Data has always been powerful, no matter what segment you use it in. It gives us an insight into what the trends are in the market. However, one segment where data has a lot of potential that is going to waste is healthcare. Healthcare desperately needs data analysis and predictive analytics to make more sense of the different trends that are happening and to make more proactive approaches to helping people get better.
While access to healthcare is a basic human need, it is one of the most expensive ones. However, experts believe that data analytics, if used right, can help reduce costs drastically. In addition to that, they also expect data to help figure out diseases faster, as well as bring in more medical innovation.
Before we delve into data analytic and how it can revolutionize the healthcare industry, let’s first understand what data analytics actually is.
What is Data Analytics?
Data Analysis is the process of inspecting, cleaning, organizing and modeling data to discover similar patterns and make reasonable conclusions. There are four main segments when it comes to dealing with data – data mining, data integration, data analysis and data visualization.
Data mining refers to the process of collecting data from various sources, including devices that people use today. Every time they interact with their smartphones, people collect data depending on the app they used, how long they used it for, what did they do on the app, etc. Data integration is a precursor to data analysis and simply a form of bringing together data from different sources into one place to make it easier to access the data. Data analysis is the stage where data is cleaned and organized to ensure it makes more sense. And, finally, data visualization is the output of data analysis to offer a clearer picture of what trends the people should be expected to see.
There are many different types of data analytics including business intelligence, descriptive statistics, exploratory data analysis, confirming data analysis, predictive analysis, text analysis, etc. While each type is used in different segments, data analytics can be considered as an umbrella term that covers all the different types.
Barriers to Data Analytics
According to a joint study by IBM and MIT, the main barriers that organizations faced when trying to adopt data analytics were – inability to get the data, the culture does not encourage the sharing of data, lack of understanding of the benefits of analytics, competing administrative priorities, and lack of executive sponsorship. While this study was conducted way back in 2010, it continues to remain relevant even today.
Ways Data Analytics Affects Healthcare
The use of data analytics in healthcare is growing tremendously and is currently at an all-time high. According to an eHealth Initiative, 90% of the 102 healthcare organizations asked claimed that they use analytics for their quality improvement initiatives and revenue cycle management.
According to a 2015 CDC report, the reason for the rise of data in healthcare can be credited to the innumerous benefits that it offers including 82% improvement in patient care, 63% reduced readmissions rates, 62% improvement in overall health outcomes, and 54% improved financial reporting capabilities.
The most important part of data analytics in healthcare is the healthcare enterprise data warehouse (EDW). In the simplest terms, an EWD is a record that gathers all the information on a patient and records them in one easy to access place for medical providers. This includes information clinical, financial, patient satisfaction, etc. This allows doctors and administrators to have access to all information regarding patients and healthcare in one file. The system can also access all previously siloed data and also create near real-time reports from across the organization. This helps in not only reducing cost across the organization but also allows medical providers to give the patient the best care possible.
If you’ve ever caught an episode of television show, Pure Genius, which was sadly cancelled after one very short season – the main focal point of the show was to use technology to gather as much information as possible for their patients and also to offer them real-time updates on their patients such as heart rate, blood pressure, and anything else they would like to monitor. This is one of the main objectives of integrating data analytics in healthcare.
5 Reasons How Analytics Will Change Healthcare
1. EDW Will Offer More Value
As previously mentioned, the Healthcare enterprise data warehouse will allow doctors, admins and other medical personnel access to information regarding the patients’ health and wealth. They won’t have to rely on limited information to treat their patients, they will be able to simply check old diagnosis, medicines prescribed, type of healthcare they’ve been previously offered, older symptoms, etc. before they can make a fresh diagnosis. This also gives way for preventive health measures, where patients who have a family history of a disease can be monitored for symptoms.
2. Big Data will Become Actionable Data
With the data on hand, hospitals can prevent hospital readmissions by using remote patient monitoring. It prevents readmissions by providing continuity of patient-derived data with the hospital, recognizing actionable trending data before it results in a trip to the ER and a subsequent admission to the hospital.
Access to big data can also help show trends in preventive measures related to drugs. Big data can help in clinical trials. It will allow practitioners to survey medical devices, new pharmaceuticals, and drugs that transition from prescription to over the counter could be critical in discovering adverse reactions and other events that are not captured during controlled (relatively short-term) approval trials or regulated prescribing.
3. Personalized Medicine
With the information acquired on the patient, doctors will be able to offer a more personalized experience. Using information, the doctors won’t have to continue testing for the best type of medical assistance, instead of using technology they can offer diagnosis and/or treatment of a disease based on geography, race, and genomics.
4. Reduce Bias in Care
Where humans exist, there is bound to be bias. However, with technology into the picture, bias can be reduced to a greater extend. The technology won’t take into consideration geographical variations when finding the best diagnosis for the patient, offering them quality treatment at the same cost.
5. Decrease Cost of Care
Integration of data would add more transparency to the health care system, which will help significantly reduce costs. Similarly, the information will help admins best utilize their services by running their hospitals more efficiently.
As we can see, data analytics is definitely and significantly changing the healthcare sector for the better. The integration of data analytics will ensure more transparency, access to better information, more knowledge and even result in better healthcare for individual patients. Data would offer a patient’s entire previous history to the doctor, who won’t have to sit there asking the patient for a summary.
Healthcare also has the potential for AI-driven data such as apps that can ask patients their symptoms even before they ever have to enter the hospital. There are now apps such as AI Doctor or Ada that can check your symptoms and then offer you a diagnosis based on the symptoms provided.
Do you agree that healthcare has a lot of potential with the integration of data? Let us know in the comments down below!