What is Healthcare Data Analytics?

The healthcare sector is dominated by the expertise, skills, and knowledge regarding the ins and outs of the medical field. Since every step is taken and a decision made can alter the course of action and affect human health and life, so alongside the above, there are also factors beyond these that influence the healthcare sector which include accuracy in decision making, and confidence in tasks, and operations. 

 

This accuracy is brought through data analytics, an aspect that spins the thread on which the healthcare sector operates. With technology constantly evolving, healthcare is on its way to becoming another sector whose future is driven by data. 

 

Speaking of the role of data, you can also take a look at our blog on Role of Big Data in the Healthcare industry 

 

Data-driven analytics promotes early identification and intervention of diseases while also playing a role in consolidating institutions to administer faster, accurate, and more secure patient care. Employing data analytics in healthcare can aid in curtailing the treatment cost, predicting disease eruptions, thwarting avoidable ailments, and enhancing the overall quality of treatment and life of patients.

 

 

What is Healthcare Data Analytics?

 

In layman’s terms, Healthcare analytics can be understood as the gathering and analysis of healthcare sector data with the purpose of deriving insights and prompting decision-making. Ranging from main areas like medical expenses, clinical data, patient behavior, or pharmaceuticals, healthcare data analytics can be employed at both the macro and micro level to sufficiently boost operations, enhance patient care, and curtail overall expenses.

 

Nevertheless this data, while being highly advantageous is also pretty complicated. Be it the data from electronic health records (EHR) or the data gained by assessing real-time vital signs, the data is not only derived from a number of varying sources, but it is also required to follow government regulations, making it a complex and precarious process. 

 

In any industry, a data analytics and Business Intelligence (BI) solution can enhance operational efficiency, curtail costs, and simplify processes by calculating and employing KPIs for detecting opportunities and shaping up decision-making, making every participant from the patients and providers to payers and suppliers, unlocking the value of data benefits for everyone.

 

You can also sneak a peek at our blog on IoT in Healthcare

 

                                                                                                                                                                                   

Understanding Healthcare Data Analytics in various sectors

 

Possessing the ability to curtail treatment expenses or predict epidemic eruptions, Healthcare data analytics holds the efficacy to enhance the overall quality of life. Health professionals are not that distinct from business entrepreneurs when it comes to something like data analytics as both parties are constantly on the lookout for the most effective strategies to utilize these numbers.

 

In the case of hospitals and healthcare managers, data analytics in healthcare facilitates both administrative and financial data along with information for aiding in patient care endeavors, offering better services, and boosting prevailing procedures.

 

Prompt and timely physician scheduling is yet another area where data analytics is dominating in healthcare. In this situation, healthcare analytics provides a precise account of physician records as well as the history and requirements of the patient for ensuring that the most suitable physician is provided for the patients who most require it. 

 

Employing healthcare analytics will play a role in aiding healthcare providers in making use of data to derive insights for multiple operational areas. The donations and grants sections of hospitals and foundations is one crucial area where analytics can be deployed to enhance endeavors. 

 

With donations being based on the yearly budgets for various healthcare providers, organizing and tracking costs and operations becomes crucial for setting pertinent goals. It can also be effective for keeping track of donor engagement, retention, as well as prior contributions.

 

In the case of insurance companies, the process of healthcare analytics facilitates a simpler and more homespun pathway for tracking existing claims, clients, and premiums. Being equipped with enhanced real-time measurements as well as notable visualizations allows insurance firms to modify policies, oversee open claims, and introduce improved service costs.

 

Speaking of insurance, you can also spare a glance for our blog on 7 uses of big data in the insurance industry. 

 

 

6 Benefits of Healthcare Data Analytics

 

1. Predictive Analytics In Healthcare

 

The role of Predictive Analytics in healthcare is vast and far-reaching, its applications stretching far beyond businesses. For instance, a US research collaborative, Optum Labs, has gathered EHRs of more than 30 million patients to set up a database for predictive analytics tools that will enhance the delivery of care.

 

The primary aim is to aid doctors in making decisions propelled by data faster and enhance the treatment of patients. This is especially in the case of patients having complex medical histories and suffering from multiple conditions. The new tools can also predict if a patient is for instance, at risk of diabetes, thus offering them advice to use extra screenings or management of weight.

 

 

2. Care for High-Risk Patients

 

Healthcare is generally costly and complex for patients who seek emergency treatment or services. Although it's not always necessary that the high expenses will also provide an improved result, becoming an inconvenience for the patients. 

 

The digitized healthcare records allow the patterns and histories of patients to be detected more effectively. Predictive analytics can play a significant role in isolating patients who show chances of being at risk for crisis situations owing to chronic health issues. This will provide physicians with an opportunity to supply corrective plans that reduce emergency visits. For properly assessing these patients and providing them with personalized care and treatment solutions, appropriate data becomes a necessity owing to which the application of a Business Intelligence (BI) solution is crucial in healthcare when it comes to keeping high-risk patients secure. 

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How Data Analytics is revolutionizing healthcare

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3. Satisfaction of patients

 

The satisfaction of the patient and the level of their engagement with the healthcare facility becomes a valid cause of worry. Health tracking devices like wearables allow physicians to be more involved in preventative care for patients, enabling the patients to be more cognizant regarding their role in their own health. This comprehension plays a two-fold role by both helping to enhance the relationship between physicians and their patients as well as in reducing hospitalization rates. By employing such devices various health concerns can be avoided. 

 

 

4. Deal with Human Error

 

Human errors often lead to various avoidable health issues and insurance claims for instance if a doctor prescribes an inaccurate dosage or medication. This results in an increase in the risk exposed to patients as well as the expenses of insurance and claims exposed to the healthcare facilities. 

 

The data analytics tools can be adopted for examining the data of the patients and the medications prescribed in order to substantiate data and notify the users of any rare prescriptions or dosages to cut down on human error and avert any case of death or health issues of the patient. Especially in the case of fast-paced environments in which physicians deal with multiple patients on a common day, this becomes a useful solution to avoid errors. 

 

  

5. Industry Advancement

 

Alongside offering an advantage to the prevailing healthcare industry issues, data analytic tools also offer long term benefits for advancing the industry in the future. Data analytics can be adopted for filtering massive sections of data swiftly to determine treatment alternatives or solutions for varying diseases with the aim of providing both accurate solutions on the basis of historical data and facilitating personalized solutions to unique concerns for particular patients.

 

From predictions of epidemics, cures for diseases, improvement in the quality of life, preventable care, prior detection and assessment of risk, when it comes to the advancement of the healthcare industry, data analytics has endless applications. 

 

 

6. Cost Reduction

 

An extensive chunk of funds is expended by treatment centers, clinics, and hospitals on a task like financial management, generally owing to understaffing or overstaffing. This inconvenience can be resolved through predictive analysis, which plays a part in helping to predict the admission rate and safeguarding that the suitable staff is available for meeting the requirements of the patient. 

 

This allows the patients to gain the care they require swiftly and efficiently with more curtailed waiting periods, while also scaling down the overall staffing requirements and a dearth of beds which is often faced by hospitals owing to a lack of proper financial management. 

 

 

Challenges of Data Analytics in Healthcare

 

• Owing to the dearth of effective data governance processes, gathering data poses to be one of the biggest hindrances in the healthcare field. It is crucial for the data to be clear, to the point, and properly formatted for it to be adopted across a number of healthcare areas. 

 

• Although the records of the patients are generally stored for swift and smooth access in a centralized database, yet the actual challenge arises when information is required to be shared beyond healthcare professionals. 

 

• Yet another growing challenge for healthcare providers is data security, owing to the issue of repeated hacking and violations in security which are required to be dealt with on a regular basis.

 

•  While handling sensitive data such as the data of patients, a great deal of caution and prudence is required since any sort of leak of valuable information can lead to significant damages and expenses. 

 

 

 

Conclusion

 

Nearly every sector from advertising and marketing to finance and banking relies on data for gaining dynamic insights of business activities and procedures in order to propel and expand their operations. 

 

Although data analytics still has a long pathway ahead of it, and is yet to be applied to its fullest extent, the process has played a role in resolving various persistent issues and is a weapon which holds a great degree of promise for the near future. On being properly executed, the process unleashes endless possibilities which have the potential of revolutionising the healthcare sector.