Supply Chain Management for Healthcare

Supply chain management is one of the key ways to improve the level of health care services. Good supply chain management is crucial for the healthcare industry to improve hospital capacity, reduce operating costs and improve people's satisfaction.

In healthcare supply chain management, there are many factors, such as inventory and transportation, among which demand is the most critical one. Therefore, an accurate and robust forecasting model is crucial and valuable for the healthcare industry to make better plans on operation and investment. In healthcare industry, medical device is a very important branch.

Because of the high cost of medical device, the investment in the medical supply chain is often huge. Also, the efficiency of healthcare supply chain is relatively low, compared with retail industry and electronic supply chain. Therefore, we have opportunity to improve the efficiency of healthcare supply chain by building an accurate demand forecasting approach which can react to real markets.

Importance of Supply Managemeint in Healthcare Sector

Literature Review

To solve the problems mentioned above, we propose a forecasting model for medical device with online search quires. There are several steps in the model. First, the search engine quires about the disease are collected from the Internet. Second, the correlation between search engine quires and medical device demand is tested. Third, the search engine quires and historical demand are used to train machine learning models. Finally, the forecasting results are compared with univariate demand forecasting approaches which are commonly used demand forecasting models. The trained model can be used to assist the management of healthcare supply chain to improve efficiency.

The role of big data in healthcare industry

We conducted a literature review about the role of big data in healthcare industry, and the application of big data in demand forecasting.The development and popularization of the Internet make it more convenient and fast for people to get information. People have learned to use search engines to find all kinds of information about diseases. The famous search engines are Google, Yahoo, Bing and so on. At the same time, some online diagnosis and treatment platforms have appeared on the Internet to provide patients with early disease consultation. For example, MELIVE, Teladoc, American Well and so on. Some sites allow patients to conduct online diagnosis and treatment with real doctors in the form of online chat, while others use artificial intelligence to realize preliminary triage of patients.

The use of these online applications generates a large amount of data available. By analyzing these data, we can get people's attention to different diseases and understand the distribution of diseases in the population. At the same time, the Internet will provide people with real-time news about health care, which may affect people's confidence and acceptance of health care.

According to McKinsey’s report in 2013, the revolution of big data is accelerating the innovation in healthcare industry. By using cloud computing and big data analysis technology, some reseacrhers established a patient-centered medical application and service network physical system, to solve the problem of different data storage formats . The reseacrhers introduced the characteristics of medical big data and the challenges in data analysis, and showed the application of a variety of big data in medical and health care. In addition, Harsh and Seshadri highlighted data security and personal privacy issues in healthcare big data analysis. Therefore, the research question of this study is whether big data can improve the accuracy of demand forecasting model.

Solution

In order to reduce the cost of healthcare supply chain and increase the income of healthcare enterprises, the demand for medical equipment needs to be accurately forecasted. The development of the Internet makes people get used to getting knowledge from websites. Therefore, the search index on the Internet can help us understand the public's preference for certain needs.

And Today we show our customers the proposed forecasting model for medical device demand with online search queries. We apply the model on one medical device demand and compare the performance of the model with other univariate demand forecasting approaches and thats how we give this service to our customers

What We Offer With Supply Chain Analytics?

We use the search engine index to help build the forecasting model for you. First, we examine the relationship between demand, search engine index and historical demand, and use the most relevant variables to build the prediction model.