Geographic Variation in Health Insurance Coverage: United States, 2020

This report presents state, regional, and national estimates of the percentage of people who were uninsured, had private health insurance coverage, and had public health insurance coverage at the time of the interview.

A budget impact analysis of substituting sitagliptin with liraglutide in type 2 diabetes from a private health insurance perspective in Egypt

Introduction Type 2 diabetes mellitus causes a sizable burden globally from both health and economic points of view. This study aimed to assess the budget impact of substituting sitagliptin with liraglutide versus other glucose-lowering drugs from the private health insurance perspective in Egypt over a 3-year time horizon. Methods Two budget impact models were compared with the standard of care (metformin, pioglitazone, gliclazide, insulin glargine, repaglinide, and empagliflozin) administered in addition to liraglutide or sitagliptin versus the standard of care with placebo. A gradual market introduction of liraglutide or sitagliptin was assumed, and the existing market shares for the other glucose-lowering drugs were provided and validated by the Expert Panel. The event rates were extracted from the LEADER and TECOS trials. Direct and mortality costs were measured. Sensitivity analyses were performed. Results The estimated target population of 120,574 type 2 diabetic adult patients was associated with cardio vascular risk. The budget impact per patient per month for liraglutide is EGP29 ($6.7), EGP39 ($9), and EGP49 ($11.3) in the 1st, 2nd, and 3rd years, respectively. The budget impact per patient per month for sitagliptin is EGP11 ($2.5), EGP14 ($3.2), and EGP18 ($4.1) in the 1st, 2nd, and 3rd years, respectively. Furthermore, adoption of liraglutide resulted in 203 fewer deaths and 550 avoided hospitalizations, while sitagliptin resulted in 43 increased deaths and 14 avoided hospitalizations. The treatment costs of liraglutide use are mostly offset by substantial savings due to fewer cardiovascular-related events, avoided mortality and avoided hospitalizations over 3 years. Conclusion Adding liraglutide resulted in a modest budget impact, suggesting that the upfront drug costs were offset by budget savings due to fewer cardiovascular-related complications and deaths avoided compared to the standard of care. Sitagliptin resulted in a small budget impact but was associated with increased deaths and fewer hospitalizations avoided.

Impact of Gender and Age on Claim Rates of Dread Disease and Cancer Insurance Policies in Taiwan

In this paper, the impact of both gender and age on the claim rates of dread disease and cancer insurance policies were examined using unique data taken from Taiwan’s private health insurance policies issued by non-life insurers during the 2012 to 2015 policy years. Those aged 30–39 served as the reference group. For the total number of dread disease policies, male insureds had a higher non-cancer claim probability than female insureds, while an age under 20 was associated with much lower claim rates for dread disease policies than for ages over 50. The claim rate for dread disease policies increased rapidly beginning at age 40 for both cancerous and non-cancerous diseases amongst male insureds. Amongst female insureds, those under 20 had much lower claim rates for dread disease policies. Only those aged 50–59 had a higher claim rate for non-cancerous diseases. For the total number of cancer insurance policies, male insureds had lower claim rates than female insureds, with an upward trend being associated with age. For male (female) insureds aged over 40 (20), the claim rates of cancer increased with age.

Unobtrusive measures of prejudice: Estimating percentages of public beliefs and behaviours

This study was concerned with how accurate people are in their knowledge of population norms and statistics concerning such things as the economic, health and religious status of a nation and how those estimates are related to their own demography (e.g age, sex), ideology (political and religious beliefs) and intelligence. Just over 600 adults were asked to make 25 population estimates for Great Britain, including religious (church/mosque attendance) and economic (income, state benefits, car/house ownership) factors as well as estimates like the number of gay people, immigrants, smokers etc. They were reasonably accurate for things like car ownership, criminal record, vegetarianism and voting but seriously overestimated numbers related to minorities such as the prevalence of gay people, muslims and people not born in the UK. Conversely there was a significant underestimation of people receiving state benefits, having a criminal record or a private health insurance. Correlations between select variables and magnitude and absolute accuracy showed religiousness and IQ most significant correlates. Religious people were less, and intelligent people more, accurate in their estimates. A factor analysis of the estimates revealed five interpretable factors. Regressions were calculated onto these factors and showed how these individual differences accounted for as much as 14% of the variance. Implications and limitations are acknowledged.

THE DRIVERS OF VOLUNTARY PRIVATE HEALTH INSURANCE DEMAND IN EUROPEAN COUNTRIES

During the pandemic, health care services have gained in importance. One of the ways used to finance these services is through voluntary private health insurance. Existing studies on the demand for voluntary private health insurance are based predominantly on the micro-economic level. Therefore, the aim of this paper is to analyse the factors of demand at the macro-economic level. The analysis covers economic and demographic factors, the quality of the public health care system, risk aversion and the status of the population’s health. The empirical research is based on the databases of 29 European countries in the period from 2013 to 2017 and on the dynamic panel model. The results of the empirical analysis revealed that income, price, urbanization, health care system quality, risk aversion/education and self-perceived health are important determinants of demand for voluntary private health insurance in European countries.

Back to the medical classes-Part I- Strategy for return to the presential practices during COVID-19 pandemics in a Brazilian Medical School

Introduction: In Brazil, practices of medical students have been interrupted due to COVID-19 to meet emergency demands. Aim: To describe a strategy for a controlled return to the presential practices for medical students. Methods: We developed a standardized protocol to be applied before and during the return of the practical classes in medical students of Universidade Federal Fluminense, in the follow months after COVID-19 pandemic beginning. The protocol was comprised in three parts: Remote training on COVID-19 prevention; Face-to-face training focused in COVID-19 prevention, handwashing and personal protective equipment use; Investigation of students COVID-19 status before starting practical activities and weekly monitoring for COVID-19 during seven weeks. The training was done by medical teachers in small groups for medical students of the last lective semester. Results: The classes were interrupted on March 12, 2020 and returned in August 10, 2020. Seventy-one students were trained and followed. The mean age was 26.6 years (26.7 +/- 0.835) and 54% were female. Forty-nine (69%) students over 71 had a private health insurance, 60 (84.5%) shared a house/apartment with one or more person and 12(16.9%) reported a previous comorbidity. Eighteen (25.4%) over 71 reported previous symptoms of COVID-19, being positive in two students. During the follow-up, fourteen (19.7%) over 71 students were placed in quarantine due to signals/symptoms compatible with COVID-19 or contact with symptomatic case. Only two cases (2.8%) were confirmed and occurred in Brazilian epidemiological week 37. Conclusion: The protocol was successful in minimizing COVID-19 acquisition during practical classes of medical students.

Patterns and predictors of smartphone ownership in a cardiology inpatient population

Introduction Mobile health (mHealth) interventions have grown in popularity, particularly for chronic disease management. Uptake of these interventions depends on patient smartphone ownership. Purpose To examine the smartphone ownership rate among cardiac inpatients and identify the associated demographic factors. Methods Between February 2019 and March 2020, 565 patients were screened for potential enrolment in the TeleClinical Care (TCC) pilot study at two hospitals in Australia. All patients had an admission diagnosis of acute coronary syndrome or heart failure. Mobile phone ownership was documented at the time of screening. Retrospectively, each patient's electronic medical record was examined for: age, sex, primary diagnosis, suburb of residence, private health insurance subscription, smoking status and occupation. Continuous variables were analysed using a multinomial logistic regression model. Categorical variables were analysed using a generalised linear model. Results Mobile phone ownership was documented for 523 patients (92.6%). 60.6% of all patients owned smartphones, and 14.9% owned basic mobile phones. 24.5% of patients did not own any mobile phone. The average age of participants was 70.8 years. Smartphone ownership rates were high among patients in the 18–49 (96%), 50–59 (89%) and 60–69 (85%) year groups. The differences between these groups were not statistically significant. In the age group 70–79 years, however, smartphone ownership fell to 56.5% (p<0.001, figure 1). The relative risk (RR) of not owning a smartphone increased by 12% for each additional year of age. Overall, smartphone ownership was less more common in women than men [79/179 (44.1%) vs. 238/344 (69.2%), RR 0.78, 95% CI 0.67–0.91, P=0.003, age-adjusted) driven by a difference in patients aged 70 or above [36/131 (27.5%) vs. 82/168 (48.9%), RR 0.66, 95% 0.49–0.90, p<0.001]. After adjustment for age and sex, patients with a primary diagnosis of ACS were more likely to own a smartphone compared to those with HF [227/316 (71.8%) vs. 90/207 (43.5%), RR 1.22, 95% CI 1.04–1.43, P=0.015]. Patients with private health insurance were more likely to own a smartphone than those who were uninsured [68.9% (162/235) v 54.0% (154/285), RR 1.28, 95% CI 1.13–1.43, P<0.001, figure 2). Smartphone ownership was significantly higher in those who were currently working, compared to those who were retired (117/119, 98.3% vs. 56/87, 64.3%, RR 0.76, 95% CI 0.64 – 0.89, P=0.001), even after adjustment for age. Patients living in the region with lowest average household income had the lowest rate of smartphone ownership (52.4%). There was no significant difference in smartphone ownership based on type of occupation. Conclusion Smartphone ownership was common in this inpatient population. Patients who are older, female and of lower socioeconomic background are less likely to own smartphones, and future mHealth programs should be cognizant of this. FUNDunding Acknowledgement Type of funding sources: Public hospital(s). Main funding source(s): Prince of Wales Hospital, Department of Cardiology Figure 1. Smartphone ownership by age Figure 2. Insurance status