T The power of data analytics in healthcare cannot be understated. Today’s healthcare ecosystem is presented with huge volumes of operational and clinical data ⁠—paving new paths for actionable clinical intelligence. The high adoption of healthcare analytics is fueled by the need to manage complex and diverse data sets, changing regulations, and increased innovations from population health management to value-based care and precision medicine. Organizations are largely leveraging healthcare analytics capabilities to drive new processes and strategies for value-based care.

Data Analytics in the Wake of COVID-19

Now, more than ever healthcare data plays a significant role in gathering and tracking relevant data to accelerate the COVID-19 emergency response. Real-time crisis management platforms are implemented to combine situational data including hospital capacity, alternative treatment locations (Hospitals without walls), testing kit quantities, and Protective gear availability to facilitate immediate emergency response decisions.

This shifting healthcare landscape demands that organizations treat data with a strategic mindset – that harnesses systems and data processes to influence decision-making and drive actionable insights. This level of healthcare analytics data will enable health systems to focus their efforts on patient centricity and better responsiveness to disaster management.

The Combined Power of Data and Expertise

Organizations that leverage the capabilities of healthcare analytics are reported to have a 5%-6% higher productivity and output than their peers. Big data is one of the top differentiators for high performing organizations – fostering increased revenues (8%) and reduced operational expenses. In the healthcare landscape, big data analytics is proven to significantly enhance overall health outcomes, reduce readmissions, and improve financial reporting. With robust data sources increasing from wearables, IoT-enabled devices, electronic health records and social media, insight-driven health can help identify patterns in information – enabling health systems to predict, infer and conceive care plans and strategies that might not be otherwise obvious.

Data-driven organizations harness clinical and operational data capabilities to get deeper insights into business health check and achieve operational excellence and intuitive design strategies for the future. In a value-based healthcare landscape, an external organization like an electrocardiogram (ECG) evaluates data to create a collaborative culture that fosters connected and continuous care across the continuum. In the healthcare industry, these are the top considerations we observed in building a data-driven healthcare organization.

Top 3 Considerations in Empowering Data-driven Healthcare Organization

1. Identifying the Right Healthcare Analytics Tools
Data-driven organizations use a strategic combination of data warehousing and analytics solutions that provide accurate and actionable insights. For instance, an AI tool can promptly discover COVID-19 utilizing a patient’s CT scan and clinical data. This highlights the use of blending clinical data into the diagnosis process – a perfect use case for AI-powered healthcare analytics. One-size fits all approach does not meet the varying needs; organizations need to choose from several options

• Claims-based data solutions
• EHR-based analytic systems
• Population Health Management solutions
• Enterprise-wide data analytic platforms

Your organization must analyze the best-fit solutions with flexible and scalable options to meet your business's current and future needs.

2. Managing the Healthcare Analytics Team
Healthcare systems must develop an organizational structure to perform data analysis and manage the enterprise-wide flow of information. At the initial level, this means that the frontline staff uses analytics tools to gather the most important information to improve operational excellence. As an organization grows, this will have a significant impact on building a more meaningful structure and use of data. This structure will continue to evolve around systems optimization and data integrity – while promptly responding to data requests.

3. Infusing Data into the Organizational Culture
Make data a significant part of the company culture, where stakeholders are up-to-date with relevant statistics that impact organizational performance. These statistics can go on the dashboards and conference room walls for analysis and strategic roadmap. While tools and resources help digital transformation, creating transparent healthcare analytics data on performance against strategies can have a significant impact on organizational culture.

Final Thoughts

For most healthcare systems, becoming a data-driven organization is somewhat unplanned and happens by chance⁠—resulting in responding to value-based care analytic requirements and cost pressures. They witness the transformative benefits of data-driven decision making to build more mature strategies and solutions to support overall processes over time.

It is recommended that organizations start with targeted measures by addressing some of the pressing business challenges, before developing a more holistic approach and implementing a cultural change across the enterprise. However, to be truly competitive, organizations need to design an inclusive and comprehensive roadmap with 10-15 years in the future ⁠— incorporating data into the organizational culture and scaling up plans to achieve business value.

Robust and insightful data have the power to unlock new possibilities, transform an organization and differentiate it from competitors. To learn more on harnessing the capabilities of insight-driven health in your organization,
talk to our team