Background: Pre-eclampsia (PET) is one of the major causes of maternal and neonatal morbidity and mortality1. Misclassification of PET can lead to biased or erroneous results in epidemiologic studies resulting in false conclusions. Objectives: The objectives of this thesis are to determine the validity of PET diagnosis in pregnant women in administrative database using the ICD-10-CA codes, to explore the nature of misclassification, and to estimate whether misclassification of PET diagnosis in administrative database may result in biased conclusions. Methods: Pregnant women who participated in the Ottawa and Kingston (OaK) Birth Cohort study and delivered in the Ottawa Hospital were included in the study. All cases with hypertensive disorder of pregnancy in the study population were adjudicated to confirm diagnosis of PET. This adjudicated dataset was used as a reference standard. The PET incidence in hospital discharge database was compared with PET incidence calculated from the reference standard database. Results: 2887 of the requested charts were available for review. The PET incidence was much lower in administrative database (1.47%) than in the OaK Birth Cohort Study (3.6%). The results of the study demonstrated that hospital discharge database via ICD-10-CA was not very sensitive to determine incidence of PET since sensitivity of ICD-10-CA diagnostic codes for PET was low (35.92% with 95% Confidence Intervals (CI): 26.7; 45.9) but specificity, PPV, and NPV were high. The majority of misclassified cases belonged to the category (according to the proposed classification) “PET pregnancies coded with incorrect ICD-10-CA code” (78.88%) followed by the category “Pregnancies affected by PET coded as normal” (14.08%). Conclusion: Using hospital discharge database and ICD-10-CA coding to determine incidence of PET in certain settings may yield low sensitivity. Researchers should validate the results when using the hospital discharge database for PET research to ensure that the findings based on analyses of such data demonstrate what they claimed to demonstrate.

Background: Pre-eclampsia (PET) is one of the major causes of maternal and neonatal morbidity and mortality1. Misclassification of PET can lead to biased or erroneous results in epidemiologic studies resulting in false conclusions. Objectives: The objectives of this thesis are to determine the validity of PET diagnosis in pregnant women in administrative database using the ICD-10-CA codes, to explore the nature of misclassification, and to estimate whether misclassification of PET diagnosis in administrative database may result in biased conclusions. Methods: Pregnant women who participated in the Ottawa and Kingston (OaK) Birth Cohort study and delivered in the Ottawa Hospital were included in the study. All cases with hypertensive disorder of pregnancy in the study population were adjudicated to confirm diagnosis of PET. This adjudicated dataset was used as a reference standard. The PET incidence in hospital discharge database was compared with PET incidence calculated from the reference standard database. Results: 2887 of the requested charts were available for review. The PET incidence was much lower in administrative database (1.47%) than in the OaK Birth Cohort Study (3.6%). The results of the study demonstrated that hospital discharge database via ICD-10-CA was not very sensitive to determine incidence of PET since sensitivity of ICD-10-CA diagnostic codes for PET was low (35.92% with 95% Confidence Intervals (CI): 26.7; 45.9) but specificity, PPV, and NPV were high. The majority of misclassified cases belonged to the category (according to the proposed classification) “PET pregnancies coded with incorrect ICD-10-CA code” (78.88%) followed by the category “Pregnancies affected by PET coded as normal” (14.08%). Conclusion: Using hospital discharge database and ICD-10-CA coding to determine incidence of PET in certain settings may yield low sensitivity. Researchers should validate the results when using the hospital discharge database for PET research to ensure that the findings based on analyses of such data demonstrate what they claimed to demonstrate.

Background: Pre-eclampsia (PET) is one of the major causes of maternal and neonatal morbidity and mortality1. Misclassification of PET can lead to biased or erroneous results in epidemiologic studies resulting in false conclusions. Objectives: The objectives of this thesis are to determine the validity of PET diagnosis in pregnant women in administrative database using the ICD-10-CA codes, to explore the nature of misclassification, and to estimate whether misclassification of PET diagnosis in administrative database may result in biased conclusions. Methods: Pregnant women who participated in the Ottawa and Kingston (OaK) Birth Cohort study and delivered in the Ottawa Hospital were included in the study. All cases with hypertensive disorder of pregnancy in the study population were adjudicated to confirm diagnosis of PET. This adjudicated dataset was used as a reference standard. The PET incidence in hospital discharge database was compared with PET incidence calculated from the reference standard database. Results: 2887 of the requested charts were available for review. The PET incidence was much lower in administrative database (1.47%) than in the OaK Birth Cohort Study (3.6%). The results of the study demonstrated that hospital discharge database via ICD-10-CA was not very sensitive to determine incidence of PET since sensitivity of ICD-10-CA diagnostic codes for PET was low (35.92% with 95% Confidence Intervals (CI): 26.7; 45.9) but specificity, PPV, and NPV were high. The majority of misclassified cases belonged to the category (according to the proposed classification) “PET pregnancies coded with incorrect ICD-10-CA code” (78.88%) followed by the category “Pregnancies affected by PET coded as normal” (14.08%). Conclusion: Using hospital discharge database and ICD-10-CA coding to determine incidence of PET in certain settings may yield low sensitivity. Researchers should validate the results when using the hospital discharge database for PET research to ensure that the findings based on analyses of such data demonstrate what they claimed to demonstrate.