Data Analytics in Healthcare

The challenge to improve patient outcomes and care team coordination while reducing costs can’t be overcome without data to provide actionable insights and streamline processes. Data analytics in healthcare can advance staffing allocation, preventative care, patient engagement, operational efficiencies, and more. In this article, we explore how the move toward value-based care is driving the need for data and how today’s healthcare organizations are using data analytics to achieve better results for patients and their own operations. 

How Value-Based Care Is Driving Data Analytics in Healthcare

Value-based care isn’t new, but the industry’s pace in implementing it has accelerated. Although there are a variety of models for value-based care, what they have in common is moving from a focus on the number of procedures performed to improvement in patient outcomes. With value-based care, preventative care becomes central since it reduces rates of acute illness. 

Many healthcare organizations have already begun implementing value-based care models and are now seeking to optimize them. Because the focus is on outcomes, and outcomes must be measured using data, healthcare analytics plays a central role in implementing and optimizing value-based care models. Data provides essential information on the effectiveness of value-based care approaches as well as opportunities for innovation and cost reduction. Additionally, organizations are using predictive analytics to design incentive structures that make sense in pay-for-performance models.

How Healthcare Organizations Are Using Data Analytics

Let’s dive deeper into some of the specific ways today’s organizations are using data analytics in healthcare.

Staffing

Under- and over-staffing are an ongoing challenge to delivering quality care and achieving operational efficiency. With data analytics, hospitals and other healthcare facilities can avoid under- and over-staffing. By looking at historical admissions data and using predictive models to forecast demand in the near future, healthcare organizations can allocate staff accordingly. 

Patient engagement

Patient engagement has been linked to better health outcomes. And being involved in tracking their health stats can help keep patients engaged. For example, patients with certain conditions such as heart disease and diabetes can wear health monitoring devices that generate data and send it to their primary care doctors. Clinicians can then use that data to better understand a patient’s progress and use it to craft a more effective treatment plan.

Preventative care

Healthcare data can also identify risk factors and spot new health issues before they develop into acute illnesses. While the risk factors for some conditions are well known, such as the correlation of lung disease and smoking, many are not as obvious. When physicians have access to data that pinpoints risk factors relevant to a patient, they can deliver more-effective treatment plans. 

Operational improvements

The application of data analytics can also be used to achieve significant cost savings. From purchasing to resource utilization, data analytics can reveal opportunities to increase efficiency and lower costs.

Clinical trials

Scientists can use real-time data from monitoring devices to quickly identify patterns and issues. And clinical trial data along with advanced diagnostic analytics and predictive analytics can be used to mitigate cognitive biases to make more-objective decisions.

Examples of Healthcare Analytics in Action

To see how organizations are using data analytics in healthcare, let’s look at examples of two Snowflake customers. 

hc1

hc1, a leading provider of healthcare analytics solutions, helps public health officials stay ahead of the coronavirus outbreak by turning previously static lab data into actionable healthcare insights. hc1 has the largest repository of live, normalized lab orders and results in the U.S., including data on 160 million unique individuals with over 19 billion clinical transaction results. Powered by Snowflake, the hc1 platform has the power to ingest and organize data from all U.S. laboratories and offers a COVID-19 lab testing dashboard that delivers real-time visibility for public health officials seeking to track COVID-19 testing and infection rates and monitor hospital capacities in their regions.

Paladina Health

Paladina Health is transforming how primary care is financed and delivered, addressing escalating costs and the main causes of poor healthcare quality. Its payment and care model creates a partnership with clients, engaging patients and driving significant improvements to health outcomes, patient satisfaction, and cost. Paladina Health uses data analytics to generate insights from third-party sources, including EMR, member management, prescription fulfillment, provider referrals, and FDA-approved drug information, to lower costs and delight its patients. 

Snowflake for Data Analytics in Healthcare

Whether focused on delivering quality care or developing next-generation therapeutics, Snowflake empowers healthcare organizations with modern, powerful, and advanced analytics for the deepest insights possible. The Snowflake Data Cloud allows teams to centralize data in a single, secure location and unlock deeper insights with faster analytics that help improve patient outcomes, deliver quality member experiences, and streamline operational inefficiencies. And Snowflake’s built-in security and governance features support HIPAA, HITRUST, SOC 1 and 2 Type II, PCI DSS, and FedRAMP (moderate) requirements.

To see Snowflake’s healthcare data capabilities firsthand, sign up for a free trial.