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Record W270606572

Perceived Disparities in Access to Health Care Due to Cost for Women with Disabilities

2009· article· en· W270606572 on OpenAlexaboutno aff
Diane L. Smith, Maribeth S. Ruiz

Bibliographic record

VenueJournal of rehabilitation · 2009
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealthcare Policy and Management
Canadian institutionsnot available
Fundersnot available
KeywordsHealth careWheelchairPopulationBusinessService providerMedicineUniversal designPublic healthNursingFamily medicineService (business)Environmental healthMarketingPolitical science
DOInot available

Abstract

fetched live from OpenAlex

Individuals with disabilities tend to have more health care access problems, have secondary health conditions, have unmet health care needs, and are less likely to be satisfied with medical care than those without disabilities (Batavia, 1995; Hagglund, Clark, Conforti, & Shigaki, 1999). With nearly 20% of the US population with one or more disabilities, there is a great need to address the barriers that prevent this population from accessing the health care services, such as physician services, that they require (US Bureau of Census, 2006). Scheer, Kroll, Neri and Beatty (2003) defined three broad categories of barriers to health care services: environmental, structural, and process. Environmental barriers include issues of office accessibility, such as parking, entry, restrooms, waiting rooms, examination rooms, and diagnostic equipment. Physician's offices have been noted to lack equipment and space essential for treatment of patients using wheelchairs. Many offices are without adequate room to maneuver a wheelchair, use examination tables that are too high, and do not have sit-in scales (DeJong, 1997). Transportation barriers such as the lack of access to public transportation, publicly funded door-to door transportation, and taxicab services, also have an effect on the perceived accessibility of health care services (Scheer et al., 2003). Structural barriers refer to a lack of financial resources for necessary services. Process barriers relate to the delivery of service. For example, lack of provider knowledge and lack of timeliness of service are issues frequently reported by patients. Provider attitudes have also been cited as a barrier to accessing services (Au & Man, 2006) Cost as a Barrier to Health Care Access Addressing structural barriers specifically, Sheer and colleagues (2003) argue that limited health benefit programs, whether publicly or privately funded, may not provide for services such as physical and occupational therapy, high quality and well-fitted functional durable medical equipment, and mental health services. In addition, a considerable proportion of people with disabilities report serious problems accessing prescription drugs (32%), dental care (29%), equipment (21%), mental health services (17%), and home care (16%) due to cost (Kennedy & Erb, 2002; Schultz, Shenkin, & Horowitz, 1998). Barriers to Physician Services for Women with Disabilities There is a limited but growing body of research focused on health care disparities faced by women with disabilities. According to a study by Parish and Huh (2006), women with disabilities experience poorer health and preventive care than women without disabilities. Results of this study revealed that 19 percent of women with disabilities postponed such care compared with the 8 percent of women without disabilities. Additionally, 20 percent of women with disabilities postponed getting needed medications compared to 6 percent of women without disabilities A study by Parish and Ellison-Martin (2007) examined a national sample of low-income female Medicaid recipients and found that despite having similar potential for care (i.e., health insurance, usual source of care, and having a physician as a usual source of care) compared to women without disabilities, women with disabilities had substantially worse rates of receiving medical care and medication when they were needed. In a study utilizing a national publicly available dataset, Smith (2008) found that women with disabilities had less access to health care than women without disabilities and men with disabilities. Chevarley, Theirry, Gill, Ryerson, and Nosek (2006) found that women with three or more functional limitations were more likely to report being unable to get general medical care, dental care, prescription medicines, or eyeglasses compared to women without functional limitations. The primary reason cited for being unable to receive general care were financial problems or limitations in insurance. …

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.692
Threshold uncertainty score0.331

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.044
GPT teacher head0.335
Teacher spread0.291 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations7
Published2009
Admission routes1
Has abstractyes

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