Around the world, societies are aging at a rapid pace. The demographic transition and the challenges surrounding elderly care are defining issues of our time. Aging populations strain public finances and existing models of social support, affect economic growth, and change disease patterns and prevalence. Many countries, therefore, contemplate policy changes to their retirement, pensions, and health care systems. China, which faces a fast-growing trend of aging cohorts, is no exception.
To alleviate the pressure of elderly care on public finances, the Chinese government has been considering raising retirement ages and corresponding changes in social health insurance and pension policy. A new study now helps evaluate such retirement reforms and provides evidence to inform policy in China and elsewhere by probing the effects of retirement on health care utilization.
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The study’s co-authors, including Karen Eggleston, director of the Asia Health Policy Program at APARC, leverage administrative data from medical claims for over 80,000 insured adults in a megacity in eastern China to explore the effect of retirement on outpatient and inpatient care utilization. In this case, urban employee insurance beneficiaries receive a reduced patient cost-sharing rate upon retirement. By focusing on a relatively well-insured population with comprehensive administrative data on insurance plan design and overall resource use at retirement, the study provides new evidence about mechanisms such as the reduced out-of-pocket price of health care, the opportunity cost of time, and the interaction of these demand-side factors with supply-side incentives. Eggleston and her colleagues report on their findings in the journal Health Economics.
In this relatively well-insured population, annual health care utilization significantly increases primarily because of more intensive use of outpatient care at retirement. This increase in outpatient care stems from a decline in the patient cost-sharing rate, the reduced time constraints upon retirement, and the interaction of these factors with supply-side incentives such as prescribing antibiotics. There is no evidence of change in inpatient care at retirement.
The economics of medical expenditure growth and its interaction with population aging is of considerable policy importance for countries in all income groups. “Our findings may provide useful evidence as one consideration for policymakers in other cities in China and elsewhere looking to increase insurance benefits and control medical spending for burgeoning elderly populations.
The study’s co-authors, including Karen Eggleston, find that health care expenditures among Chinese covered by relatively generous health insurance significantly increase at retirement, primarily due to an increase in the number of outpatient visits.
China’s national health reforms over the past two decades have brought the system closer to the modern, safe, reliable, and accessible health system that is commensurate with China’s dramatic economic growth, improvement in living standards, and high hopes for the next generation.
China’s national health reforms of 2009—continuing many reforms undertaken since SARS (2003)—consolidated a system of social health insurance covering the entire population for basic health services, contributing to a surge in healthcare utilization while reducing out-of-pocket costs to patients – which declined from 56% to 28% of total health expenditures between 2003 and 2017. An expanded basic public health service package, funded by per capita government budget allocations that include a higher central government subsidy for lower-income provinces, provides basic population health services to all Chinese. Now the governance structure consolidates the purchaser role for social health insurance schemes under the National Healthcare Security Administration, with most other health sector functions under the National Health Commission. China’s world-leading technological prowess in multiple fields spanning digital commerce to artificial intelligence—and accompanying innovative business models such as WeDoctor that have not yet been fully integrated into the health system—hold promise for supporting higher quality and more convenient healthcare for China’s 1.4 billion.
However, many challenges remain, from dealing with COVID-19 and its aftermath to other lingering challenges, from promoting healthy aging to the political economy of addressing patient-provider tensions, changing provider payment to promote “value” rather than volume, and deciding which new medical therapies qualify as “basic” for the basic medical insurance schemes. To make China’s investments in universal health coverage and the accompanying rapid medical spending growth sustainable in the longer run, policies need to help the most vulnerable avoid illness-induced poverty, increase health system efficiency, strengthen primary care, and reform provider payment systems.
Diabetes is one of the fastest-growing health challenges of the 21st century. On the frontlines of the epidemic rise in the number of people with diabetes is the Asia-Pacific region. China, in particular, has by far the largest absolute burden of diabetes, with an estimated 116 million adults living with the disease accounting for one-quarter of patients with diabetes globally. By 2045, the number of adults living with diabetes in the country is expected to increase to 147 million, not including the large diaspora community China provides worldwide.
Evaluating the health and economic outcomes of diabetes and its complications is vital for formulating health policy. The existing predictive outcomes models for type 2 diabetes, however, were developed and validated in historical European populations and may not be applicable for East Asian populations with their distinct epidemiology and complications. Additionally, the existing models are typically limited to diabetes alone and ignore the progression from prediabetes to diabetes. The lack of an appropriate simulation model for East Asian individuals and prediabetes is a major gap for the economic evaluation of health interventions.
New collaborative research now addresses these limitations. The research team includes APARC’s Asia Health Policy Program Director Karen Eggleston. The researchers developed and validated a patient-level simulation model for predicting lifetime health outcomes of prediabetes and type 2 diabetes in East Asian populations. They report on their findings in the journal PLOS Medicine.
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The chronic progression to diabetes-related complications is apt for computer simulation modeling due to the long-term nature of health outcomes and the time lag for interventions to impact patient outcomes. It is problematic, however, to estimate the impacts of health interventions on East Asian populations with diabetes using existing models, which were developed and validated in European and North American populations with different epidemiology and outcomes.
To fill in this gap, Eggleston and her colleagues set out to develop and validate an outcomes model for the progression of diabetes and related complications in Chinese populations. They compared this new model, called the Chinese Hong Kong Integrated Modeling and Evaluation (CHIME), to two widely used existing models developed and validated in the United Kingdom (known as the United Kingdom Prospective Diabetes Study Outcomes Model 2, or UKPDS-OM2) and in the United States/Canada (called Risk Equations for Complications of type 2 Diabetes, or RECODe). Despite the continuum of risk across the spectrum of risk factor values, these two existing models ignore the progression from prediabetes to diabetes.
The CHIME integrates prediabetes and diabetes into a comprehensive model comprising 13 outcomes. These include mortality, micro- and macrovascular complications, and the development of diabetes. The researchers developed the CHIME simulation model using data from a population-based cohort of 97,628 participants in Hong Kong with type 2 diabetes (43.5%) or prediabetes (56.5%) from 2006 to 2017. Known as the Hong Kong Clinical Management System (CMS), this cohort makes one of the largest Chinese electronic health informatics systems with detailed clinical records.
The next step was to externally validate the CHIME model against individual-level data from the China Health and Retirement Longitudinal Study (CHARLS) cohort (2011-2018), a nationally representative longitudinal cohort of middle-aged and elderly Chinese residents age 45 and older. The researchers validated the CHIME model against six outcomes measures recorded in the CHARLS data and an additional 80 endpoints from nine published trials of diabetes patients using simulated cohorts of 100,000 individuals.
The researchers found that the CHIME model outperformed the widely used UKPDS-OM2 and RECODe models on the data used, meaning that the validation of the CHIME model was more accurate for trials with mainly Asian participants than trials with mostly non-Asian participants. The results indicate that the CHIME model is a validated tool for predicting the progression of diabetes and its outcomes, particularly among Chinese and East Asian populations, for which the existing models have been unsuitable.
With the new model, clinicians and health economists can evaluate population health status for prediabetes and diabetes using routinely recorded data and therapies related to the long-term management of diabetes. In particular, the CHIME outcomes model enables them to assess patients' quality of life and measure cost per quality-adjusted life-years over the long-time horizon of chronic disease conditions. The new model thus supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes, address micro- and macrovascular complications associated with these conditions, and improve life expectancy.
A research team including APARC's Karen Eggleston developed a new simulation model that supports the economic evaluation of policy guidelines and clinical treatment pathways to tackle diabetes and prediabetes among Chinese and East Asian populations, for whom existing models may not be applicable.
Existing predictive outcomes models for type 2 diabetes developed and validated in historical European populations may not be applicable for East Asian populations due to differences in the epidemiology and complications. Despite the continuum of risk across the spectrum of risk factor values, existing models are typically limited to diabetes alone and ignore the progression from prediabetes to diabetes. The objective of this study is to develop and externally validate a patient-level simulation model for prediabetes and type 2 diabetes in the East Asian population for predicting lifetime health outcomes.
We developed a health outcomes model from a population-based cohort of individuals with prediabetes or type 2 diabetes: Hong Kong Clinical Management System (CMS, 97,628 participants) from 2006 to 2017. The Chinese Hong Kong Integrated Modeling and Evaluation (CHIME) simulation model comprises of 13 risk equations to predict mortality, micro- and macrovascular complications, and development of diabetes. Risk equations were derived using parametric proportional hazard models. External validation of the CHIME model was assessed in the China Health and Retirement Longitudinal Study (CHARLS, 4,567 participants) from 2011 to 2018 for mortality, ischemic heart disease, cerebrovascular disease, renal failure, cataract, and development of diabetes; and against 80 observed endpoints from 9 published trials using 100,000 simulated individuals per trial.
The CHIME model was compared to United Kingdom Prospective Diabetes Study Outcomes Model 2 (UKPDS-OM2) and Risk Equations for Complications Of Type 2 Diabetes (RECODe) by assessing model discrimination (C-statistics), calibration slope/intercept, root mean square percentage error (RMSPE), and R2. CHIME risk equations had C-statistics for discrimination from 0.636 to 0.813 internally and 0.702 to 0.770 externally for diabetes participants. Calibration slopes between deciles of expected and observed risk in CMS ranged from 0.680 to 1.333 for mortality, myocardial infarction, ischemic heart disease, retinopathy, neuropathy, ulcer of the skin, cataract, renal failure, and heart failure; 0.591 for peripheral vascular disease; 1.599 for cerebrovascular disease; and 2.247 for amputation; and in CHARLS outcomes from 0.709 to 1.035.
CHIME had better discrimination and calibration than UKPDS-OM2 in CMS (C-statistics 0.548 to 0.772, slopes 0.130 to 3.846) and CHARLS (C-statistics 0.514 to 0.750, slopes −0.589 to 11.411); and small improvements in discrimination and better calibration than RECODe in CMS (C-statistics 0.615 to 0.793, slopes 0.138 to 1.514). Predictive error was smaller for CHIME in CMS (RSMPE 3.53% versus 10.82% for UKPDS-OM2 and 11.16% for RECODe) and CHARLS (RSMPE 4.49% versus 14.80% for UKPDS-OM2). Calibration performance of CHIME was generally better for trials with Asian participants (RMSPE 0.48% to 3.66%) than for non-Asian trials (RMPSE 0.81% to 8.50%). Main limitations include the limited number of outcomes recorded in the CHARLS cohort, and the generalizability of simulated cohorts derived from trial participants.
Our study shows that the CHIME model is a new validated tool for predicting progression of diabetes and its outcomes, particularly among Chinese and East Asian populations that has been lacking thus far. The CHIME model can be used by health service planners and policymakers to develop population-level strategies, for example, setting HbA1c and lipid targets, to optimize health outcomes.
In an effort to provide greater financial protection from the risk of large medical expenditures, China has gradually added catastrophic medical insurance (CMI) to the various basic insurance schemes. Tongxiang, a rural county in Zhejiang province, China, has had CMI since 2000 for their employee insurance scheme, and since 2014 for their resident insurance scheme.
Compiling and analyzing patient-level panel data over five years, we use a difference-in-difference approach to study the effect of the 2014 introduction of CMI for resident insurance beneficiaries in Tongxiang. In our study design, resident insurance beneficiaries are the treatment group, while employee insurance beneficiaries are the control group.
We find that the availability of CMI significantly increases medical expenditures among resident insurance beneficiaries, including for both inpatient and outpatient spending. Despite the greater financial protection, out-of-pocket expenditures increased, in part because patients accessed treatment more often at higher-level hospitals.
Better financial coverage for catastrophic medical expenditures led to greater access and expenditures, not only for inpatient admissions—the category that most often leads to catastrophic expenditures—but for outpatient visits as well. These patterns of expenditure change with CMI may reflect both enhanced access to a patient's preferred site of care as well as the influence of incentives encouraging more care under fee-for-service payment.
This study is part of Karen Eggleston's research project Addressing Health Disparities in China
Does the new wave of digital technologies portend a future in which robots and automation increasingly replace workers and destroy livelihoods? In one of the first studies of service sector robots, APARC experts find evidence to offset dystopian predictions of robot job replacement.
The researchers — Asia Health Policy Program Director Karen Eggleston, SK Center Fellow Yong Suk Lee, and University of Tokyo health economist Toshiaki Iizuka, our former visiting scholar — set out to examine how robots affect labor, productivity, and quality of care in Japan’s nursing homes. Their findings indicate that robot adoption may not be detrimental to labor and may help address the challenges of rapidly aging societies.
Eggleston recently joined the Future Health podcast, an initiative of the New South Wales Ministry of Health, to discuss the study and its implications. The program is available both as a video and audio podcast. Watch and listen below:
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Published by the National Bureau of Economic Research, the study suggests that robot adoption has increased employment opportunities for non-regular care workers, helped mitigate the turnover problem that plagues nursing homes, and provided greater flexibility for workers. It is also published in AHPP's working paper series and is part of a broader research project by Eggleston, Lee, and Iizuka, that explores the impact of robots on nursing home care in Japan and the implications of robotic technologies adoption in aging societies.
The study has attracted media attention. The Financial Times Magazine, in a feature story and podcast, called it “groundbreaking in several ways but perhaps most clearly for setting its sights not on manufacturing but on the services sector, where robots are only just beginning to make their mark.” The Freakonomics Radio podcast also hosted Eggleston and Lee for a conversation about their research as part of an episode on collaborative robots and the future of work.
On the Future Health podcast, Karen Eggleston discusses the findings and implications of her collaborative research into the effects of robot adoption on staffing in Japanese nursing homes.
