Here is How Big Data Can Transform Patient Experience

Introduction:

This is Paul’s story. Paul started experiencing pain in his knee after his gym session. As we all usually do, Paul assumed the pain would go away in a couple of days. This is all of our initial reaction when we feel a little apprehensive, but console ourselves that the pain will self-resolve. This is due to our disinclination to visit the doctor, which may be related to the cost and time involved. After a few days, he is confronted with the reality of increased pain, which is negatively affecting his daily activities. The first step in the process, Paul decides to visit his Primary Care Physician (PCP). This is followed by multiple referrals to specialists. The initial uneasiness of attending the physician has substantially increased due to the lack of information through the process. Questions run through Paul’s mind over the competence of the specialist doctors, the costs involved, and whether his insurance will cover the visits. The value of the process is diminished due to a lack of information and the time involved. When treatment is finally offered, Paul is hopeful, but the disappointment sets in again due to no relief. This is a common occurrence, where the individual is left with the feeling that they have to live with the pain and detach themselves from the healthcare system. 

As of today, healthcare costs represent almost 18% of GDP —nearly $600 billion more than the expected benchmark for U.S. Enter Big Data. It allows a doctor to gain holistic and comprehensive information about a patient, through digitized records that relate to individual details, along with demographic relevancies. This encourages swift diagnosis, prompt treatments, faster recoveries, and most importantly, reduced costs. Successful implementation of big data analytics can offer $300 billion to $450 billion in reduced healthcare spending.

Big Data Advantages:

Let’s look at some specific healthcare examples, wherein big data is making revolutionary advances.

1) Health Tracking

When it comes to healthcare, the potentialities of big data analytics are immense. As more and more patient experience volunteer health information, the ability to comprehend genetics, environmental factors, and lifestyle choices toward diagnosis and predictive analysis is set to magnify by leaps and bounds. Moreover, through wearables and IoT sensors, patient populations can be transformed in numerous ways to keep the population healthy. Health tracking is significantly advanced through continual real-time tracking, EHR, video consultations, etc. Improved patient experience care and higher patient engagement are all enabled through this system. 

2) Assisting High-Risk Patients

Big data can be used toward predictive modeling in the identification of high-risk patients and thereby, aid in the provision of preventive care. Through an analysis of poor lifestyle choices, addictions, etc., care-givers can identify and target high-risk individuals and develop preventive care treatment plans to improve patient health and keep chronic diseases at bay. Diseases, such as depression, diabetes, etc. can be avoided. A risk score of patients can be prepared based on this data, and timely intervention can prove crucial. 

3) Real-time Alerting

From continual monitoring of patient health through real-time trackers to timely emergency assistance, real-time alerting serves as a significant aid in avoiding untimely loss of lives that occur due to the absence of timely care. The physician uses this form of big data analysis to receive real-time alerts on their patient’s health conditions through an application that is enabled on the patient’s personal device. Data is generated to further help providers to create prescriptions and to promote social awareness. Moreover, through intelligent analytics, any abnormal activity raises an alert, such as when blood pressure rises considerably, or an asthma attack is identified. 

4) Performance Management (BI for Hospital)

Big data analytics can go a long way toward increasing business intelligence within hospitals by including applications, infrastructure tools, and practices that are involved in accessing and analyzing information that drives performance. This allows a hospital to gain visibility into opportunities for improvement. The most efficient means to achieve this is through a piece-by-piece approach that undertakes an analysis of the operational, financial, and clinical data and offers actionable insights toward improvement. This method will increase the healthcare organization’s revenue, along with operational efficiency.

5) Prevent Opioid Abuse

Using big data to prevent substance abuse has addressed a major concern across the U.S. healthcare system. Substance abuse is a grave concern since it rates higher in the cause of deaths than road accidents as well. Therefore, a big data application has been developed that assists in the identification of high-risk patients.

Through advanced analytics, risk factors are used to predict the likelihood of a patient abusing opioids. These analytics extend themselves to data from insurance companies and pharmacies, which will help with comprehensive information supply. Physicians are alerted with predictive reports, and innovative methods are applied to ensure that patients don’t overdose on opioids unconsciously. 

Conclusion

Big data analytics in healthcare has allowed doctors to prevent and treat chronic diseases and enable them to improve patient health in an unprecedented manner. Through the analysis of big data, the health sector has the potential to achieve a mammoth of success and solve long issues of healthcare. Reduced costs, increased patient satisfaction, and time management are only some advantages that this technology offers. Big data holds the promise to improve and drive multiple levels of value within healthcare organizations. Innovative tools can be applied, and healthcare organizations are poised to succeed by leveraging these technologies.