Dataset Information

Identifying disparities in patient-centered care experiences between non-Latino white and black men: results from the 2008-2016 Medical Expenditure Panel Survey.

ABSTRACT:

Background

Patient-centered healthcare in the context of a medical home (PCMH) is an important pathway to reducing healthcare inequities. To date, no work has examined the prevalence of care experiences associated with PCMH among non-elderly Black males.

Methods

We analyzed data, on 22 indicators representative of six healthcare domains associated with PCMH experiences, from non-Latino White (NLW) and Black males aged 18-64 from the 2008-2016 Medical Expenditure Panel Survey (n?=?47,405). We used generalized linear models to test whether Behavioral Model factors attenuate any differences in access to these domains between NLW and Black males, and decomposition techniques to examine the contribution of these factors to reported differences.

Results

Black males reported 1) lower access to personal primary care providers, 2) poorer quality communication with providers, and 3) lower levels of care comprehensiveness (all p?ConclusionsBlack men, in the U.S, continue to face barriers to accessing high quality, patient-centered care, specifically as it relates to accessing specialty care, medical tests, and patient-provider communication.

SUBMITTER: Mitchell JA

PROVIDER: S-EPMC7268709 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying disparities in patient-centered care experiences between non-Latino white and black men: results from the 2008-2016 Medical Expenditure Panel Survey.

Mitchell Jamie A JA Williams Ed-Dee G EG Li Yuyi Y Tarraf Wassim W

BMC health services research 20200603 1

<h4>Background</h4>Patient-centered healthcare in the context of a medical home (PCMH) is an important pathway to reducing healthcare inequities. To date, no work has examined the prevalence of care experiences associated with PCMH among non-elderly Black males.<h4>Methods</h4>We analyzed data, on 22 indicators representative of six healthcare domains associated with PCMH experiences, from non-Latino White (NLW) and Black males aged 18-64 from the 2008-2016 Medical Expenditure Panel Survey (n = ...[more]

PMID: 32493469

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Project description:There is a growing emphasis on the need to engage patients in order to improve the quality of health care and improve health outcomes. However, we are still lacking a comprehensive understanding on how different measures of patient experiences interact with one another or relate to health status. This study takes a network perspective to 1) study the associations between patient characteristics and patient experience in health care and 2) identify factors that could be prioritized to improve health status.This study uses data from the two-year panels from the Medical Expenditure Panel Survey (MEPS) initiated between 2004 and 2011 in the United States. The 88 variables regarding patient health and experience with health care were identified through the MEPS documentation. Sex, age, race/ethnicity, and years of education were also included for analysis. The bnlearn package within R (v3.20) was used to 1) identify the structure of the network of variables, 2) assess the model fit of candidate algorithms, 3) cross-validate the network, and 4) fit conditional probabilities with the given structure.There were 51,023 MEPS interviewees aged 18 to 85 years (mean = 44, 95% CI = 43.9 to 44.2), with years of education ranging from 1 to 19 (mean = 7.4, 95% CI = 7.40 to 7.46). Among all, 55% and 74% were female and white, respectively. There were nine networks identified and 17 variables not linked to others, including death in the second years, sex, entry years to the MEPS, and relations of proxies. The health status in the second years was directly linked to that in the first years. The health care ratings were associated with how often professionals listened to them and whether professionals' explanation was understandable.It is feasible to construct Bayesian networks with information on patient characteristics and experiences in health care. Network models help to identify significant predictors of health care quality ratings. With temporal relationships established, the structure of the variables can be meaningful for health policy researchers, who search for one or a few key priorities to initiate interventions or health care quality improvement programs.

Dataset Information

Identifying disparities in patient-centered care experiences between non-Latino white and black men: results from the 2008-2016 Medical Expenditure Panel Survey.

Background

Methods

Results

Publications

Identifying disparities in patient-centered care experiences between non-Latino white and black men: results from the 2008-2016 Medical Expenditure Panel Survey.

Similar Datasets

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