Sick patients have more data: the non-random completeness of electronic health records.

Nicole Weiskopf, Alex Rusanov, Chunhua Weng

Research output: Contribution to journalArticle

32 Citations (Scopus)

Abstract

As interest in the reuse of electronic health record (EHR) data for research purposes grows, so too does awareness of the significant data quality problems in these non-traditional datasets. In the past, however, little attention has been paid to whether poor data quality merely introduces noise into EHR-derived datasets, or if there is potential for the creation of spurious signals and bias. In this study we use EHR data to demonstrate a statistically significant relationship between EHR completeness and patient health status, indicating that records with more data are likely to be more representative of sick patients than healthy ones, and therefore may not reflect the broader population found within the EHR.

Original languageEnglish (US)
Pages (from-to)1472-1477
Number of pages6
JournalAMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium
Volume2013
StatePublished - 2013
Externally publishedYes

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Electronic Health Records
Patient Advocacy
Health Status
Noise
Research
Population
Datasets
Data Accuracy

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Sick patients have more data : the non-random completeness of electronic health records. / Weiskopf, Nicole; Rusanov, Alex; Weng, Chunhua.

In: AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium, Vol. 2013, 2013, p. 1472-1477.

Research output: Contribution to journalArticle

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