As governments around the world, particularly in Asia, strive to provide their population with affordable and effective healthcare services, many are turning to data analytics to help them achieve their goals.
The generation of data in the healthcare sector is nothing new. In fact, the industry has always generated vast amounts of data pertaining to patient records, regulatory compliance and administrative records.
With big data in the global healthcare market estimated by BIS Research to reach nearly USD 69 billion by 2025, healthcare professionals are looking at how best to use these data. This includes to reduce costs of treatment, predict outbreaks of epidemics, detect early signs of illnesses, prevent diseases and help improve the quality of life for patients and the public.
The list of benefits that data and predictive analysis will bring to the healthcare industry is a long one. These are the four crucial ones that healthcare businesses and practitioners need to be aware of to convince your stakeholders to start adopting data analytics into your business.
Healthcare practitioners and clinicians generally do not have the ability to accurately predict an individual’s treatment success. These medical professionals habitually follow a non-optimal trial-and-error approach in prescribing treatment options. These treatments are generally recommended based on generic information as most drugs are developed and tested for the average patient with a specific disease.
But because all of us are individuals and may be different from the average person, a medication may not work and the patient would likely be switched to another medication. This approach can lead to adverse drug responses, patient dissatisfaction or worse, serious health issues.
Here is where personalized medicine kicks in. Using specific patient data, healthcare providers can compare a combination of drugs for specific genomic profiles, increase research quality, safety and efficiency as well as reduce costs and eliminate waste.
Key to a country’s healthcare system is being able to provide people with easy access to the care they require. Delays in treatment not only increase the risk for patients but can also result in irreversible disease progression and escalate the costs for the patient and the healthcare system.
Rural residents generally find it difficult to access quality healthcare due to their location, transportation infrastructure and lack of treatment facilities. Telemedicine is a fast-growing option to overcome this.
Leveraging big data and Internet-connected medical devices, real-time data such as the patient’s vital signs, blood pressure and heart rate can be easily obtained. As both patients and caregivers can track the patient’s overall health and predict possible life-threatening events, doctors are able to administer correct medication dosages.
Telehealth also plays an important role in disaster relief. Drones are used to collect data at the ground level to help emergency personnel make prompt decisions on medical supplies deployment. In some cases, drones were used to deliver defibrillators in advance of paramedics during a disaster.
The ability to spot trends and assess the chances of events happening is one of the biggest benefits of modern predictive analytics tools. Predictive analytics can help determine patients who are at greater risk of contracting a disease or illness.
Thanks to technology in the form of wearable devices and personal diagnostic tools, data like age, blood pressure, cholesterol and blood glucose levels are integrated with health conditions, dietary habits and the physical environment to keep the user on top of their health condition.
Diagnostic analytics can work backward from the symptoms to determine the cause of a condition or illness. Physicians and doctors can use the diagnosis results to save time, increase the accuracy of treatment and avoid potential errors of judgment.
Ask any healthcare researcher what the major challenge is when designing clinical trials and the answer you will likely get is: finding the right participants.
Historically renowned for being a time consuming and expensive affair, data-driven technology has greatly evolved this aspect of clinical trials. With the use of mobile apps, specific people can be selected and reached in a personalized, fast and cost-effective way. These apps can keep participants engaged with the trial via reminders, personalized messages and trial progress reports.
Similarly, like mobile apps, social media platforms too can play a role in enhancing the selection of patients for clinical trials. A researcher can mine data to see what the top global locations are where people talk most about a medical condition and proceed to create a sentiment analysis to determine which geographical areas they should focus on.
For any government, providing quality and effective healthcare is an ongoing process. Healthcare officers and practitioners are constantly on the lookout for any tools and technology that can help increase accessibility, reduce cost and improve the quality of healthcare. Data analytics is a strong option to help achieve these goals.
How do you think data analytics is changing healthcare services in your own market or region? Get in touch with us here.