In a world that’s overwhelmed daily by new digital technology and where customer experience rules the roost, can the healthcare industry be any different? Big Data emerges as the superhero as the demand grows for healthcare organizations to become more patient- centric with personalized medicine, improved outcomes, reduced costs and more holistic treatment. Increasing analytics competency and leveraging data analytics solutions can improve the value of healthcare for all stakeholders.

Understanding healthcare data analytics

We enjoy a wealth of health data—personal health files, medical cost sheets, treatment plans, insurance records, right down to real-time visibility into an individual’s vital signs. This data originates from diverse sources such as wearables, practitioner logs, hospital records, payment histories, and insurance claims. These add immense value and bring meaningful insights into patient care, hospital management, diagnosis, preventive measures, and improved healthcare. Adopting a data-driven approach to healthcare benefits patients as well as the healthcare system. This leads to improvisation, innovation and progress toward a transition to value-based care.

But privacy, security and compliance requirements add complexity to healthcare data analytics. This increases the time, effort and resources invested to develop a more efficient and accurate data analytics solutions. Government initiatives join industry demands in this expansion. These stem from requirements to increase digitalization in all spheres of life including healthcare, and community influence to bring down medical costs and improve patient outcomes. All these factors converge to enable data analytics to play a bigger and more intelligent role in the healthcare industry.

Types of available healthcare data 

Before we dive deeper into the benefits that healthcare data analytics brings, here’s a quick classification of the major types of available healthcare data:

  • E-health records – derived from wearables, individual’s devices, doctor visits, health check-ups, specialized reports of bloodwork, imaging, etc.
  • Administrative data – collected during doctor visits and hospital admissions, or maintained by ancillary healthcare establishments
  • Claims records – meticulously maintained by insurance providers and hospital management systems
  • Health surveys – carried out by individual researchers, academic or medical institutions, pharmaceutical companies
  • Clinical trials data

Each of these data types guides patient treatment, operational functionality, and even predictive healthcare. Using the data results in improved experiences for all interested parties.

How the patient benefits

The entire spectrum of healthcare providers use intelligent, data-driven digital interventions. But how does this change the healthcare experience for the individual patient? If used in the right spirit, data analytics in healthcare has the sure potential of enhancing the patient’s experience. Here’s how:

Fewer visits to the hospital

We cannot eliminate the need for medical care. But we can use data analytics to predict and eliminate the need for readmission, defined as going back to the hospital within 30 days of discharge from a previous stay. We can assess data about the patient’s living conditions or lifestyle for patterns that could lead to readmission. Analyzing such data can result in more timely intervention and effective medication/treatment.

Reduced waiting time

Nobody likes to wait; definitely not when you’re already anxious and visiting the doctor. Yet a waiting period before you walk in for your consultation is inevitable—stretching from minutes to even an hour. We can put healthcare analytics to good use here. Frequent appointment reminders for patients to be on time, as well as dashboard views for the medical staff, can help improve the situation on the ground. (And so decreases all patients’ waiting time.) Doctors can analyze the duration of the consultation as per the patient’s complaint or illness to schedule appointments, injecting more efficacy and reliability into the system.

Customized care

Data analytics infuses the maximum value into healthcare through customized care. Access to real-time information about the patient can guide the doctor’s judgement—resulting in personalized and more accurate treatment for every patient. Analytics realized through data collected through connected wearables, the patient’s entire medical history, the recent progression of a condition, response to previous treatment, etc. creates this value.

Increased value for other stakeholders

As stated earlier, applying data analytics intelligently to healthcare is advantageous for all stakeholders in this industry. Patients benefit from better diagnosis, treatment and reduced costs. Providers experience efficient systems, access to valuable patient data and consequently higher satisfaction expressed by more content patients. The supporting cast in this scenario such as insurance payers or medical equipment suppliers have a clearer view of risk factors, patient outcomes and are able to tweak their offerings accordingly. And the society as a whole gets access to improved and less expensive healthcare. Most importantly—and rightly so—it builds transparency and greater trust between patients and their doctors.

The road ahead

The picture is not perfect yet. The healthcare industry has yet to use data analytics to its maximum potential. These solutions need to show extreme ease of use and trouble-free maintenance. But these hurdles provide the impetus for focused research, innovation, and breakthrough solutions. At the end of the day, we look to lead happier and healthier lives. Data analytics is the right step forward in healthcare.