Healthcare Analytics: Transforming Data Into Better Health Outcomes

Healthcare analytics is a type of data analytics focused on using current and historical data for actionable insights, improved patient outcomes, and heightened decision-making within the medical field. In the healthcare industry, data analysis can be used for everything from predicting disease trends to enhancing patient engagement and improving practice efficiency by optimizing staffing levels. Healthcare analytics is a guiding light for healthcare professionals, removing the guesswork from various questions surrounding the medical and business ends so that practices can make more informed decisions.

While healthcare analytics may be pivotal for modern medical practices, not all facilities have a deep understanding of these digital technologies quite yet. At Weave, we offer a comprehensive analytics platform that helps healthcare professionals build more efficient and effective offices. Below, our team discusses everything you need to know about using data analytics to improve patient outcomes and healthcare services at your practice.

Understanding Healthcare Analytics

Healthcare analytics involves the strategic and insightful use of historical and current data to drive informed planning, decision-making, management, and evolution in healthcare organizations. These insights can cover micro- and macro-level data, revealing improvement paths in patient care quality, diagnoses, and business efficiency. The analysis plays a crucial role in healthcare by enhancing patient care, improving health outcomes, optimizing costs, and streamlining operations. This enables healthcare providers to make informed and effective decisions.

The Evolution From Traditional Healthcare Organizations to Data-Driven Approaches

As technology continues evolving, so does healthcare delivery. The healthcare industry has been far behind the rest of the world in big data analytics for quite a few years now because of a severe lack of resources, a lack of aligned incentives, and other unique barriers. Only in the last couple of decades have U.S. healthcare organizations begun adopting EHR systems to move away from paper records.

Fast forward to 2024, and healthcare leaders are taking major strides to far more innovative data management approaches as the introduction of AI-based learning has made data analysis far more powerful, effective, affordable, and appealing to providers in the industry. Approximately 86% of businesses in the healthcare industry, life science, and tech scope now use AI technology in their day-to-day operations.

To learn more about the current state and future outcomes of providers in the industry, sign up for our webinar on Healthcare Business Insights.

The Impact of Healthcare Analytics on Patient Care

Healthcare data analytics don’t just provide business outcomes. With health data-driven insights you can improve diagnoses, treatments, and patient outcomes at your facility:

• Diagnostic data: Data visualization tools and health data analytics can streamline diagnosis by removing unnecessarily manual aspects. For example, AI tools can automatically analyze X-rays and other medical images at your facility for faster and more accurate diagnoses. Data scientists have also used clinical data to streamline the PTSD diagnostic process, eliminating unnecessary questions so your providers can accurately diagnose patients with fewer prying questions.
• Treatment data: One of the primary ways healthcare analytics can improve treatments is through the ability to predict trends. By leveraging predictive analytics, providers can locate potential diseases or concerns in high-risk patients before they arise to begin treatments as soon as possible. Research shows that predictive analytics provides stronger treatment effectiveness when used in patients with HPV-positive throat cancer.
• Patient outcomes: Advanced analytics can provide optimal patient outcomes as providers gain an unobstructed view of the patient’s full medical history contextualized by artificial intelligence. With heightened data accuracy, prescriptive analytics, and valuable insights, providers can make more informed decisions regarding the patient’s health care. Providers can also leverage medical research in much quicker and easier ways using their integrated health system and electronic health records to develop strategies regarding clinical care.

Case Studies and Real-world Applications

Researchers from the University of Michigan Rogel Cancer Center developed a sensitive blood test to predict whether metastatic HPV-positive throat cancer patients would respond to treatments earlier than standard imaging allows. The data-driven test allowed researchers to create a more thorough treatment and testing potential in clinical trials for patients with metastatic HPV throat cancer.

In another example, researchers from the Boston University School of Public Health developed a machine-learning system to improve PTSD diagnostic assessments. The current assessment involves a lengthy questionnaire, which can be taxing for the patient and time-consuming for the provider. The researchers used data analytics to test the questions across 1,265 U.S. veterans.

Radiology provides a prime example of healthcare analytics used to improve efficiency and patient outcomes. With AI algorithms, practices can accurately analyze image results across patient populations in a fraction of the time.

Healthcare Data Analytics: Beyond Patient Care

One of the more obvious applications of healthcare data analytics is on the business end of things. By leveraging financial and administrative data, you can streamline your practice’s operations for increased revenue and reduced wasted resources. Here are some of the top benefits of healthcare analytics when used for internal data storage and insights:

• Better operational efficiency: With insightful patient data, scheduling information, and statistical methods, your practice can cut wasted efforts to streamline efficiency. For example, your patient data may reveal that you only need two providers on staff on Tuesdays rather than three. With ideal data quality and descriptive analytics, you can identify previous patterns in everything from claims data to long wait times to make your practice more efficient.
• Informed policy making: Healthcare analysis through historical data helps your practice make the right decisions for optimal business results.
• Increased cash flow: When you boost patient satisfaction through improved treatments and outcomes, you can get more patients on your schedule and retain them. Increased scheduling rates lead to a greater cash flow level.
• Improved practice esteem: Your practice’s premier healthcare analytics should improve the patient experience, as patients enjoy streamlined care and better outcomes. With this, you may see improved patient reviews and an overall heightened practice esteem that boosts your name within the industry.

When selecting an analytics provider, be sure to choose third-party data solutions within the health informatics or health analytics realm, as your healthcare data must comply with HIPPA (Health Insurance Portability and Accountability Act) standards. If you want to learn more about public health analytics or data sharing, view our e-book on Keeping Your Business Secure in Today’s Digital World.

The Role of AI and Machine Learning in Predictive Analytics

Healthcare analytics has changed drastically in recent years with the evolution of AI and machine learning. Previously, health data analysts faced the enormous challenge of unstructured data, or “big data,” without a reasonable way to sort through the mounds of information for helpful insights aside from using their data analysis skills. Now, AI and machine-learning technologies automatically sort through healthcare data for patterns and trends so medical facilities or data management teams can immediately view easy-to-read insights, diagnoses, or whatever else they wish to learn.

Preparing for a Future With Advanced Healthcare Analytics

The fields of data analytics and health data analytics are shifting as the technology continues evolving. Today, population health analysts, population health management professionals, health informatics teams, or other professionals in the field must be skilled in machine-learning technology rather than manual entries and analyses. As a practice owner, you must be prepared to adopt the latest health analytics tools to streamline your practice’s operations.

Weave’s Role in Advancing Healthcare Analytics

At Weave, we offer an advanced healthcare analytics platform that features everything you need for effective staff and patient communication, including the following solutions:

• Phone analytics
• Practice analytics
• Message analytics
• Review analytics
• Auto recall analytics
• Financial analytics
• Scheduling analytics
• And more

Streamline Your Practice’s Analytics Today

Healthcare analytics carry a transformative power in modern medicine with the ability to improve population health and organizational efficiency. Get a demo of Weave today to see how we can streamline your practice’s analytics for better patient and team communication.