Healthcare data analytics overview

Data-driven insights that can improve patient care

The healthcare industry is undergoing many transformative changes, such as implementing new electronic health record (EHR) systems and processes, and the pace of those changes is likely going to increase. Older approaches to care are quickly being replaced and healthcare organizations will need more effective clinical data management to take advantage of new, potentially transformative trends in technology and analytics.

Some of the trends emerging from efforts to incorporate big data in healthcare include:

  • Moving away from acute and episodic care models to value-based care
  • Increasing opportunities to benefit from large collections of healthcare data
  • Robust analytics that could help resolve complex health challenges
     

Simplifying collection and organization of healthcare data is a promising first step for most healthcare organizations. But having tools uncover the most useful data in a vast collection of information will be key for organizations to get the most value from big data in healthcare. Healthcare data analytics help organizations uncover vital insights in their data that could help them identify opportunities to provide more value, efficacy and better-quality care at an affordable cost.

A doctor sitting and laughing with a tablet in her hands

Responding to the revolution in healthcare

AI & machine learning in healthcare data analytics

The right response to healthcare’s digital transformation is an informed approach. The first step begins by leveraging the best tools available. In general, artificial intelligence (AI) and other automation tools – aim to enhance and amplify the work of professionals. They enable these professionals to gain new insights, accelerate discoveries and amplify human knowledge.

AI and machine learning platforms are among those being considered by leading organizations given their ability to reason, deduce and “understand” the interactions taking place with their users. These systems are capable of absorbing tremendous amounts of data – both structured and unstructured—and then offer hypotheses for the user to consider, along with a confidence level for every insight and answer.
 
From there, healthcare professionals continue the process. Armed with the results, healthcare providers, health and human services professionals and researchers are more easily able to identify the connections, correlations and patterns to the puzzles they are working to solve.

A woman showing some graphics to people

Predictive analytics produce value

Turning data into actionable insights

To convert healthcare data into actionable insights, organizations will need focused information regarding their organization’s true costs, the quality of the service they provide and the actual relevancy of that service.

That information could also help organizations pursue positive trends like:

  • Service models evolving from quantity-based, fee-for-service models to patient-centric, value-based care systems
  • Clinical IT moving towards more centralized and connected enterprise IT infrastructures
  • Clinical devices becoming more connected with increasingly automatic data integration
  • Collaborative communication tools and real-time location sensing devices uniting clinical IT and enterprise IT networks

 

Discoveries from actionable insights could be studied continuously and used to increase the value of an organization’s work.

 

Cloud in healthcare

75%

Seventy-five percent of surveyed healthcare providers feel optimistic that cloud will lead to improved point-of-care decisions.

Blockchain in healthcare

70%

Seventy percent of executives out of 205 surveyed said they expect to have blockchain networks in production in 2020.

Healthcare data analytics case studies

Motivate to participate

Collecting analytics and genomic data

IBM Watson Health™ is attempting to help identify treatment options for patients with specific genetic mutations using genomic data and other healthcare analytics. This type of clinical data management could help move biomedical research forward.

Moving toward improved value and patient care

Through a health information exchange or HIE, focused on interoperability, information in EHR, healthcare analytics and other relevant data could flow more easily across a healthcare system and make it easier for healthcare providers to collaborate and spot trends.

Solutions

Watson Health healthcare analytics solutions

IBM Watson Health is creating solutions to enable a smarter, more connected healthcare system that can help assist clinicians to deliver better care and empower people to make better choices. In addition to the company’s investment in health technology research and innovation, IBM healthcare solutions help enable organizations to achieve greater efficiency within their operations; collaborate to help improve performance; and integrate with new partners for a more sustainable, personalized system focused on value.

 

Modernizing government health

Solutions allow government agencies to extract meaningful insights from data to help improve cost, access, quality and outcomes for populations.

Help with costs for providers

Take steps to improve your health system’s clinical, operational and financial performance.

Helping radiologists interpret images

Watson Health enterprise imaging solutions enhance workflows and deliver efficiencies that drive immediate impact while helping physicians prepare for the future.

 

Launching life science solutions

IBM Watson Health life sciences solutions provide companies with analytics and expertise to help develop treatments more efficiently and effectively.