Incomplete and possibly selective recording of signs, symptoms, and measurements in free text fields of primary care electronic health records of adults with lower respiratory tract infections

Publication date

2024-02

Authors

Rijk, Merijn HORCID 0000-0003-4190-2126
Platteel, Tamara N
Mulder, Marissa M.M.
Geersing, Geert-JanORCID 0000-0001-6976-9844
Rutten, Frans HORCID 0000-0002-5052-7332ISNI 0000000389122794
van Smeden, MaartenORCID 0000-0002-5529-1541
Venekamp, Roderick PORCID 0000-0002-1446-9614ISNI 0000000393819260
Leeuwenberg, A MORCID 0000-0002-2892-0285

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Document Type

Article

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Abstract

Objectives: To assess the completeness of recording of relevant signs, symptoms, and measurements in Dutch free text fields of primary care electronic health records (EHR) of adults with lower respiratory tract infections (LRTI). Study Design and Setting: Retrospective cohort study embedded in a prediction modeling project using routine health care data of the Julius General Practitioners’ Network of adult patients with LRTI. Free text fields of 1,000 primary care consultations of LRTI episodes between 2016 and 2019 were manually annotated to retrieve data on the recording of sixteen relevant signs, symptoms, and measurements. Results: For 12/16 (75%) of the relevant signs, symptoms, and measurements, more than 50% of the values was not recorded. The patterns of recorded values indicated selective recording of positive or abnormal values. Recording rates varied across consultation type (physical consultation vs. home visit), diagnosis (acute bronchitis vs. pneumonia), antibiotic prescription issued (yes vs. no), and between practices. Conclusion: In EHR of primary care LRTI patients, recording of signs, symptoms, and measurements in free text fields is incomplete and possibly selective. When using free text data in EHR-based research, careful consideration of its recording patterns and appropriate missing data handling techniques is therefore required.

Keywords

Electronic health record, Lower respiratory tract infection, Missing data, Natural language processing, Primary care, Routine health care data, Epidemiology

Citation

Rijk, M H, Platteel, T N, Mulder, M M M, Geersing, G J, Rutten, F H, van Smeden, M, Venekamp, R P & Leeuwenberg, T M 2024, 'Incomplete and possibly selective recording of signs, symptoms, and measurements in free text fields of primary care electronic health records of adults with lower respiratory tract infections', Journal of Clinical Epidemiology, vol. 166, 111240, pp. 1-10. https://doi.org/10.1016/j.jclinepi.2023.111240