Raw data might not appear groundbreaking, but in healthcare, big data is paving the way for enhanced patient outcomes, operational efficiency, and the emergence of innovative healthcare models.
Real-time analytics have a pivotal role in reshaping traditional approaches as data complexity skyrockets. Big data plays a significant role in optimizing workforce management, financial analysis, and resource allocation. Additionally, it empowers clinicians to deliver superior care by tracking patient symptoms and devising preventive care strategies.
Big data’s influence extends to fostering healthcare innovation. The ability to analyze vast datasets fosters unprecedented innovation opportunities, exemplified by the U.S. Centers for Medicaid and Medicare Services saving $210 million through its fraud prevention system.
The prominence of data in healthcare is undeniable. Let’s explore the top trends shaping big data’s role in healthcare:
1. Evolving Categories:
Previously defined by three Vs (volume, velocity, and variety), big data now encompasses five Vs, including value and veracity. These new dimensions impact healthcare significantly:
- Volume: Ongoing innovation, spurred by COVID-19 and technological advancements, generates an unprecedented volume of data.
- Velocity: Beyond Electronic Health Records (EHR), data collection from apps and patient portals accelerates. Traditional methods are supplemented with rapid, efficient data collection.
- Variety: Healthcare institutions aggregate data from diverse sources, necessitating strategies to unify this data effectively.
- Value: Recognizing the immense value of healthcare data in comparison to credit card data is a key shift.
- Veracity: Ensuring data trustworthiness and quality remains paramount for patient outcomes and data security.
2. Data Lakes:
Given the influx of data from various sources, data lakes have become essential for storing and organizing healthcare’s big data. Data lakes enable flexible data processing while preserving raw data, crucial for managing non-EHR data like insurance claims, imaging, demographics, genetics, and more.
3. Predictive Analytics:
Predictive analytics emerges as a major trend in leveraging big data for informed decision-making across healthcare operations. Cost savings and improved patient outcomes are driving its adoption, with applications spanning clinical, financial, and administrative domains.
4. Diverse Data:
Incorporating diverse data sources is pivotal for achieving equitable healthcare solutions. Big data’s richness, stemming from its multiple sources, provides valuable insights, including socioeconomic and social determinants, enabling a holistic view of patients and tailored treatment paths.
5. Big Data and AI:
Big data serves as the bedrock of effective AI implementation in healthcare, supporting AI’s rapid growth. Clean and aggregated data pipelines are essential for AI development.
Challenges persist, however, as not all healthcare systems possess the capability to collect and process complex data. Improving interoperability and data integration remains a priority in the big data landscape of healthcare.