Contraception · 2018
Use of an electronic health record data sharing system for identifying current contraceptive use within the WWAMI region Practice and Research Network.
СтатьяПоддержка NIH: внешняя программаПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Godfrey Emily M, West Imara I, Holmes John, Keppel Gina A, Baldwin Laura-Mae
Аннотация
OBJECTIVE: To evaluate the ability of electronic health record (EHR) data extracted into a data-sharing system to accurately identify contraceptive use.
STUDY DESIGN: We compared rates of contraceptive use from electronic extraction of EHR data via a data-sharing system and manual abstraction of the EHR among 142 female patients ages 15-49 years from a family medicine clinic within a primary care practice-based research network (PBRN). Cohen's kappa coefficient measured agreement between electronic extraction and manual abstraction.
RESULTS: Manual abstraction identified 62% of women as contraceptive users, whereas electronic extraction identified only 27%. Long acting reversible (LARC) methods had 96% agreement (Cohen's kappa 0.78; confidence interval, 0.57-0.99) between electronic extraction and manual abstraction. EHR data extracted via a data-sharing system was unable to identify barrier or over-the-counter contraceptives.
CONCLUSIONS: Electronic extraction found substantially lower overall rates of contraceptive method use, but produced more comparable LARC method use rates when compared to manual abstraction among women in this study's primary care clinic.
IMPLICATIONS: Quality metrics related to contraceptive use that rely on EHR data in this study's data-sharing system likely under-estimated true contraceptive use.
STUDY DESIGN: We compared rates of contraceptive use from electronic extraction of EHR data via a data-sharing system and manual abstraction of the EHR among 142 female patients ages 15-49 years from a family medicine clinic within a primary care practice-based research network (PBRN). Cohen's kappa coefficient measured agreement between electronic extraction and manual abstraction.
RESULTS: Manual abstraction identified 62% of women as contraceptive users, whereas electronic extraction identified only 27%. Long acting reversible (LARC) methods had 96% agreement (Cohen's kappa 0.78; confidence interval, 0.57-0.99) between electronic extraction and manual abstraction. EHR data extracted via a data-sharing system was unable to identify barrier or over-the-counter contraceptives.
CONCLUSIONS: Electronic extraction found substantially lower overall rates of contraceptive method use, but produced more comparable LARC method use rates when compared to manual abstraction among women in this study's primary care clinic.
IMPLICATIONS: Quality metrics related to contraceptive use that rely on EHR data in this study's data-sharing system likely under-estimated true contraceptive use.