Transforming Your Business with Healthcare Data Analysts

The world as we know it is being transformed by big data, which is the enormous collection of digital information and insights. Healthcare is one of the areas being most significantly affected. The vast amount of data collected and generated from numerous sources can be analyzed by a healthcare data analyst. To give an example, healthcare data can come from medical devices and hardware, or personal wearable fitness trackers, smart watches, or even data-driven sensors. Heart-rate devices are frequently reliant upon a body-placed node which relays critical information about a patient.

However, it goes far beyond just personal health and stats. Those making decisions about the operation of large facilities such as hospitals can also be informed by big data analytics. Care trends, supplies, patient waiting times and a plethora of other information can help improve overall care and experiences within any given facility. Growing costs, such as unnecessary spending on resources, can also be mitigated by big data.

By using what is generally known as business intelligence or data analytics, healthcare providers can delve deeper into what kind of information is pivotal to normal operations. After the data is processed and extracted, valuable insights can be derived for the improvement of all aspects of a system or facility.

At the base of this process, of course, is the data analyst. They spend most of their time poring over raw data and churning it over in order to develop actionable intelligence. In essence, the whole data collection, discovery, and extraction process is headlined by them. This raises a crucial question: in what ways can a healthcare data analyst help to improve the business?

1. More Informed Decision Processes

Data which flows in from active channels and devices is frequently in its raw form. This is the simplest manner in which to explain nearly unreadable datasets, which are comprised of varying types of contents and numbers. It requires organization, collation, and processing to truly understand the information and make it accessible. These will return actionable insights like trends, statistics, and behaviors et cetera.

Simply, it must be seen like this: simple devices like blood sugar monitors collect information about the glucose levels of a patient. As would be expected, this information is transferred digitally as a series of numbers which are neither organized nor readable for instance, the information won’t be displayed in chronological order on a sheet of paper.

In order to use those digital readings, make them comprehensible and identify patterns (for instance, a history of elevated glucose levels) a data analyst must assess the entire collection of raw data. They will then produce a report, which is likely to then be passed on to either the patient or health professionals.

Via this process, data can be turned into useful information by healthcare data analysts, and in the long run, this information can help to develop more informed decision-making processes.

2. Make Accurate Predictions

As well as the cultivation of more informed decision-making processes, healthcare professionals are also able to leverage the information into the distant future. This is known as predictive analytics. In the context of retail, this can be something as straightforward as trying to gauge whether a business decision or process is going to be successful. In health care, however, predictive measures are significantly more complicated.

As an example, consider a health facility or hospital which must be constantly vigilant about patient demands. They have a responsibility to ensure the right amount of supplies are provided consistently, and that rooms and staff are available to meet incoming patients. It is possible to use predictive tools in order to help analyze when a hospital is at its busiest, or when waiting times are especially long.

Another option for the healthcare industry is to use the data for more direct medical means, such as predicting potential disease or health issues based on a patient’s history or genetics. Doctors can make increasingly more accurate predictions concerning possible health ailments or treatments. As an example, the healthcare startup Prognos has access to 13 billion patient records. This constitutes an enormous amount of data on which AI is applied in order to help make earlier predictions about diseases.

3. Identify New Support Solutions

New opportunities and avenues of success can be created by data, especially in large amounts. When dealing with a situation which is going wrong, the first step you must take is to step back and analyze what is wrong and how it must be fixed. This process operates under the same idea, however, using their access to enormous stores of information, data analysts are able either to improve existing processes or introduce new ones.

It has suddenly become possible to increase efficiency in areas where it was never previously thought possible. Another option is that problems which have plagued a facility for years become much easier to solve.

At all times, a healthcare data analyst interacts both with streams of data and the entire organization, inclusive of individual members within a team. They can help both pinpoint the bottlenecks in processes and get to the bottom of what is happening and learning how to fix issues.

4. Bridge the Gap Between Management and the Workforce

The medical and healthcare industry is troubled by the fact that nurses, doctors, and other health professionals don’t always have enough time to liaise with management or other decision-makers in order to propose solutions to common problems they are experiencing. This is because they are busy pushing through their day, working, and saving lives. Consequently, there is frequently a disconnect between management and how various decisions are approached.

This gap can be bridged by healthcare data analysts, who are able to help provide the necessary details and insights which spark further action.

5. Get Ahead of the Data Curve

Every new piece of technology or process which is implemented brings about a new data stream with which to contend. This requires having knowledge of where it is going, how best to make use of it, and the legal and regulatory issues a business must face.

Nobody wants to be continuously fighting the currents in a data-driven environment. It is best to be ahead of the data curve, always using new information to inform processes and make processes or facilities more efficient. If you hire the right data analysts, they will make this happen. Moreover, they will help to make sure that any money spent on data and analytics is worth investing in.

Prepare for a Digital Future

At the end of the day, the tools and techniques employed by data analysts can provide any business with the ideal information and insights to help push towards success. It isn’t any different in the healthcare industry, even if the data comes in varying formats or is handled differently.

You are already working in order to reduce costs, improve operations, and improve efficiency significantly. Data can take you closer to these goals more quickly, particularly when the right kind of data is analyzed by people who understand it. This can help you be more confident in your decision making.

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Kolabtree is the leading online marketplace for freelance scientists and researchers. Their global pool of 5,500+ freelance experts are typically PhD-qualified and are from institutions like MIT and Harvard University. Services offered include statistical analysis, scientific consulting, data analytics, scientific writing and literature search. Kolabtree has helped businesses around the world, including Volkswagen and Sage Publishing, access scientific expertise quickly and easily. The platform lets you choose a budget of your choice, and interact with freelancers before making a hire. It's free to post your requirement on the project and receive quotes from experts. Kolabtree’s freelancers have helped businesses develop a product, write a technical report, perform a data analysis, and more.

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Original piece written by Nathan Sykes. Nathan Sykes is a freelance tech writer from Pittsburgh, PA. He enjoys writing about the latest news and trends in AI, big data, cloud computing and other emerging technologies.


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Last updated: Jul 29, 2021 at 5:15 AM

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