Healthcare Analytics: Importance & Market Landscape in 2024

Healthcare analytics software helps deliver clinical insights into patient care and personalize medicines while reducing operating costs for healthcare providers, in addition to other use cases. There are hundreds of companies offering analytics products and solutions for healthcare organizations. It is best to start with a definition and categorization of these companies.

What exactly do healthcare analytics vendors do?

Healthcare is data-rich. Diverse data types include:

• patient clinical data including lab results, diagnosis
• claims and cost data
• R&D results including published papers, clinical trial results
• other data on patient behavior

Systems provided by healthcare analytics vendors allow companies to access numerous data sources within healthcare providers’ own records in different systems. Additionally, they can provide access to data from other healthcare providers and clinical studies.

With this abundance of data, it is difficult to consider healthcare analytics without artificial intelligence. Natural language processing (NLP) capabilities allow companies to analyze diagnostic text, published research, and other textual data. Image processing capabilities allow analyzing outputs of various medical imaging techniques.

Understand healthcare analytics vendor landscape in 2 minutes

To choose a vendor in this area, you must understand the vendor landscape and compare vendors to choose the most suitable vendor for your business. Evaluating vendors and making the right vendor assessment can be a time-consuming effort.

There are the 4 main types of vendors in this industry:

1. Established technology providers

Companies like IBM or SAS are the oldest group of companies offering healthcare analytics services. Founded long before the dot-com bubble, these companies have established relations with a large number of Fortune 500 companies. They leverage these relationships to offer healthcare analytics services.

Just because they are older companies does not mean that they do not have the leading-edge solutions. IBM has been instrumental in making AI a household term thanks to Watson and has been pioneering the use of Watson in healthcare.

The fact that your company potentially already works with these vendors also makes it easy to adapt their solutions.

2. AI vendors with healthcare analytics offering

Founded in the 2000s, vendors like Ayasdi and Digital Reasoning Systems are focused on developing AI services to transform industries like healthcare, financial services, retail. They are generally larger and more established than purely healthcare-focused companies.

3. Purely healthcare analytics focused vendors

Founded in the 2000s and 2010s, this group includes both large and small companies. For example, Linguamatics, one of the largest healthcare analytics-focused vendors, boasts that its product is used by almost every global pharma company.

4. IoT-based solutions that facilitate Healthcare Analytics

Though analytics discipline for IoT data is mostly referred to as IoT analytics or edge analytics, IoT devices are great enablers for healthcare analytics as well. Devices such as wearables or IoT-connected inhalers can help healthcare providers acquire required data for monitoring, analytics, and making a data-driven decision.

• Telit can enable patient monitoring through IoT devices and provide actionable insights to improve patient outcomes and control costs.
• caresyntax leverages IoT and analytics to provide decision support for surgical teams. It claims that its product is used in >7,000 operating rooms supporting >10 million procedures per year.

For a comprehensive list of vendors and detailed information about each vendor you can check our sortable/filterable list of healthcare analytics companies.

Why is it critical to choose the right healthcare analytics system?

Healthcare data is unique and difficult to measure. Finding the optimal vendor can make the difference between a system of limited use and a transformative one. The healthcare analytics vendor will need to tackle these issues:

• Data federation issues:
  • Data silos: From EMR to different departmental software, healthcare data tends to be stored in silos.
  • Privacy issues: Complex federal and state-level regulation determines how private data is handled.

• Data quality issues:
  • Unrecorded data: Difficulty of inputting structured data into EMR is leading practioners to leave important data out of the system.
  • Inconsistent or variable definitions: For example, diagnostic criteria changes over time as physicians gain a better understanding of patient conditions. Diffusion of new definitions takes time and happens in irregular patterns
• Analytics challenges
  • Complexity: We still don’t know exactly how the body or the mind works. Complexity of health is beyond complexity of systems like transportation, manufacturing or finance
  • Format issues: From scanned paper to videos, data comes in numerous formats

How can companies build custom healthcare analytics solutions?

Healthcare has unique challenges and not every healthcare analytics use case can be addressed effectively with off-the-shelf solutions. Feel free to read more about developing custom AI solutions for your company’s needs. For example, healthcare companies can run data science competitions to build effective solutions at low cost for their specific problems. If you want to learn more about custom AI solutions, feel free to read our whitepaper on the topic or reach us to identify custom AI, solution partner:

You can check our list of medical data annotation tools to find the option that best suits your medical computer vision project needs.

If you are ready to invest in off-the-shelf healthcare analytics solutions, we can also help you:

Sources:

AJMC.com

Wikipedia