Spatial cluster detection for repeatedly measured outcomes while accounting for residential history

The Use of Geographic Data to Improve Asthma Care Delivery and Population Health

The authors examine uses of geographic data to improve asthma care delivery and population health and describe potential practice changes and areas for future research.

The utility of EMR address histories for assessing neighborhood exposures

PURPOSE

Electronic medical records (EMRs) include residential address histories, which may alleviate exposure misclassification caused by exclusion of patient spatiotemporal location. EMR data are increasingly available but rarely leveraged as a measure of cumulative environmental exposure, in part due to limited understanding of the validity of EMR-derived address histories.

METHODS

We compared EMR address histories to self-reported histories among 100 patients of a safety-net health care system completing a telephone survey. We assessed agreement and compared seven neighborhood-level environmental exposures as assessed using both data sources.

RESULTS

While 17.1% of respondents did not live at the most recent EMR-derived address during the survey, nearly all (98%) lived there at some point. For respondents with more than one EMR-derived address (N = 64), 87.5% had once lived at the previous EMR address. Of these, 30.4% lived at 1 or more additional residences between the two most recent EMR address. For all measures, neighborhood-level environmental exposures did not differ when using EMR-derived versus self-report addresses.

CONCLUSIONS

More recent EMR-derived addresses are more accurate, and differences compared to self-reported addresses in neighborhood-level exposures are negligible. EMR-derived address histories are incomplete and likely suffer from collection bias; future research should further assess their validity and reliability.

Bayesian importance parameter modeling of misaligned predictors: soil metal measures related to residential history and intellectual disability in children

In this paper, we propose a novel spatial importance parameter hierarchical logistic regression modeling approach that includes measurement error from misalignment. We apply this model to study the relationship between the estimated concentration of soil metals at the residence of mothers and the development of intellectual disability (ID) in their children. The data consist of monthly computerized claims data about the prenatal experience of pregnant women living in nine areas within South Carolina and insured by Medicaid during January 1, 1996 and December 31, 2001 and the outcome of ID in their children during early childhood. We excluded mother-child pairs if the mother moved to an unknown location during pregnancy. We identified an association of the ID outcome with arsenic (As) and mercury (Hg) concentration in soil during pregnancy, controlling for infant sex, maternal race, mother's age, and gestational weeks at delivery. There is some indication that Hg has a slightly higher importance in the third and fourth months of pregnancy, while As has a more uniform effect over all the months with a suggestion of a slight increase in risk in later months.

Spatial Cluster Detection for Longitudinal Outcomes using Administrative Regions

This manuscript proposes a new spatial cluster detection method for longitudinal outcomes that detects neighborhoods and regions with elevated rates of disease while controlling for individual level confounders. The proposed method, CumResPerm, utilizes cumulative geographic residuals through a permutation test to detect potential clusters which are are defined as sets of administrative regions, such as a town, or group of administrative regions. Previous cluster detection methods are not able to incorporate individual level data including covariate adjustment, while still being able to define potential clusters using informative neighborhood or town boundaries. Often it is of interest to detect such spatial clusters because individuals residing in a town may have similar environmental exposures or socioeconomic backgrounds due to administrative reasons, such as zoning laws. Therefore these boundaries can be very informative and more relevant than arbitrary clusters such as the standard circle or square. Application of the CumResPerm method will be illustrated by the Home Allergens and Asthma prospective cohort study analyzing the relationship between area or neighborhood residence and repeated measured outcome, occurrence of wheeze in the last 6 months, while taking into account mobile locations.