Healthcare Data Analytics: The Ultimate Guide for 2020 (+3 examples)

Healthcare data analytics is revolutionising healthcare for both practices and patients.

But the healthcare analytics market is a difficult landscape to navigate.

Even the pros have trouble working their way through such a fragmented industry!

Between big names, acquisitions, mergers and the influx of healthcare analytics startups, we understand how it can be quite daunting at first.

As a health professional, you most certainly don’t want to be left behind.

But, is it too late to start?

Never! It’s never too late to learn about how health analytics can truly transform your organisation.

In this guide, we’re going to introduce you to:

  1. Types of Healthcare Analytics
  2. Use-cases for Healthcare Analytics
  3. Top 5 Analytics Software Providers
  4. What to Look for When Choosing an Analytics Partner

Healthcare Analytics is an Indispensable Tool

Image by Gerd Altmann from Pixabay

Big data is no longer a tech buzzword. Early adopters and innovators have already made great progress on the data and digital maturity scale, which can be intimidating for those who are just starting.

We are now entering a new age of big data where the focus has shifted towards finding new ways to solve healthcare challenges using predictive and prescriptive analytics.

Healthcare analytics has the potential to set your practice apart from competitors. If you are looking to integrate patient data, improve staff performance, or improve the patient care experience, big data is an indispensable tool.

In a practical sense, proper use of analytics in healthcare BI can help you:

  • Reduce medical supply costs
  • Boost revenue
  • Reduce readmission rates and waiting times
  • Improve the patient care experience
  • Optimise your appointment schedule
  • Reduce time spent on paperwork
  • Make quicker and more accurate data-driven decisions
  • Deliver more personalised care
  • Improve interoperability
  • Enhance quality of care
  • Plan strategically

“We are moving slowly into an era where big data is the starting point, not the end.”

Pearl Zhu

Types of Healthcare Analytics

Along the analytics maturity model, there are 3 main types of healthcare data analytics: descriptive, predictive, and prescriptive.

Descriptive Health Analytics

According to HealthAnalytics.com, ‘Descriptive analytics is the ability to quantify events and report on them in a human-readable way’.

So, how is this used?

Descriptive analytics makes use of historical data to help healthcare providers with making better decisions in a more precise and timelier manner. For example, descriptive analytics can provide insights into a sudden peak in patients with similar symptoms for support during diagnosis and identification of outbreaks where this could’ve been a very time-consuming manual analysis that could cost lives.

You’ll see descriptive data in analytics dashboards and reports.

Predictive Analytics

This where most health organisations aim to be on the data analytics model. It takes an enormous effort and teamwork to get to this level of analytics. Imagine taking your historical descriptive data and using machine learning to analyse patterns and trends at a much deeper level.

As the name implies, predictive analytics assists healthcare providers with predicting the next steps or outcomes of things like certain treatments, care plans, as well outbreaks.

Prescriptive Analytics

This is where health analytics become most useful. Where descriptive and predictive analytics help with understanding and monitoring data, prescriptive analytics will help with taking meaningful action.

According to Healthcareitnews.com, “The benefits of [prescriptive analytics] range from the identifying areas of improvement in treatment and protocols to reducing the rate of re-admitted patients, and lowering the cost of healthcare in general- from patient bills to the cost of operations in hospital billing departments.”

3 Use-cases for Healthcare Analytics

Video source: HuffPost

Population Health Management

Using predictive analytics, health organisations improve the overall health of communities and deliver a better standard of care by identifying individuals who are at risk and responding with the appropriate treatment much earlier.

Optimised Scheduling

Health professionals are used to having busy diaries, but cancellations do occur. And, when these cancellations happen at very short notice, it can lead to a loss of revenue and time wasted. Analytics can help optimise your schedule, reduce wait times, and even predict the likelihood of a cancellation.

Patient Relationship Management

A connected customer is spoilt for choice when it comes to service providers, but what sets one practice apart from another is the level of customer care – or in this sense – patient care.

Both descriptive and prescriptive analytics assist with improving your ability to respond to insights about the patient experience and thereby improve engagement and retention rates.

Top 5 Market leaders in Healthcare Analytics Solutions

1. IBM Watson Health

Video source: IBM Think Academy

We’re starting with a real heavy hitter when it comes to health analytics. Combined with a powerful platform and advanced AI solutions, IBM Watson Health is one of the best analytics providers in healthcare.

IBM Watson Health Insights provides access to rich data sets, analytics, AI and blockchain technologies to generate actionable and relevant insights to help organisations with research, decision-making as well as workflows and operational management.

The platform features curated dashboards, self-service reporting, data storytelling, AI capabilities and comparative benchmarking, among other powerful capabilities.

Their solutions are tailored for government, health providers, life sciences, and consulting services.  IBM Watson is well suited for enterprise-level organisations who are looking to manage data transformation at scale.

Case studies:

2. Definitive Healthcare

Image source: https://www.definitivehc.com/

Founded in 2011, Definitive Healthcare is a relative newcomer to the healthcare analytics industry. The company now employs over 320 people in a youthful, vibrant environment.

Definitive Health has a range of solutions which are geared towards accelerating data transformation and optimising one’s healthcare business strategy, marketing, and staffing.

Their data products provide access to many sources of data such as hospital data, medical claims records, long-term care facilities, ambulatory surgery centres, clinics, and over 1.7 million other healthcare professionals around the US.

They also offer a free trial, which is an excellent way to get to know their platform and dashboards in greater detail.

Case studies:

3. Flatiron Health OncoAnalytics

Video source: Flatiron Health

Flatiron Health is one of the leading healthcare software providers in oncology. Their analytics product, OncoAnalytics forms part of Flatiron’s brilliant suite of features tailored for oncology practices and cancer research centres.  

The platform provides customers with access to deep insights from sources such as EHRs, practice management and billing. Although it processes such a large amount of data, their dashboard does a great job of sorting, analysing and displaying key trends and information in a user-friendly way.

OncoAnalytics is the perfect addition to the Flatiron Oncology platform and by gaining access to their OCM (Oncology Care Model) data, practices are empowered to participate in their 5-year voluntary value-based care program.

4. Datapine Healthcare Analytics

Datapine stands out among other healthcare data analytics startups with their innovative data analysis tool.

This Berlin-based company is on a mission to help healthcare providers to run more efficiently, optimise revenue generation, improve quality of care, and increase patient satisfaction levels with their powerful data analysis and visualisation capabilities.

For those who are looking for a hands-on experience of the platform, Datapine offers demo dashboards, and a free trial.

Case study:

Jefferson Medical Center: improved operational efficiency by more precise methods of analysing employee productivity.

5. Informatica

Informatica is the leading data solution provider in The Netherlands. They’ve been named as a leader in 5 Gartner Magic Quadrant Reports relating to data quality, management solutions, and integration.

The company provides solutions for organisations undergoing digital and data transformation who require assistance with cloud migrations, data governance, compliance and analytics.

Their healthcare data analytics platform is designed to boost productivity, drive efficiency, improve patient engagement, improve data quality, and improve the overall customer experience at scale.

The platform also integrates easily with other systems in order to collect data from various sources including social, IoT, and medical devices and create a 360 view of the customer.

Case studies:

Dana-Farber Cancer Institute: management of the integration of multiple systems in order to understand how their funding is spent.

Humana: increased access to data from all operating units and leveraged customer data in order to create personalised care plans and improve customer visibility.

“The latest trend of increasing collaboration between healthcare organizations and pharmaceutical companies to improve treatment plans is escalating the market on the global platform, revolutionizing the healthcare sector, completely.”

Medgadget.com

Finding the Right Healthcare Analytics Partner

When it comes to data transformation and analytics adoption maturity, there are often so many stakeholders, systems, siloed data, and other information in play, that it can quite easily veer into the wrong direction.

Making even the slightest error or misjudgment can result in catastrophic damages not only to one’s organisation, but to the lives of your patients. Data stewardship and transformation should not be taken lightly especially when it comes to privacy, security, and accuracy.

Which is why it’s so important to work with a top tier healthcare data analytics solution partner. When reviewing these partners, be sure to review the following:

  • Their data science expertise
  • Data sources and compliancy
  • Current clients and average length of contracts
  • Case studies
  • Data security measures
  • Data visualisation samples (dashboards, reports, charts etc.)
  • Their contribution to the broader medical community
  • What systems they integrate with
  • What added value they bring
  • Their ability to potentially provide bespoke solutions and innovation

Don’t miss out our latest healthcare solutions, platforms, and app reviews. Download our app to stay up to date.

References:

Healthcare Analytics Software reviews:
https://www.g2.com/categories/healthcare-analytics

10 High-Value Use Cases for Predictive Analytics in Healthcare
https://healthitanalytics.com/news/10-high-value-use-cases-for-predictive-analytics-in-healthcare

Unlock the Power of Data Across: Health Systems and Institutions
https://www.sisense.com/solutions/healthcare/

12 Examples of Big Data Analytics In Healthcare That Can Save People
https://www.datapine.com/blog/big-data-examples-in-healthcare/

How Health Care Analytics Improves Patient Care:
https://healthinformatics.uic.edu/blog/how-health-care-analytics-improves-patient-care/

Top 20 in Healthcare Analytics: In-Depth Guide [2020 update]
https://blog.aimultiple.com/healthcare-analytics-vendors/

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