Data analytics is the process of collecting, curating, and correlating data to produce actionable outcomes. By using data from multiple sources, companies can explore historical patterns, identify current trends, and predict future outcomes.
In healthcare, data analytics benefits patients, operations, and population health management. From a patient perspective, data about illnesses and treatments can lead to the creation of personalized care plans.
For operations, analytics helps optimize workflows and resource allocations. And when it comes to management at scale, analysis tools can be used to track population-scale trends that can help inform emergency response.
Data Analytics in Healthcare: Three Key Areas
Let’s explore each analytics area in more detail.
1. Patient Care
There are several ways organizations can leverage analytics for improved patient care.
First are personalized treatment plans. By combining data about a patient’s current health status with information about past illnesses or concerns — such as a history of chronic or acute illness, or adverse reactions to specific medications — clinical teams can create plans that target specific symptoms or address root causes while helping patients preserve their quality of life.
Analytics may also be used to help predict disease progression. While many illnesses have predictable long-term patterns, their progression for individual patients is partially determined by personal health factors. By collecting and integrating patient data into predictive analytics tools, clinicians can better understand and prepare for disease progression.
2. Hospital Operations
Hospital operations benefit from analytics. Consider staffing levels. Although hospitals and skilled nursing facilities often require specific staff ratios to remain in compliance, ensuring these targets are met can become challenging as organizations deal with ongoing staff churn and the long-tail legacy of Covid-19.
By applying analytics to staffing data, healthcare companies can determine optimal staffing levels given current availability and identify where to allocate diminishing resources to ensure the best business results (e.g., which patients are higher risk and need more attention).
Workflow optimization is another analytics pathway. For example, analytics solutions may be used to pinpoint operational bottlenecks, such as redundant patient data entry, which waste available staffing resources on repeated tasks. Once identified, teams can take steps to streamline these redundant operations.
3. Population Health Management
From a population health standpoint, analytics can help improve care at scale. Thanks to the vast amount of anonymous demographic information now available, it’s possible for organizations and government agencies to effectively track disease outbreaks or pinpoint areas of increased viral risk.
These population-level tools also let healthcare providers identify disparities across regions, income levels, or other demographic features.
The Benefits of Healthcare Analytics
By implementing healthcare analytics, organizations can improve patient outcomes. Teams can track patients’ progress, measure their satisfaction and predict the number and type of treatments they may need.
Analytics also provides the opportunity for reduced costs and improved efficiency by helping healthcare providers identify and eliminate redundancies. At scale, these tools set the stage for improved strategic decision-making that can positively impact both patient experience and revenue generation.
What’s Next? The Future of Data Analytics in Healthcare
Much like data itself, analytics is a dynamic and growing healthcare field. New developments on the horizon include:
Artificial Intelligence (AI)
Artificial intelligence and machine learning make it possible for analytics solutions to “learn” from data and deliver patient care and monitoring results that even non-specialists can read.
Telemedicine and Remote Patient Monitoring
What began in 2020 as a pandemic response measure has become a critical part of healthcare operations. By applying analytics to telemedicine and remote patient monitoring, care teams can gain a better understanding of what patients need, and when they need it most.
Integration with Healthcare Education
Integrating analytics into healthcare education can help clinicians gain real-world insight. Using anonymized patient and demographic data, teams can make better decisions with greater confidence.
Connecting the Dots with Healthcare Analytics
Data analytics helps organizations connect the dots across patient care, operational outcomes, and population health management. And the value of analytics is only growing as solutions such as AI and remote monitoring become a reality.
Put simply? The sooner, the better, when it comes to adopting healthcare analytics.