Musculoskeletal Pain Medication Use in Middle Age and Older Adults in 15 European Countries and Israel

Exploring patient medication adherence and data mining methods in clinical big data: A contemporary review

BACKGROUND

Increasingly, patient medication adherence data are being consolidated from claims databases and electronic health records (EHRs). Such databases offer an indirect avenue to gauge medication adherence in our data-rich healthcare milieu. The surge in data accessibility, coupled with the pressing need for its conversion to actionable insights, has spotlighted data mining, with machine learning (ML) emerging as a pivotal technique. Nonadherence poses heightened health risks and escalates medical costs. This paper elucidates the synergistic interaction between medical database mining for medication adherence and the role of ML in fostering knowledge discovery.

METHODS

We conducted a comprehensive review of EHR applications in the realm of medication adherence, leveraging ML techniques. We expounded on the evolution and structure of medical databases pertinent to medication adherence and harnessed both supervised and unsupervised ML paradigms to delve into adherence and its ramifications.

RESULTS

Our study underscores the applications of medical databases and ML, encompassing both supervised and unsupervised learning, for medication adherence in clinical big data. Databases like SEER and NHANES, often underutilized due to their intricacies, have gained prominence. Employing ML to excavate patient medication logs from these databases facilitates adherence analysis. Such findings are pivotal for clinical decision-making, risk stratification, and scholarly pursuits, aiming to elevate healthcare quality.

CONCLUSION

Advanced data mining in the era of big data has revolutionized medication adherence research, thereby enhancing patient care. Emphasizing bespoke interventions and research could herald transformative shifts in therapeutic modalities.

Factors Influencing Self-Reported Medication Use in the Survey of Health Aging and Retirement in Europe (SHARE) Dataset

The validity of self-reported medication use in epidemiological studies is an important issue in healthcare research. Here we investigated factors influencing self-reported medication use for multiple diagnoses in the seventh wave of the Survey of Health Aging and Retirement in Europe (SHARE) dataset in n = 77,261 participants (ages: mean = 68.47, standard deviation = 10.03 years). The influence of mental, physical, and sociodemographic parameters on medication self-report was analyzed with logistic regressions and mediation models. Depression, memory function, and polypharmacy influenced the self-report of medication use in distinct disorders to varying degrees. In addition, sociodemographic factors, knowledge about diagnosis, the presence of several chronic illnesses, and restrictions of daily instrumental activities explained the largest proportion of variance. In the mediation model, polypharmacy had an indirect effect via depression and memory on self-reported medication use. Factors influencing medication self-report vary between different diagnoses, highlighting the complexity of medication knowledge. Therefore, it is essential to assess the individual parameters and their effect on medication behavior. Relying solely on medication self-reports is insufficient, as there is no way to gage their reliability. Thus, self-reported medication intake should be used with caution to indicate the actual medication knowledge and use.

Socioeconomic status and health behaviors as predictors of changes in self-rated health among older persons in Israel

There is a considerable body of scientific knowledge about factors associated with self-rated health (SRH), a common measure of health status. However, less is known about the factors associated with changes in SRH over time. In order to fill this gap, the aim of the current study was to examine a combination of socioeconomic, psychosocial, and health behaviour variables in explaining changes in SRH among older adults. The study used data from two time periods in Israel of the Survey of Health, Aging and Retirement in Europe (SHARE) to analyse the predictive contribution of Time 1 socioeconomic, psychosocial and behavioural variables and changes in these variables over time to changes in SHR. The sample included 1,549 older persons interviewed at baseline (years 2009-2010) and four years later (year 2013). Using bivariate and multivariate regression models, the findings show that 26 percent and 23 percent of the participants reported either improvement or a deterioration in their SRH, respectively. Decline in SRH was predicted by a combination of Time 1 socioeconomic (subjective assessment of a household's ability to make ends meet), psychosocial (QoL and in trust in people), and behavioural factors (moderate physical activity) and decline in these factors over time. The findings demonstrate that changes in those variables make an additional significant contribution for explaining changes in SRH. The findings suggest that in addition to identification of low SES, poor psychosocial and behavioural factors as risk factors to poor SRH changes in these factors should be monitored among older populations.

Risk factors and health status among older adults in Europe: a socioeconomic analysis

The risk of developing a major non-communicable disease is critically affected by lifestyle choices. This study examined the consequences of factors that might predict a change in the self-rated health of older adults and aimed to assess their monetary costs. In particular, two predisposing risk factor moderators were studied: high blood pressure and high cholesterol. The effects of these on two serious adverse cardiovascular events - heart attack and stroke - were estimated. Using data from the Survey of Health, Aging and Retirement in Europe (SHARE) carried out in 2014, a two-stage procedure was applied as well as pairwise comparison. The results revealed the significant role of socioeconomic status in health outcomes. Behavioural risk factors were found to be significant predictors for heart attack and stroke. The findings support the claim that variables such as age, wealth and behavioural risk factors are additional predictors of a change in these two diseases. The monetary consequences can reach up to 12.8 thousand Euros for older adults per unit of predisposing risk factor. Since national health budgets are limited, health policies might be prioritized.

How Many Older Informal Caregivers Are There in Europe? Comparison of Estimates of Their Prevalence from Three European Surveys

Informal caregivers are people providing some type of unpaid, ongoing assistance to a person with a chronic illness or disability. Long-term care measures and policies cannot take place without taking into account the quantitatively crucial role played by informal caregivers. We use the European Health Interview Survey (EHIS), the European Quality of Life Survey (EQLS), and the Study on Health and Ageing in Europe (SHARE) to measure the prevalence of informal caregivers in the European population, and analyze associated socio-demographic factors. This rate ranges between about 13 percent in Portugal and Spain, and more than 22 percent in Luxembourg, Belgium, and Denmark. It declines in older age groups and, on average, is lower in men than in women in all countries studied, and lower among the poorly educated compared to those with higher levels of education. However, large variance was observed in the average share of informal caregivers for most countries between the three surveys. Our findings, estimated through the three surveys, reveal common trends, but also a series of disparities. Additional research will be needed to enable policy makers to access a richer and more harmonized body of data, allowing them to adopt truly evidence-based and targeted policies and interventions in this field.

Out-of-pocket spending of deceased cancer patients in five European countries and Israel

OBJECTIVE

Cancer imposes a substantial economic burden on society, health and social care systems, patients and their families. This study aims to examine the out-of-pocket spending of cancer patients in their last year of life, in six countries with health insurance system hat have a defined benefits package.

METHODS

Data from SHARE and SHARE End-of-Life surveys among people aged +50 were analysed. Family members of deceased persons were interviewed in order to learn about the circumstances of their relative's death.

RESULTS

The average out-of-pocket spending for health and social services during the last year of life was 4.5% of the total household income, 2.2% in the Netherlands, 4.3% in Israel, 5% in Germany, 5.1% in Austria, 5.1% in Belgium and 8.2% in Switzerland. Whereas the out-of-pocket spending on nursing home care was 7.8% of the total household income in Switzerland, in the Netherlands and in Israel it was negligible. In contrast, the out-of-pocket spending for home care due to disability surged to 5.6% in Israel and 3.7% in Austria, whereas in other countries it was very low.

CONCLUSION

This information is important to health and social policymakers, in order to better adapt the benefits package to the patients' needs.