Social disadvantage, healthcare utilization, and colorectal cancer screening

Leveraging longitudinal patient address and health records data

Amy E. Hughes, Jasmin A Tiro, Bijal A. Balasubramanian, Celette S Skinner, Sandi Pruitt

Research output: Contribution to journalArticle

Abstract

Background: Social disadvantage predicts colorectal cancer outcomes across the cancer care continuum for many populations and places. For medically underserved populations, social disadvantage is likely intersectional—affecting individuals at multiple levels and through membership in multiple disadvantaged groups. However, most measures of social disadvantage are cross-sectional and limited to race, ethnicity, and income. Linkages between electronic health records (EHR) and external datasets offer rich, multilevel measures that may be more informative. Methods: We identified urban safety-net patients eligible and due for colorectal cancer screening from the Parkland-UT Southwestern PROSPR cohort. We assessed one-time screening receipt (via colonoscopy or fecal immunochemical test) in the 18 months following cohort entry via the EHR. We linked EHR data to housing and Census data to generate measures of social disadvantage at the parcel- and block-group level. We evaluated the association of these measures with screening using multilevel logistic regression models controlling for sociodemographics, comorbidity, and healthcare utilization. Results: Among 32,965 patients, 45.1% received screening. In adjusted models, residential mobility, residence type, and neighborhood majority race were associated with colorectal cancer screening. Nearly all measures of patient-level social disadvantage and healthcare utilization were significant. Conclusions: Address-based linkage of EHRs to external datasets may have the potential to expand meaningful measurement of multilevel social disadvantage. Researchers should strive to use granular, specific data in investigations of social disadvantage. Impact: Generating multilevel measures of social disadvantage through address-based linkages efficiently uses existing EHR data for applied, population-level research.

Original languageEnglish (US)
Pages (from-to)1424-1432
Number of pages9
JournalCancer Epidemiology Biomarkers and Prevention
Volume27
Issue number12
DOIs
StatePublished - Dec 1 2018

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Electronic Health Records
Early Detection of Cancer
Colorectal Neoplasms
Delivery of Health Care
Health
Vulnerable Populations
Logistic Models
Continuity of Patient Care
Population Dynamics
Censuses
Colonoscopy
Patient Safety
Population
Comorbidity
Research Personnel
Research
Neoplasms
Datasets

ASJC Scopus subject areas

  • Epidemiology
  • Oncology

Cite this

@article{96db54d65e1343ea9a096a07dd8a74aa,
title = "Social disadvantage, healthcare utilization, and colorectal cancer screening: Leveraging longitudinal patient address and health records data",
abstract = "Background: Social disadvantage predicts colorectal cancer outcomes across the cancer care continuum for many populations and places. For medically underserved populations, social disadvantage is likely intersectional—affecting individuals at multiple levels and through membership in multiple disadvantaged groups. However, most measures of social disadvantage are cross-sectional and limited to race, ethnicity, and income. Linkages between electronic health records (EHR) and external datasets offer rich, multilevel measures that may be more informative. Methods: We identified urban safety-net patients eligible and due for colorectal cancer screening from the Parkland-UT Southwestern PROSPR cohort. We assessed one-time screening receipt (via colonoscopy or fecal immunochemical test) in the 18 months following cohort entry via the EHR. We linked EHR data to housing and Census data to generate measures of social disadvantage at the parcel- and block-group level. We evaluated the association of these measures with screening using multilevel logistic regression models controlling for sociodemographics, comorbidity, and healthcare utilization. Results: Among 32,965 patients, 45.1{\%} received screening. In adjusted models, residential mobility, residence type, and neighborhood majority race were associated with colorectal cancer screening. Nearly all measures of patient-level social disadvantage and healthcare utilization were significant. Conclusions: Address-based linkage of EHRs to external datasets may have the potential to expand meaningful measurement of multilevel social disadvantage. Researchers should strive to use granular, specific data in investigations of social disadvantage. Impact: Generating multilevel measures of social disadvantage through address-based linkages efficiently uses existing EHR data for applied, population-level research.",
author = "Hughes, {Amy E.} and Tiro, {Jasmin A} and Balasubramanian, {Bijal A.} and Skinner, {Celette S} and Sandi Pruitt",
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T1 - Social disadvantage, healthcare utilization, and colorectal cancer screening

T2 - Leveraging longitudinal patient address and health records data

AU - Hughes, Amy E.

AU - Tiro, Jasmin A

AU - Balasubramanian, Bijal A.

AU - Skinner, Celette S

AU - Pruitt, Sandi

PY - 2018/12/1

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N2 - Background: Social disadvantage predicts colorectal cancer outcomes across the cancer care continuum for many populations and places. For medically underserved populations, social disadvantage is likely intersectional—affecting individuals at multiple levels and through membership in multiple disadvantaged groups. However, most measures of social disadvantage are cross-sectional and limited to race, ethnicity, and income. Linkages between electronic health records (EHR) and external datasets offer rich, multilevel measures that may be more informative. Methods: We identified urban safety-net patients eligible and due for colorectal cancer screening from the Parkland-UT Southwestern PROSPR cohort. We assessed one-time screening receipt (via colonoscopy or fecal immunochemical test) in the 18 months following cohort entry via the EHR. We linked EHR data to housing and Census data to generate measures of social disadvantage at the parcel- and block-group level. We evaluated the association of these measures with screening using multilevel logistic regression models controlling for sociodemographics, comorbidity, and healthcare utilization. Results: Among 32,965 patients, 45.1% received screening. In adjusted models, residential mobility, residence type, and neighborhood majority race were associated with colorectal cancer screening. Nearly all measures of patient-level social disadvantage and healthcare utilization were significant. Conclusions: Address-based linkage of EHRs to external datasets may have the potential to expand meaningful measurement of multilevel social disadvantage. Researchers should strive to use granular, specific data in investigations of social disadvantage. Impact: Generating multilevel measures of social disadvantage through address-based linkages efficiently uses existing EHR data for applied, population-level research.

AB - Background: Social disadvantage predicts colorectal cancer outcomes across the cancer care continuum for many populations and places. For medically underserved populations, social disadvantage is likely intersectional—affecting individuals at multiple levels and through membership in multiple disadvantaged groups. However, most measures of social disadvantage are cross-sectional and limited to race, ethnicity, and income. Linkages between electronic health records (EHR) and external datasets offer rich, multilevel measures that may be more informative. Methods: We identified urban safety-net patients eligible and due for colorectal cancer screening from the Parkland-UT Southwestern PROSPR cohort. We assessed one-time screening receipt (via colonoscopy or fecal immunochemical test) in the 18 months following cohort entry via the EHR. We linked EHR data to housing and Census data to generate measures of social disadvantage at the parcel- and block-group level. We evaluated the association of these measures with screening using multilevel logistic regression models controlling for sociodemographics, comorbidity, and healthcare utilization. Results: Among 32,965 patients, 45.1% received screening. In adjusted models, residential mobility, residence type, and neighborhood majority race were associated with colorectal cancer screening. Nearly all measures of patient-level social disadvantage and healthcare utilization were significant. Conclusions: Address-based linkage of EHRs to external datasets may have the potential to expand meaningful measurement of multilevel social disadvantage. Researchers should strive to use granular, specific data in investigations of social disadvantage. Impact: Generating multilevel measures of social disadvantage through address-based linkages efficiently uses existing EHR data for applied, population-level research.

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