Five Ways Of Providing Better Healthcare Through Data Analysis

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The healthcare sector is catering to a massive population. While manual data management was possible in the past, it is no longer adequate with the current population explosion.

 

Technology is needed now more than ever, as the chances of making errors are much higher in an overburdened sector.

 

According to a 2016 survey, medical malpractice is the third leading cause of death in the United States, claiming over 250,000 American lives annually. Only practical usage of data analytics can remedy this.

 

Data analytics relies upon optimizing patient care through machine learning, predictive analytics, and artificial intelligence, which yields better patient outcomes.

 

By introducing automation, medical errors have dipped to below 45% in the United States alone. Therefore, studying data analytics is essential to pick up how this futuristic technology has shifted the healthcare industry’s services.

 

Here’s how data analysis is a trailblazer within the healthcare sector:

1.    Provides Better Security To Sensitive Hospital Data

Hospitals account for over 30% of data breaches in the United States alone. By 2020, security breaches cost healthcare companies over $5 trillion, putting a significant dent in many hospital budgets.

 

Most high-profile hackers target hospitals because of valuable patient data, which is highly profitable to sell. Therefore, most hospitals should use big data analytics to monitor large data sets while scanning database activity to identify and neutralize threats.

 

Big data will provide accurate time detection, allowing hospitals to revisit their cybersecurity details and repair loose ends. This is How Big Data Impacts Healthcare Management: protecting patient data, safeguarding the sanctity and reputation, and preventing financial losses of a thriving healthcare sector.

 

Big data also helps healthcare management gauge their security details. This will enable them to upgrade their firewall, encrypt patient data and install alerts to report fraudulent activity like inaccurate insurance claims, helping patients contact their insurance companies and get better returns on claims.

2.    Catalyzes Drug Development

Drug development is a complex process with a median cost of over $900 million in 2020 alone. Despite the high numbers, developing a drug is not an easy process with an exceedingly low success rate resulting in less than 10% of new drugs hitting the market.

 

Unfortunately, medicines are the cornerstone of the healthcare industry. With new diseases on the horizon, pill production cannot stop.

 

Therefore, the healthcare sector should utilize artificial intelligence to be a driving force behind drug development.

 

AI can make drug production easier by allowing researchers to use complex software which will help generate ideas of the necessary chemical components for the new pills.

 

Since AI operates with an over 80% accuracy rate, the identified chemical components will let researchers immediately create an experimental drug.

 

Apart from providing information on the necessary chemical components, the AI will scan through a database of patient data to help find prospective candidates for the trial.

 

The algorithm will ensure the candidates can participate in trials with no underlying health concerns or a solid reaction to the side effects guaranteeing safe and efficient drug testing. In this manner, faster transitions can be made to clinical trials in phase 2 of the drug development process.

 

After the pills are consumed, AI uses the volunteer’s data to identify biomarkers that are molecules within the body which indicate a response to the drug.

 

This will allow researchers to conclude the trials early, analyze the data and produce new medicines for common illnesses.

3.    Automates Patient Data

According to a study in 2020, medical errors are the third leading cause of death in the United States. These errors arise when healthcare practitioners cannot record patient data accurately since manual data entries are prone to human errors.

 

Data analytics have solved this pervasive problem with electronic health charts. These are digital health charts that use big data to drive patient outcomes.

 

An EHR will provide each patient with a complete digital record containing relevant medical history, allergies, lab tests, and demographics.

 

This information, once successfully entered, will get encrypted and will only be available to the attending doctor. All doctors need to do from that point on is to manage the EHR.

 

In the United States, about 3 out of 4 healthcare practitioners have expressed their satisfaction in using an EHR to deliver patient care.

 

Big data also empowers the EHR to send reminders such as requesting the patient for a follow-up, triggering a warning when the doctor makes a data entry mistake, and notifying the patient to get tested.

 

This streamlines patient care and helps practitioners deliver high-quality care without compromising patient safety.

4.    Enhances Patient Engagement

Over 40% of adult Americans use wearable devices such as Apple watches and Fitbit. This has enabled leading companies that manufacture these smart devices to utilize big data and provide hospitals with patient information. Smart devices keep track of a patient’s health by monitoring their heart rate, sleeping habits and counting their steps to chart their activity levels.

 

Some devices also come with an in-built fall detection which immediately detects when a patient has collapsed and notifies emergency helplines.

 

This can significantly help take care of geriatric patients better by minimizing injuries and providing them timely help. It will also help patients with muscle problems and conditions like Parkinson’s to find assistance right away.

 

Patients with increased heart rate and chronic insomnia can get their data sent from the device to the hospital’s database for their doctors. The smart device can also notify the patient when it detects unusual activity like heart murmurs, shallow breathing, and unsteady steps to take effective remedial measures.

 

Enhanced patient engagement allows hospitals to provide better care and personalized treatment, which is more effective. Patients will look after themselves better and be more involved instead of relying on physicians alone.

5.    Better Telemedicine

Telemedicine has become a staple of modern healthcare. It is a remote healthcare monitoring service that allows healthcare practitioners to consult patients over the Internet.

 

This feature uses Artificial Intelligence to navigate through patient data. In 2020, 70% of American patients ranging from 18 to 59 years used telehealth, and these numbers are on the up and up.

 

Remote patient services will cut back on needless healthcare expenses and only encourage critical patients to visit the hospital.

 

This will keep the ER fully stocked, reduce the workload of healthcare practitioners, and save the hospital’s budget.

 

Telemedicine also utilizes cloud technology to store patient data and retrieve information from wearable devices and smartphones for accurate diagnosis.

 

Doctors will have an easier time providing more personalized healthcare according to patient data. Doctors can use the telemedicine database to study public health through predictive analysis and information available on the Internet of things.

 

This will expand the hospital network and initiate more retail clinics.

Final Thoughts

Modern technology is a one-step solution to most healthcare problems. Data analysis has become an integral part of medicine.

 

It is now helping hospitals take care of sensitive data, prevent leaks, and digitize patient information. This helps keep hospital records safe and provides better and faster diagnoses.

 

One of the essential services data analysis offers is drug development.

 

With the rising costs, the healthcare sector needs a quicker solution to manufacture pills. Data analysis has also facilitated patients in becoming more engaged with their health through smart devices and telehealth.

 

Data will become more complex but more effective for different sectors as technology evolves.

 

 

 

 

 

 

 

 

 



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