What Is Healthcare Analytics? How to Use Data for Better Health

People only care about two things: their health and their data.

Imagine a world where we could use technology to manage population health, improve chronic care, enhance healthcare performance, and predict diseases. If you, like me, were pleased with the world you were able to imagine, congratulations! This fantasy is now a reality.

By leveraging the right tools, such as healthcare analytics software, institutions and providers can make their lives and their patients’ lives easier through better data capture, operational efficiency, and data-backed treatment outcomes.

Healthcare analytics provide insights that help healthcare providers be more effective during operations. When healthcare analytics tools are integrated with business intelligence and data visualization systems, providers can get real-time information that leads to better decision-making.

Capitalizing on data for healthcare also improves patient care and clinical data management through efficient diagnoses and business management.

Importance of data analytics in healthcare

The healthcare industry deals with a lot of data. Inaccuracies in information can directly impact healthcare quality and put patient safety at risk due to ill-informed clinical processes.

By helping collect verifiable data that has actionable insights, healthcare analytics promotes fact-based decision-making and improves overall data planning, measurement, and management.

One of the healthcare industry's biggest challenges is cost reduction that doesn’t compromise patient care. Using analytics and data warehouse software helps maintain the financial health of an organization and essentially allows for more care with less resource expenditure. To focus on patient-centric processes, providers and physicians can implement healthcare analytics to simplify and automate everyday tasks and increase productivity.

It’s no surprise that healthcare companies work in unpredictable and fast-paced environments. The recent health crises, changing government regulations, and evolving market dynamics continue to complicate the healthcare industry.

Such drastic shifts necessitate smarter decisions to stay competitive, improve healthcare delivery, and meet consumer expectations and demands.

What is the role of data analytics in healthcare?

Since healthcare analytics mostly consists of effectively deriving insights from data analysis and data science, it is also referred to as healthcare data analytics.

Data analytics and management in the healthcare industry are primarily concerned with data collection and organization into a central information repository. Because so much data is exchanged between providers and systems daily, administrative healthcare workers rely heavily on these analytics to structure all the information and refine existing data management processes.

The relationship between data analytics and healthcare is integral as the technology helps healthcare organizations keep a competitive edge in the market. It allows for better service quality, advanced care, and efficient processes.

In a world running on technology, healthcare providers benefit from software such as medical device tools and machine learning systems to simplify data collection, verification, and analysis. Using data analytics as a part of information processing methods helps maintain a structured data repository, converts complex data into easy-to-understand insights, and enables better decision-making.

When leveraging data analytics, everyone at every level has to be comfortable with the technology and understand its true impact. Because analytics –  especially big data analytics – supports providers, staff, and other stakeholders with detailed patient information that can offer personalized and precise treatment options.

Healthcare analytics examples

Healthcare analytics use cases range from patient engagement to increased revenue through patient care. The good part about healthcare analytics is that regardless of how it is used, it helps drive insights that improve the performance of healthcare organizations.

Patient care

Healthcare practitioners can further performance improvement in patient care by applying data analytics. Using statistics and data modeling offers value-based payment initiatives for high-risk patients.

Predictive analytics in healthcare also help identify patient and program costs early on and can aid in patient management and treatment of chronic diseases.

Physician performance

Implementing healthcare data analytics is also beneficial for evaluating the performance and effectiveness of healthcare professionals. Collected data insights provide feedback related to patient care and service delivery.

An important step in assessing providers’ performance is shifting from a volume-based approach to a value-based one, backed by real-time updates and actionable goals.

Public health analysis

Obtaining, reviewing, and organizing population data to predict healthcare trends are common aspects of healthcare analytics. Public health organizations typically use demographic information, mortality reports, procedural data, and medical claims data to monitor disease trends and discover recurring patterns.

When used for this particular case, healthcare analytics helps guide disease control programs across different regions and is helpful in resource allocation for communities and the general population.

Benefits of healthcare data analytics

Healthcare analytics is largely associated with risk mitigation, informed business decisions, and refined information processing methods. However, there are several other benefits to integrating this technology with day-to-day operations.

• Improves clinical care quality: As the demand for better healthcare services increases, more organizations seek access to more detailed patient data. Comprehensive data helps unlock important patterns and trends regarding diagnosis and treatment.

• Helps develop actionable initiatives: By enabling holistic decision-making, healthcare analytics can inform the health initiatives of a population. Disease management, outbreak forecasting, and resource allocation to communities are some initiatives organizations can take through acquired data insights.
• Personalizes patient journey: Understanding the root cause of why patients may or may not be responding to campaigns is critical to understanding patient engagement. A personalized customer journey can also increase market share, uncover different care preferences, and enhance communication through live agents and chatbots.

How to build a healthcare data analytics strategy

While having the right technology and tools can make everything more efficient, forming a dedicated team that develops, plans, and creates a full-fledged healthcare analytics strategy helps address key issues. A strategy also works towards shared goals and improves communication across stakeholders.

Leverage high-quality data

Accurate and well-formatted data is critical in the healthcare world. To ensure good data quality, there should be data cleaning systems for every data set. This process is particularly crucial because most healthcare data is unstructured and contains essential information about patients, staff members, and organizational performance.

Complete and relevant data prevents data silos because this information helps pool internal and external data into a streamlined information repository. Having access to standardized data from a single data lake can create more growth opportunities and reduce the number of administrative and clinical errors.

When providers and technicians are confident in the quality and accuracy of data, it gives them more time to work on patient care. Using structured data is also beneficial when working with multiple healthcare data management tools.

Identify and eliminate data biases

One of the biggest challenges with data analysis is the issue of implicit and explicit biases in the collected information. This concern is exacerbated for healthcare institutions such as hospitals since the data in question plays an integral role in patient health.

Any data analytics strategy must account for potential biases and suggest ways to remove them. While the method by which organizations eliminate data biases differs, a tried and tested way to overcome the issue is by working with people who understand the importance of pure data and are aligned on data goals.

Ensure that caregivers, developers, and technicians work closely to meet patient needs with the correct type and amount of information. Use systems such as electronic health records (EHR) software that integrates with healthcare analytics tools to maintain data consistency.

Prioritize patient and data privacy

All successful health initiatives make sure all clinical data complies with the Health Insurance Portability and Accountability Act (HIPAA). The information must also be shared securely across hospitals, research centers, diagnostic facilities, and ancillary providers. When data is shared among several parties, data privacy management can become a cause of concern.

High-quality data that is HIPAA compliant must be used by healthcare companies while working with different partners to prevent data breaches. Implementing data security procedures for all entities involved, including insurers and provider affiliations, keeps patient information safe and confidential, which helps build trust in the healthcare system.

Capitalize on expertise

When in doubt, seek experts out.

Healthcare organizations are responsible for collecting and analyzing massive data amounts daily. It can be challenging to ensure data quality and standardization without professionals who have specialized data processing skills.

Employing data scientists can help extract insights that could be overlooked and reduce the knowledge gap. Expertise doesn’t only refer to industry leaders – investing in solutions like predictive analytics software also works well with healthcare analytics tools to determine data patterns and trends that help plan optimal healthcare outcomes.

Best healthcare analytics software

Processing and analyzing large amounts of data is seamless with the right technology. Healthcare providers depend on systems that improve data collection, management, and sharing to optimize operations and comply with regulations.

To qualify for inclusion in the healthcare analytics category, a solution must:

• Provide a healthcare-specific data warehouse to capture and maintain data
• Analyze and visualize collected data
• Integrate with EHRs

*Below are five healthcare analytics software based on G2 data collected on June 2, 2022. Some reviews may be edited for clarity.

1. UpToDate

UpToDate is an evidence-based clinical decision support system that helps clinicians provide better patient care. It offers clinical and aligned drug decision support, built-in patient education, and voice-enabled mobile access features to deliver the latest data to users.

What users like:

“I appreciate the ease of searching for pre-appraised, high-quality medical research. I like that the research is fully vetted and conservative, making me feel confident in its bedside application.”

- UpToDate Review, Andrew H.

What users dislike:

“The mobile application is challenging to navigate; it contains all the same critical information –  symptoms, differential diagnoses, management algorithms, drug dosages – but it is all a bit more clustered and difficult to find.”

- UpToDate Review, Zachary Z.

2. Virgin Pulse

Virgin Pulse is a solution that focuses on driving health outcomes, reducing costs, and achieving deliverables for individual well-being. Virgin Pulse uses predictive analytics, artificial intelligence, and data to support clients and members across the entire health and benefits lifecycle.

What users like:

“I appreciate the ease of use and engaging experience that I receive when using Virgin Pulse. The focus on whole-person health is extremely important, and the tool aligns with that very well with areas related to nutrition, physical activity, and mental, financial, and social well-being.”

- Virgin Pulse Review, Alyssa K.

What users dislike:

“There is some difficulty accessing company challenges on the mobile application. It would be ideal to see the challenge, leaderboards, etc., on the application. Additionally, there is some difficulty when adding habits from journeys. It does not easily allow you to end tracking a habit and start a new one.”

- Virgin Pulse Review, Tracey L.

3. Definitive Healthcare

A software that transforms data, analytics, and expertise into commercial healthcare intelligence, Definitive Healthcare is a SaaS platform that offers solutions for clients in Biopharma, Medical Devices, healthcare providers, or any industry looking to sell products in the healthcare market.

What users like:

“The overall information and analytical content of this site are invaluable for someone working in healthcare sales. I use this platform daily, and it always serves my needs.”

- Definitive Healthcare Review, Stratton D.

What users dislike:

“Lately, a failure has been specified regarding updates in some fields of the system; one of these is that they do not maintain renewals of the members of the C-suite frequently. When it comes to interacting with customers with potential features, the information to be distributed, in some cases, is often out of date, providing inaccessible data that no longer works.”

- Definitive Healthcare Review, Thelma K.

4. Cerner Care Taker

Cerner Care Taker uses technology to create solutions that let communities engage in their health. The tool supports clients by surfacing data that makes it easy to manage operations while equipping them with the knowledge they need to provide well-informed and smart patient care.

What users like:

“The calendar of the schedule has a nice layout. I like how it previews a patient's name, ID number, length of visit, and reason for the visit. I like how the entire history of the patient's appointments is listed in one place for an easy scroll through. It also lists who the provider is.”

- Cerner Care Taker Review, Kira D.

What users dislike:

“The downside that I've encountered most frequently seems to be more of a bug. Occasionally, when searching for a patient, it will return with no patient found, even if everything is correct.”

- Cerner Care Taker Review, Jacob W.

5. Healthgrades Quality Solutions

Healthgrades Quality Solutions empowers stronger and more meaningful connections between patients and their healthcare providers. It helps hospitals measure clinical trends and work to continuously improve patient care and outcomes.

What users like:

“I like that you have one spot to go and do extensive research and digging on your physician. I also like that you can search multiple providers and compare them all on one screen.”

- Healthgrades Quality Solutions Review, Alex C.

What users dislike:

“The only thing I dislike is coming across profiles that are incomplete. I feel as someone working in the healthcare profession, you should be able to access the information you need on one site and that these practitioners should ensure that their information is regularly updated on the site.”

- Healthgrades Quality Solutions Review, Kim W.

Great outcomes with healthcare data analysis

Employing healthcare analytics offers a range of insights on both macro and micro levels. It helps expand reach, simplifies data processing, and improves the patient's overall experience.

By making everyday tasks more efficient, data analytics in healthcare helps prevent diseases and enhances the quality of life.

It’s evident that data analytics provides valuable health information and improves patient outcomes. Learn how electronic data capture helps manage clinical trial data for seamless data sharing and smoother trial proceedings.