Big data in healthcare supports which outcomes?

• A. Increasing manual data entry requirements.
• B. Worsening health outcomes for the population.
• C. Disease management, reducing healthcare spending, and improving outcomes.
• D. Eliminating the need for clinicians.

Answer: (C)

Big data in healthcare enables disease management, lowers costs, and improves patient outcomes by turning large, diverse data into actionable insights. By integrating electronic health records, claims, imaging, genomics, wearables, and social determinants of health, analytics can identify patients at high risk, tailor interventions, and monitor responses over time. This supports proactive care and chronic disease management, catching complications early, preventing hospitalizations, and optimizing treatment plans. When care is targeted to those who need it most and unnecessary tests or procedures are reduced, systems become more efficient while preserving or enhancing quality. The overall effect is better decision support for clinicians, timelier care, and population health strategies that address quality, safety, and equity.

The other choices don’t fit because big data aims to reduce manual data entry and administrative burden, not increase it. It also seeks to improve outcomes rather than worsen them. And while analytics enhance clinical decision-making, they do not eliminate the need for clinicians.