ShuLian Yikang Empowers Nearly 6,000 Primary Healthcare Institutions in Sichuan with AI-Driven Medical Insurance Cost Control Solutions

On May 17, the “2017 China Primary Healthcare Innovation Practice Forum” was grandly held in Chengdu. As one of the participants, Chengdu Shulianyikang Technology Co., Ltd. received the award selected by VCBeat.“Best Practices in Primary Healthcare”Awards.

To understand how this company, with healthcare cost containment as its core business, manages cost control in primary care, VCBeat held an in-depth conversation with Xing Yong, Deputy General Manager of Shulianyikang.

Over the past two decades since its inception, China’s basic medical insurance system has witnessed widespread public unfamiliarity and skepticism. During this period, abuses and irregularities—such as excessive medical treatment within hospitals, fraudulent reimbursement claims using fabricated documentation, and “bed-hanging” (fake hospitalizations)—have accounted for approximately 30% of total healthcare expenditures.

“Controlling these 30% of costs has always been a key objective for Shulianyikang.“Xing Yong said.

Commercial health insurers and basic medical insurance are part of the same system. Therefore, in addition to engaging with government entities, Shulianyikang is also reaching out to commercial insurers such as Sunshine Life Insurance, PICC Health, and Taikang.

First, since commercial insurance assumes the government’s critical illness insurance program, regulatory measures are equally necessary in this domain to identify fraud, medical waste, and overtreatment, thereby establishing a risk management system and reducing premium costs. Additionally, commercial insurers require data—such as the number of individuals at high risk for complications—to support product design and facilitate the development of innovative products. Therefore, collaboration with healthcare cost-containment companies can help them create products that better align with actual market needs.

Furthermore, insurance product design often requires analyzing data from as many healthcare institutions in a region as possible. Only in this way can insurers achieve more precise targeting of the local population, thereby tailoring their products to better meet local demands.

DRGs and Case-Based Payment are two new medical insurance payment models currently being promoted by the government.At the current stage, the most common form of medical insurance isTotal BudgetCalculation。namelyby government departments or insurance institutionsThrough the analysis ofHospitalService OverviewConductFollowing comprehensive evaluation and calculations, in accordance with the terms agreed upon through negotiations with the hospitalA payment method with the annual total budget as the upper limit.

The advantages of the global budget system lie in eliminating the economic incentives for healthcare providers to deliver excessive medical services, thereby effectively controlling the unreasonable growth of healthcare costs. Since costs under a global budget are fixed, hospitals can proactively plan ahead and allocate healthcare resources rationally. Furthermore, this payment settlement method is straightforward, helping to reduce administrative costs.

However, there are also drawbacks. Under the "hard constraint" of a fixed global prepaid budget, healthcare providers may underprovide medical services and experience a decline in service quality. Furthermore, given the numerous uncertainties, determining the annual global budget for hospitals is an extremely challenging task.

Xing Yong believes: “The global budgeting approach simplifies the overall management of healthcare insurance funds, but it fails to incentivize healthcare institutions’ intrinsic motivation for cost containment. To better stimulate healthcare institutions’ proactive efforts in controlling costs, a composite payment model should be adopted, combining global budgeting with capitation, case-based payment, and DRG-based cost control.”

Taking single-disease payment as an example, it not only incentivizes hospitals to control costs but also maximizes the assurance of healthcare service quality.

Therefore, when hospitals implement payment scheme reforms, Chengdu Shulianyikang Technology Co., Ltd. provides the medical insurance authorities with fund simulation mechanisms and models to help them assess the impact of such policies on patients, hospitals, and the insurance fund.

Chengdu Shulianyikang Technology Co., Ltd. focuses on controlling healthcare costs by establishing a big data platform built upon rule-based audits. The system first provides pre-event alerts through rule-based reviews, then leverages big data anti-fraud models to conduct in-depth mining of operational data, HIS-extracted data, and reimbursement data. This process identifies hidden violations such as insurance fraud, medical waste, and over-treatment. Finally, it offers decision support for the formulation of new medical insurance policies through methods like fund simulation and thematic analysis reports, thereby creating a comprehensive cost-control solution that covers the entire chain of big data audit and supervision for medical insurance.

Currently, Shulianyikang’s Yikang Big Data Regulatory System has been iterated to its third version, evolving from versions 1.0 and 2.0 to the 3.0 stage.

Phase I,Shulianyikang primarily provides rule-based cost control.；

Phase II,Shulianyikang conducts post-event supervision from a big data perspective., it consolidates medical behavior data of insured individuals across all periods and locations, along with diagnostic and treatment data from healthcare institutions. By leveraging over one hundred big data algorithmic models within its anti-fraud engine, it identifies fraudulent and non-compliant activities. Compared to the rule-based auditing in Phase I, big data technology addresses issues of data authenticity and insurance fraud, thereby enhancing the long-term effectiveness of cost containment. Meanwhile, it introduces data analytics-driven decision support to assist in the formulation of medical insurance policies, ensuring the scientific and rational use of the fund;

Phase III: Shulianyikang Incorporated Real-Time Monitoring.The first two stages involve ex-post oversight, whereas the third stage introduces real-time monitoring, which can capture required data from various Hospital Information Systems (HIS) in real time for analysis using big data algorithmic models. By comprehensively monitoring medical practices in real time, cost containment measures are implemented proactively, thereby curbing unreasonable growth in medical expenses at the source.

With the continuous implementation of tiered diagnosis and treatment and the downward allocation of medical resources, the primary entities responsible for cost control are gradually extending or shifting toward primary healthcare institutions.。

Chengdu Shulianyikang Technology Co., Ltd. has entered the grassroots healthcare market by focusing on health insurance cost control, positioning itself as a third-party regulatory platform. With medical payment as its entry point and leveraging a big data-driven regulatory decision-making platform, it integrates payment, medical services, health management, and pharmaceutical supply chains to build a comprehensive ecosystem.

In early 2017, Shulianyikang integrated its big data cost-control system into the Sichuan Provincial Primary Healthcare Institutions Management Information System.Helping nearly 6,000 primary healthcare institutions across the province standardize medical service practices, enhance the quality of care, and achieve proactive cost control.。 

Xing Yong stated, “In the future, large tertiary hospitals will primarily focus on treating complex and rare diseases; therefore, cost containment efforts will mainly target these conditions. In contrast, supervision for primary healthcare institutions will focus on common diseases and chronic conditions. However, the Yikang Big Data Supervision System ensures that medical insurance funds are protected from any fraudulent activities, regardless of whether medical services are provided at large tertiary hospitals or primary healthcare institutions.”