2020
DOI: 10.7812/tpp/19.126
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Identifying Patients with Rare Disease Using Electronic Health Record Data: The Kaiser Permanente Southern California Membranous Nephropathy Cohort

Abstract: This retrospective, observational cohort study of mechanically ventilated patients at 21 community and 2 academic hospitals demonstrated that in 28,758 derivation cohort admissions, every 10% increase in SpO2/ FiO2 time at risk (SF-TAR) was associated with a 24% increase in adjusted odds of hospital mortality. The SF-TAR can identify ventilated patients at increased risk of death, offering modest improvements compared with single SpO2/FiO2 and P/F ratios. This longitudinal, noninvasive, and broadly generalizab… Show more

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Cited by 15 publications
(11 citation statements)
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“…First, we developed a population-based approach on the basis of EHR data combined with targeted physician adjudication to identify and characterize long-term outcomes of adults with primary NS. This approach could be applied by other health systems to identify adults with primary NS, and future efforts leveraging validated natural language processing algorithms and other machine-learning methods on unstructured EHR data could facilitate even more efficient population-level identification of primary NS, by avoiding the need for manual adjudication 35 36 Second, the substantial excess risk of ESKD with primary NS and particularly in those with FSGS or MN highlight the need for careful surveillance in these patients, optimizing control of risk factors for kidney disease progression, and identification of novel etiology-specific therapies.…”
Section: Discussionmentioning
confidence: 99%
“…First, we developed a population-based approach on the basis of EHR data combined with targeted physician adjudication to identify and characterize long-term outcomes of adults with primary NS. This approach could be applied by other health systems to identify adults with primary NS, and future efforts leveraging validated natural language processing algorithms and other machine-learning methods on unstructured EHR data could facilitate even more efficient population-level identification of primary NS, by avoiding the need for manual adjudication 35 36 Second, the substantial excess risk of ESKD with primary NS and particularly in those with FSGS or MN highlight the need for careful surveillance in these patients, optimizing control of risk factors for kidney disease progression, and identification of novel etiology-specific therapies.…”
Section: Discussionmentioning
confidence: 99%
“…Nonetheless, the trend in total heart failure prevalence in Germany over the last decade is rather flat and cannot explain the increases observed for CA [28]. On the other hand, rare diseases such as amyloidosis in general might be rather under-coded which leads to underestimation of CA prevalence and incidence as reported for other rare disease [30]. Nonetheless, assuming that these general limitations of the data source do not change relevantly within 10 years our findings on the temporal trend will not be impacted relevantly.…”
Section: Limitationsmentioning
confidence: 88%
“…Previous research has typically focused on specific rare conditions. Sun et al [42] used ICD-9 codes to identify membranous nephropathy patients in the Kaiser Permanente health system, while Dickey et al [43] used exome sequencing from the UKB to investigate whether erythropoietic protoporphyria may be under-diagnosed. The UKB [44] has also been analyzed more broadly, with rare variants in JAK2 and F11 associated to groups of myeloproliferative disease and congenital coagulation defects, respectively.…”
Section: Discussionmentioning
confidence: 99%