Big Data Management Emerges as a Lifesaver for the Healthcare Industry

The healthcare industry often faces pressure to reduce costs while improving treatment outcomes. In this regard, big data is poised to become a savior for the sector. However, data alone is insufficient; what matters more is how these data are analyzed to distill informed intervention decisions and guide healthcare professionals in selecting optimal treatment plans. This approach has the potential to significantly enhance the accuracy of outcomes and substantially reduce associated costs.

The development of data management has benefited the healthcare sector in the following three areas:

1. Data collection through electronic medical records;

2. Achieve data sharing through health information exchange;

3. The emergence of databases from relevant enterprises and new analytical tools has significantly enhanced data analysis capabilities.

Whether you maintain an optimistic stance of full acceptance toward big data or harbor partial, reasonable skepticism, enhanced healthcare analytics systems have continually demonstrated their advantages in health planning. The increased accessibility of data has significantly promoted the development of data analytics systems in the healthcare sector, enabling them to optimize treatment outcomes, improve the quality of care, and enhance managerial decision-making capabilities.

So, how does big data help enhance the analytical capabilities of healthcare professionals?

Here are three ways big data helps enhance healthcare analytics capabilities.

1. Precise Target Population Identification

Health plans serve populations with diverse characteristics and varying health statuses. How, then, do you determine who is at risk for coronary heart disease and who is likely to develop diabetes? For whom are additional screenings effective, and for whom are they not? Who stands to benefit from weight management programs and smoking cessation initiatives? To deliver the most appropriate medical care, the first step is to analyze various information sources, ranging from claims data and patient-reported information to health risk assessments.

For example, health risk assessment data can help healthcare providers quickly determine what kind of health or medical care plans newly admitted patients may require. Without such data, significant time would be wasted in identifying which patients need medical assistance. Furthermore, health and medical care plans can fully leverage medical analytics to understand which factors serve as facilitators and how behaviors can be modified. If we can gain a deeper understanding of the differences in screening rates among various populations, we can identify barriers to screening and select the most effective strategies to encourage specific groups to complete recommended screening procedures. This is particularly important when managing large populations, as it helps identify individuals who are likely to benefit from medical interventions, thereby improving health outcomes and reducing costs.

2. Provide appropriate interventions at the right time

Big data can enhance the analytical capabilities of healthcare professionals. It has two primary application areas: one is identifying at-risk populations, and the other is ensuring that each patient receives the most appropriate medical intervention plan and corresponding medical assistance when needed. In this field, the combined application of technological advancements and analytical methods has yielded significant results. For example, some postoperative patients or those with chronic diseases wear wireless monitoring devices in their daily lives, which can provide a large amount of real-time information.

If more people begin to understand their own health risks, monitor their physical condition, and share relevant information with healthcare professionals, the healthcare system’s ability to provide timely and appropriate interventions will be enhanced. However, we also need a collaborative and coordinated approach: regardless of which healthcare workers are involved or in what setting, all parties should have access to consistent information and share the same goals. As data becomes more accessible and analytical capabilities improve, systems can more rapidly identify high-risk populations, recommend timely interventions, and provide data-driven monitoring measures.

3. Adjust the plan and terminate the cycle
Now, as information on health, disease, and healthcare delivery becomes increasingly accessible and abundant, related health plans can be adjusted more rapidly. Most research findings on care management and health plans are positive. For example, a recent study sought to test the hypothesis that targeted care management programs alter the likelihood of appropriate medication prescribing and clinical testing, while also improving medication adherence. The results showed that, in the absence of health plan interventions, only 7.3% of patients prescribed asthma control medications adhered to their prescriptions. The study also examined pneumococcal vaccination and statin therapy metrics. The findings indicated that, by the fourth year, only 16.6% of patients prescribed statins adhered to their prescriptions in the absence of care management interventions.

Enhancing medical analytics capabilities can improve the quality of health plans and strengthen the ability to develop new ones. If big data analytics are applied to healthcare, the accuracy of analytical results is likely to increase significantly, while related costs will be substantially reduced. According to reports, preventive measures—such as early cholesterol screening for patients with relevant medical histories, or hypertension screening for adults and former smokers—could save more than $38 billion in healthcare costs by preventing downstream medical events, identifying the most appropriate treatment plans at an early stage, and avoiding ad hoc chronic care.



While applying big data analytics to healthcare can yield substantial benefits, security concerns cannot be overlooked. Ongoing data breaches have placed hospital data centers under significant strain. Under pressure, these data centers must acquire, analyze, and secure data while simultaneously providing actionable insights to business managers, clinicians, and patients. Many data centers are struggling to meet these emerging demands.

An article titled “Accelerating the Pace of Innovation: The Evolution of Data Centers in the Cloud Era,” published on the BPI (Business Performance and Innovation) website, examines how organizations are adapting to a new paradigm for commercial data centers and networking. Concurrent with this survey, several leading figures in the healthcare IT industry have put forward seven recommendations, which may offer valuable insights and reference points for practitioners and organizations in the field.

1. Migrate the data center to the cloud.According to this report, global demand for internal data center equipment and solutions surged to $122 billion in 2014. However, despite the significant growth in demand, many hospitals have struggled to keep pace with the rapid expansion of commercial needs. What they require is robust data management capability, including the flexibility to rapidly scale up computing power and expand storage capacity as needed. The report notes that many administrators have stated that, faced with a variety of options, they seek hybrid solutions that offer the greatest benefits during the migration of their data centers to the cloud. In developing these solutions, reliable consultants will play a crucial role.

2. Ensure compliance and security.Nowadays, organized criminal groups resell personal information on the black market, and competitors resort to unscrupulous means to obtain trade secrets. These factors have given rise to a large number of cyberattack cases. According to the report, the more data stored in a given location, the more valuable it is to hackers, making it an easier target for cyberattacks. From a compliance perspective, security regulations themselves are riddled with loopholes. The report points out that each scenario should be discussed within the context of its regional factors, including the actual operational status of local telecommunications services, political realities, state-specific regulations, and any other factors potentially involved in transferring data from one location to another.

3. New requirements have emerged for the IT industry.To perform their jobs more effectively, technical professionals are required to master certain skills to better adapt to an increasingly flexible and dynamic environment. According to reports, when asked about their expectations for employee competencies in the coming year, IT industry managers listed the following: application development (41%); desktop support/IT helpdesk support (36%); business intelligence and analytics (25%); and security maintenance (24%). The skills and procedures required for operating data centers have undergone dramatic changes. Martin Zuckerman, CEO of Teswaine Technologies, a company specializing in data center engineering consulting, stated, “The new skills needed today are at the application layer, rather than at the transport, physical, or security layers.”

4. Insights and Challenges from Regional Disparities.According to this report, a reality faced when establishing a global enterprise today is that our world is divided not only by borders but also into distinct segments by factors such as privacy laws, energy shortages, temperature variations, and labor availability. This places higher demands on IT professionals, who must ensure data security in complex environments.

5. Enterprise Applications.A large number of enterprise applications, such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) suites, were previously driven by on-premises installations. However, the emergence of cloud-based applications has fueled demand for “Hybrid ERP” or “Postmodern ERP.” The future environment will encompass a comprehensive suite of more flexible tools that integrate on-premises applications with custom-built applications adopting the Software-as-a-Service (SaaS) model in the cloud.

6. The role of automation is becoming increasingly prominent.According to reports, data centers and software-defined networks represent a critical step toward automation—and the next logical one. Automation enables more efficient resource utilization and reduces costs. More importantly, by reducing complexity, accelerating product development, and facilitating global expansion, automation enhances an organization’s ability to scale.

7. High Reliability and Disaster Recovery Capabilities.A critical function of IT service providers in the healthcare industry is to ensure high service reliability, which must be maintained even if data centers are destroyed by natural disasters. Migrating all or part of geographically dispersed data centers to the cloud can help healthcare IT departments overcome various challenges posed by complex social and cyber environments.

Compiled by: Lv Xiaoyi
Responsible Editor: Huang Jia