scholarly journals Health Insurance Coverage of Permanent Hair Removal in Transgender and Gender-Minority Patients

2020 ◽  
Vol 156 (5) ◽  
pp. 561 ◽  
Author(s):  
Nick Thoreson ◽  
Dustin H. Marks ◽  
J. Klint Peebles ◽  
Dana S. King ◽  
Erica Dommasch
Keyword(s):  
Health Insurance ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Hair Removal ◽  
Gender Minority ◽  
And Gender ◽  
Permanent Hair Removal

scholarly journals Examining gender differentials and determinants of private health insurance coverage in Zambia

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
James Mulenga ◽  
Mulenga C. Mulenga ◽  
Katongo M. C. Musonda ◽  
Chilizani Phiri
Keyword(s):  
Health Insurance ◽  
Rural Areas ◽  
Agricultural Sector ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Healthcare Services ◽  
Probit Regression ◽  
Gender Differentials ◽  
And Gender ◽  
Professional Occupation

Abstract Background Health insurance is an essential aspect of healthcare. This is because it enables the insured to acquire timely and essential healthcare services, besides offering financial protection from catastrophic treatment costs. This paper seeks to establish gender differentials and determinants of health insurance coverage in Zambia. Methods The data used in this study was obtained from the 2018 Zambia Demographic and Health Survey. Data were analyzed using STATA 13.0 software and focused on descriptive and Probit regression analyses. Results The study reveals that for women and men, age, wealth category, education, and professional occupation are positively associated with health insurance while being self-employed in the agricultural sector negatively influences health insurance coverage for both sexes. Other variables have gender-specific effects. For instance, being in marital union and having a clerical occupation increases the probability of having health insurance for women while being in the services, skilled, and unskilled manual occupations increases the probability of having health insurance for men. Further, residing in rural areas reduces the probability of having health insurance for men. Conclusion The study concludes that there are differences in factors that influence health insurance between women and men. Hence, this study highlights the need to enhance health insurance coverage by addressing the different factors that influence health insurance coverage among men and women. These factors include enhancing education, job creation, diversifying insurance schemes, and gender consideration in the design of National Health Insurance Scheme.

scholarly journals Multimorbidity Patterns of Chronic Diseases among Indonesians: Insights from Indonesian National Health Insurance (INHI) Sample Data

2020 ◽  
Vol 17 (23) ◽  
pp. 8900
Author(s):  
Atina Husnayain ◽  
Nopryan Ekadinata ◽  
Dedik Sulistiawan ◽  
Emily Chia-Yu Su
Keyword(s):  
Health Insurance ◽  
Chronic Diseases ◽  
National Health Insurance ◽  
National Health ◽  
Claims Data ◽  
Survey Methods ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Sample Data ◽  
And Gender

Given the increasing burden of chronic diseases in Indonesia, characteristics of chronic multimorbidities have not been comprehensively explored. Therefore, this research evaluated chronic multimorbidity patterns among Indonesians using Indonesian National Health Insurance (INHI) sample data. We included 46 chronic diseases and analyzed their distributions using population-weighted variables provided in the datasets. Results showed that chronic disease patients accounted for 39.7% of total patients who attended secondary health care in 2015–2016. In addition, 43.1% of those were identified as having chronic multimorbidities. Findings also showed that multimorbidities were strongly correlated with an advanced age, with large numbers of patients and visits in all provinces, beyond those on Java island. Furthermore, hypertension was the leading disease, and the most common comorbidities were diabetes mellitus, cerebral ischemia/chronic stroke, and chronic ischemic heart disease. In addition, disease proportions for certain disease dyads differed according to age group and gender. Compared to survey methods, claims data are more economically efficient and are not influenced by recall bias. Claims data can be a promising data source in the next few years as increasing percentages of Indonesians utilize health insurance coverage. Nevertheless, some adjustments in the data structure are accordingly needed to utilize claims data for disease control and surveillance purposes.

scholarly journals Measuring inequity in using routinely collected data in an emergency setting: a systematic review

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
K Morisod ◽  
X Luta ◽  
J Marti ◽  
T Brauchli ◽  
J Spycher ◽  
...  
Keyword(s):  
Systematic Review ◽  
Health Insurance ◽  
Access To Care ◽  
Health Equity ◽  
Hospital Care ◽  
Insurance Coverage ◽  
Health Insurance Coverage ◽  
Health Inequity ◽  
Race Ethnicity ◽  
And Gender

Abstract Background The international literature has highlighted many potential challenges in terms of inequitable access to care. In the last few years, health equity is becoming an increasingly important issue for policymakers, particularly in developed countries. The aim of this systematic review was to find how equity is measured and to identify some of its determinants. Methods We conducted a systematic review on all major databases (Medline Ovid SP, PubMed, Embase and Web of Science), following the PRISMA guidelines. We included published observational studies that reported on health equity and using administrative data, with a focus on emergency and unplanned hospital care. Study selection and data extraction were conducted independently and compared by two reviewers. Results In total, 223 records were screened and 39 articles met the inclusion criteria. Studies come from the United States (US) (23), United Kingdom (6), Canada (4), Australia (2) and some European countries (4). To measure health inequity, most of the studies used at least one of these 4 indicators: hospitalisations for chronic ambulatory care sensitive conditions (or preventable hospitalisations), emergency hospitalisation rate, readmissions or mortality. The most relevant health equity determinants concerned race/ethnicity (19), poverty (17), health insurance coverage (17) and gender (16). Race/ethnicity and gender are important determinants of inequities. Concerning poverty, despite the use of heterogeneous indicators, most of studies showed a socio-economic gradient of access to care. Health insurance coverage was often used but with conflicting results. Conclusions The use of indicators linking primary, emergency and hospital care seems to be particularly relevant to measure health inequity. Race/ethinicity, gender and socio-economic status are clear determinants of inequitable access to care. More studies are needed to explain and analyse the determinants of health equity. Key messages Health equity remains a major issue even for high-income countries health care system. Quantitative data about health equity still are needed to support policymaker’s recommendation.

Health insurance coverage in Minnesota: Trends from 2001 to 2004

2006 ◽  
Author(s):  
April Todd-Malmlov ◽  
Alexander Oftelie ◽  
Kathleen Call ◽  
Jeanette Ziegenfuss
Keyword(s):  
Health Insurance ◽  
Insurance Coverage ◽  
Health Insurance Coverage
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