Unveiling the Distinction: Predictive vs. Prescriptive Analytics in Healthcare

Data analytics is the buzzword right now. It has become a vital and inevitable part of organisations across all sectors, including healthcare. The healthcare sector is one of the primary avenues heavily reliant on patient-related data. This data dependency has already led to the emergence of specialised healthcare data analytics solutions.

In this context, predictive and prescriptive analytics are two types of data analytics used extensively in healthcare. These two technologies contribute to a holistic understanding of patients’ health. Using the insights derived from both analytics, healthcare facilities can make better decisions regarding patient care and operational management.

Before we learn about predictive and prescriptive analytics, let’s see how data analytics forms the foundation for both.

Data Analytics & Its Role in Healthcare?

Data analytics is the extensive process of collating and analysing data to derive actionable insights that facilitate critical decisions. In the realm of healthcare, data analytics examines volumes of patient-related datasets to draw conclusions that healthcare organisations can use to make effective patient-care decisions.

Data analytics is proving to be immensely useful in:

• Identifying the strong and weak aspects of a healthcare organisation
• Providing insights about future trends based on existing data
• Confirming the necessity and non-necessity of specific products and services
• Analysing the actual impact of medical decisions on patients
• Analysing the impact of consumer behaviour

Despite the various challenges in fully implementing it, data analytics in healthcare is intended to be applied to every aspect of patient care and hospital management, such as:

• Improving patient care
• Predicting disease outbreaks
• Find less expensive treatments for certain conditions
• Simplify administrative operations
• Enhance the utilisation of resources
• Enhance coordination between medical teams
• Enable the development of new treatments
• Support clinical decisions with new insights
• Enable accurate diagnosis of medical conditions
• Enable health insurance calculation
• Automate hospital administrative procedures
• Effective prediction and prevention of diseases
• Support clinical and drug-related research

Let’s now analyse predictive and prescriptive analytics.

Also Read: Prescriptive Analytics & Its Benefits For Healthcare

Defining Predictive & Prescriptive Analytics

Predictive analytics extracts vital insights from data to predict patterns and trends. This technology uses AI, data mining, and statistical modelling to analyse historical and real-time data to make critical healthcare predictions. Healthcare professionals use these predictions to enable accurate disease diagnosis, minimise health risks, and provide personalised treatments.

It is also important to remember that predictive analytics do not make specific recommendations. They only state facts that a possibility is LIKELY to occur because of some prior action. The word “likely” clearly implies that there is no guarantee about a future outcome. Predictive analytics gives only a probability of its occurrence.

Prescriptive analytics, on the other hand, takes things a notch further than predictive analytics. It identifies a certain number of actions that can be taken in response to a given prediction. This technology also derives data from various sources and uses high-end technology to recommend the best actions and what they may lead to.

When it comes to predictive analytics vs. prescriptive analytics, the latter is more advanced because it creates complex models from diverse data sources. It also uses ML algorithms to arrive at conducive data-based decisions.
This approach enables organisations to anticipate future outcomes, allowing them to test different scenarios and make well-informed decisions.

In short, predictive and prescriptive analytics are like two peas in a pod or two different segments of the same orange. They originate from the same source but have distinct qualities. Also, one is not better than the other; rather, they are both integral parts of a unified whole.

So, let’s analyse the aspects that differentiate the two.

Distinctions Between Predictive & Prescriptive Analytics

In essence, prescriptive analytics is more complex than predictive analytics. Nevertheless, irrespective of what is implemented, you need to know how to optimise both for your benefit.

3 Ways to Make Predictive & Prescriptive Analytics Work For You

1. Identify and prioritise your healthcare goals before implementing analytics solutions.
   This approach will help you find the questions related to what you are planning to use.
2. Gather adequate data about patients to create reliable data sets. A complete understanding of your patients will help you predict vital aspects and find the best solution.
3. Adopt an analytics solution to sort through the vast volumes of data and derive actionable insights. Just like any kind of analysis, it's important to ensure that the data being used is complete and current in order to improve accuracy.

Concluding Point

Both predictive and prescriptive analytics are treasure troves for healthcare organisations. They can predict so much, from the effectiveness of treatments for certain conditions to the likelihood of a patient’s response to medical intervention to prescribing diagnostic protocols for patients based on their characteristics and behaviours.

As experts in healthcare data analytics solutions, Health Vectors can help improve care by enabling you to make smarter, data-driven decisions. Contact our team to help you choose what’s best for your healthcare organisation.