from 69% to 82%. In addition to data quality, the financial benefits are notable. A projected annual return on investment of $216,094 was calculated, based on an internal analysis showing that in a sample of 124 patients, 10% could have qualified for higher VERA funding based on accurate coding, generating an estimated $17,427 in additional reimbursement per patient. This cost-benefit ratio supports the recommendation to staff dedicated coders. Other interventions were also utilised, such as updating the national encounter form and auto-populating documentation in Dragon software, but had limited impact and did not directly address diagnosis accuracy respectively.
Conclusions
Targeted interventions improved coding accuracy, but sustainability remains a challenge due to time and system limitations. Future efforts should focus on hiring full-time coders. These steps can further enhance coding quality and potentially increase hospital revenue.
Background
Accurate clinical coding that reflects all diagnoses and problems addressed during a patient encounter is essential for the cancer program’s data quality, research initiatives, and securing VERA (Veterans Equitable Resource Allocation) funding. However, providers often face barriers such as limited time during patient visits and difficulty navigating Electronic health record (EHR) systems. These challenges lead to inaccurate coding, which undermines downstream data integrity. This quality improvement (QI) study aimed to identify these barriers and implement an intervention to improve coding accuracy, while also assessing the financial implications of improved documentation.
Methods
This QI study was conducted at the Albany Stratton VA Medical Center, focusing on hematology/ oncology outpatient encounters. A baseline chart audit of diagnosis codes from June 2023 revealed an accuracy rate of 69.8%. To address this, an intervention was implemented in which dedicated coders were assigned to support attending physicians in coding for over a two-week period. These coders reviewed and corrected diagnosis codes in real-time. A follow-up audit conducted after the intervention showed an improved coding accuracy of 82%.
Discussion/Implications
Coding remains a timeconsuming task for providers, made more difficult by EHR systems that are not user-friendly. This study demonstrated that involving dedicated coders significantly improves documentation accuracy—from 69% to 82%. In addition to data quality, the financial benefits are notable. A projected annual return on investment of $216,094 was calculated, based on an internal analysis showing that in a sample of 124 patients, 10% could have qualified for higher VERA funding based on accurate coding, generating an estimated $17,427 in additional reimbursement per patient. This cost-benefit ratio supports the recommendation to staff dedicated coders. Other interventions were also utilised, such as updating the national encounter form and auto-populating documentation in Dragon software, but had limited impact and did not directly address diagnosis accuracy respectively.
Conclusions
Targeted interventions improved coding accuracy, but sustainability remains a challenge due to time and system limitations. Future efforts should focus on hiring full-time coders. These steps can further enhance coding quality and potentially increase hospital revenue.