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ICD10Data.com is a free reference website designed for the fast lookup of all current American ICD-10-CM (diagnosis) and ICD-10-PCS (procedure) medical billing codes.
Purpose: To validate the use of selected International Classification of Disease Codes 10th revision (ICD-10) to predict (positive predictive value) anaphylaxis due to vaccination using emergency department (ED) data.
The 2021 ICD-10-CM/PCS code sets are now fully loaded on ICD10Data.com. 2021 codes became effective on October 1, 2020, therefore all claims with a date of service on or after this date should use 2021 codes. New ICD-10 Covid-19 Coronavirus Code ICD-10-CM code U07.1 2019-nCoV acute respiratory disease
Conclusion: The PPV of the local or ICD-10 code for AMI was high for inpatient claims in Japan. The PPV was even higher for the ICD-10 code for AMI for those patients who received AMI care through the DPC case mix scheme.
Positive predictive value (PPV), the proportion of cases identified that are true cases, is one statistic used to evaluate degree of misclassification and is a commonly prioritized attribute of surveillance systems. 4 For surveillance systems that require review or investigation of identified cases, suboptimal PPV will necessitate unnecessary allocation of resources. Additionally, compromised PPV may flood the perceived case pool with non-cases making statistics such as mortality rates appear more favorable than reality. In the midst of a pandemic, where time and resources can be scarce, a surveillance system that is precise while being concurrently sufficiently sensitive is not only optimal but essential. To our knowledge, only one US study has examined PPV of code U07.1. 5 In this study, Kadri et al evaluated 52,000 hospitalizations occurring early in the pandemic from April 1, 2020 to May 31, 2020 and found the PPV of discharge diagnoses of code U07.1 to be 91.52%. Unlike sensitivity and specificity which assess the intrinsic accuracy of an instrument, PPV is population specific. It is therefore unknown whether the performance of diagnostic coding for identifying COVID-19 infection is similar for patients receiving ambulatory care, in other healthcare systems, or if it has remained stable since the code’s introduction in April 2020.
Using manual chart review as the gold standard, we assessed the PPV of ICD-10 code U07.1 to identify patients with active COVID-19 disease across multiple clinical settings within VA from April 1, 2020 through March 31, 2021. Counter to our original hypothesis, the PPV did not improve monotonically throughout the one-year observation period, with the lowest PPV (80%) occurring in quarter 2, July–September of 2020, and the highest PPV (86%) occurring in quarter 3, October–December of 2020. Inpatient settings were the most accurate while outpatient settings yielded considerably more false positives.
First, evaluating the PPV of administrative codes can be used to quantify the uncertainty of estimates in epidemiologic research. 13 Second, understanding the context in which coding errors occur can inform efforts to improve future documentation practices and increase the usefulness of the codes for both research and surveillance. One proposed solution for improvement in coding and documentation is education followed by audit and feedback during a code’s initial roll-out.
The purpose of this study was to determine the PPV of ICD-10 code U07.1 for identifying COVID-19 disease among patients at the VA. Given the likelihood of coding errors when the code was newly released due to unfamiliarity with the code, we hypothesized that PPV may have improved across time and the reasons for inaccuracies (ie, false positives) paralleled the changing clinical environments.
The availability of COVID-19 testing expansions outside of patients’ usual places of care is a critical reason that non-laboratory-based mechanisms for surveilling patients has been necessary in VA. When a patient tests positive or is diagnosed outside of the VA but seeks care within VA, structured lab data may not reach the VA medical record. These patients would not be identified in VA if a case definition included only VA lab positive patients. Supplementing laboratory data may be particularly important for specific patient populations, such as low-income and/or rural patients, if they more heavily rely on testing sites outside the VA.
However, in this nationwide US study, we found ICD-10 diagnosis code U07.1 has low PPV, especially in outpatient settings, making it not sufficiently accurate for comprehensive COVID-19 surveillance. Future work should focus on interventions to improve coding practices and to standardize adoption so ICD-10 codes can be a viable option for future pandemic surveillance.
We reviewed the medical records of 710 patients admitted at six departments of infectious diseases in Danish hospitals from February 27 through May 4, 2020 with an ICD-10 diagnosis code of Coronavirus disease (COVID-19) and found an overall positive predictive value (PPV) of 99%.
COVID-19 is a potentially life-threatening infection for aging and other vulnerable populations.
In Denmark, medical care is tax-supported and free of charge at the point of delivery for all residents. A unique civil registration number assigned at birth or immigration allows for the unique identification of all Danish residents and unambiguous linkage between registries. 7
During the study period, a total of 710 patients were assigned a diagnosis code of COVID-19 ( Table 1 ). The median age of patients was 61 years (IQR 47–74) and 285/710 (40%) were females.
This study observed a very high PPV of COVID-19 diagnosis codes for patients hospitalized in Denmark during the first wave of the pandemic. The PPV ranged 97–100% in all examined subgroups including sex, age groups, and when stratified by diagnosis code.
CI, Confidence interval; COVID-19, Corona virus disease 2019; ICD-10, International Classification of Diseases versions 10; PPV, Positive predictive value; SARS-CoV-2, Severe acute respiratory syndrome coronavirus 2.
Positive predictive value (PPV), the proportion of cases identified that are true cases, is one statistic used to evaluate degree of misclassification and is a commonly prioritized attribute of surveillance systems. 4 For surveillance systems that require review or investigation of identified cases, suboptimal PPV will necessitate unnecessary allocation of resources. Additionally, compromised PPV may flood the perceived case pool with non-cases making statistics such as mortality rates appear more favorable than reality. In the midst of a pandemic, where time and resources can be scarce, a surveillance system that is precise while being concurrently sufficiently sensitive is not only optimal but essential. To our knowledge, only one US study has examined PPV of code U07.1. 5 In this study, Kadri et al evaluated 52,000 hospitalizations occurring early in the pandemic from April 1, 2020 to May 31, 2020 and found the PPV of discharge diagnoses of code U07.1 to be 91.52%. Unlike sensitivity and specificity which assess the intrinsic accuracy of an instrument, PPV is population specific. It is therefore unknown whether the performance of diagnostic coding for identifying COVID-19 infection is similar for patients receiving ambulatory care, in other healthcare systems, or if it has remained stable since the code’s introduction in April 2020.
Using manual chart review as the gold standard, we assessed the PPV of ICD-10 code U07.1 to identify patients with active COVID-19 disease across multiple clinical settings within VA from April 1, 2020 through March 31, 2021. Counter to our original hypothesis, the PPV did not improve monotonically throughout the one-year observation period, with the lowest PPV (80%) occurring in quarter 2, July–September of 2020, and the highest PPV (86%) occurring in quarter 3, October–December of 2020. Inpatient settings were the most accurate while outpatient settings yielded considerably more false positives.
First, evaluating the PPV of administrative codes can be used to quantify the uncertainty of estimates in epidemiologic research. 13 Second, understanding the context in which coding errors occur can inform efforts to improve future documentation practices and increase the usefulness of the codes for both research and surveillance. One proposed solution for improvement in coding and documentation is education followed by audit and feedback during a code’s initial roll-out.
The purpose of this study was to determine the PPV of ICD-10 code U07.1 for identifying COVID-19 disease among patients at the VA. Given the likelihood of coding errors when the code was newly released due to unfamiliarity with the code, we hypothesized that PPV may have improved across time and the reasons for inaccuracies (ie, false positives) paralleled the changing clinical environments.
The availability of COVID-19 testing expansions outside of patients’ usual places of care is a critical reason that non-laboratory-based mechanisms for surveilling patients has been necessary in VA. When a patient tests positive or is diagnosed outside of the VA but seeks care within VA, structured lab data may not reach the VA medical record. These patients would not be identified in VA if a case definition included only VA lab positive patients. Supplementing laboratory data may be particularly important for specific patient populations, such as low-income and/or rural patients, if they more heavily rely on testing sites outside the VA.
However, in this nationwide US study, we found ICD-10 diagnosis code U07.1 has low PPV, especially in outpatient settings, making it not sufficiently accurate for comprehensive COVID-19 surveillance. Future work should focus on interventions to improve coding practices and to standardize adoption so ICD-10 codes can be a viable option for future pandemic surveillance.