Big Data in Healthcare – Possibilities and Potential

Ibad Rehman

14 Dec, 2023


4 min read


Today, no major breakthrough in the field of healthcare is possible without Data.

Whether it is an effort to enhance the operations of a healthcare organization, an endeavor to improve the healthcare situation of a region, or an effort to advance the field of medicine itself, it cannot be accomplished without reliance on data.

Applications of data in the field of healthcare are vast and multi-dimensional. For healthcare organizations, it is crucial to understand the role, importance, and potential applications of Big Data in the field of healthcare.

Data Types in Healthcare

Patient Records:

  • Medical Records: These records transcend mere documentation of illnesses, illuminating patterns that can predict potential ailments or predispositions.
  • Behavioral Data: Mental health has gained prominence, with patient behavior, stress levels, and lifestyle data becoming instrumental in proactive mental health strategies.
  • Biometrics: From retina scans foreseeing potential vision issues to DNA sequencing predicting genetic diseases, biometrics are shaping the future of personalized medicine.

Population Healthcare Data:

This type of data serves as an early warning system, shedding light on potential community-level health threats, such as flu outbreaks or sudden spikes in specific ailments.

Administrative Data:

Administrative data encompasses patient admissions, discharges, billing, and related aspects, offering insights into operational efficiency improvements that reduce patient waiting times and streamline hospital operations.

Avenues for Data Utilization

Patient Service Delivery:

What medical institute wouldn’t want to enhance patient experiences using data? By comprehending a patient’s complete health journey, healthcare providers can offer timely interventions, personalized care plans, and remote monitoring for chronic patients.

  • Unified Patient Records: Integrated Electronic Health Records (EHR) systems capture a patient’s medical history, treatments, allergies, medications, and other vital data, providing a holistic view for better decision-making.
  • Predictive Analytics: Analyzing patient data enables the prediction of potential health risks, allowing for timely interventions and the prevention of costly late-stage treatments.
  • Telemedicine: Data-driven remote monitoring systems track chronic patients’ health in real-time, reducing hospital visits and ensuring consistent patient care.
  • Personalized Treatment Plans: Analyzing individual patient data helps create tailor-made treatment plans, considering genetics, environment, and lifestyle.
  • Feedback Loops: Patient feedback data aids in the continuous refinement and improvement of care processes and patient experiences.

Healthcare Organization Administration:

Data’s role in helping organizations optimize operations and streamline administration is undisputed. Data analytics assist hospitals in managing resources efficiently, predicting patient influx, and ensuring top-tier care provision.

  • Resource Optimization: Analytics monitor hospital resources, including bed availability, medical supplies, and staff scheduling, ensuring optimal allocation.
  • Demand Forecasting: Analyzing past patient influx patterns predicts future demands, aiding in better resource planning and management.
  • Cost Management: Data analytics identify areas of excessive spending and streamline processes for cost efficiency.
  • Performance Metrics: Establish data-driven Key Performance Indicators (KPIs) to monitor and evaluate healthcare professionals’ quality of care.
  • Patient Flow Analysis: Monitoring and analyzing the patient’s journey within healthcare facilities identifies bottlenecks and optimizes patient flow, reducing waiting times.

Propelling Healthcare Advancements – Research and Development:

Imagine clinical trials boosted by AI, expediting drug discoveries and treatments. Big Data also aids in genomic research, facilitating breakthroughs in genetic diseases.

  • AI in Clinical Trials: AI algorithms swiftly analyze extensive trial data, accelerating the drug discovery process with accurate results.
  • Genomic Analysis: Big Data tools process large-scale genomic data, unveiling patterns and insights into genetic diseases.
  • Collaborative Research Platforms: Centralized databases enable global collaboration among researchers, expediting breakthroughs through shared insights.
  • Data-Driven Patient Recruitment: Data analytics identify ideal candidates for clinical trials, ensuring diverse and representative samples for more reliable results.
  • Real-world Evidence (RWE) Collection: Harness EHRs and wearable devices are used to gather real-world patient data, inform drug development, and refine treatment protocol.

Public Health Policy:

Governments can draft and implement health policies based on real-time data, ensuring timely responses to public health needs.

  • Real-time Disease Surveillance: Implement systems for real-time monitoring and analysis of public health data to respond promptly to outbreaks and health crises.
  • Data-Driven Policy Creation: Use data analytics to identify health trends, disparities, and needs, ensuring policies remain relevant and impactful.
  • Feedback Mechanisms: Establish systems for continuous public feedback on health policies, refining them based on lived experiences.
  • Population Health Management: Analyze data from diverse sources like wearables, mobile apps, and EHRs to gain insights into broader population health trends and address systemic issues.
  • Transparency and Reporting: Regularly publish data-driven health reports to keep the public informed and build trust in health policies and interventions.

Why Your Healthcare Organization Should Harness Data:

The Promise of Enhanced Healthcare Service Delivery:

Data empowers personalized treatments and real-time patient recovery monitoring, ensuring optimal health outcomes.

Geisinger, a Pennsylvania-based institution, exemplified this promise by using electronic health records (EHR) to enhance coronary artery bypass graft (CABG) surgery outcomes. Through data-driven best practices and protocol adherence, they improved outcomes, reduced complications, and established fixed pricing for CABG surgeries.

The Opportunity to Impact Public Health:

Data equips healthcare organizations to launch community health initiatives, focusing on preventive care and addressing healthcare disparities.
The New York City Department of Health and Mental Hygiene used data to identify neighborhoods with high rates of type 2 diabetes, initiating the National Salt Reduction Initiative (NSRI) to reduce salt intake. This collaborative effort led to a significant reduction in salt in food products, benefiting public health.

A Chance for Innovation and Medical Advancement:

Data played a pivotal role in the Human Genome Project, which mapped all human DNA genes and paved the way for personalized medicine.
Discoveries like the identification of BRCA1 and BRCA2 gene mutations linked to breast and ovarian cancer risks allowed for targeted screenings and personalized treatment, all stemming from data-driven research.

Embrace the Power of Data:

In a world increasingly reliant on data, healthcare is no exception. The transformative power of data in this field is not just a promise; it’s a reality that’s changing the way we approach healthcare, from the individual patient’s experience to global public health initiatives. Embracing the power of data is not just a choice but a necessity to create a healthier future for all.

Data’s vast implications and tremendous potential in healthcare beckon organizations to become data-driven. Partner with Cubix, a prominent big data development company with a proven track record, a global clientele, and a portfolio of successful projects to steer your organization in the right direction.


Ibad Rehman

Keen to experiment with new approaches, yet obsessed with sticking to the basics - trying to find the right balance between the two.


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