Yao'an Tech Empowers Primary Care Physicians with Drug Knowledge Graph and Big Data: Simulated Prescribing, Medication Review, and More

Accurate diagnosis and prescription for patients are among the most critical care responsibilities of primary care physicians. While the work may appear straightforward, it is highly specialized, requiring not only a strong awareness of primary healthcare services but also substantial accumulation of clinical and pharmacological knowledge. It is imperative to enhance primary care physicians’ capabilities in diagnosis, treatment, prescription writing, and safe medication use.

Beijing Yaoan Technology Co., Ltd. (hereinafter referred to as “Yaoan Technology”) was established in 2014. It is a high-tech internet company that leverages prescription big data and intelligent algorithms to serve primary care physicians and pharmacists, with the ultimate goal of ensuring medication safety for patients. Yaoan Technology provides authoritative knowledge on safe medication use to healthcare professionals and patients, helping to mitigate medication risks, reduce adverse drug reactions, and even prevent drug-induced diseases.

Yaoan Technology, in collaboration with domestic medical and pharmaceutical experts and leveraging vast prescription data, has developed the WeChat mini-program “Cloud Prescription Review.” The platform features four core modules—prescription simulation, medication review, prescription big data, and a drug knowledge graph—providing users with prescription simulation training and safe medication guidance services.

VCBeat (WeChat ID: vcbeat) has learned that since its launch in June 2018, Yaoan Technology’s “Yun Ping Fang” platform has accumulated over 50,000 users, with approximately 500 daily visits.

“Families with elderly members are well aware that many seniors need to take multiple medications, which can easily lead to adverse drug interactions,” analyzed Ye Jingyun, founder of Yaoan Technology. He pointed out that grassroots physicians are often the first point of contact for these patients; enhancing their prescribing capabilities can significantly mitigate such risks. Furthermore, as family members have the most frequent contact with the elderly, educating them about drug incompatibilities and related information can also help prevent these issues, adding an extra layer of safety to medication use.

How to Ensure Medication Safety? How to Help Primary Care Physicians Improve Their Prescription-Writing Skills?

Since its establishment, Yaoan Technology has customized and developed intelligent rational drug use systems for several community hospitals in Beijing, accumulating a vast amount of clinical knowledge on medication safety.

In 2014, under the leadership of the Beijing Municipal Health and Family Planning Commission, a Prescription Review Working Group for community hospitals was established to enhance the capacity for rational drug use in Beijing’s community hospitals. Yaoan Technology undertook part of the project’s technical research and development, supported training for primary care physicians, and developed a Prescription Review System that enables intelligent automated review of all prescriptions.

It is understood that, after several years of accumulation, Yaoan Technology has collected over 100 million de-identified real-world prescriptions.

Additionally, Yaoan Technology has accumulated extensive drug information from multiple sources—including package inserts, pharmacopoeias, expert consensus statements, and scientific literature—and integrated them into a drug knowledge graph. The knowledge base currently contains over 16,000 drug package inserts, covering 98% of all domestically marketed drugs approved by the National Medical Products Administration (NMPA). It is updated in real time based on NMPA revision announcements to ensure comprehensiveness and accuracy.

After the knowledge graph and prescription data collection were largely completed, Yaoan Technology began developing a safe medication platform in 2017 to assist primary care physicians and ordinary households.

How was the final product implemented? Yaoan decided to adopt a WeChat Mini Program, as it is more lightweight than a native app and offers better interactivity than a WeChat Official Account.

After six months of research and development, Yaoan Technology has launched “Yun Ping Fang,” a WeChat mini-program that integrates simulated prescribing, medication review, prescription big data, and a drug knowledge graph.

In simulated prescribing, trainee physicians can make diagnoses and write prescriptions based on real, typical outpatient cases provided by experts from tertiary hospitals, and the cloud-based prescription review system will evaluate the diagnoses and prescriptions.

During the medication review phase, the system evaluates the appropriateness of prescriptions based on inputted prescription and patient information (such as gender, age, physical condition, etc.), including contraindications and interactions, duplicate medications, food-drug interactions, and contraindications for special populations, while providing users with precautions for medication use.

Prescription Big Data Function: Based on massive volumes of real-world prescriptions, through data cleaning, error identification/exclusion, and modeling, prescription models for 2,000 disease types have been developed. Users can leverage these models to understand real-world medication patterns for these conditions.

Drug Knowledge Graph: Connecting information on drugs, diseases, populations, and more to form an information network, providing users with drug-centric, multi-dimensional vertical search capabilities.

The big data tool “Yun Ping Fang” provides a new medium for training and exchange among experts and primary care physicians, strengthening guidance and training for primary care physicians. It aims to build a new ecosystem for disease diagnosis, treatment training, and management that is expert-led, big data-enabled, and widely participated in by primary care doctors, thereby ensuring patients’ safe medication use.

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