Big Data

Application of Big Data to the Medical Care System

Healthcare Big Data refers to collecting, analyzing, and exploiting customer, patient, physical, and clinical data that is too large or complex to be understood by traditional data processing methods. Machine learning algorithms and data scientists mostly analyze big data. The increase in health data is in reaction to the digitization of health records. This has encouraged the industry to use data analytics to make strategic business decisions. In the face of health data challenges – such as volume, velocity, range, and veracity – healthcare systems need to adopt technologies capable of collecting, preserving, and analyzing this information to produce actionable insights.

What is Big Data?

Big data refers to many digitized, consolidated, standardized, interpreted, and modeled information. In health care, big data uses specific statistics from the population or individuals. The aim is to research technological advancements, minimize costs, and even treat diseases. Healthcare information collection has moved to the digital arena in recent years. This made analysis quicker and more accurate.

The growth in big data today means changes not only for people but also for the healthcare industry. Now, providers make decisions based on more large-scale information than just their experience.

The need for big data in medicine is at an all-time high for this new approach. This means that technologies such as SaaS BI tools and the companies that produce them are struggling to fulfil the increasing need.

How Big Data Is Helping Medical Care Right Now?

  • Create a 360-degree, holistic view of consumers, patients, and doctors.
  • Improve the personalization and quality of Medical care with comprehensive patient profiles.
  • Identify geographic markets with high growth prospects.
  • Inform physician relationship management activities by monitoring physician preferences and clinical appointment information.
  • Boosting health marketing efforts with information about the client, patient, and physician needs;
  • Have a clear identification of patterns in health conditions and patient satisfaction.
  • Optimize hospital growth by improving Medical care quality, effectiveness, and personalization.

Big Data Applications In Medical care

Let’s explore 6 real-world applications of big data analysis. These show how an analytical approach can improve procedures, improve patient safety and ultimately save lives:

1. Prediction of Expected Patient Number

This application enables shift managers to accurately estimate the number of doctors needed to serve patients effectively.

Insight of this application:

  • It helps to find a solution to predicting the number of doctors available at a given time.
  • It uses 10 years of Hospital Records. Then apply Time Analysis methods to measure healthcare organizations’ admission rates.
  • Focuses on reducing patient waiting times and improving the quality of health care services.
  • It provides an easy-to-use interface for all types of people. These include doctors, shift supervisors, nurses, and soon.

2. Strategic Planning using Health Data

This application incorporates health-related data to encourage patients to visit a healthcare organization for medical purposes. It collects different types of data, including demographics, population, results of tests, etc. After analyzing the large data, the results of strategic planning are used to carry out certain activities.

Insight of this application:

  • Implement data science to detect issues that are not apparent at first sight.
  • Try to determine the patient’s behavior by studying the heat map of their location.
  • Identify the causes for certain issues. These include rapid population growth or some epidemic disease spread.
  • Notifies related personnel, whether the Medical care process can be updated after the data-centric approach results have been analyzed.
  • Emphasizes the number of hospitals or emergency facilities available. Such a significant step, such as establishing new healthcare agencies, will be taken as a result.

3. Cure Cancer using Big Data

Cancer is a disease that has no specific cure. Irregular cell growth causes it. One of the strongest steps to use big data is to find a solution to a critical issue. It uses patient data and analyzes it to invent new treatments for cancer Medical care. So, this research is still in progress and can bring new light to tackle other harmful diseases.

Insight of this application:

  • Try to fit complex information collected from a wide range of sources. The greatest difficulty is to interface data sets with each other.
  • Collects all previous biopsy results, and doctors may take information before making a decision.
  • Helped to discover Desipramine that works as an antidepressant in some lung cancers.
  • It enables physicians to compare health care services to identify the best. Also, it helps to bring about a better outcome.
  • Provides samples of tumors, survival rates, and Medical care records. So, this research is still in progress. It can bring new light to tackle other harmful diseases.

4. Big Data Analytics in Heart Attack Prediction

Heart disease is one of the worst health problems that cause many lives every year. It is not easy to tackle the burden of unexpected heart attacks. This is because it requires a large amount of data collection. It is also important to compare the relationship between datasets and data mining. So, this will enable us to extract hidden patterns to predict an acute heart attack risk. Hence, this application monitors the pattern and, if necessary, informs that you should take action.

Insight of this application:

  • Intended to test complex datasets to detect, manage and treat heart-related disorders.
  • Examines large national and international datasets to achieve the goal of producing better results.
  • Analyzing the user’s eating habits, diet, and drug history can predict if he/she is at risk for cardiovascular disease.
  • Track records collected from wearable devices can measure blood cell flow, heart rate, etc. These records can help predict a heart attack risk in the future.
  • It also uses data mining to visualize and dig deep into a data set.

5. Real-Time Alerting

This application serves all individuals to reduce the untimely loss of life. It helps treat people well when they begin to suffer. Many people had already died as a result of their extremely late arrival at the hospital. As a result, this application tracks any patient in real-time. And it exchanges the necessary data with the physicians to take steps before the condition becomes serious.

Insight of this application: 

  • It uses the influential data provided by the Clinical Decision Support software. And helps health care professionals to make decisions when generating medications.
  • Collect patient health data for the use of wearable devices to promote social awareness.
  • All data is stored in cloud-based storage and processed using sophisticated tools. If any irrational activity is detected, the related personnel will be alerted automatically.
  • When any patient faces severe complications due to high blood pressure or asthma, the doctor will be notified.
  • This application includes a plan to use the power of data science to enhance the Medical care process for particular diseases.

The Bottom Line

Big data analysis in healthcare has helped doctors to battle horrifying diseases such as Cancer. Data science has a huge effect on the health industry. Health data science can solve health problems, save lives, and allow us time to take precautions. It’s going to save huge money and the most valuable time, too.

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