Health data helps physicians make important patient care decisions

Like all areas of data analytics, the term refers to the use of large amounts of data to give organizations or professionals actionable insights, applied here to healthcare. As healthcare costs continue to rise, cost-cutting measures derived from healthcare data analytics offer hospitals and healthcare systems a simple way to reduce costs while improving outcomes.

Considering the trillions of dollars spent on healthcare worldwide, it’s no surprise that “by 2025, the health-related analytics market will reach approximately $28 billion” (Healthworld.com).

Types of data analysis

Descriptive analysis: This is the most basic of all analyses. This examines an event that happened in the past. For example, a health data analyst might track a hospital’s data for the past five years to research seasonal patient admission trends.

Diagnostic analysis: This type of analysis is used to determine why an event occurred. For example, a healthcare provider might ask, “Why is there an increase in patient dissatisfaction this month in our post-visit surveys?” »

Predictive analysis: This form of analysis is used to predict something that will happen in the future. For example, a hospital may predict, based on trends over the past decade, that incoming cardiac patients will most likely increase by 20% this year.

Prescriptive analysis: It is probably the most important form of analysis in healthcare and the fastest growing trend. This form of analysis takes pre-existing data and implements treatment plans. For example, a health care provider can use a smart device to automatically scan a patient’s vital signs, preemptively warn them that they are at risk of developing a medical condition, and direct them to see their health care provider for health.

How Data Analytics is Used in Healthcare

Below are three examples of how health data analytics has affected the healthcare industry.

Predicting Hospital Utilization

If there’s one thing we’ve learned from the COVID-19 pandemic, it’s that there are a limited number of hospital beds. Although the pandemic can be considered a black swan event, being able to predict hospital bed utilization is vital to any functioning healthcare system. In a form of predictive analytics, French hospitals used an analytics program created by Intel to predict emergency room visits and hospital admissions. Using a number of time-series analysis algorithms, the team managed to create a browser-based interface that allows doctors to predict admission rates by considering various factors such as flu season and heat waves.

“Seeing the prediction app leverage all the data and deliver useful, actionable insights has made our medical staff imagine the huge benefit it will bring to both staff and our patients,” said Dr Sébastien Beaune, director of the emergency department of one of the hospitals. “Having a better understanding of patient flows in our emergency departments – or even predicting these flows – is absolutely essential if we are to improve the quality of our care.” (Intel.com, DataPine)

Assessment of comorbidities

Taking inspiration from the famous poem by John Donne, we can say that no disease is an island in itself. Not only do clinicians need to address the disease a patient is suffering from, but they need to be aware of other comorbidities that patients may have, especially diseases with widespread effects like type 2 diabetes. Again, data analysis can be useful.

Adam Wilcox, director of the Center for Applied Clinical Informatics at Washington University School of Medicine and a member of the American Medical Informatics Association, believes that the next frontier for health data analytics will be at this critical juncture. Data analysis allows physicians to determine which patients are most likely to develop serious complications and which are most at risk of developing sepsis following longer hospital stays. Additionally, being able to calculate the risks associated with comorbidities will allow physicians to slow disease progression before things get much more difficult to manage (TechTarget).

Make sure patients show up

This one might seem obvious, but you’d be surprised how many adverse medical outcomes could be avoided simply by patients attending their doctor’s appointments. (Not to mention the money hospital systems lose when a patient doesn’t show up!) The American Journal of Roentgenology reported how a hospital system used a combination of artificial intelligence, predictive analytics, and a simple reminder system to repair an alarming MRI. no-show rate. After the procedure, the hospital experienced a 17% increase in attendance (American Journal of Roentgenology).

The future of healthcare

There is no doubt that data analytics will totally transform the healthcare industry in the decades to come. We are already witnessing the start of a new era where analytics tools, IoT devices and AI technology are all helping to make healthcare more efficient and save lives. If you want to start a career in the world of healthcare data analytics, our master’s program at Touro College Illinois is the perfect place to start. The Master Data Analytics in Healthcare will give you the tools and knowledge to make an impact in the healthcare industry.