The volume of healthcare-related data is rapidly expanding due to the growing use of telemedicine, the spread of IoT devices, and the acceptance of EHRs. Healthcare firms can utilize that data to drive growth strategies and innovate patient care mechanisms as long as they mine it carefully. By processing such data, healthcare companies can improve their operations and build new and better ways to treat their patients in a proper manner. Furthermore, data mining aids in cost optimization, treatment improvement, and fraud prevention.
There are many ways a healthcare company can get data mining done: setting up an in-house team, hiring freelancers, or outsourcing healthcare data mining services to an experienced third-party company.
In this post, we’ll cover the most critical benefits of healthcare data mining as well as the best ways to approach it. We’ll also cover how you can benefit if you outsource healthcare data mining services.
Why Is Data Mining Important in the Healthcare industry?
About 30% of all global data is produced by the healthcare industry solely, and this percentage can reach 36% by 2025. This data contains a wide range and volume of insights that can transform the healthcare industry in several ways. When healthcare organizations are able to make sense of that data, it gives them huge strategic advantages.
Here are a few of the most common reasons why data mining is important in the healthcare sector:
1. Increased Diagnosis Accuracy
Mining healthcare data can enable medical practitioners to quickly and conclusively diagnose patients using the best available evidence. Blood tests, X-rays, and MRI pictures, among other types of data, can be promptly analyzed and categorized to aid in the early diagnosis of cancers and other problems. When complex illnesses with ambiguous symptoms are being treated, doctors can use the information processed with the help of data mining to see what type of treatment can be done, what kind of medicines can be given, etc.
2. Improved Predictive Analytics in Healthcare Firms
Using predictive analytics and healthcare data mining, medical practitioners can prepare themselves for various ups and downs and subsequently improve patient care. They can-
● be prepared for seasonal and other illness surges.
● easily deal with staff shortages and medicine shortages.
●implement innovative techniques and technology while eliminating outdated ones.
3. Extensive Healthcare Knowledge Banks
With the help of insights derived from the data mining process, medical firms can build an extensive knowledge bank. That can be used to expedite decision-making (operational or patient care-related) without wasting the time of doctors, diagnostic personnel, and administrators. Those insights can also be used to train enhanced systems and automate the process of prescribing the right medicine, suggesting the right test, etc.
4. Highly Enhanced Clinical Decision-Making:
A growing number of hospitals are implementing CDSS (clinical decision support systems). These systems either use machine learning to draw conclusions from data analysis or use a knowledge base and rules to guide decisions. Data mining is extremely useful for these types of solutions, such as when comparing a patient's history and symptoms with recent clinical studies or cases similar to theirs.
5. Better Treatment Frequency:
Every healthcare practitioner aspires to serve their patients with the highest quality of medical care. Data mining makes it simple to evaluate the various treatment options, evaluate their effectiveness, and choose the best one suited. Additionally, by using data from medical IoT devices, practitioners may monitor their patients' status and modify treatment as necessary.
6. Helps in Avoiding Harmful Drug & Food Interactions:
When taken together or in conjunction with specific foods, some medications may become less effective or have undesirable side effects. Before using a new medication, the US Food and Drug Administration advises patients to see a physician or pharmacist. In a clinical context, there isn't always time for that.
Healthcare data mining can reduce these hazards. Even though the most hazardous drug interactions have been extensively researched, there is always a potential for human mistakes and the ongoing development of new medications. A system that can track the chemical makeup of pharmaceuticals and examine research and clinical data will be helpful to doctors, nurses, and patients alike.
7. Improves Relations with Customers:
The addition of a data mining module to your CRM program has many advantages. The top three are as follows:
●The system can link individuals with specific problems to healthcare providers who can assist and have the necessary training. This boosts client happiness and produces better results.
●Hospitals can better anticipate potential complications and recovery times by using data collected from comparable instances. This facilitates scheduling follow-up appointments and avoids readmissions.
●The CRM can track consumer pharmacy purchases when the appropriate data is available for analysis. Doctors can use this information to determine whether a patient adheres to their treatment regimen and takes the recommended medications.
●Healthcare providers can increase efficiency and foster patient loyalty by using data mining.
8. Superior Insurance Fraud Detection
The capacity to spot fraudulent insurance claims is another benefit of adopting data mining in the healthcare sector. The Coalition Against Insurance Fraud estimates that in 2021, erroneous and fraudulent claims totaled a staggering $3.1 billion. Thanks to modern analytics, healthcare data mining tools can cut down on those losses by spotting irregularities and warning signs in documents.
A Few Examples of the Utility of Data Mining in Healthcare
Faster diagnostic processes, higher accuracy rates, and limitless prospects for new medical studies are all results of the rapid growth of data analytics technologies. Here are a few instances of data mining in healthcare that demonstrate this.
1. Brain tumor segmentation using data mining
2. Identification & prevention of fraud
3. Exploring dietary patterns of patients
How to Get Data Mining Done in Healthcare
There are primarily four ways of getting data mining done for your healthcare business.
These are:
1. Crowdsourcing:
It’s the cheapest option out of all four. In this, your company will ask individuals (freshers, trainees, etc.) to complete data mining-related tasks for you at minimal or no cost. It’s the most time-consuming of all four and provides the least privacy and data security. Additionally, the quality of work is also the lowest.
2. Freelancing:
Freelancing is a good option for small-scale startups where cost-cutting is an utmost priority. However, it may lead to minimal data security, the quality of work can fluctuate, and the scalability is questionable.
3. In-house Team:
With this model, data security and privacy are the highest among all four, but the cost is also the highest. It is ideal for companies to have enough capital, infrastructure, trainers, a hiring team, etc. But they won’t be able to provide quality work right away, you will have to give them enough time (usually a few months) and training before expecting high-quality work.
4. Outsourcing to Agencies:
This is one of the best options as it makes an excellent balance between cost-effectiveness, is quickest among all four, and the quality of work is unmatchable. Even huge companies having enough resources for in-house teams are outsourcing their data mining work because of those advantages.
Pro Tip: Your business can even opt for a 30% - 70% ratio where 30% of work is done by an in-house team, and 70% is outsourced. This practice has started becoming quite common in American and European countries.
Conclusion
Hopefully, now you are aware of the role data mining can play in the healthcare sector. There are still several more benefits and examples which will vary from business to business, and some will be region specific as well. However, there is doubt in the fact that data mining is critical to growing your firm, and a healthcare data mining company can help expedite your growth on that path.
Author Bio:
Jessica is a Content Strategist, currently engaged at Data-Entry-India.com- a globally renowned data entry and management company -for over five years. She spends most of her time reading and writing about transformative data solutions, helping businesses to tap into their data assets and make the most out of them. So far, she has written over 2000 articles on various data functions, including data entry, data processing, data management, data hygiene, and other related topics. Besides this, she also writes about eCommerce data solutions, helping businesses uncover rich insights and stay afloat amidst the transforming market landscapes.
