Predictive Analytics — Creating the Pathway to Success for the Healthcare Industry
Predictions made with the sole purpose of making predictions are purely a misuse of the prediction capabilities offered by AI and machine learning. Healthcare leverage predictive analytics to extract meaningful insights, make informed decisions and turn them into action. The power of historical and real-time data can be utilized to predict future outcomes, anomalies in the processes, and consequences thereby. The healthcare sector is a perfect candidate for the implementation of predictive analytics as it contributes to population health management, financial success, and better results across the value-based care continuum.
In the healthcare industry, predictive analytics is taking charge of multiple things that doctors have been trying to achieve for a long time, on a large scale. It has changed the way we have been measuring, aggregating, and making sense of previously difficult-to-obtain or unavailable data pertaining to behaviors, psychology, and biometry.
Harnessing the power of newly obtained datasets and combining it with the practiced science of epidemiology and clinical medicine helps us understand the effect of external factors on the human body, eventually paving the way to improvements in medical procedures and personalized treatment.
Predictive Analytics makes use of techniques such as data mining, statistics, data modeling, AI, and machine learning to analyze historical as well as real-time data and predict future events. It aids in strengthening many areas of the healthcare segment, such as patient care, chronic disease management, supply chain management, and hospital administration.
Where does the market of predictive analytics in the healthcare industry stand?
If we concentrate on recent reports and studies, we get some surprising stats that reveal how predictive analytics is revolutionizing the healthcare industry. The global healthcare predictive analytics market is estimated to grow at a CAGR of 28.3% to reach $ 50.5 Billion by 2024. The rapid adoption of data-backed decision-making and the steps taken to increase Electronic Health Records (EHR) adoption by several nations are playing a crucial role in the deployment of analytics in the healthcare industry.
Some other key factors responsible for the market growth include the rise in demand to increase efficiency in healthcare while minimizing healthcare spending by reducing unnecessary costs, implementation of personalized and evidence-based treatment, the emergence of big data, need for reducing healthcare spending while ensuring improved results for patients, and exponentially growing patient registries.
What does Predictive Analytics have to offer?
An extremely accurate prediction is necessary for timely medical interventions. You shouldn’t be surprised if I tell you that predictive analytics is highly in demand in the healthcare segment. Machine learning models have already started progressing to predict crucial information related to acute kidney injury, stroke, cancer, and other medical conditions. Needless to mention, the working of predictive analytics is not bound to illnesses only. Many healthcare service providers are on the lookout for machine learning-based solutions to solve healthcare problems like unnecessary hospital readmissions and lack of personalized medicine plans. It’s evident that the promising features of predictive analytics in healthcare can offer incredible benefits. Some of which are enlisted here for your reference.
1. Predictive analytics can help you cleanse and analyze a massive amount of data in an instant for the evaluation of treatment options to cure several life-threatening diseases. It doesn’t only provide precise solutions based on historical data but also offers customized treatment options to cater to the needs of every unique patient. If we estimate the trends, we can say, predictive analytics is likely to assist medical professionals in the development of treatment plans as per individual patient needs.
2. Instead of providing users with mere information about events that already took place, predictive analytics tools go one level further and approximate future outcomes with the help of trends and patterns in the past.
3. Predictive analytics ensures medical professionals, finance teams, and hospital administrators receive timely warnings about potential threats and decide what can be the best course of action to stop unwanted events from happening.
4. Sensitive areas of healthcare such as intensive care, emergency care, and surgical operations where a patient’s life depends on a quick response time along with the detailed insights of what’s going on, predictive analytics keep clinicians and surgeons one step ahead of the events that are likely to happen.
5. Apart from direct benefits in terms of treatment and care, predictive analytics also saves a huge deal of costs by helping healthcare facility providers in selecting the right site locations for hospital and clinic setups.
6. Expansion of existing facilities and services is a risky and expensive process. Furthermore, it is prone to serious losses. Predictive analytics help you leverage competitor data and insights to avoid futile investments.
7. The healthcare industry can deploy predictive modeling for treatment protocol optimization. It leads healthcare authorities, regulatory bodies, and independent organizations under the industry to manage resources better and provide an enhanced experience to patients.
8. In addition to the abovementioned benefits, analytics modeling helps healthcare organizations achieve enhanced customer satisfaction. By appropriate measuring and staff scheduling, organizations can reduce patient-wait time, optimize appointment processing, and insurance processing.
The bottom line:
Predictive analytics keeps healthcare professionals abreast of insights into future threats, risks, and opportunities so that they can make appropriate choices to achieve the desired results. As patient-related data is exploding with every passing day, the healthcare industry now has more sophisticated big data analytics capabilities. Healthcare is shifting from descriptive analytics that simply offered pieces of information based on past events to predictive insights that estimate future outcomes based on trends and patterns over a period. Though predictive analytics might seem just one of the three stages of advanced analytics, it is actually helping today’s healthcare industry take a huge leap in the direction of success by enabling them to provide efficient, cost-effective, personalized, and well-administered services.
