How important is data management?

Appropriate management of the ever-increasing amount of data has a significant impact on business improvement. The medical field is no exception, and there is a wide variety of data to be managed, including chart management, diagnostic support, and new drug development. In this article, we will explain the importance of data management and introduce examples of NetApp services that support data utilization, especially in the medical field.

Table of contents

Importance of data management

“Data management” does not mean simply storing and storing data in databases, file servers, etc. As an asset of a company or organization, rules for addition, deletion, and update are established, and it includes organization for moving, viewing, and sharing data. In addition, in order to make data available for use at any time, we will develop functions such as speedy search, long-term storage, and deletion of unnecessary data.

According to an international research report on data management and revenue, employees spend an average of two hours a day searching for desired data. In addition, approximately 65% ​​of Japanese companies have invested in proper data management, successfully reducing costs and improving employee productivity.

Good data management helps you find the data you need quickly and reduces waste in the search process. This facilitates data utilization, improving operational efficiency and speeding up decision-making. Recently, there is a tendency to emphasize decision-making based on data insights, and the importance of data management is increasing.

In addition, the cost of long-term data storage is enormous. Costs can be minimized by consolidating targets in data management and defining cycles from data creation to destruction.

How to manage and use data in the medical field

There are many benefits to data management in the medical field as well. In the following, we will explain how data management is done and possible methods in the medical field.

Manage patient data

Medical charts, which record basic patient information and medical progress, are obligated to be stored. Medical charts must be handled with great care, as they include billing procedures, medical history, allergies, family relationships, and more.

In the past, paper medical records were the mainstream, but in recent years, the introduction of electronic medical records is progressing. “Electronic medical record” refers to “a database management system that edits and manages electronic information that can be collectively managed by replacing paper medical records with an IT system”, and also refers to the electronic information itself contained therein. .

With the introduction of this electronic medical record, the burden of reservation reception, accounting work, medical record entry, prescription work, etc. will be reduced, and work efficiency will be greatly improved. In addition, it is expected to have the effect of capturing the results requested from inspection companies, reducing storage space, checking information in real time, and preventing troubles due to misreading.

Receipts, which can be called “receipts for medical expenses,” are also being digitized. Until now, medical receipt inspection was an important task in medical office work, but with computerization, it is now just checking whether it has been created correctly. By centralizing the receipt information, it is possible to use it for specific medical examinations and specific health guidance, and to understand information such as side effects of pharmaceuticals.

Use as big data

In recent years, there has been a trend in medical care to make comprehensive judgments based on the vast amount of diagnostic information available in science, and to select the optimal treatment methods based on evidence. The Ministry of Health, Labor and Welfare has also enacted the Next-Generation Medical Infrastructure Act, providing anonymously processed patient data to companies and research institutes and promoting a system for smooth utilization.

These medical big data can be used in various ways. It is possible to provide medical care by analyzing the optimal treatment method for each patient, taking into consideration the patient’s age, symptoms, condition, etc. In addition, it is possible to integrate medical data of patients treated in different clinical departments, obtain new knowledge, and improve treatment outcomes.

For example, treating periodontal disease based on the statistical result that diabetics are more likely to develop periodontal disease will contribute to improving the health condition of diabetes patients. Applying machine learning to artificial intelligence for medical big data not only supports doctors’ diagnosis, but also leads to early detection and early treatment of diseases through CT image analysis.

In addition, new drug development generally takes time, and in addition, there are problems that “development costs are high and the probability of success is low.” The use of medical big data is expected to improve the quality of research data, speed up development, and reduce costs. It is also effective in improving the safety of pharmaceuticals, as it makes it easier to compare and compare the frequency of side effects.

Utilization in medical treatment and care

Data management in the medical field can be done not only with personal computers but also with smartphones and tablets by utilizing information and communication technology (ICT). Telemedicine using information communication equipment has been recognized as a medical practice, so it can also be used for medical treatment in places where medical facilities are insufficient, such as remote islands and depopulated areas. In addition, these technologies can be used to treat patients who cannot visit medical institutions due to disability, illness, bedridden, or other reasons.

It is also used in systems that support doctors’ diagnosis. One example is SYNAPSE Case Match, a similar case search system jointly developed by Fujifilm and Shizuoka Cancer Center that combines AI technology and a rich case database. Appropriate management and utilization of data on each individual patient will lead to improved and more efficient patient care.

NetApp services that support data utilization in the medical field

NetApp supports data utilization in the medical field and provides patient-oriented solutions and products. Below is an overview of the company and examples of its use in the medical field.

What is NetApp

NetApp is a company that provides services related to various data management such as collection, storage, management and protection. Established in 1992, we have been leading the industry since the dawn of corporate IT. In recent years, we have been focusing on cloud services, such as partnering with the world’s largest cloud provider. The world’s top-class famous companies have adopted it, and it is a company that has gained trust in a wide range of industries, including medical care.

NetApp provides IT services that can be used for a variety of purposes, such as simplifying data management in the medical field, reducing costs, and speeding up diagnosis. System development is done by a team of clinicians, telemedicine/medical imaging professionals, and data scientists. Testing for clinical workloads ensures cost-effective non-disruptive systems with secure compliance.

NetApp use cases in the medical field

There are three main uses of NetApp: “speeding up data utilization,” “AI support,” and “provision of telemedicine.” Let’s take a closer look at each.

Accelerate data utilization

Speedy access to medical data improves the quality of patient care. In clinical situations where seconds can make the difference between life and death, it is necessary to make the right decision in an instant and provide the best treatment. NetApp can partner with clinical EHRs (electronic health records) and PACS (picture archiving and communication systems) ISVs (independent software vendors) to accelerate time to diagnosis.

It also simplifies data management by operating on a single platform, whether on-premises or in the cloud. It is an OS that can operate without stopping the system, and the safety of the service can be ensured.

Assisted by AI

Analyze structured and unstructured data to unlock new insights with AI-enabled infrastructure. In addition to a wide range of IoT applications, data analysis is possible with a variety of resources such as genomic research, clinical software, insurance claims platforms, and research databases. AI and machine learning can be used to identify diseases with high accuracy even in complex medical conditions.

It is also important to eliminate the silos of medical data and use it for detailed analysis. By responding to the systematic use of AI by medical institutions and maximizing the use of AI for the knowledge and clinical cases required in healthcare, we will also contribute to the strengthening of the organization.

Providing telemedicine

NetApp can connect to critical data and software at the scale you need, so you can effectively deliver telemedicine and drive telemedicine projects. Solutions for VDI ( virtual desktop ) realize a workflow that provides highly confidential patient information and virtual medical care in a safe and secure environment.

It is also possible to minimize the occurrence of latency (data communication delay time). In this way, one of NetApp’s strengths is its ability to connect to data and software.

summary

In the medical field, the digitization of medical charts and receipts is progressing, and the importance of data management is increasing. NetApp is a service that contributes to speeding up data utilization, supporting AI, and providing telemedicine. Simply visit our support page to get the support you need right away, and our no-cost trial makes getting started with NetApp quick and risk-free.