» Articles » PMID: 8043732

Illiteracy Among Medicaid Recipients and Its Relationship to Health Care Costs

Overview
Date 1994 Jan 1
PMID 8043732
Citations 60
Authors
Affiliations
Soon will be listed here.
Abstract

Poor literacy is associated with poor health status, but whether illiteracy is also linked to higher medical care costs is unclear. We characterized the literacy skills of 402 randomly selected adult Medicaid enrollees to determine if there was an association between literacy skills and health care costs. Each subject's literacy skills were measured with a bilingual (English/Spanish) reading-assessment instrument. We also reviewed each subject's health care costs over the same one-year period. The mean reading level of this Medicaid population was at grade 5.6. Mean annual health care costs were $4,574 per person. There was no significant relationship between literacy and health care costs. While there are compelling reasons to improve poor reading skills among Medicaid enrollees, illiteracy in this population does not appear to contribute to the high cost of providing government-sponsored care.

Citing Articles

Association of Primary Care Access with Health-Related ChatGPT Use: A National Cross-Sectional Survey.

Ayo-Ajibola O, Julien C, Lin M, Riddell J, Duan N, Kravitz R J Gen Intern Med. 2025; .

PMID: 39930155 DOI: 10.1007/s11606-025-09406-9.


Awareness of lung cancer among urban residents in Sichuan Province and its impact on their willingness to choose medical institutions for cancer screening.

Chai Q, Li R, Bao T, Yang Z, Liu Q, Chen F Front Public Health. 2025; 12():1388140.

PMID: 39850860 PMC: 11756509. DOI: 10.3389/fpubh.2024.1388140.


Both English- and Spanish-Language Anterior Cruciate Ligament Reconstruction Online Patient Education Materials Are Written at Higher-Than-Recommended Reading Levels.

Ghahremani J, Chapek M, Xie V, Watarastaporn T, Al-Khatib N, Navarro R Arthrosc Sports Med Rehabil. 2025; 6(6):100982.

PMID: 39776507 PMC: 11701936. DOI: 10.1016/j.asmr.2024.100982.


Evaluating the quality and readability of ChatGPT-generated patient-facing medical information in rhinology.

Fazilat A, Brenac C, Kawamoto-Duran D, Berry C, Alyono J, Chang M Eur Arch Otorhinolaryngol. 2024; .

PMID: 39724239 DOI: 10.1007/s00405-024-09180-0.


Accuracy of Prospective Assessments of 4 Large Language Model Chatbot Responses to Patient Questions About Emergency Care: Experimental Comparative Study.

Yau J, Saadat S, Hsu E, Murphy L, Roh J, Suchard J J Med Internet Res. 2024; 26:e60291.

PMID: 39496149 PMC: 11574488. DOI: 10.2196/60291.