Healthcare produces some of the most complex and abundant data. The volume of healthcare data generated globally has grown from 153 exabytes in 2013 to a projected estimate of 2,314 exabytes in 2020, making data analytics integration an absolute necessity.

A massive volume of data is captured annually between electronic health records, lab test results, MRI scans, patients’ wearable devices, and research studies. Hidden within this mass of poorly structured data are gems that can improve your organization’s patient care, operational efficiency, and profitability.

Unfortunately, data analytics integration has been a significant challenge for most CIOs and other healthcare leaders. That’s why we have decided to address the challenges posed and show you how to improve data analytics and its integration in healthcare.

Below we’ll be discussing some of the critical benefits of analyzing healthcare data effectively and the tips for achieving integration.

What Is Healthcare Data Analytics?

Simply put, data analytics are the tools and techniques used to capture, store, and analyze healthcare data to create information that’s useful to healthcare providers, clinicians, patients, and government institutions.

Effective use of data analytics in healthcare should offer the following benefits:

  • Raise the quality of patient care
  • Prevent escalation of conditions
  • Provide warning signals to doctors
  • Improve care outcomes
  • Lower operational costs
  • Give accurate forecasts of community health and disease trends
  • Enhance cost-effective inventory management
  • Reduce waste
  • Improve utilization of clinicians consulting hours
  • Support smart decision making

How to Achieve Data Analytics Integration

The following tips can help your organization integrate data analytics and achieve your desired results:

1. Integrate Your Disparate Systems for More Efficient Data Sharing

Are your EHR, lab information system (LIS), radiology information system (RIS), and billing admin systems interconnected? If they are not, you need to integrate them right away.

Invest in a robust interface engine that can use industry-standard protocols like HL7 FHIR to link all your healthcare information systems. This is a vital step towards the effective analysis of the data you generate in your organization. After that, you should develop a robust information-sharing culture that enhances interoperability and uses big data for predictive analysis.

2. Choose Analytics Tools That Have Multiple Capabilities

Extensive data analysis is a complicated process. And only a robust tool with multiple capabilities can handle it effectively.

Some of the features you should look for in your analytics tool include:

  • Cluster Analysis: Showing population clusters that need treatment of a chronic disease
  • Quality Assurance: Analysis of hospital performance against established benchmarks
  • Machine Learning: Prediction of risk posed by disease and successful determination of epidemics
  • Processing of Natural Language: Ability to turn speech to text and reduce the cost and time for data processing.

3. Use Cloud-Based Tools With Scalable Storage Capacity

With the massive volume of data generated, your analytics tools must have flexible storage. Cloud computing offers you flexible data storage.

When you need more storage space, you can increase your quota. If your demand for storage drops, you can change your data storage plan.

4. Employ Stringent Security Measures

While you strive to improve integration and data analysis, you need to protect sensitive data. Ensure that you comply with all HIPAA regulations on the protection of patient privacy and information.

Use robust encryption protocols to protect data. Enforce access control and use two-factor authentication to protect access to user accounts.

5. Train All Healthcare Personnel to Interpret Reports Correctly

After putting a solid analytics framework in place, you need trained eyes to use the graphs, predictions, and reports. Don’t assume that all health professionals will know how to make the best use of analytics tools. Invest in relevant training.

Training will empower clinicians to use analytics reports to improve diagnosis, avoid dangerous prescriptions, and offer personalized care. Always remember that incorrect interpretations will defeat the purpose of investing in data analytics tools.

See Healthcare Data Analytics in Action

Take a step towards effective data analytics integration in your organization today. Call Lifepoint at 877.522.8378 to book a free demo of our data analytics solutions. You can also talk to us through our contact page to discuss all your interoperability and integration needs.