Ten Years of New Healthcare Reform: Four Major Transformations in Medical Insurance Cost Control

In recent years, under the combined effects of the gradual improvement of the universal health insurance system, the accelerating trend of population aging, and the continuous rise in medical expenses, the payment pressure on health insurance funds has been increasing day by day, with some regions facing the risk of fund "deficit." To ensure the security of health insurance funds and achieve the sustainable development of medical insurance, cost containment in health insurance has become an inevitable trend.

Health Insurance Cost Containment: Targeting Unreasonable Medical Expenses to Reduce Improper Expenditures of Health Insurance Funds and Improve Fund Utilization Efficiency. One of the objectives of the new healthcare reform is to effectively lower medical costs and address the difficulties and high expenses faced by the public in accessing medical care. Indeed, health insurance cost containment directly impacts the vital interests of the general population.

As a product emerging alongside China’s medical insurance system, cost containment in medical insurance is a long-term endeavor. Over the past decade of healthcare reform, with continuous adjustments and improvements to national medical insurance policies, medical insurance cost containment has undergone multiple transformations during its development.

It is understood that a single medical institution generates tens of thousands to hundreds of thousands of claims annually, which underscores the large scale and high professional specificity of health insurance supervision. Traditional supervisory methods have relied primarily on manual random audits. Such extensive, non-targeted audit approaches suffer from low coverage, inefficiency, and prolonged audit cycles, resulting in suboptimal cost-control outcomes for health insurance funds. To address staffing shortages and achieve comprehensive, automated review of reimbursement data, health insurance authorities across various regions are increasingly adopting information technology solutions to assist in the audit process.

Around 2010, cities such as Tianjin and Shanghai took the lead in exploring the development of healthcare service monitoring systems. In the following years, rule-based intelligent health insurance monitoring systems were rapidly deployed across China. With the assistance of information technology, local health insurance authorities found that rule-based audits transformed the previous situation where health insurance inspections heavily relied on manual spot checks, significantly improving audit efficiency.

However, as the system has been in operation for an extended period, the drawbacks of rule-based audits have gradually become apparent in actual practice, with cost-containment effectiveness showing a diminishing trend. The primary reason is that healthcare institutions, having become familiar with the structure of these rules through long-term exposure to the audit process, intentionally circumvent them driven by profit-seeking motives, thereby undermining the rules’ cost-containment efficacy.

Furthermore, although the implementation of rule-based audits has, to some extent, curbed the unreasonable growth of medical expenses, issues such as overprescribing, drug abuse, and falsification of medical records remain unmitigated. There is an urgent need for healthcare security authorities to adopt more efficient regulatory measures to reduce the leakage of healthcare security funds.

In recent years, the rapid development of new-generation information technologies, such as artificial intelligence and big data, has provided new approaches for the construction of intelligent monitoring systems for medical insurance. Some regions have begun to explore the use of big data analytics—including case-based reasoning, analysis of medical behavior patterns, evaluation of diagnosis and treatment plans, and network diffusion analysis of doctor-patient interactions—to enhance the identification of fraudulent insurance claims and ensure the rationality of medical insurance reimbursements.

Practice has demonstrated that big data-based cost containment measures exhibit significant advantages in terms of long-term effectiveness, fraud detection capabilities, self-evolving capacity, the dimensionality of data processed, and platform scalability. Furthermore, the integration of big data technologies has transformed traditional medical insurance policy formulation from “experience-based decision-making” to “data-driven decision-making,” thereby enhancing the scientific rigor and rationality of medical insurance fund management and further safeguarding the security of these funds.

In the long run, big data-based cost containment measures will be a major future trend.

Whether in the stage of manual spot checks or during the phase assisted by information technology for audit support, China’s medical insurance supervision initially relied on post-event audits and penalties for violations. However, a single region may need to process millions of claims annually, among which tens of thousands to even hundreds of thousands are suspected of being non-compliant. The review of these suspected non-compliant claims is undoubtedly a massive undertaking.

Furthermore, as unreasonable medical service practices have already occurred and the medical insurance fund has already been disbursed, the healthcare security authorities also face the challenging task of post-hoc recovery of non-compliant expenditures from the medical insurance fund.

Violations such as fraud and over-treatment in the medical insurance sector remain persistent despite repeated prohibitions. Given the financial sustainability concerns of medical insurance funds, it is essential to strengthen precise oversight of these funds. Pre-adjudication of medical insurance claims has emerged as an effective approach explored by local medical insurance authorities to achieve precise fund supervision. By shifting the review process to the healthcare provider level, this strategy curbs non-compliant medical services before they occur, thereby controlling unreasonable growth in medical expenses at the source. This not only helps healthcare institutions standardize their diagnostic and treatment practices but also ensures the scientific and rational use of medical insurance funds.

Meanwhile, the implementation of pre-audit for health insurance claims has effectively reduced the workload of health insurance authorities in reviewing problematic claims item by item and recovering non-compliant health insurance funds. This allows health insurance departments to devote more resources to improving the efficiency of health insurance fund utilization, thereby delivering greater benefits to the public.

Currently, under the framework of pre-audit integration for health insurance, a multi-level, multi-modal, and end-to-end health insurance supervision system featuring “pre-event alerts, in-process monitoring, and post-event correction” has been rolled out across China. Reconstructing the audit and supervision model for medical expenses by health insurance authorities, and facilitating the transition from unilateral management to collaborative governance, represents both the objective of intelligent health insurance monitoring and an inevitable trend in cost containment.

Health insurance payment is a critical component of basic medical insurance management and the deepening of healthcare reform. Since the launch of the new healthcare reform, various regions have actively explored reforms in health insurance payment methods, such as global budgeting, single-disease payment, and Diagnosis-Related Group (DRG) payment. These diverse payment mechanisms influence healthcare service delivery, thereby controlling unreasonable expenditures from the health insurance fund.

Global BudgetingGlobal budgeting has become one of the most widely adopted healthcare payment methods across China in recent years. It primarily refers to a mechanism whereby healthcare security administrations and healthcare providers negotiate in advance to establish a total budget for covered medical services within a specific scope over a defined future period (typically one year). Payments are then capped at this predetermined budget amount, regardless of the actual costs incurred.

The implementation of global budgeting has, to some extent, curbed the unreasonable growth of medical expenses. However, this粗放 (extensive/crude) management approach has also exposed certain issues. For instance, within the budget limits, healthcare institutions tend to exhaust their allocated funds as quickly as possible; conversely, once the budget is exceeded, in an effort to control fund expenditure, these institutions may refuse critically ill patients covered by medical insurance or reduce the quality of medical services. This leads to a phenomenon of rushed cost-containment measures at the end of the year, resulting in significant negative social impact.

Single-Disease Payment refers to the independent accounting and total cost control of the entire diagnosis and treatment process for a relatively independent disease without complications, implementing price cap management and bundled payment. Under this bundled payment model, medications, medical consumables, and diagnostic tests used by patients become costs of clinical services rather than means for healthcare institutions to generate revenue. This approach helps standardize medical practices, instill cost-consciousness among medical staff, prevent over-treatment, excessive testing, and over-prescribing, thereby incentivizing healthcare institutions to proactively control costs and earn additional revenue.

However, single-disease payment also has certain drawbacks. For instance, healthcare institutions may provide inadequate treatment to reduce costs, leading to patient readmissions and greater consumption of medical resources and health insurance funds. Therefore, single-disease payment is often implemented in conjunction with clinical pathway management, enabling the control of medical expenses while ensuring the quality of care.

Furthermore, while China currently has approximately 300 single-disease categories, tens of thousands of disease types have actually been identified. Consequently, a payment method based on grouping diseases according to factors such as severity of condition and consumption of diagnostic and therapeutic resources has emerged, known as Diagnosis-Related Group (DRG) payment.

From an international perspective, DRG-based payment is a model adopted by many countries and has yielded favorable outcomes over long-term implementation. In China, localized exploration of DRG-based payment was first carried out in cities such as Beijing and Shanghai, with pilot reforms for DRG-based billing and payment officially launched in 2016.

Currently, China has fully implemented a diversified and composite health insurance payment system dominated by diagnosis-related group (DRG) payments since 2017. The system has evolved from a single global budget model to a coexisting framework incorporating multiple payment methods, including single-disease payment, DRG payment, capitation, and per-diem payment. This approach aims to achieve scientific and effective cost containment in health insurance while ensuring medical quality.

China’s healthcare security system is primarily based on basic social medical insurance. With economic development and improvements in living standards, the contradiction between a single-payer healthcare supply system and the public’s diversified demands for medical services has continued to intensify. International experience suggests that healthcare security systems should be multi-tiered and multi-pillared, with social insurance and commercial health insurance each leveraging their respective advantages to achieve diverse coverage objectives. From the perspective of national healthcare reform, commercial medical insurance serves as a robust supplement to basic medical insurance and can effectively alleviate operational pressures on the public medical insurance system.

Supported by relevant policies, medical insurance departments across various regions have progressively opened up the participation of commercial insurance institutions in the operation of medical insurance programs, including government-administered initiatives such as critical illness insurance. Currently, multiple provinces and municipalities, including Anhui, Jiangsu, Qinghai, Fujian, and Shanxi, have begun exploring the comprehensive administration of basic medical insurance by commercial insurance institutions.

After years of rapid development, commercial health insurance is gradually becoming a crucial component of the healthcare payment system. As this trend expands, the administration of basic medical insurance is shifting from sole oversight by government medical insurance authorities to joint regulation involving both basic medical insurance and commercial health insurance. This collaborative governance model will effectively reduce operational costs for basic medical insurance, enhance management efficiency and service quality, further transform government functions, and stimulate market vitality.

Healthcare insurance cost containment is a policy-driven sector; throughout its development, every shift has sent shockwaves through the industry. For enterprises, it is by no means easy—but certainly not impossible—to rapidly gain insights into future market trends amid uncertainty, make accurate forecasts, and develop suitable products in the shortest possible time.

In 2015, Shulianyikang was incubated at the Industry-Academia-Research Integration Base of the University of Electronic Science and Technology of China (UESTC). Leveraging the UESTC Big Data Research Center—the largest and most comprehensively structured big data research institution in China—Shulianyikang possesses an inherent DNA for big data-driven cost control. The company boasts a renowned expert team with over a decade of experience in data mining, healthcare, medical insurance, and information technology, along with expert resources from the Sichuan Evidence-Based Medicine Committee and commercial medical insurance companies. Its management team has profound backgrounds in healthcare informatization and extensive industry experience, having accumulated substantial practical expertise in applying big data to health insurance supervision.

As a cost-containment enterprise, Shulianyikang has accurately grasped the several shifts in the field of medical insurance cost control and made early strategic deployments, ensuring its products' leading position in the market. Taking Shulianyikang's big data solution for medical insurance supervision as an example, as early as 2015, Shulianyikang collaborated with the Big Data Research Center of the University of Electronic Science and Technology of China to commercialize research achievements in "big data + medical insurance cost control," launching its first big data-based cost-containment product.

Over the following two years, Shulianyikang upgraded its products from big data-based cost control to a synergistic model combining big data and rule-based cost control, shifting from post-event review to pre-event prevention and in-process control. It added functional modules such as global budgeting and single-disease payment, ultimately forming a comprehensive big data solution for medical insurance supervision that integrates six core services: intelligent auditing, real-time monitoring, data analysis, big data regulatory oversight, decision support, and data visualization. This solution provides efficient cost-control services to medical insurance administrative departments, ensuring the safe and rational use of medical insurance funds.

Currently, this solution has been implemented across China, cumulatively analyzing and processing billions of settlement records and medical behavior data points, covering 108 million insured individuals.

Leveraging its big data-driven cost containment capabilities, Shulianyikang stood out in the National Social Insurance Big Data Application Innovation Competition hosted by the China Society of Social Insurance in 2017, securing seventh place nationwide. The company has engaged in multiple collaborations with the China Society of Social Insurance, including specialized seminars on big data-enabled health insurance supervision. Notably, it served as the exclusive participant in the research project “Study on Disability and Dementia Assessment Levels in Long-Term Care Insurance,” and jointly participated in the research project “Study on Drug Management and Intelligent Monitoring in Basic Medical Insurance.”

Moreover, within just three years, Chengdu Shulianyikang Technology Co., Ltd. has established in-depth partnerships with provincial and municipal Health and Family Planning Commissions, Human Resources and Social Security Bureaus, tiered medical institutions, 6,000 primary healthcare facilities in Sichuan Province, listed pharmaceutical companies, and major insurance companies. The company’s industry valuation has now exceeded RMB 100 million.

As the state continues to intensify its efforts in controlling healthcare insurance expenditures, such cost containment has gradually become the new normal, with a potential market size reaching hundreds of billions of yuan. Notably, during this year’s “Two Sessions,” the State Council’s institutional reform plan proposed consolidating the responsibilities for basic medical insurance and maternity insurance for urban employees and residents (previously under the Ministry of Human Resources and Social Security), the New Rural Cooperative Medical Scheme (previously under the National Health and Family Planning Commission), drug and medical service price management (previously under the National Development and Reform Commission), and medical assistance (previously under the Ministry of Civil Affairs). These four functions were unified to establish the National Healthcare Security Administration, underscoring the state’s high level of emphasis on healthcare insurance.

With the establishment of the National Healthcare Security Administration, health insurance, as a cost-controlling party, will wield greater authority. What transformations lie ahead for healthcare cost containment remains to be seen.