Elizabeth Krusemark

A novel measure of socioeconomic status using individual housing data to assess the association of SES with rheumatoid arthritis and its mortality: a population-based case–control study

Objectives To assess whether HOUSES (HOUsing-based index of socioeconomic status (SES)) is associated with risk of and mortality after rheumatoid arthritis (RA). Design We conducted a population-based case–control study which enrolled population-based RA cases and their controls without RA. Setting The study was performed in Olmsted County, Minnesota. Participants Study participants were all residents of Olmsted County, Minnesota, with RA identified using the 1987 American College of Rheumatology criteria for RA from 1 January 1988, to 31 December 2007, using the auspices of the Rochester Epidemiology Project. For each patient with RA, one control was randomly selected from Olmsted County residents of similar age and gender without RA. Primary and secondary outcome measure The disease status was RA cases and their matched controls in relation to HOUSES as an exposure. As a secondary aim, post-RA mortality among only RA cases was an outcome event. The associations of SES measured by HOUSES with the study outcomes were assessed using logistic regression and Cox models. HOUSES, as a composite index, was formulated based on a summed z-score for housing value, square footage and number of bedrooms and bathrooms. Results Of the eligible 604 participants, 418 (69%) were female; the mean age was 56±15.6 years. Lower SES, as measured by HOUSES, was associated with the risk of developing RA (0.5±3.8 for controls vs −0.2±3.1 for RA cases, p=0.003), adjusting for age, gender, calendar year of RA index date, smoking status and BMI. The lowest quartile of HOUSES was significantly associated with increased post-RA mortality compared to higher quartiles of HOUSES (HR 1.74; 95% CI 1.10 to 2.74; p=0.017) in multivariate analysis. Conclusions Lower SES, as measured by HOUSES, is associated with increased risk of RA and mortality after RA. HOUSES may be a useful tool for health disparities research concerning rheumatological outcomes when conventional SES measures are unavailable.

Ethnicity, Socioeconomic Status, and Health Disparities in a Mixed Rural-Urban US Community—Olmsted County, Minnesota

OBJECTIVE To characterize health disparities in common chronic diseases among adults by socioeconomic status (SES) and ethnicity in a mixed rural-urban community of the United States. PATIENTS AND METHODS We conducted a cross-sectional study to assess the association of the prevalence of the 5 most burdensome chronic diseases in adults with SES and ethnicity and their interaction. The Rochester Epidemiology Project medical records linkage system was used to identify the prevalence of coronary heart disease, asthma, diabetes, hypertension, and mood disorder using International Classification of Diseases, Ninth Revision codes recorded from January 1, 2005, through December 31, 2009, among all adult residents of Olmsted County, Minnesota, on April 1, 2009. For SES measurements, an individual HOUsing-based index of SocioEconomic Status (HOUSES) derived from real property data was used. Logistic regression models were used to examine the association of the prevalence of chronic diseases with ethnicity and HOUSES score and their interaction. RESULTS We identified 88,010 eligible adults with HOUSES scores available, of whom 48,086 (54.6%) were female and 80,699 (91.7%) were non-Hispanic white; the median (interquartile range) age was 45 years (30-58 years). Overall and in the subgroup of non-Hispanic whites, SES measured by HOUSES was inversely associated with the prevalence of all 5 chronic diseases independent of age, sex, and ethnicity (P<.001). While an association of ethnicity with disease prevalence was observed for all the chronic diseases, SES modified the effect of ethnicity for clinically less overt conditions (interaction P<.05 for each condition [diabetes, hypertension, and mood disorder]) but not for coronary heart disease, a clinically more overt condition. CONCLUSION In a mixed rural-urban setting with a predominantly non-Hispanic white population, health disparities in chronic diseases still exist across SES. The extent to which SES modifies the effect of ethnicity on the risk of chronic diseases may depend on the nature of the disease.

Clinical documentation variations and NLP system portability: a case study in asthma birth cohorts across institutions

Abstract Objective To assess clinical documentation variations across health care institutions using different electronic medical record systems and investigate how they affect natural language processing (NLP) system portability. Materials and Methods Birth cohorts from Mayo Clinic and Sanford Children’s Hospital (SCH) were used in this study (n = 298 for each). Documentation variations regarding asthma between the 2 cohorts were examined in various aspects: (1) overall corpus at the word level (ie, lexical variation), (2) topics and asthma-related concepts (ie, semantic variation), and (3) clinical note types (ie, process variation). We compared those statistics and explored NLP system portability for asthma ascertainment in 2 stages: prototype and refinement. Results There exist notable lexical variations (word-level similarity = 0.669) and process variations (differences in major note types containing asthma-related concepts). However, semantic-level corpora were relatively homogeneous (topic similarity = 0.944, asthma-related concept similarity = 0.971). The NLP system for asthma ascertainment had anF-score of 0.937 at Mayo, and produced 0.813 (prototype) and 0.908 (refinement) when applied at SCH. Discussion The criteria for asthma ascertainment are largely dependent on asthma-related concepts. Therefore, we believe that semantic similarity is important to estimate NLP system portability. As the Mayo Clinic and SCH corpora were relatively homogeneous at a semantic level, the NLP system, developed at Mayo Clinic, was imported to SCH successfully with proper adjustments to deal with the intrinsic corpus heterogeneity.

Ascertainment of asthma prognosis using natural language processing from electronic medical records

NLP algorithm successfully determined asthma prognosis (i.e., no remission, long-term remission, and intermittent remission) by taking into account asthma symptoms documented in EMR, and addressed the limitations of billing code-based asthma outcome assessment.

Usefulness of asthma predictive index in ascertaining asthma status of children using medical records: An explorative study

Frequent wheezing in original asthma predictive index (API) was defined by parental report of recurrent wheezing within 1 year during the first 3 years of life. The nature of frequent wheezing in children, particularly aged over 3 years, has not been studied. We aimed to assess the frequency and interval of wheezing to define frequent wheezing in ascertaining asthma for children using medical records.