Before we get into healthcare data management, let us have a brief understanding of what data management is and why is it essential in the current context.

Data management is a piece that comes into the picture once all the data is ported to a centralized location (called data lake or data warehouse) and needs to be massaged to make it ready for analytics and insights.

In a healthcare environment, data flows from various internal as well as external sources, and there is always some repetition in the data attributes. Cleansing, scrubbing, and de-duplication of the data to make it analytics-ready is an important aspect of the whole analytics process. That apart, there are various compliances such as GDPR and HIPPA, where one has to ensure that data is appropriately masked, and no personal data is fully divulged to any party.

When we consider the various complexities in data management, it does not come as a surprise that the enterprise data management market is slated to reach approximately 150 billion dollars by 2023, growing at a rate of 12 % CAGR.

In light of this information, it is also worth noting that the healthcare analytics market is set to reach USD 50 billion by 2024. Only the data interoperability market size will become USD 5 billion.

Healthcare is primarily a knowledge industry, where a lot of data is collected for care management, financial planning, and advancement of knowledge. Thus, it is becoming extremely important to collect all such data in a central pool from where it can become easy to perform analytics and derive actionable insights. EHRs or electronic health records need a structure in which they store data. Today, a lot of data is also streamed from various wearables, and that also needs to be stored. Given all this, it has become extremely critical for hospitals to manage their data flawlessly.

The Complexity of Healthcare Data Management

Various kinds of data come into the picture when it comes to healthcare data management. It contains medication records, demographic data, diagnosis data, genetics data, data about patient history, socio-economic data, etc.

This data is further divided into two other substrata – structured and unstructured data. Structured data examples would be the prescribed medication, dosage, ECG results, census records, lab analysis, etc. Unstructured data includes diaries, instructions, blogs, and tweets. In an industry like healthcare, it makes more sense to tap into the potential of unstructured data. It is estimated that the amount of data is set to grow by 48% annually!

The Benefits of Healthcare Data Management

Seamless Communication and Collaboration: The most fundamental benefit of healthcare data management is the strategic advantage that if offers. With centralized access to health data, various caregivers can communicate with each other and ensure that the best possible treatment is doled out to the patients.

Better Compliance: All the industries are mired with compliance requirements, and healthcare, as a highly regulated industry, is even more so. HIPAA is the law that governs healthcare data management. This law mandates that the whole process of data acquisition, storage, securing, and analyzing data is done securely. With a structured approach to healthcare data management, it is easier for healthcare institutions to manage stringent compliance and regulatory requirements.

Better Patient Care: Better data management helps in easier research about disease linkages and also helps in improving the quality of patient care. With strong data management practices, everybody in the ecosystem can get a 360-degree view of the patient, a view that encompasses various aspects ranging from socio-economic factors to diagnosis results. With the entire gamut of information available, it is easier for the caregivers to update the medication and treatment plan.

The Critical Aspects of Healthcare Data Management

However, the whole transition process has its own set of challenges. The data available with the healthcare domain, with the streaming data being made available from IoT devices is growing exponentially. Managing all that is going to be tricky. Another challenge that is even bigger than the first one is a cultural change. The whole industry has to shift towards a data-driven mentality. This shift in paradigm has to be inculcated from the top.

The three critical aspects of healthcare data are –

Measurement of progress: This stems from the fact that the organization has to be willing to acknowledge that data is a strategic asset and can add a lot of value to the services being provided.

Management of the exponentially growing data: As the structured and unstructured data is growing, it is important to have proper data governance in place. Governance methodologies and the tools available in the market can ensure that the organizations know where the data is and what is its lineage.

Data monetization: This is one of the key aspects. The biggest buyers of this data are going to be payer organizations. Data management can ensure that we can smoothly process and monetize the data.

In summary, it is safe to say that in light of the various compliance challenges, regulatory needs, constant pressure to reduce costs and aspirations to innovate new revenue models, it is crucial for healthcare institutions to manage their data judiciously.