The results show that the pandemic’s broad social and economic impact has adversely affected population health well beyond those directly suffering from COVID-19. Study participants with chronic conditions faced significant challenges in managing their symptoms during the pandemic. They experienced a loss of income and difficulties in accessing healthcare or medications, with the resulting delayed and foregone care leading to uncertain longer-term effects. For a nontrivial portion of participants, these factors are associated with the worsening of diabetes symptoms. The threat is twofold among people living in rural populations with limited access, availability, and affordability of healthcare services.

A Global Health Priority

The unintended adverse consequences of the COVID-19 pandemic on chronic disease care may also further aggravate inequality in health outcomes. “If the trend continues and no immediate actions are taken to mitigate pandemic impacts,” Eggleston and her colleagues caution, then “the Asia-Pacific region will struggle to achieve the 2030 Sustainable Development Goal (SDG) target 3.4 to reduce premature mortality from non-communicable diseases by a third relative to 2015 levels and to promote mental health and wellbeing.”

Addressing the pandemic’s unintended negative social and economic impacts on chronic disease care is a global health priority, determine the researchers. They propose several measures to help provide timely care for people with chronic conditions in resource-constrained settings. These include implementing innovations in healthcare delivery models to improve the adoption of healthy lifestyle changes and self-management of chronic disease and mild COVID-19 symptoms, increasing investment in interventions to provide social and economic support to disadvantaged populations, and strengthening primary healthcare infrastructure and support of healthcare providers.

The study was supported in part by funding from Shorenstein APARC’s faculty research award, Stanford King Center for Global Development, and a seed grant from the Stanford Center for Asian Health Research and Education.

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Challenges for Primary Health Care Services

China, a large and rapidly developing middle-income country with a hospital-based service delivery system for its aging population, makes a suitable case study of efforts to promote PHC management. Over the past several decades, PHC use in China has significantly decreased relative to hospital-based care. This trend is a natural consequence of the country’s unprecedented increases in living standards and improvements in financial risk protection, which increase patients’ demand for quality care and spur self-referral to providers with higher-perceived quality like hospital outpatient departments.

The performance differences between PHC and hospital-based care are especially stark in China’s rural areas, where management of chronic diseases relies heavily on grassroots physicians, who have limited medical education and training. That is why Eggleston and her colleagues set out to provide new empirical evidence about the effectiveness of a program that promotes PHC management of hypertension and diabetes for rural Chinese. Part of the National Basic Public Health Service Program for rural Chinese, it financially rewards PHC grassroots physicians for managing residents with chronic diseases.

Collaborative Research in the Era of Great Power Competition

Eggleston’s co-authors include her colleagues at the Zhejiang Provincial Center for Disease Control and Prevention (Zhejiang CDC). Their study is the culmination of Eggleston’s multiyear collaborative research project with the Zhejiang CDC team, "Addressing Health Disparities in China," which looks to Tongxiang county in Zhejiang as a case study of China's responses to healthcare inequalities and population aging challenges in rural and urban areas. The project also involved two Stanford doctoral students who worked with Eggleston.

“This kind of collaboration, where we utilize the data that's available to answer an important question while respecting the privacy of the individuals and hopefully delivering benefits to them through more effective or affordable programs in the future perhaps is a promising model for researchers here and elsewhere to undertake,” she notes.

Disentangling the Effect of Primary Health Care Management

To study the program’s effectiveness, the researchers assembled a unique dataset linking individual-level administrative and health information between 2011 and 2015 for rural Chinese diagnosed with hypertension or diabetes in Tongxiang, a mostly rural county of Zhejiang province in southeast China. Collected by the Tongxiang CDC and Zhejiang CDC, the compiled database links basic demographic information, health insurance claims, PHC service logs, and health check-up records — four sets of data that are rarely linked and analyzed in combination in China healthcare research.

Targeting the program’s effects on healthcare utilization, spending, and health outcomes, Eggleston and her colleagues compare residents in neighboring villages that straddle township boundaries. These residents are similar in their individual and environmental characteristics that shape health care use but are subject to different PHC management practices. This “border sampling” allows the researchers to disentangle the effects of PHC management from other underlying spatial differences that impact health care utilization. For each township, the researchers use a management intensity index that reflects the cumulative efforts of PHC physicians to screen their communities and keep patients within the PHC management programs for controlling hypertension and diabetes. Each township’s experience with PHC management over the 5-year study period is thus a case study for rural China.

Net Value in Chronic Disease Management

The results are encouraging for China's investment in primary care management of chronic diseases. Eggleston and her colleagues find that patients residing in a village within a township with more intensive PHC management had a relative increase in PHC visits, fewer specialist visits, fewer hospital admissions, and lower spending compared to neighbors with less intensive management. They also tend to have better medication adherence and better health outcomes as measured by blood pressure control.

The results suggest that PHC chronic disease management in rural China improves net value in multiple ways — increasing PHC utilization, reducing avoidable hospitalizations, decreasing medical spending, and improving intermediate- and long-run health outcomes — all while leveraging existing resources rather than restricting care.

The findings also help inform investments in primary health care in LMICs. They highlight the latent potential of frontline healthcare workers in such settings to be more productive and show that financially rewarding these grassroots workers for managing residents with chronic diseases helps improve health outcomes. Moreover, they offer empirical evidence that supports the effectiveness of chronic disease management programs as part of broader regional initiatives to address population health.

Modeling Health Outcomes Among East Asian Populations

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.

Towards Reducing the Disease Burden of Diabetes

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.