Healthcare institutions that deal with the industry’s business side or a healthcare professional working with patients directly constitute the healthcare value chain. Within this construct, data analytics offer a strong foundation for strategic, impactful decision-making. The ability to work with and analyze huge data sets allows healthcare professionals—and institutions—to make informed treatment decisions and, on a broader scale, accurately predict future trends or events.

This blog explores data analytics, its role in healthcare, and some of the main advantages of leveraging data analytics in the healthcare industry.

Understanding data analytics in the healthcare industry

Healthcare data analytics refers to analyzing current and historical industry data to predict trends with higher accuracy and improve outreach. The field covers a wide range of businesses and offers valuable insights on both the macro and micro levels. It can provide strategic solutions to improve patient care quality, diagnosis, clinical data, and business management. Coupled with business intelligence solutions and other data visualization tools, data analytics in healthcare enables healthcare institutions and managers to operate with higher efficiency by offering real-time information that can support better decision-making.

Benefits of data analytics in the healthcare industry

Some key benefits of data analytics in the healthcare industry include the following:

a. Better patient care

Healthcare analytics allow providers to analyze massive volumes of patient data and determine the best treatment for them. This, in turn, helps them treat patients better, especially those with critical or severe illnesses such as multiple sclerosis, cardiovascular diseases, chronic renal disorders, etc.

Additionally, the use of natural language processing (NLP) in healthcare also allows healthcare providers and medical facilities to accurately measure and track the performance of employees and physicians either through surveys or sentiment analysis in some cases.

Healthcare institutes can also use AI-based data analytics and predictive analysis for specific situations, such as the duration of a patient’s stay in the hospital.

b. Reduced healthcare costs

The ever-rising healthcare costs have always been a cause of concern for various stakeholders. Fortunately, using predictive and prescriptive analytics allows healthcare organizations and practitioners to work on cost optimization and build detailed models for reducing costs and patient risks. 

Direct patient-centric benefits are the primary goal. However, healthcare data analytics can also be instrumental in reducing appointment no-shows, preventing equipment breakdowns, better managing supply chain costs, and decreasing fraud.

c. Electronic Health Records (EHRs)

Healthcare data analytics are also used extensively for EHRs.

Adding to the demographic and medical information, these EHRs document patients’ allergies, test results, medications, and more. EHRs can keep these records for several years, removing the concern about data loss or similar issues resulting in incomplete records. 

Another significant benefit of electronic health records in healthcare is their instant accessibility, which eliminates the need for sharing patient information from one medical facility to another, thus optimizing patient healthcare.

d. Improved diagnostics

Better and improved diagnostics is one of the most significant advantages of data analytics in healthcare.  Massive amounts of data—subjected to various algorithms—can be used to diagnose illnesses faster and more accurately. These algorithms can also recommend the best possible tests to help you confirm the diagnosis, which eliminates instances of unnecessary testing.

e. Predictive modeling

Predictive modeling analyzes current and historical data to predict future outcomes more accurately. These models use the latest techniques, such as data mining, statistics, and machine learning to identify patterns and accordingly predict outcomes. The predictive models built with the collected health data offer solutions on the macro and micro levels.

This kind of predictive analytics can alert healthcare professionals to potential risks. For instance, behavioral data analysis can help healthcare organizations predict treatment outcomes, potential hazards for chronic illness, and even the risk of self-harm.

f. Improved interactions with patients

Technologies such as AI and NLP can help patients better understand complex medical terminologies and their overall health. The other significant advantage here is the use of NLP-enabled patient voice in healthcare, which allows healthcare providers to get an idea of how their patients feel about the interaction with a service provider or healthcare professional. This helps healthcare providers respond appropriately and implement the best possible strategies to improve the patient experience, leading to improved patient interactions.

g. Better decision-making

Data-driven decision-making in healthcare procedures that allows healthcare professionals to identify trends and patterns accurately and gain relevant insights from the data is another significant benefit of data analytics.

The last few years have also seen an increased emphasis on using AI, ML, and data analytics in various surgical procedures. The vast field of surgical data science can specifically enable technologies such as surgical robotics and speech recognition to help healthcare providers and surgeons plan their scheduled medical procedures with higher precision.

h. Telemedicine and real-time monitoring

Telemedicine and the advent of the Internet of Things (IoT) are two of the latest trends in healthcare. In addition, big data analytics enables patients to get better and more effective care without visiting any healthcare facility. Big Data analytics allows these facilities to analyze their data better to plan and allocate their resources more effectively.

Data analytics also allow healthcare facilities to improve their operations, lower costs, and make their processes much more efficient.

Conclusion

Healthcare is one of the most evolving and complicated industries regarding data management.

The exponential growth of complex healthcare data makes it quite challenging for legacy systems to assist healthcare institutions and medical practitioners to gain insights from such massive volumes of data and improve the overall quality of their services.

PreludeSys is one of the leading technology partners for healthcare organizations to help collaborate, implement, and leverage the power of data analytics. We have many years of proven experience to help you brainstorm and design a robust clinical support system. Our expertise assists healthcare institutions and medical practitioners to improve efficiency and maximize business profitability.

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