How Data Analytics is Helping Healthcare Services

Healthcare

The use of technology has been integrated into every sector and industry and the healthcare industry is no exception. One of the building blocks of all technological operations is data. One could even say that our world system thrives on data.

The use of Healthcare data services in many healthcare institutions is quite common nowadays. These days, data analytics has made the job of medical professionals much easier than it used to be in the past.

Therefore, in this article, we will reveal what data analytics is and how it is helping the healthcare service industry.

Let’s get started…

 

What Data Analytics Is

This refers to the process whereby quantitative data is interpreted with the purpose of revealing qualitative insights, providing answers to questions, and helping in the identification of trends.

It can also be defined as the process whereby raw datasets are examined to discover trends, reach conclusions, and also aid in the identification of improvement potential.

This information can be analyzed manually or digitally with the use of algorithms and software. With the aid of charts and graphs, one can easily display facts and figures thereby making it easier for others to understand.

 

What Healthcare Data Is

These are all the details that pertain to the well-being and health of a single patient or a group of people. Such information is collected by medical professionals, government organizations, insurance companies using several health information systems (HIS) as well as other tools.

Some of these tools are:

  • Personal Health Records (PHRs)
  • Electronic Health Records (EHRs)
  • Patient Portals
  • Electronic Prescriptive Services (E-prescribing)
  • Health-Related Smart Phone Apps
  • Master Patient Indexes (MPI) etc.

 

Data Analytics Types

1. Descriptive Analysis

This involves the examination and description of a thing that has already occurred. In other words, it makes use of historical evidence with the purpose of reaching conclusions and discovering patterns. Hence, this method allows us to gain insight into the past.

When applied in the medical field, descriptive analysis can help medical practitioners determine and evaluate the contagiousness of a virus through examination of the positive tests of a certain population within a period of time. Click here to find out how fast a virus spreads.

2. Diagnostic Analysis

This deals with seeking to understand the reason behind an event. It tries to find out what led to a particular incident both in the past and in the present.

In medical practice, this analysis enables health personnel to diagnose what illness a patient is suffering from by observing the symptoms they are exhibiting.

3. Predictive Analysis

The focus of this method is to provide answers to questions about possible future events by exploring historical data, assumptions, and past trends. In other words, this analysis makes use of previous evidence to predict future events. Hence, it allows the users to prevent the occurrence of certain events even before they occur.

Medical practitioners use models created from this analysis to forecast seasonal diseases using available information from the past years. With such information, they can warn the people within that affected region of the coming disease and how they can protect themselves against it.

4. Prescriptive Analysis

This analysis enables the identification of definite action that needs to be taken by an individual or group of people to achieve their set goals. We could also say that it allows one to predict future outcomes. With the information gathered, the best action to take can be determined.

Prescriptive analytics is used in the assessment and evaluation of already existing conditions to ascertain their risk level in relation to future conditions that might develop, and provide the necessary detail needed to implement precise preventive treatment while putting the already determined risk into consideration.

 

Healthcare Data Analytics Application

1. Assessment and Development of Practitioners

With the use of gathered information from patients, the services of medical professionals can be assessed to discover the areas that need to be worked on. When such areas are discovered, training can be carried out to develop the personnel in that area.

For example, if the information gathered has shown that a certain healthcare practitioner isn’t as empathic as their patient would like, that can be worked on to enable such a professional to get better in that area.

2. Detection of Scan Anomalies

With the aid of machine-learning algorithms, scans can be analyzed to determine their efficiency and accuracy. This is very valuable as many errors with scans have led to all sorts of misdiagnosis. Visit https://www.healthline.com/health-news/many-people-experience-getting-misdiagnosed to read up on why misdiagnosis is common. Being able to detect those anomalies can save lives and time.

3. Prediction of Outbreaks

With proper data analytics, disease spread can be reduced when such is predicted before they occur. For example, the CDC works tirelessly to collect data about all kinds of illnesses. This allows them to monitor and predict if an outbreak will occur or not.

The healthcare industry is benefitting a great deal from data analytics. We have looked at some of these benefits in the article above.

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