Kamille Herskind, Peter Bjødstrup Jensen, Christina Anne Vinter, Lone Krebs, Lene Friis Eskildsen, Anne Broe, Anton Pottegård, Mette Bliddal
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引用次数: 0
Abstract
Purpose: This study aimed to systematically evaluate the validity of variables related to pregnancy, delivery, and key characteristics of the infant in the Danish National Patient Register using maternal medical records as the reference standard. Patients and Methods: We reviewed medical records of 1264 women giving birth in the Region of Southern Denmark during 2017. We calculated positive (PPV) and negative (NPV) predictive values, sensitivity, and specificity to estimate the validity of 49 selected variables. Results: The PPV was ≥ 0.90 on most pregnancy-related variables including parity, pre-gestational BMI, diabetes disorders, and previous cesarean section, while it was lower for hypertensive disorders, especially mild to moderate preeclampsia (0.49, 95% CI 0.32– 0.66). Sensitivity ranged from 0.80 to 1.00 on all pregnancy-related variables, except hypertensive disorders (sensitivity 0.38– 0.71, lowest for severe preeclampsia). On most delivery-related variables including obstetric surgical procedures (eg cesarean section and induction of labor), pharmacological pain-relief, and gestational age at delivery, PPV’s ranged from 0.98 to 1.00 and the corresponding sensitivities from 0.87 to 1.00. Regarding infant-related variables, both the APGAR score registered five minutes after delivery and birthweight yielded a PPV of 1.00. Conclusion: Obstetric coding in the Danish National Patient Register shows very high validity and completeness making it a valuable source for epidemiologic research.
Plain Language Summary: Danish register data are often used for epidemiological research in reproduction. The registers are based on coded information to the registers based on information from medical records. The quality of the register data is highly dependent of the validity of the codes. Yet there is a lack in our knowledge of the validity of data related to pregnancy, childbirth, and the characteristics of the newborn baby. We therefore aimed to validate the Danish National Patient Registry data related to pregnancy and childbirth by comparing the registered code with information from the medical records. We scrutinized medical records from 1264 women giving birth in the Region of Southern Denmark during 2017. We compared the registration in the medical record with the registered code in the Danish National Patient Registry by calculating how accurate the register data are according to 49 different variables. Results showed that registered codes in the Patient Registry for pregnancy- and childbirth-related conditions and key infant characteristics were to a high degree in agreement with the data from the medical report with few exceptions. In conclusion, the study revealed that the Danish National Patient Register provides highly accurate and comprehensive data for most pregnancy, delivery, and infant-related variables. This underscores the register’s value as a reliable source for epidemiologic research in reproductive health.
Keywords: registries, sensitivity and specificity, validity, epidemiology, pregnancy, delivery
期刊介绍：
Clinical Epidemiology is an international, peer reviewed, open access journal. Clinical Epidemiology focuses on the application of epidemiological principles and questions relating to patients and clinical care in terms of prevention, diagnosis, prognosis, and treatment.
Clinical Epidemiology welcomes papers covering these topics in form of original research and systematic reviews.
Clinical Epidemiology has a special interest in international electronic medical patient records and other routine health care data, especially as applied to safety of medical interventions, clinical utility of diagnostic procedures, understanding short- and long-term clinical course of diseases, clinical epidemiological and biostatistical methods, and systematic reviews.
When considering submission of a paper utilizing publicly-available data, authors should ensure that such studies add significantly to the body of knowledge and that they use appropriate validated methods for identifying health outcomes.
The journal has launched special series describing existing data sources for clinical epidemiology, international health care systems and validation studies of algorithms based on databases and registries.
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