Abstract
Objective
To compare rates of patient-reported kidney stone disease to Electronic Health Records
(EHR) kidney stone diagnosis using a common dataset to evaluate for socio-demographic
differences, including between those with and without active care.
Methods
From the All of Us research database, we identified 21,687 adult participants with
both patient-reported and EHR data. We compared differences in age, sex, race, education,
employment status and healthcare access between patients with self-reported kidney
stone history without EHR data to those with EHR-based diagnoses.
Results
In this population, the self-reported prevalence of kidney stones was 8.6% overall
(n = 1877), including 4.6% (n = 1004) who had self-reported diagnoses but no EHR data.
Among those with self-reported kidney stone diagnoses only, the median age was 66.
The EHR-based prevalence of kidney stones was 5.7% (n = 1231), median age 67. No differences
were observed in age, sex, education, employment status, rural/urban status, or ability
to afford healthcare between groups with EHR diagnosis or self-reported diagnosis
only. Of patients who had a self-reported history of kidney stones, 24% reported actively
seeing a provider for kidney stones.
Conclusion
Kidney stone prevalence by self-report is higher than EHR-based prevalence in this
national dataset. Using either method alone to estimate kidney stone prevalence may
exclude some patients with the condition, although the demographic profile of both
groups is similar. Approximately 1 in 4 patients report actively seeing a provider
for stone disease.
Abbreviations:
EHR (Electronic Health Record), SNOMED (Systematized Nomenclature of Medicine), ICD (International Classification of Disease), NHANES) (National Health and Nutritional Examination Survey)To read this article in full you will need to make a payment
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Article info
Publication history
Published online: November 23, 2022
Accepted:
November 13,
2022
Received:
September 1,
2022
Publication stage
In Press Journal Pre-ProofFootnotes
Financial Disclosure: The authors declare that they have no relevant financial interests.
Funding Support: This project utilized the All of Us research database. The All of Us Research Program is supported by the National Institutes of Health, Office of the Director: Regional Medical Centers: 1 OT2 OD026549; 1 OT2 OD026554; 1 OT2 OD026557; 1 OT2 OD026556; 1 OT2 OD026550; 1 OT2 OD 026552; 1 OT2 OD026553; 1 OT2 OD026548; 1 OT2 OD026551; 1 OT2 OD026555; IAA #: AOD 16037; Federally Qualified Health Centers: HHSN 263201600085U; Data and Research Center: 5 U2C OD023196; Biobank: 1 U24 OD023121; The Participant Center: U24 OD023176; Participant Technology Systems Center: 1 U24 OD023163; Communications and Engagement: 3 OT2 OD023205; 3 OT2 OD023206; and Community Partners: 1 OT2 OD025277; 3 OT2 OD025315; 1 OT2 OD025337; 1 OT2 OD025276. In addition, the All of Us Research Program would not be possible without the partnership of its participants. RH, YX, and CB are supported by R21 DK127075.
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