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The Feasibility of using Electronic Health Records (EHRs) to describe demographic and clinical indicators of Migrant and Seasonal Farmworkers
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Details:
  • Pubmed ID:
    26479964
  • Pubmed Central ID:
    PMC4744472
  • Description:
    Few extensive, national clinical databases exist on the health of migrant and seasonal farmworkers (MSFWs). Electronic health records (EHRs) are increasingly utilized by Federally Qualified Health Centers (FQHCs) and have the potential to improve clinical care and complement current surveillance and epidemiologic studies of underserved working populations, such as MSFWs. The aim of this feasibility study was to describe the demographics and baseline clinical indicators of patients at an FQHC by MSFW status. The authors described 2012 patient demographics, social history, medical indicators, and diagnoses by MSFW status from the de-identified EHR database of a large, multisite Colorado Migrant Health Center (MHC). Included in the study were 41,817 patients from 2012: 553 (1.3%) MSFWs, 20,665 (49.4%) non-MSFWs, and 20,599 (49.3%) who had no information in the MSFW field. MSFWs were more often male, married, employed, Hispanic, and Spanish-speaking compared with non-MSFWs. The most frequent diagnoses for all patients were hypertension, overweight/obesity, lipid disorder, type 2 diabetes, or a back disorder. Although there were significant missing values, this feasibility study was able to analyze medical data in a timely manner and show that Meaningful Use requirements can improve the usability of EHR data for epidemiologic research of MSFWs and other patients at FQHCs. The results of this study were consistent with current literature available for MSFWs. By reaching this vulnerable working population, EHRs may be a key data source for occupational injury and illness surveillance and research.

  • Document Type:
  • Collection(s):
  • Funding:
    RC4 ES019405/ES/NIEHS NIH HHS/United States
    T42 OH008421/OH/NIOSH CDC HHS/United States
    U50 OH007541/OH/NIOSH CDC HHS/United States
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