In an age when patient needs are becoming more complex and the healthcare industry is attempting to evolve to prioritize personalized, patient-centered care, healthcare data analytics has never been more vital. The fact of the matter is, most healthcare professionals are not data analytics experts, and hospital systems as well as healthcare organizations need qualified experts in healthcare analytics.
As you begin to see the role that you can play as a healthcare analytics professional, you may find that now is an excellent time to begin pursuing a master's degree in healthcare analytics.
What Is Healthcare Analytics?
Healthcare analytics is defined by the International Organization for Standardization as the process of extracting patterns and actionable insights from raw healthcare data to allow healthcare providers to develop a precise course of treatment for the individual patient.
Raw healthcare data harvested and analyzed through healthcare analytics may include patient medical records, family history, genetic trackers, and blood work.
The fact of the matter is that healthcare analytics is a unique and growing field that blends the science and art of healthcare with the precision of technology. Through the proper application of healthcare analytics, hospital systems and healthcare facilities have the ability to streamline operations, improve patient outcomes, allocate resources efficiently, and implement data-based decision-making in their organizations.
Key Applications of Healthcare Analytics
As healthcare organizations continue to leverage the power of machine learning and healthcare analytics, it has become clear that there are many key applications in which this data and the subsequent insights can be used.
According to the ISO, these are some of the key applications of healthcare analytics:
Personalized Medicine and Predictive Analytics
Modern patients have complex needs, requiring healthcare providers to be able to provide them with personalized patient care. However, true personalization in medicine cannot be achieved without accurate and precise healthcare data. Through predictive analytics, healthcare providers can evaluate the healthcare data and actionable insights available to develop a plan that addresses the unique needs of the individual patient.
For example, according to the Breast Cancer Research Foundation, predictive analytics is playing a powerful role in today's breast cancer treatment plans. The BCRF notes that breast cancer is an incredibly complex disease, and there are many factors that can influence the severity of the disease and the outcomes for the patient. Predictive analytics tools and AI technology are playing a pivotal role in developing precise and personalized treatment plans for patients who have been diagnosed with breast cancer.
Clinical Decision Support
The Agency for Healthcare Research and Quality defines clinical decision support (CDS) as the process used in the healthcare industry to offer providers and patients information that will help them decide on a treatment plan. Clinical decision support is often given at the point of care, emphasizing the importance of enhancing clinical decision support with actionable insights from healthcare data. The leading CDS tools rely heavily on healthcare analytics to improve patient outcomes and increase patient satisfaction ratings.
Improving Hospital Operations
As hospital administrators continue to navigate staffing shortages and supply chain disruptions, healthcare analytics can play a powerful role in improving overall operational efficiency. Administrators and managers can leverage healthcare analytics tools to:
- Optimize the flow of patients within the facility.
- Allocate staff according to patient priorities.
- Allocate resources in a way that improves efficiency yet maximizes patient outcomes.
Reduced Healthcare Costs
In an era of rising costs across the board, healthcare administrators are faced with the challenge of reducing healthcare costs without compromising the quality of care that patients receive at the facility. Fortunately, healthcare data analytics can be used to identify opportunities for cost savings and streamline resource allocation, allowing healthcare administrators to make strategic decisions based on the actionable insights available.
In addition, data analytics in healthcare supports early disease detection and improved preventative care, which will organically lead to reduced healthcare costs over time. The powerful combination of improved resource allocation and enhanced, personalized medicine can have a significant impact on the cost of healthcare in the modern era.
Population Health Management
Population health management is defined by the American Hospital Association as the strategic process of improving patient outcomes within a defined and specific group. A population may be identified based on demographic information, such as age, race, socioeconomic status, or geographic location. When attempting to improve the health and outcomes of a specific population, healthcare analytics can play a powerful role. Hospital administrators can rely on actionable insights to implement strategic measures that will address the needs of a specific population and improve overall outcomes.
The Impact of Healthcare Analytics on Patient Outcomes
By harvesting both patient data and clinical data, healthcare analytics experts can offer providers actionable insights that they can use to improve patient outcomes, both on a personal level and at the population level.
Healthcare analytics can improve patient outcomes through:
Personalized Healthcare
Data analysis is the key to delivering patients personalized healthcare services. To personalize the healthcare experience for each patient and to improve outcomes overall, CompTIA notes that healthcare analytics experts rely on three key types of data analysis:
- Descriptive analytics are used to harvest historical patient data and identify trends that have been taking shape over time. Descriptive analytics can provide context for any patient care plan.
- Prescriptive analytics rely on machine learning to provide physicians and other members of the medical team with a data-based strategy for providing the patient with the best possible care. Predictive analytics evaluates historical data as well as predicts future trends based on that data.
- Predictive analytics involves the use of advanced forecasting tools to predict what may happen next, based on the best available data and the treatment plan that the healthcare providers will be implementing.
As demand for more personalized healthcare services continues to increase, it's expected that healthcare analytics will play a more prevalent role in the healthcare industry.
Early Disease Detection and Prevention
Through advanced data collection and analysis efforts, healthcare providers are often able to identify the signs and symptoms of disease far before the patient begins experiencing any issues. This allows for earlier disease detection than ever before, which can allow patients to take preventative steps as soon as possible. Not only does early disease detection improve patient outcomes, but it can also lower the cost of healthcare across the board.
Reducing Hospital Readmissions
Hospital readmissions are problematic for several reasons. To start, the readmission process is dangerous for patients, highlighting the fact that they may not have received the care that they need or that they did not understand the treatment plan for moving forward. These readmissions also put a strain on hospital resources and increase the overall cost of healthcare.
Predictive analytics utilizing data collected from electronic health records can play a powerful role in addressing the high hospital readmission rates that currently exist. Predictive analytics can identify patients at high risk of readmission, allowing healthcare providers to implement additional measures to prevent that readmission from happening.
Enhancing Chronic Disease Management
By increasing the prevalence of data analytics in healthcare, healthcare providers can enhance their chronic disease management practices. Research published in the Health Care Management journal states that data analysis can allow healthcare providers to provide real-time treatment plans based on the best available data that can prevent complications, reduce hospital admissions, and improve overall patient outcomes. Ultimately, healthcare data analytics can ensure that patients diagnosed with chronic diseases, such as heart disease or diabetes, can enjoy more effective care and lower healthcare costs.
Reduction in Medical Errors
One of the most pivotal applications of healthcare analytics is that it can help reduce medical errors. Medical errors are not only life-threatening to patients, but they can also be draining on the medical system, reducing the efficiency of staff operations and increasing overall costs. By relying heavily on precise and accurate healthcare data, healthcare providers can implement strategic patient-centered care plans that address the unique needs of patients. There is less room for error when actionable insights from the most powerful healthcare data analytics tools are available.
The Future of Healthcare Analytics
The health informatics and healthcare analytics field is expected to grow exponentially in the coming years. The Bureau of Labor Statistics (BLS) notes that the demand for qualified data scientists is expected to rise by more than 36 percent between 2023 and 2033, making this one of the fastest-growing fields of our time. As healthcare organizations and medical providers continue to rely more heavily on analytics to provide patient-centered care and reduce operational costs, it's expected that there will be heightened demand for healthcare analytics experts.
AI and Machine Learning
Artificial intelligence and machine learning technology will continue to reshape the healthcare analytics field. However, it’s important to note that AI and machine learning technology will not replace the need for qualified healthcare analytics experts. In fact, the emergence of these advanced technologies actually highlights the importance of having experts in healthcare analytics available. Healthcare analytics professionals will need to know how to leverage AI and machine learning technology to streamline data collection efforts and improve the actionable insights provided to healthcare teams. Those considering a degree in healthcare analytics will have an opportunity to learn more about the role of AI technology in today's healthcare landscape and the best practices for leveraging this technology in their own professional roles.
Big Data and Real-Time Analytics
There is a growing demand for real-time analytics and instant actionable insights from healthcare providers who want to leverage data analytics at the point of care. Healthcare analytics experts will continue to work with advanced technology that allows them to harvest patient data and provide immediate results, allowing healthcare providers to better utilize the data available and personalize treatment plans as effectively and efficiently as possible. As the healthcare data analytics field continues to grow and evolve, real-time data analysis will play a more prominent role.
Explore the Role of Data Analytics in Healthcare at Champlain College Online
Analytics for healthcare will continue to be in high demand in the years to come, particularly as the healthcare field continues to prioritize data-based decision-making within individual organizations and facilities. At Champlain College Online, we offer an online master's in healthcare analytics degree program that equips students with the advanced skills needed to navigate the role of data analytics in healthcare.
Request more information about our online graduate degree programs today.
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