Linking individual medicare health claims data with work-life claims and other administrative data

Preventing COVID-19 from the perspective of industrial information integration: Evaluation and continuous improvement of information networks for sustainable epidemic prevention

COVID-19 is accelerating industrial information integration (III) for sustainable epidemic prevention and innovation design. It is important to emphasize that this interaction makes it reciprocal. To prevent COVID-19, the III of industrial sectors should be strengthened to encourage innovation for sustainable epidemic prevention. Accordingly, we studied the overall dynamic change trend of industrial sectors' information integration networks (IIN), the characteristics of individual IIN, and their influence on IIN performance. In the study, the gravity model and social network analysis were used to determine the variables of industrial sectors' information distance and quality, and to construct the IIN of industrial sectors. The results show that the overall relevance of the IIN of industrial sectors is low, and the network density fluctuates, with high network efficiency and poor stability. Two-way, strong correlation between industrial sectors is relatively low. The spillover effect of industrial sectors in the upstream of the industrial chain is poor, and it is difficult to have a strong information integration driving effect on the downstream industrial sectors. The interplate linkage of the IIN of industrial sectors is insufficient. Compared with point centrality and closeness, improvement of the betweenness centrality of industrial sectors can significantly improve IIN performance.

Investigating the Early Life Determinants of Type-II Diabetes Using a Project Talent-Medicare Linked Data-set

The increasing prevalence of Type II Diabetes (T2D) presents a serious health and financial public crisis. Our study examines the hypothesis that adolescents' perceptions of economic insecurity, along with absolute and relative socioeconomic status (SES), can contribute to T2D prevalence later in life. Project Talent (PT) Survey data, collected on high school students in 1960, have been linked to Medicare records from 2012, presenting a unique opportunity to examine measures gathered in adolescence and T2D prevalence later-in-life among a large, national, and diverse sample (n=88,849). Our results provide compelling evidence that real, perceived, and relative SES in adolescence have persistent impacts on later-in-life diabetes risk, even when controlling for possible confounders such as cognitive ability, conscientiousness, and early-adulthood educational attainment.

The impact of retirement on health: quasi-experimental methods using administrative data

Background

Is retirement good or bad for health? Disentangling causality is difficult. Much of the previous quasi-experimental research on the effect of health on retirement used self-reported health and relied upon discontinuities in public retirement incentives across Europe. The current study investigated the effect of retirement on health by exploiting discontinuities in private retirement incentives to test the effect of retirement on health using a quasi-experimental study design.

Methods

Secondary data (1997–2009) on a cohort of male manufacturing workers in a United States setting. Health status was determined using claims data from private insurance and Medicare. Analyses used employer-based administrative and claims data and claim data from Medicare.

Results

Widely used selection on observables models overstate the negative impact of retirement due to the endogeneity of the decision to retire. In addition, health status as measured by administrative claims data provide some advantages over the more commonly used survey items. Using an instrument and administrative health records, we find null to positive effects from retirement on all fronts, with a possible exception of increased risk for diabetes.

Conclusions

This study provides evidence that retirement is not detrimental and may be beneficial to health for a sample of manufacturing workers. In addition, it supports previous research indicating that quasi-experimental methodologies are necessary to evaluate the relationship between retirement and health, as any selection on observable model will overstate the negative relationship of retirement on health. Further, it provides a model for how such research could be implemented in countries like the United States that do not have a strong public pension program. Finally, it demonstrates that such research need-not rely upon survey data, which has certain shortcomings and is not always available for homogenous samples.