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Predictive Analytics in Healthcare – Extraction of Actionable Insights

Jul 4, 2022

The healthcare sector has experienced a massive shift in the data analytics system – from basic descriptive analytics to a contemporary world of predictive analytics. In healthcare, predictive analytics provides estimates of a future outcome based on previous data patterns. According to a recent report, the global healthcare predictive analytics market was valued at USD 1.48 billion in 2015 and is expected to grow at a CAGR of 29.3% over the forecast period of 2015 to 2025 (source).

Source: Grandview Research

Role of Healthcare Predictive Analytics

Predictive analytics uses statistical algorithms, data, and machine learning techniques to recognize the likelihood of future healthcare outcomes based on previous data. It enables the healthcare industry to streamline business operations, provide enhanced care and avert any crisis likely to occur through actionable insights, thereby reducing healthcare costs. It is driven by the accelerated use of the Internet of Things (IoT) and Artificial Intelligence (AI); algorithms are fed with real-time and historical data to derive predictions. Medical professionals use these predictive algorithms to support clinical decision-making.

Our predictive analytics expertise at Key Management Group Inc. enables healthcare companies to predict and transform their business into new markets and expand growth opportunities through insights-driven decision making. To know further, please visit https://bit.ly/3wfXexj.

Here are a few reasons to choose KMG as your healthcare predictive analytics partner:

Patient Scheduling & Pattern Analysis

The Predictive analytics model of KMG helps to predict the highs and lows of a care provider’s facility, leading to effective patient scheduling and avoiding deadlocks in the facility. Predictive analytics can analyze the capability of the care center and typical patterns of the incoming patients and assist hospitals in booking appointments on any given day.

Reduction in Hospital Readmission Rates

Predictive analytics leveraged by KMG enables healthcare organizations to identify patients with a high risk of readmission, warn them, and provide them with better preventive care. For instance, let us take a look at the Texas hospital that has managed to cut its readmission rates by 5% using predictive analytics.

Chronic Disease Management & Preventive Care

Machine learning and remote patient monitoring are vital predictive analytics tools, and these work hand-in-hand to support the hospital’s decision-making through risk scoring and threshold alerts. Moreover, a notification can be triggered to check with patients managing chronic long-term health issues.

Reduced Patient Leakage by Optimized Operations

KMG leverages predictive analytics that helps to sift through the patient data, allowing hospitals to understand patient patterns and optimize operations. As a result, this permits the hospitals to preplan the processes which avert patient leakage.

Patient At-Risk Identification

Many patients have some risk factors, and predictive analytics helps recognize these factors, such as diabetic patients who need urgent hospitalization. Personalized prediction of the likelihood of chronic diseases can trigger the early intervention of care providers evading patients’ emergency room visits.

Conclusion

The Healthcare sector has witnessed the productive implementation of predictive analytics in its operations. In the upcoming days, healthcare providers who will embrace predictive analytics will provide the greatest care to their patients while streamlining their operational expenditures.

KMG’s expertise has helped healthcare companies strengthen processes while empowering them to introduce new products to deliver improved care and services. Connect with us at https://bit.ly/3sPyU36 for a healthcare technology partnership.  

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