Rural - Urban Differences in Health Care Quality Assessment

Spasojevic, Nada; Vasilj, Ivan; Hrabac, Boris; Čelik, Damir

doi:10.5455/msm.2015.27.409-411

Cited by 27 publications

(27 citation statements)

References 9 publications

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“…By examining the differences in tweet sentiment between metropolitan and nonmetropolitan areas, we sought to determine if the discussion of care online differs based on population size. We found that metropolitan areas across the United States have higher percent positive tweets compared with nonmetropolitan areas, which supports research on differences in health care in rural populations compared with the care in urban populations [ 7 ]. Metropolitan cities have been found to have better access to care because many have large health care institutions and resources nearby that smaller communities lack [ 7 , 8 ].…”

Section: Discussionsupporting

confidence: 83%

“…Traditional assessments have also documented differences in access to health care [ 5 ]. Research has shown that access to health care varies based on where a patient lives [ 6 , 7 , 8 ]. Patient care is often dependent upon the policies of the state a patient lives in, distance to the nearest health care facilities, and insurance coverage, which varies across the United States.…”

Section: Introductionmentioning

confidence: 99%

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Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

Sewalk¹,

Tuli²,

Hswen³

et al. 2018

J Med Internet Res

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BackgroundThere are documented differences in access to health care across the United States. Previous research indicates that Web-based data regarding patient experiences and opinions of health care are available from Twitter. Sentiment analyses of Twitter data can be used to examine differences in patient views of health care across the United States.ObjectiveThe objective of our study was to provide a characterization of patient experience sentiments across the United States on Twitter over a 4-year period.MethodsUsing data from Twitter, we developed a set of 4 software components to automatically label and examine a database of tweets discussing patient experience. The set includes a classifier to determine patient experience tweets, a geolocation inference engine for social data, a modified sentiment classifier, and an engine to determine if the tweet is from a metropolitan or nonmetropolitan area in the United States. Using the information retrieved, we conducted spatial and temporal examinations of tweet sentiments at national and regional levels. We examined trends in the time of the day and that of the week when tweets were posted. Statistical analyses were conducted to determine if any differences existed between the discussions of patient experience in metropolitan and nonmetropolitan areas.ResultsWe collected 27.3 million tweets between February 1, 2013 and February 28, 2017, using a set of patient experience-related keywords; the classifier was able to identify 2,759,257 tweets labeled as patient experience. We identified the approximate location of 31.76% (876,384/2,759,257) patient experience tweets using a geolocation classifier to conduct spatial analyses. At the national level, we observed 27.83% (243,903/876,384) positive patient experience tweets, 36.22% (317,445/876,384) neutral patient experience tweets, and 35.95% (315,036/876,384) negative patient experience tweets. There were slight differences in tweet sentiments across all regions of the United States during the 4-year study period. We found the average sentiment polarity shifted toward less negative over the study period across all the regions of the United States. We observed the sentiment of tweets to have a lower negative fraction during daytime hours, whereas the sentiment of tweets posted between 8 pm and 10 am had a higher negative fraction. Nationally, sentiment scores for tweets in metropolitan areas were found to be more extremely negative and mildly positive compared with tweets in nonmetropolitan areas. This result is statistically significant (P<.001). Tweets with extremely negative sentiments had a medium effect size (d=0.34) at the national level.ConclusionsThis study presents methodologies for a deeper understanding of Web-based discussion related to patient experience across space and time and demonstrates how Twitter can provide a unique and unsolicited perspective from users on the health care they receive in the United States.

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Section: Discussionsupporting

confidence: 83%

Section: Introductionmentioning

confidence: 99%

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

Sewalk¹,

Tuli²,

Hswen³

et al. 2018

J Med Internet Res

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“…Previous evidence shows significant differences in availability and provision of health care between urban and rural health facilities [ 44 , 47 , 49 ]. This is supported by the current study, which found that the odds of preparedness for outpatient HTN treatment are higher among urban health facilities compared to rural health facilities.…”

Section: Discussionmentioning

confidence: 99%

Preparedness of lower-level health facilities and the associated factors for the outpatient primary care of hypertension: Evidence from Tanzanian national survey

Bintabara

Mpondo

2018

PLoS ONE

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IntroductionSub-Saharan Africa is experiencing a rapid rise in the burden of non-communicable diseases in both urban and rural areas. Data on health system preparedness to manage hypertension and other non-communicable diseases remains scarce. This study aimed to assess the preparedness of lower-level health facilities for outpatient primary care of hypertension in Tanzania.MethodsThis study used data from the 2014–2015 Tanzania Service Provision Assessment survey. The facility was considered as prepared for the outpatient primary care of hypertension if reported at least half (≥50%) of the items listed from each of the three domains (staff training and guideline, basic diagnostic equipment, and basic medicines) as identified by World Health Organization-Service Availability and Readiness Assessment manual. Data were analyzed using Stata 14. An unadjusted logistic regression model was used to assess the association between outcome and explanatory variables. All variables with a P value < 0.2 were fitted into the multiple logistic regression models using a 5% significance level.ResultsOut of 725 health facilities involved in the current study, about 68% were public facilities and 73% located in rural settings. Only 28% of the assessed facilities were considered prepared for the outpatient primary care of hypertension. About 9% and 42% of the assessed facilities reported to have at least one trained staff and guidelines for hypertension respectively. In multivariate analysis, private facilities [AOR = 2.7, 95% CI; 1.2–6.1], urban location [AOR = 2.2, 95% CI; 1.2–4.2], health centers [AOR = 5.2, 95% CI; 3.1–8.7] and the performance of routine management meetings [AOR = 2.6, 95% CI; 1.1–5.9] were significantly associated with preparedness for the outpatient primary care of hypertension.ConclusionThe primary healthcare system in Tanzania is not adequately equipped to cope with the increasing burden of hypertension and other non-communicable diseases. Rural location, public ownership, and absence of routine management meetings were associated with being not prepared. There is a need to strengthen the primary healthcare system in Tanzania for better management of chronic diseases and curb their rising impact on health outcomes.

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“…In the bivariate analysis, the association between place of residence (urban and rural) and socio-economic variables such as age, region, education, wealth index, type of facility were analyzed to examine possible statistical implications. There were significant statistical association based on the type of residence (urban or rural) and region, wealth index, level of educational attainment and type of healthcare facility accessed [ 22 ].…”

Section: Discussionmentioning

confidence: 99%

Urban-rural difference in satisfaction with primary healthcare services in Ghana

Yaya

Bishwajit

Ekholuenetale

et al. 2017

BMC Health Serv Res

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Background: Understanding regional variation in patient satisfaction about healthcare systems (PHCs) on the quality of services provided is instrumental to improving quality and developing a patient-centered healthcare system by making it more responsive especially to the cultural aspects of health demands of a population. Reaching to the innovative National Health Insurance Scheme (NHIS) in Ghana, surpassing several reforms in healthcare financing has been a milestone. However, the focus of NHIS is on the demand side of healthcare delivery. Studies focusing on the supply side of healthcare delivery, particularly the quality of service as perceived by the consumers are required. A growing number of studies have focused on regional differences of patient satisfaction in developed countries, however little research has been conducted concerning patient satisfaction in resource-poor settings like in Ghana. This study was therefore dedicated to examining the variation in satisfaction across rural and urban women in Ghana. Methods: Data for the present study were obtained from the latest demographic and health survey in Ghana (GDHS 2014). Participants were 3576 women aged between 15 and 49 years living in non-institutional settings in Ghana. Summary statistics in percentages was used to present respondents' demographic, socioeconomic characteristics. Chisquare test was used to find association between urban-rural differentials with socio-economic variables. Multiple logistic regression was performed to measure the association of being satisfied with primary healthcare services with study variables. Model fitness was tested by pseudo R

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Rural - Urban Differences in Health Care Quality Assessment

Cited by 27 publications

References 9 publications

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

Using Twitter to Examine Web-Based Patient Experience Sentiments in the United States: Longitudinal Study

Preparedness of lower-level health facilities and the associated factors for the outpatient primary care of hypertension: Evidence from Tanzanian national survey

Urban-rural difference in satisfaction with primary healthcare services in Ghana

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