This paper combines SHARE Corona Survey and SHARE Wave 7 data for 25 European countries and Israel (
N
= 40,919) with institutional and epidemic-related country characteristics to investigate ...healthcare access for Europeans aged 50+ during the outbreak of COVID-19. We use a micro–macro approach to examine whether and to what extent barriers to accessing healthcare measured by reported unmet healthcare needs vary within and between countries. We consider various aspects of barriers and distinguish among: (1) respondents who forewent medical treatment because they were afraid of becoming infected with the Coronavirus; (2) respondents who had pre-scheduled medical appointments postponed by health providers due to the outbreak; and (3) respondents who tried to arrange a medical appointment but were denied one. Limited access to healthcare during the initial outbreak was more common for the occupationally active, women, the more educated and those living in urban areas. A bad economic situation, poor overall health and higher healthcare utilisation were robust predictors of unmet healthcare. People aged 50+ in countries of ‘Old’ Europe, countries with higher universal health coverage and stricter containment and closure policies were more likely to have medical services postponed. Policymakers should address the healthcare needs of older people with chronic health conditions and a poor socio-economic status who were made more vulnerable by this pandemic. In the aftermath of the health crisis, public health systems might experience a great revival in healthcare demand, a challenge that should be mitigated by careful planning and provision of healthcare services.
The COVID-19 pandemic posed a major threat to the well-being of older Europeans. Its economic and social effects, however, varied across countries. This multidisciplinary book presents the first ...results of analyses that combined the renowned longitudinal database of SHARE with new data from two telephone surveys that were uniquely conducted during the pandemic. The analyses address important policy-related issues, such as: Did social distancing destabilize family and social support networks? Did the pandemic increase health, social and economic inequality? Who had to forego essential health care because of the pandemic? Did lockdown affect one’s physical and mental health? Did the shift towards remote work affect workload and well-being? Were different housing conditions related to the spread of the virus? ; The COVID-19 pandemic posed a major threat to the well-being of older Europeans. Its economic and social effects, however, varied across countries. This multidisciplinary book presents the first results of analyses that combined the renowned longitudinal database of SHARE with new data from two telephone surveys that were uniquely conducted during the pandemic. The analyses address important policy-related issues, such as: Did social distancing destabilize family and social support networks? Did the pandemic increase health, social and economic inequality? Who had to forego essential health care because of the pandemic? Did lockdown affect one’s physical and mental health? Did the shift towards remote work affect workload and well-being? Were different housing conditions related to the spread of the virus?
Pandemics such as the COVID-19 pandemic and other severe health care disruptions endanger individuals to miss essential care. Machine learning models that predict which patients are at greatest risk ...of missing care visits can help health administrators prioritize retentions efforts towards patients with the most need. Such approaches may be especially useful for efficiently targeting interventions for health systems overburdened during states of emergency.
We use data on missed health care visits from over 55,500 respondents of the Survey of Health, Ageing and Retirement in Europe (SHARE) COVID-19 surveys (June - August 2020 and June - August 2021) with longitudinal data from waves 1-8 (April 2004 - March 2020). We compare the performance of four machine learning algorithms (stepwise selection, lasso, random forest, and neural networks) to predict missed health care visits during the first COVID-19 survey based on common patient characteristics available to most health care providers. We test the prediction accuracy, sensitivity, and specificity of the selected models for the first COVID-19 survey by employing 5-fold cross-validation, and test the out-of-sample performance of the models by applying them to the data from the second COVID-19 survey.
Within our sample, 15.5% of the respondents reported any missed essential health care visit due to the COVID-19 pandemic. All four machine learning methods perform similarly in their predictive power. All models have an area under the curve (AUC) of around 0.61, outperforming random prediction. This performance is sustained for data from the second COVID-19 wave one year later, with an AUC of 0.59 for men and 0.61 for women. When classifying all men (women) with a predicted risk of 0.135 (0.170) or higher as being at risk of missing care, the neural network model correctly identifies 59% (58%) of the individuals with missed care visits, and 57% (58%) of the individuals without missed care visits. As the sensitivity and specificity of the models are strongly related to the risk threshold used to classify individuals, the models can be calibrated depending on users' resource constraints and targeting approach.
Pandemics such as COVID-19 require rapid and efficient responses to reduce disruptions in health care. Based on characteristics available to health administrators or insurance providers, simple machine learning algorithms can be used to efficiently target efforts to reduce missed essential care.
While we know that living alone is often associated with greater risk of financial hardship, we have limited knowledge on the possible link between the availability of public support and independent ...living. We use data from the 2014 Health and Retirement Study and the 2011–2015 Survey of Health, Ageing and Retirement in Europe to compare income and wealth profiles of the population aged 60 and above who are living alone in the United States and 19 European countries. We find that the likelihood of living alone is higher in generous welfare states, with social support and spending both positively associated with living alone. The relationship between personal resources and living alone has a smaller positive gradient in countries with robust welfare systems. The lack of adequate public support in less generous welfare states may constrain the ability of many low-income older adults without a partner to continue living independently.
The aim of this paper is to explore the association between demographic, socioeconomic and physical health variables and self-assessed health (SAH) of people aged 50 years and over in Croatia. ...Cross-sectional data was collected in 2012 in the survey "The Economics of Ageing in Croatia" that was based on the SHARE (Survey of Health Ageing and Retirement in Europe) study. Altogether 761 individuals aged 50 and over were included in the working sample that has been used in statistical analysis. Data were analysed in an ordered logistic regression model. The results show that females were more likely to report a higher category of SAH than males. Higher educational level was a statistically significant predictor of higher SAH, when controlled for other variables. This study, unlike other studies in Croatia, introduces a set of physical health variables as the determinants of health. Our results suggest that people aged 50 and over with fewer limitations, health related symptoms and diagnosed chronic conditions were more likely to report higher levels of SAH. These findings could be beneficial to policymakers in their efforts to improve health among elderly in Croatia.
This study explores the determinants of unmet healthcare needs among older Europeans following the pandemic. Using data from the SHARE study involving 37,225 individuals aged 50 and above, we examine ...the barriers to healthcare access during the COVID-19 pandemic and the utilization of telemedicine. Approximately 15% of older adults reported unmet healthcare needs after the pandemic, while almost one in three utilized telemedicine during that period. Interestingly, those who used telehealth during the pandemic were more likely to report ongoing unmet healthcare needs. Persistent inequalities in healthcare access were observed for women, those living alone, individuals with financial challenges, and in poorer health. While telemedicine played an important role in enhancing healthcare access, its impact was limited, buffering only a part of unmet healthcare needs in the pandemic. Despite challenges in telemedicine adoption among older adults, it remains a promising tool for ensuring healthcare access in future emergencies.
Only a few studies have been conducted so far on the long-term impact of war. We investigated whether a life-long impact of the war experiences could be detected in advanced-agers who have ...successfully overcome all life's challenges. The participants in this study were oldest-old (80+ years) residents of retirement homes in Zagreb (Croatia), who were divided into two groups – ‘war-exposed’ and ‘not-exposed’ – according to their direct war experience (First World War, Second World War, Croatian Homeland War). Within this 1906–1928 birth cohort, a higher percentage of participants with war experiences reached extreme longevity (95+ years). We found no significant difference (p < 0.01) between the two groups concerning demographic and socio-economic characteristics, their life satisfaction, their self-rated current health and functional ability status. Despite numerous similarities, several traits related to life-history, current quality of life, attitudes and reflections distinguish the group of participants with direct war experience. The kind of war involvement – active military service, imprisonment in concentration camps or prisons, forced migration due to war and war-related death of close family members – stretched through various aspects of the life-history features, quality of life and attitudes. It differed for men and women, so it is no wonder that the significance pattern in the two genders mostly seems mutually exclusive. Socio-economic situations strongly differed by gender and according to the kind of war exposure, amplifying the differences within the ‘war-exposed’ group in terms of the life-long impact of wars on their lives. Therefore, we could claim that the war experiences were not the same for everybody, and that they had lasting consequences on the lifecourse of persons who directly faced war-related events. The results also point to the high resilience capacity as a common feature among persons who survived direct exposure to at least two wars and yet survived to exceptionally old age.
This paper investigates how self-rated health (SRH), as a measure of general health, is associated with employment during later working life in Croatia. Using data from Wave 6 of the Survey of ...Health, Ageing and Retirement in Europe (SHARE), we estimate logistic regression models and study whether and to what extent the effects of SRH change with the inclusion of objective health measures. Worse SRH significantly decreases the probability of employment, but this effect becomes insignificant after account is taken of the objective health-related variables. This suggests that in Croatia, SRH and (a combination of) objective health indicators behave as substitutes, and either SRH or objective health measures can be adopted for the study of labour market participation. As worse health lowers the probability of employment during later working life in Croatia, in order to improve the working capacity of older adults, policymakers should strive for more efficient health promotion strategies and public health initiatives.
The COVID-19 pandemic exacerbated issues regarding access to healthcare for older people, by far the most vulnerable population group. In particular, older adults avoided seeking medical treatment ...for fear of infection or had their medical treatments postponed or denied by health facilities or health professionals. In response, remote medical services were recognized as an essential adjustment mechanism to maintain the continuity of healthcare provision. Using the SHARE Corona Survey data, we estimate logistic and multilevel regression models for the remote care of 44,152 persons aged 50 and over in 27 European countries and Israel. Our findings suggest that those aged 80+ were the least likely to use remote healthcare. However, women, better educated individuals, older adults who lived in urban areas, those with no financial strain, and active Internet users used remote medical consultations more often. Those who reported poor or fair health status, two or more chronic diseases, or hospitalization in the last 12 months were significantly more likely to use remote healthcare. Furthermore, remote medical consultations were more frequent for those who had their healthcare postponed or went without it due to fear of coronavirus infection. Finally, older adults used remote care more frequently in countries with less healthcare coverage and lower health expenditures. Health systems should prioritize vulnerable groups in maintaining continuity in access to healthcare, despite the availability of remote care. Policymakers should improve telemedicine regulation and offer incentives for providers of remote healthcare services by adapting reimbursement policies. Remote medical care could play an important role in maintaining healthcare access for older adults and increasing health systems' preparedness in future health emergencies.
PDF
